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1.
Subfossil Cladocera were sampled and examined from the surface sediments of 35 thermokarst lakes along a temperature gradient crossing the tree line in the Anabar-river basin in northwestern Yakutia, northeastern Siberia. The lakes were distributed through three environmental zones: typical tundra, southern tundra and forest tundra. All lakes were situated within the continuous permafrost zone. Our investigation showed that the cladoceran communities in the lakes of the Anabar region are diverse and abundant, as reflected by taxonomic richness, and high diversity and evenness indices (H = 1.89 ± 0.51; I = 0.8 ± 0.18). CONISS cluster analysis indicated that the cladoceran communities in the three ecological zones (typical tundra, southern tundra and forest-tundra) differed in their taxonomic composition and structure. Differences in the cladoceran assemblages were related to limnological features and geographical position, vegetation type, climate and water chemistry. The constrained redundancy analysis indicated that TJuly, water depth and both sulphate (SO4 2?) and silica (Si4+) concentrations significantly (p ≤ 0.05) explained variance in the cladoceran assemblage. TJuly featured the highest percentage (17.4 %) of explained variance in the distribution of subfossil Cladocera. One of the most significant changes in the structure of the cladoceran communities in the investigated transect was the replacement of closely related species along the latitudinal and vegetation gradient. The results demonstrate the potential for a regional cladoceran-based temperature model for the Arctic regions of Russia, and for and Yakutia in particular.  相似文献   

2.
We examined the relationship between three key environmental variables (water depth, loss-on-ignition, and bottom-water temperature) and fossil chironomid distributions sampled from within-lake gradients in three small, moderately deep (18–35 m), maar lakes on St Michael Island, western Alaska. Site-specific (one lake, 29 samples) and local (three lakes, 87 samples) inference models for reconstructing water depth were developed using partial least squares regression and calibration. These models and a previously published regional model (136 lakes, one central-lake sample from each) are used to infer water depths from 78 fossil samples spanning the last ~30,000 14C years B.P. at Zagoskin Lake. Although the site-specific [r 2 boot = 0.90, root mean square error of prediction (RMSEP) = 1.76] and local (r boot2 = 0.68, RMSEP = 4.36) inference models have better performance statistics than the regional model, few clear trends among all three models exist in the lake-level reconstruction. We propose that multiple, within-lake sampling of gradients can be used to improve the performance statistics of water-depth transfer functions and ultimately reconstruct paleohydrology in regions known to exhibit large fluctuations in moisture balance through time given that: (1) adequate analogs are established and (2) taphonomic processes important to benthic invertebrate remains are more fully understood.  相似文献   

3.
Reconstructing climate change quantitatively over millennial timescales is crucial for understanding the processes that affect the climate system. One of the best methods for producing high resolution, low error, quantitative summer air temperature reconstructions is through chironomid analyses. We analysed over 50 lakes from NW and W Iceland covering a range of environmental gradients in order to test whether the distribution of the Icelandic chironomid fauna was driven by summer temperature, or whether other environmental factors were more dominant. A range of analyses showed the main environmental controls on chironomid communities to be substrate (identified through loss-on-ignition and carbon content) and mean July air temperature, although other factors such as lake depth and lake area were also important. The nature of the Icelandic landscape, with numerous volcanic centres (many of which are covered by ice caps) that produce large quantities of ash, means that relative lake carbon content and summer air temperature do not co-vary, as they often do in other chironomid datasets within the Arctic as well as more temperate environments. As the chironomid–environment relationships are thus different in Iceland compared to other chironomid training sets, we suggest that using an Icelandic model is most appropriate for reconstructing past environmental change from fossil Icelandic datasets. Analogue matching of Icelandic fossil chironomid datasets with the Icelandic training set and another European chironomid training set support this assertion. Analyses of a range of chironomid-inferred temperature transfer functions suggest the best to be a two component WA-PLS model with r 2 jack = 0.66 and RMSEP = 1.095°C. Using this model, chironomid-inferred temperature reconstructions of early Holocene Icelandic sequences show the magnitude of temperature change compared to contemporary temperatures to be similar to other NW European chironomid sequences, suggesting that the predictive power of the model is good.  相似文献   

4.
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   

5.
Fossil assemblages of chironomid larvae (non-biting midges) preserved in lake sediments are well-established paleothermometers in north-temperate and boreal regions, but their potential for temperature reconstruction in tropical regions has never before been assessed. In this study, we surveyed sub-fossil chironomid assemblages in the surface sediments of 65 lakes and permanent pools in southwestern Uganda (including the Rwenzori Mountains) and central and southern Kenya (including Mount Kenya) to document the modern distribution of African chironomid communities along the regional temperature gradient covered by lakes situated between 489 and 4,575 m above sea level (a.s.l). We then combined these faunal data with linked Surface-Water Temperature (SWTemp: range 2.1–28.1°C) and Mean Annual Air Temperature (MATemp: range 1.1–24.9°C) data to develop inference models for quantitative paleotemperature reconstruction. Here we compare and discuss the performance of models based on different numerical techniques [weighted-averaging (WA), weighted-averaging partial-least-squares (WA-PLS) and a weighted modern analogue technique (WMAT)], and on subsets of lakes with varying gradient lengths of temperature and other environmental variables. All inference models calibrated against MATemp have a high coefficient of determination ( r\textjack2 r_{\text{jack}}^{2}  = 0.81–0.97), low maximum bias (0.84–2.59°C), and low root-mean-squared error of prediction (RMSEP = 0.61–1.50°C). The statistical power of SWTemp models is generally weaker ( r\textjack2 r_{\text{jack}}^{2}  = 0.77–0.95; maximum bias 1.55–3.73°C; RMSEP = 1.39–1.98°C), likely because the surface-water temperature data are spot measurements failing to catch significant daily and seasonal variation. Models based on calibration over the full temperature gradient suffer slightly from the limited number of study sites at intermediate elevation (2,000–3,000 m), and from the presence of morphologically indistinguishable but ecologically distinct taxa. Calibration confined to high-elevation sites (>3,000 m) has poorer error statistics, but is less susceptible to biogeographical and taxonomic complexities. Our results compare favourably with chironomid-based temperature inferences in temperate regions, indicating that chironomid-based temperature reconstruction in tropical Africa can be achieved.  相似文献   

6.
Modern assessment and monitoring of aquatic ecosystems is increasingly based on biota and the “reference condition” approach, in which the observed values (O) of biological variables are compared to those expected in the absence of human disturbance (E). To use this approach, correct estimation and validation of reference conditions are critical. Because appropriate modern or historical data are never available for this approach, palaeolimnological data offer an alternative. We used a calibration data set from 73 profundal sites in semi-pristine Finnish lakes to construct a regression model for estimating expected values for the chironomid Benthic Quality Index (BQI)—a macroinvertebrate metric widely used in bioassessment—from environmental variables that are insensitive to human disturbance. For comparison, reference values were estimated using the European legislative rationale based on a priori lake typology. Performance of the alternative approaches was assessed by internal ‘leave-one-out’ cross-validation using the calibration set and by external cross-validation using independent palaeolimnological data on BQI values representing the historical pristine status of 24 lake basins. Additionally, for 19 of these sites, which vary in their degree of human impact, the ratio of present BQI to that in pristine condition, which shows the degree of actual change, if any, was calculated from palaeolimnological data and compared with the O/E ratios based on the present chironomid data and estimated E. A linear regression model with mean depth and mean/maximum depth ratio as independent variables estimated the reference values of BQI much closer to the observed ones (r 2 = 0.58, RMSEP = 0.65 and r 2 = 0.71 RMSEP = 0.55; for internal and external cross-validation, respectively) than did the typology approach (r 2 = 0.28, RMSEP = 0.86; r 2 = 0.10, RMSEP = 0.97). The regression approach also yielded O/E ratios more similar to the actual ones (r 2 = 0.79, RMSEP = 0.09) than did the typology approach (r 2 = 0.62, RMSEP = 0.23). Our results strongly support the use of lake morphometric variables and modelling instead of categorical lake typology for the establishment of reference conditions for profundal macroinvertebrate communities and demonstrate the utility of palaeolimnological data in the validation of reference values and assessment methods.  相似文献   

7.
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   

8.
Chironomid and ceratopogonid head capsules, along with Chaoborus mandibles, were used to model mean temperature of the warmest quarter (TWARM) in Tasmania. Our transfer function is based on midge assemblages and 21 environmental variables sampled from 47 lakes. Canonical correspondence analysis (CCA) revealed seven variables that account for a significant (P ≤ 0.05) portion of the explainable variance. In order of explanatory power, these were pH, TWARM, annual radiation, magnesium, annual precipitation, SiO2, and depth. TWARM was modeled using weighted averaging partial least squares (WA-PLS) and generated a model with and RMSEP = 0.94. Advances in chironomid paleoecology are progressing very quickly in the Southern Hemisphere. Chironomid identification guides and autecological data are available for many regions, highlighting the potential for developing midge-based quantitative models to address hemispheric and interhemispheric climate hypotheses.  相似文献   

9.
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 (RMSEPjack) 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 RMSEPjack 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.  相似文献   

10.
Diatom abundances in the surface sediment samples of 41 mountain lakes in the central Austrian Alps (Niedere Tauern) were related to environmental variables using multi-variate techniques. Canonical correspondence analysis (CCA) revealed that the pH, date of autumn mixing (A mix), mean August water temperature (T Aug), dissolved organic carbon (DOC), and relative water depth (Z rel) made significant contributions to explain the diatom assemblage variation in the lakes of the training set. A weighted averaging partial least square regression and calibration model was used to establish Di-pH (R 2 boot= 0.72, RMSEPboot= 0.131), and a thermistor measurements-based PLS model for A mix (R 2 boot= 0.71, RMSEPboot= 0.006 log10 Julian days). The latter showed a better prediction than T Aug, and was used in terms of climate change. These transfer functions, together with analyses of loss on ignition (LOI), the total carbon/nitrogen (C/N)-ratios, and selected pollen, were applied to an early to mid-Holocene (11.5–4 cal. ky BP) sediment core section from an Austrian Alpine treeline lake on crystalline bedrock. Additionally, passive sample scores in the CCA of the diatom training set were used to show trends in the variables DOC and Z rel. During the early Holocene, diatoms indicative of increased pH, extended warm summers, and low water levels dominated. Between 10.2 and 7.6 cal. ky BP it was followed by diatom assemblages that indicated an increase in lake water depth and an earlier A mix. The multi-proxy data suggest that the A mix decline is the result of a series of snow-rich summer cool and wet climate fluctuations, which were divided by climate warming at ∼9 cal. ky BP. Increased A mix, LOI and DOC, and the correspondent decline in the C/N-ratios, show subsequent climate warming between 7.3 and 6 cal. ky BP. The long-term trend in Di-pH indicates the impact of catchment-related processes during the early-Holocene, that were superimposed by climate.  相似文献   

11.
Small, shallow, temperate lakes are predominant landscape features in North America, however, little is known about their long-term ecosystem dynamics, and few data exist on the chironomid fauna they harbor. Using multivariate analyses, we defined relationships between sub-fossil chironomid assemblage composition and environmental variables in 26 shallow lakes of northeastern USA and quantified how differences in taxonomic resolution affect transfer function model performance. Using redundancy analysis, we found that chironomid assemblages are best explained by turbidity, dissolved inorganic carbon and drainage basin/lake area ratio. Turbidity explained the greatest proportion of variance found in the chironomid assemblage (10.4%), followed by total nitrogen. Through ordination analyses and an analysis of similarity, we found that macrophyte density was also a significant predictor of chironomid assemblages. We used partial least squares analysis to develop a robust model for quantitative reconstruction of turbidity, with r jack2 = 0.62. When using a more coarsely resolved taxonomic dataset, we found that model performance statistics were weaker, suggesting the need for fine-resolution taxonomy. Overall, our findings highlight the importance of variables related to lake trophic state in structuring chironomid assemblages in shallow, temperate lakes and provide tools for inferring past ecological changes in these ecosystems.  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.
To quantify the relationship between diatom species assemblages and the water chemistry of southeast Australian estuaries and coastal lakes, a new dataset of 81 modern diatom samples and water chemistry data was created. Three hundred and ninety-nine species from 53 genera were identified in 36 samples from 32 coastal water bodies in eastern Tasmania and 45 samples from 13 coastal water bodies in southern Victoria. Multivariate statistical analyses revealed that the sampling sites were primarily distributed along salinity and nutrient gradients, and that salinity, nitrate + nitrite, phosphate and turbidity explained independent portions of variance in the diatom data. Species salinity optima and tolerances were determined and a diatom-salinity inference model (WAinv r 2 = 0.72, r 2jack = 0.58, RMSEP = 0.09 log ppt) was developed. This new information on diatom species’ salinity preferences provides a useful tool for quantitatively reconstructing salinity changes over time from diatom microfossils preserved in the sediments of a range of estuaries and coastal lakes in southeast Australia. This is valuable for studies investigating long-term human impacts and climate change in the region.  相似文献   

14.
Lake eutrophication is a problem in many areas of Ontario, although the history of nutrient enrichment is poorly documented. The aim of this study was to construct a diatom-based transfer function to infer past phosphorus levels in Ontario lakes using paleolimnological analyses. The relationship between diatom assemblages and limnological conditions was explored from a survey of diatoms preserved in the surface sediments of 64 Southern Ontario lakes, spanning a total phosphorus gradient of 0.004 to 0.054 mg L-1. Over 420 diatom taxa were identified, 98 of which were sufficiently common to be considered in statistical analyses. Canonical correspondence analysis (CCA) determined that pH, ammonium, aluminum, spring total phosphorus (TP), strontium, total nitrogen (TN), maximum depth (MaxZ), chlorophyll a (Chla) and mean depth were significant variables in explaining the variance in the diatom species data. The environmental optima of common diatom taxa for the limnologically important variables (TP, pH, TN, MaxZ, Chla) were calculated using weighted averaging (WA) regression and calibration techniques, and transfer functions were generated. The diatom inference model for spring TP provided a robust reconstructive relationship (r2 = 0.637; RMSE = 0.007 mg L-1; r2 boot = 0.466; RMSEboot = 0.010 mg L-1). Other variables, including pH (r2 = 0.702; RMSE = 0.208; r2 boot = 0.485; RMSEboot = 0.234), TN (r2 = 0.574; RMSE = 0.0899 mg L-1; r2 boot = 0.380; RMSEboot = 0.127 mg L-1) and MaxZ (r2 = 0.554; RMSE = 1.05 m; r2 boot = 0.380; RMSEboot = 1.490 m), were also strong, indicating that they may also be reconstructed from fossil diatom communities. This study shows that it is possible to reliably infer lakewater TP and other limnological variables in alkaline Southern Ontario lakes using the WA technique. This method has the potential to aid rehabilitation programs, as it can provide water quality managers with the means to estimate pre-enrichment phosphorus concentrations and an indication of the onset and development of nutrient enrichment in a lake.  相似文献   

15.
We analyzed surface-sediment samples collected along transects from three sub-basins of a relatively large (~115 ha), bathymetrically complex lake, in northwest Ontario, Canada, to assess the reproducibility of diatom species habitats and diversity along a water-depth gradient. Transects displayed different orientations with respect to prevailing wind direction and varied in complexity and degree of slope along the lake bottom. Each transect consisted of three replicate samples at a resolution of ~1 m water depth from ~1 to 30 m for the two deep-basin transects and from ~1 to 18 m in the shallower basin. Distinct diatom assemblages were identified in all transects: (1) a near-shore community composed largely of attached life-forms and some motile benthic taxa, (2) a mid-depth community composed largely of motile life-forms and other benthic taxa that are adapted to lower light conditions (e.g. Staurosirella pinnata), and (3) a deep-water community dominated by planktonic taxa. Species richness was highest in the benthic zones (<9 m), with greatest species evenness in the mid-depth zone (~3–9 m). Species richness and evenness were highly correlated across the three transects (r = 0.89–0.93, p < 0.01). Diatom-inferred depth models were developed from the individual transects to assess reproducibility and applicability for down-core analyses using modern analog (MAT) and weighted-averaging (WA-PLS) approaches. Coefficients of determination (r 2) for these models ranged from 0.80 to 0.98, and RMSEP ranged from 1.2 to 4.2 m. The models developed from the transect with the highest resolution sampling, gentlest non-complex slope and shallowest maximum depth were the strongest ( r\textMAT2 = 0.97 r_{\text{MAT}}^{2} = 0.97 ; r\textWA - PLS2 = 0.98 r_{\text{WA - PLS}}^{2} = 0.98 ) and had the lowest RMSEP (MAT = 1.2 m, WA-PLS = 1.3 m). These inference models can be used to infer past fluctuations in the depth of the benthic/planktonic boundary from cores retrieved near this ecotone and provide a sensitive record of the past change in location of the benthic zone. These types of data can be used to assess past variability in droughts and lake levels to better plan for potential future extremes. Such records incorporate more realistic estimates of natural variability than the ~100-year instrumental records currently used by water resource managers.  相似文献   

16.
Arctic aquatic systems are considered to be especially sensitive to anthropogenic disturbance, which can have cascading effects on biological communities as aquatic food-web structure is altered. Bio-indicators that respond to major limnological changes can be used to detect and infer major environmental change, such as climate warming, with the use of paleolimnological techniques. A multi-proxy approach was used to quantify recent environmental changes at Baker Lake, Nunavut, Arctic Canada. Analyses of fossilized remains of chironomids and diatoms were conducted on a sediment core of 20 cm in length sampled at 0.5-cm intervals. A new surface sediment training set of subfossil chironomid assemblages from 65 lakes across the eastern Canadian Arctic generated a robust (r jack2 = 0.79) surface water paleotemperature transfer function. The transfer function was applied to stratigraphic intervals from the Baker Lake sediment core to generate a paleotemperature reconstruction of sub-decadal resolution. The surface water temperature reconstruction inferred a 2°C increase in mid-summer surface water temperature for Baker Lake over the last 60 years, which was corroborated by the local instrumental record spanning the period of 1950–2007 AD. The chironomid record shows a recent decline of several cold-water taxa and appearance of warm-water indicators. This shift in community structure began circa 1906 AD, and intensified after 1940 AD. The corresponding fossil diatom record showed an increase in small planktonic Cyclotella taxa over the past 60 years, intensifying in the last 5 years, which also suggests a warmer climate and longer ice-free periods. The shifts in the diatom assemblages began later than the shifts in the chironomid assemblages, and were of lower magnitude, reflecting differences in the mechanisms in which these two indicators respond to environmental change.  相似文献   

17.
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   

18.
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   

19.
The apparent isotope enrichment factor εmacrophyte of submerged plants (εmacrophyte–DIC = δ13Cmacrophyte − δ13CDIC) is indicative of dissolved inorganic carbon (DIC) supply in neutral to alkaline waters and is related to variations in aquatic productivity (Papadimitriou et al. in Limnol Oceanogr 50:1084–1095, 2005). This paper aims to evaluate the usage of εmacrophyte inferred from isotopic analyses of submerged plant fossils in addition to analyses of lake carbonate as a palaeolimnological proxy for former HCO3 − concentrations. Stable carbon isotopic analysis of modern Potamogeton pectinatus leaves and its host water DIC from the Tibetan Plateau and Central Yakutia (Russia) yielded values between −23.3 and +0.4‰ and between +14.0 and +6.5‰, respectively. Values of ε Potamogeton–DIC (range −15.4 to +1.1‰) from these lakes are significantly correlated with host water HCO3 − concentration (range 78–2,200 mg/l) (r = −0.86; P < 0.001), thus allowing for the development of a transfer function. Palaeo-ε Potamogeton–ostracods values from Luanhaizi Lake on the NE Tibetan Plateau, as inferred from the stable carbon isotope measurement of fossil Potamogeton pectinatus seeds (range −24 to +2.8‰) and ostracods (range −7.8 to +7.5%) range between −14.8 and 1.6‰. Phases of assumed disequilibrium between δ13CDIC and δ13Costracods known to occur in charophyte swards (as indicated by the deposition of charophyte fossils) were excluded from the analysis of palaeo-ε. The application of the ε Potamogeton–DIC-HCO3 − transfer function yielded a median palaeo-HCO3 − -concentration of 290 mg/l. Variations in the dissolved organic carbon supply compare well with aquatic plant productivity changes and lake level variability as inferred from a multiproxy study of the same record including analyses of plant macrofossils, ostracods, carbonate and organic content.  相似文献   

20.
Stable oxygen isotope measurements on fossil chironomid head capsules from lake sediments show that these chitinous remains can be used to reconstruct past lake water δ18O and, indirectly, past climate change. We examined the impact of chemical pretreatment procedures on the chemical and stable oxygen isotope composition, and morphology of chironomid cuticles. Use of alkali, acids, and sodium chlorite alters the chemical composition and the morphological structure of chironomid cuticles by selective removal of chitin or proteins. Gas chromatograms of pyrolyzates show that NaClO2 causes deproteination, whereas the combined use of HCl and HF results in partial chitin removal. Head capsules pretreated with KOH contained both chitin- and protein-derived moieties, although the concentration of protein was reduced, especially after KOH treatment at high concentration (28%) and temperature (100°C). Scanning electron microscopy confirmed that a proteinaceous matrix is still present in modern and fossil head capsules after KOH treatment. This matrix, however, is largely absent in head capsules pretreated with NaClO2. A change in the proportion of chitin and proteins in our samples was associated with differences in chironomid δ18O values. Our results suggest that deproteination results in a relative increase of chironomid δ18O, whereas removal of chitin leads to decreased δ18O values. We therefore discourage the use of acids or prolonged (≥1 h) exposure to hot alkali (70°C) prior to chironomid δ18O analysis. Chitin purification by sodium chlorite causes significant weight loss, which may preclude down-core chironomid δ18O measurements. Caution and standardization are required when pretreating samples for chironomid δ18O analysis to ensure reliable, comparable, and reproducible results.  相似文献   

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