Weighted Averaging Partial Least Squares Research Articles

A modern pollen–climate dataset from China and Mongolia: Assessing its potential for climate reconstruction

A modern pollen dataset from China and Mongolia (18–52°N, 74–132°E) is investigated for its potential use in climate reconstructions. The dataset includes 2559 samples, 229 terrestrial pollen taxa and four climatic variables — mean annual precipitation (Pann): 35–2091mm, mean annual temperature (Tann): –12.1–25.8°C, mean temperature in the coldest month (Mtco): –33.8–21.7°C, and mean temperature in the warmest month (Mtwa): 0.3–29.8°C. Modern pollen–climate relationships are assessed using canonical correspondence analysis (CCA), Huisman–Olff–Fresco (HOF) models, the modern analogue technique (MAT), and weighted averaging partial least squares (WA-PLS). Results indicate that Pann is the most important climatic determinant of pollen distribution and the most promising climate variable for reconstructions, as assessed by the coefficient of determination between observed and predicted environmental values (r2) and root mean square error of prediction (RMSEP). Mtco and Mtwa may be reconstructed too, but with caution. Samples from different depositional environments influence the performance of cross-validation differently, with samples from lake sediment-surfaces and moss polsters having the best fit with the lowest RMSEP. The better model performances of MAT are most probably caused by spatial autocorrelation. Accordingly, the WA-PLS models of this dataset are deemed most suitable for reconstructing past climate quantitatively because of their more reliable predictive power.

Quaternary surface water temperature estimations: New diatom transfer functions for the Southern Ocean

Here we present an improvement of paleotemperature reconstructions for the Southern Ocean by combining new diatom data from the Pacific sector with published Atlantic and Indian sector reference data. The statistical analysis of 336 surface sediment samples recovered from a wide area of Southern Ocean environments defines a supra-regional reference data set for quantitative summer sea surface temperature (SSST) estimations. In situ temperature measurements covering the time span from approx. 1900 to 1991 were used as reference instead of more recent time series of satellite-derived data, possibly biased by ocean warming.Different transfer function (TF) models for the Imbrie and Kipp Method (IKM), the Modern Analog Technique (MAT), Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WAPLS) were tested. Best performance for IKM was obtained using the D336 set with 29 diatom taxa and three factors, resulting in root mean square error of prediction (RMSEP) of 0.833°C for SSST. MAT estimates were best with six analogs resulting in the lowest RMSEP of 0.812°C. WAPLS applied to D336 resulted in a RMSEP of 0.782°C. WA performed less well, expressed by a RMSEP of 0.974°C. Furthermore, two subsets for the Atlantic (D151) and the Pacific sectors (D107) were applied with IKM to test for the advantages of localized TFs. IKM-D151 and IKM-D107 performed comparably good as IKM-D336, with RMSEP of 0.71°C and 0.68°C, respectively.Application of the augmented reference data sets on two Pleistocene sediment records from the Atlantic (PS1768-8) and Pacific (PS58/271-1) sectors led to the best performance of IKM with D336, expressed by high overall communalities (>0.75) and fewer (PS1768-8) to no (PS58/271-1) no-analogs, compared to the regional data sets, proving IKM-D336 to deal better with higher assemblage variability. SSST estimates for both cores exhibit similar glacial/interglacial patterns for all four applied D336-based TF methods, with the best concordance between IKM and WAPLS.

Ecology of Testate Amoebae in an Amazonian Peatland and Development of a Transfer Function for Palaeohydrological Reconstruction

Tropical peatlands represent globally important carbon sinks with a unique biodiversity and are currently threatened by climate change and human activities. It is now imperative that proxy methods are developed to understand the ecohydrological dynamics of these systems and for testing peatland development models. Testate amoebae have been used as environmental indicators in ecological and palaeoecological studies of peatlands, primarily in ombrotrophic Sphagnum-dominated peatlands in the mid- and high-latitudes. We present the first ecological analysis of testate amoebae in a tropical peatland, a nutrient-poor domed bog in western (Peruvian) Amazonia. Litter samples were collected from different hydrological microforms (hummock to pool) along a transect from the edge to the interior of the peatland. We recorded 47 taxa from 21 genera. The most common taxa are Cryptodifflugia oviformis, Euglypha rotunda type, Phryganella acropodia, Pseudodifflugia fulva type and Trinema lineare. One species found only in the southern hemisphere, Argynnia spicata, is present. Arcella spp., Centropyxis aculeata and Lesqueresia spiralis are indicators of pools containing standing water. Canonical correspondence analysis and non-metric multidimensional scaling illustrate that water table depth is a significant control on the distribution of testate amoebae, similar to the results from mid- and high-latitude peatlands. A transfer function model for water table based on weighted averaging partial least-squares (WAPLS) regression is presented and performs well under cross-validation (r(2)(apparent)= 0.76, RMSE = 4.29; r(2)(jack)= 0.68, RMSEP =5.18). The transfer function was applied to a 1-m peat core, and sample-specific reconstruction errors were generated using bootstrapping. The reconstruction generally suggests near-surface water tables over the last 3,000 years, with a shift to drier conditions at c. cal. 1218-1273 AD.

Lateglacial and early-Holocene climate variability reconstructed from multi-proxy records on Andøya, northern Norway

We reconstruct mean July temperature (Tjul) from three sites on the island of Andøya, northern Norway for the period 15 000–9000 cal yr BP using three biotic proxies. A probabilistic indicator species approach (pdf method) was used for plant macrofossil data from all sites (M-Tjul). Reconstructions based on pollen (P-Tjul) (2 sites) and chironomids C-Tjul) (1 site) were done using weighted averaging and weighted-averaging partial least-squares, respectively. A sediment proxy for catchment glacier development was measured at the main site, Lusvatnet. The July temperature reconstructions from all the sites show a similar development through the deglaciation. An initial July temperature of 4 °C increased to a maximum of 7–8 °C during the Allerød at c.13 200 cal yr BP. There was no marked cooling at the start of the Younger Dryas (YD) chronozone, at Lusvatnet, C-Tjul decreased after 12 700 cal yr BP to a low of 6 °C at about 12 550 cal yr BP before increasing markedly around 12 400 cal yr BP. Conversely, P-Tjul rose slowly through the early YD. Both proxies exceeded the Allerød temperatures for around 300 years before decreasing towards a minimum of 6 °C at c. 12 000 cal yr BP. M-Tjul maintained a mean of c. 8 °C throughout the YD. Different sensitivities of proxies are discussed. Their different responses during the YD at the three sites, along with the glacial evidence, highlight the role of aridity. At c. 11 500 cal yr BP, July temperatures increased rapidly over Andøya to about 10 °C, and then rose gradually to maximum values of 12 °C at c. 9700 cal yr BP. The temperature reconstructions are consistent with the flow of Atlantic water into the Nordic Seas except during the YD, when variability in sea ice may have been more important. During the early Holocene there are some differences between sites, resulting from local site factors such as altitude and exposure, soil development, and catchment instability.

New tools for the reconstruction of Pleistocene Antarctic sea ice

Based on the quantitative analysis of diatom assemblages preserved in 274 surface sediment samples recovered in the Pacific, Atlantic and western Indian sectors of the Southern Ocean we have defined a new reference database for quantitative estimation of late-middle Pleistocene Antarctic sea ice fields using the transfer function technique. The Detrended Canonical Analysis (DCA) of the diatom data set points to a unimodal distribution of the diatom assemblages. Canonical Correspondence Analysis (CCA) indicates that not only winter sea ice (WSI) but also summer sea surface temperature (SSST) represent the most prominent environmental variables that control the spatial species distribution. To test the applicability of transfer functions for sea ice reconstruction in terms of concentration and occurrence probability we applied four different methods, the Imbrie and Kipp Method (IKM), the Modern Analog Technique (MAT), Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WAPLS), using logarithm-transformed diatom data and satellite-derived (1981–2010) sea ice data as a reference. The best performance for IKM results was obtained using a subset of 172 samples with 28 diatom taxa/taxa groups, quadratic regression and a three-factor model (IKM-D172/28/3q) resulting in root mean square errors of prediction (RMSEP) of 7.27% and 11.4% for WSI and summer sea ice (SSI) concentration, respectively. MAT estimates were calculated with different numbers of analogs (4, 6) using a 274-sample/28-taxa reference data set (MAT-D274/28/4an, -6an) resulting in RMSEP ranging from 5.52% (4an) to 5.91% (6an) for WSI as well as 8.93% (4an) to 9.05% (6an) for SSI. WA and WAPLS performed less well with the D274 data set, compared to MAT, achieving WSI concentration RMSEP of 9.91% with WA and 11.29% with WAPLS, recommending the use of IKM and MAT. The application of IKM and MAT to surface sediment data revealed strong relations to the satellite-derived winter and summer sea ice field. Sea ice reconstructions performed on an Atlantic- and a Pacific Southern Ocean sediment core, both documenting sea ice variability over the past 150,000yr (MIS 1–MIS 6), resulted in similar glacial/interglacial trends of IKM and MAT-based sea-ice estimates. On the average, however, IKM estimates display smaller WSI and slightly higher SSI concentration and probability at lower variability in comparison with MAT. This pattern is a result of different estimation techniques with integration of WSI and SSI signals in one single factor assemblage by applying IKM and selecting specific single samples, thus keeping close to the original diatom database and included variability, by MAT. In contrast to the estimation of WSI, reconstructions of past SSI variability remain weaker. Combined with diatom-based estimates, the abundance and flux pattern of biogenic opal represents an additional indication for the WSI and SSI extent.

Quantitative reconstruction of precipitation changes on the NE Tibetan Plateau since the Last Glacial Maximum – extending the concept of pollen source area to pollen-based climate reconstructions from large lakes

Abstract. Pollen records from large lakes have been used for quantitative palaeoclimate reconstruction, but the influences that lake size (as a result of species-specific variations in pollen dispersal patterns that smaller pollen grains are more easily transported to lake centre) and taphonomy have on these climatic signals have not previously been systematically investigated. We introduce the concept of pollen source area to pollen-based climate calibration using the north-eastern Tibetan Plateau as our study area. We present a pollen data set collected from large lakes in the arid to semi-arid region of central Asia. The influences that lake size and the inferred pollen source areas have on pollen compositions have been investigated through comparisons with pollen assemblages in neighbouring lakes of various sizes. Modern pollen samples collected from different parts of Lake Donggi Cona (in the north-eastern part of the Tibetan Plateau) reveal variations in pollen assemblages within this large lake, which are interpreted in terms of the species-specific dispersal and depositional patterns for different types of pollen, and in terms of fluvial input components. We have estimated the pollen source area for each lake individually and used this information to infer modern climate data with which to then develop a modern calibration data set, using both the multivariate regression tree (MRT) and weighted-averaging partial least squares (WA-PLS) approaches. Fossil pollen data from Lake Donggi Cona have been used to reconstruct the climate history of the north-eastern part of the Tibetan Plateau since the Last Glacial Maximum (LGM). The mean annual precipitation was quantitatively reconstructed using WA-PLS: extremely dry conditions are found to have dominated the LGM, with annual precipitation of around 100 mm, which is only 32% of present-day precipitation. A gradually increasing trend in moisture conditions during the Late Glacial is terminated by an abrupt reversion to a dry phase that lasts for about 1000 yr and coincides with "Heinrich event 1" in the North Atlantic region. Subsequent periods corresponding to the Bølling/Allerød interstadial, with annual precipitation (Pann) of about 350 mm, and the Younger Dryas event (about 270 mm Pann) are followed by moist conditions in the early Holocene, with annual precipitation of up to 400 mm. A drier trend after 9 cal. ka BP is followed by a second wet phase in the middle Holocene, lasting until 4.5 cal. ka BP. Relatively steady conditions with only slight fluctuations then dominate the late Holocene, resulting in the present climatic conditions. The climate changes since the LGM have been primarily driven by deglaciation and fluctuations in the intensity of the Asian summer monsoon that resulted from changes in the Northern Hemisphere summer solar insolation, as well as from changes in the North Atlantic climate through variations in the circulation patterns and intensity of the westerlies.

Pollen–climate transfer functions intended for temperate eastern Asia

Pollen data of 646 surface samples from northern China and Mongolia and climatic data from the relevant meteorological stations were collected in this study to develop more reliable pollen–climate transfer functions for temperate eastern Asia. Canonical correspondence analysis (CCA) was used to examine the pollen–climate relationships, and mean summer precipitation (MSP) and mean January temperature (MJaT) were inferred to be the first and second important factors controlling the spatial distribution of the surface pollen in the study area. The original dataset was screened with CCA for MSP and MJaT separately to detect anomalous samples that show the extreme values. The first screened dataset was established after excluding those anomalous samples, and the initial transfer function was generated using the weighted averaging partial least squares (WAPLS) method. The jackknife test was then applied to the WAPLS model for determining the optimum transfer function and for detecting large-residual samples, and the final transfer function was generated after removing the large-residual samples from the first screened dataset. The final dataset for MSP and MJaT consists of 428 and 419 samples, respectively. The root mean square errors of prediction for both WAPLS models are 34 mm and 2.7 °C, and the coefficients of determination are 0.85 and 0.73. This study suggests that the values of climatic parameters could be better estimated and the reliability of pollen–climate transfer functions would be significantly improved through removing anomalous and large-residual samples from the original dataset with mathematical methods.

Holocene climate variability reflected in diatom-derived sea surface temperature records from the subpolar North Atlantic

A detailed investigation of two deep-sea sediment cores from the Gardar Drift in the subpolar North Atlantic, cores MD99-2251 and MD99-2252, has been undertaken to determine the extent of Holocene climate variability reflected by changes in diatom floral abundances. Core MD99-2251 extends through the Holocene, while core MD99-2252 spans the last 7200 years. A new regional-based sea surface temperature (SST) calibration is derived using the weighted averaging partial least squares (WA-PLS) method based on 28 taxonomic categories within 53 coretops. WA-PLS-derived SST estimates indicate relatively small long-term SST changes of only 1–2°C during the Holocene. Notably, a well-defined thermal maximum is absent in the early Holocene record and the 8200-year event is not recognized as a discrete temperature minimum. However, lower SSTs between 8800 and 7800 years ago associated with the presence of sea ice and cold water species indicate an increased incursion of the subarctic water mass. A significant warming of ~2°C around 7000 years ago is the most unambiguous change in the SST records and is replicated in both cores. A brief interval of warmer sea surface conditions ~6000 years ago, associated with a Holocene maximum in North Atlantic Current indicator species, ended by 5300 years ago. Relatively muted SST variability is evident through the remainder of the Holocene.

Impact of Late Holocene climate variability and anthropogenic activities on Biscayne Bay (Florida, U.S.A.): Evidence from diatoms

Shallow marine ecosystems are experiencing significant environmental alterations as a result of changing climate and increasing human activities along coasts. Intensive urbanization of the southeast Florida coast and intensification of climate change over the last few centuries changed the character of coastal ecosystems in the semi-enclosed Biscayne Bay, Florida. In order to develop management policies for the Bay, it is vital to obtain reliable scientific evidence of past ecological conditions. The long-term records of subfossil diatoms obtained from No Name Bank and Featherbed Bank in the Central Biscayne Bay, and from the Card Sound Bank in the neighboring Card Sound, were used to study the magnitude of the environmental change caused by climate variability and water management over the last ~600yr. Analyses of these records revealed that the major shifts in the diatom assemblage structures at No Name Bank occurred in 1956, at Featherbed Bank in 1966, and at Card Sound Bank in 1957. Smaller magnitude shifts were also recorded at Featherbed Bank in 1893, 1942, 1974 and 1983. Most of these changes coincided with severe drought periods that developed during the cold phases of El Niño Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), or when AMO was in warm phase and PDO was in the cold phase. Only the 1983 change coincided with an unusually wet period that developed during the warm phases of ENSO and PDO. Quantitative reconstructions of salinity using the weighted averaging partial least squares (WA-PLS) diatom-based salinity model revealed a gradual increase in salinity at the three coring locations over the last ~600yr, which was primarily caused by continuously rising sea level and in the last several decades also by the reduction of the amount of freshwater inflow from the mainland. Concentration of sediment total nitrogen (TN), total phosphorus (TP) and total organic carbon (TOC) increased in the second half of the 20th century, which coincided with the construction of canals, landfills, marinas and water treatment plants along the western margin of Biscayne Bay. Increased magnitude and rate of the diatom assemblage restructuring in the mid- and late-1900s, suggest that large environmental changes are occurring more rapidly now than in the past.

Total phosphorus changes in New York and New Jersey lakes (USA) inferred from sediment cores

We used sediment diatoms to infer historical changes in total phosphorus (TP) concentration in 26 New York and New Jersey (USA) lakes using a top–bottom approach (i.e., the top of the core represents present conditions and the bottom represents past conditions). Detailed stratigraphic analyses were performed on cores from Greenwood (New Jersey and New York) and Cossayuna lakes (New York). TP reconstructions were performed using 2 weighted-averaging partial-least-squares (WA-PLS) transfer functions: (1) an interregional 278-lake calibration set from northeastern United States (NE-US model: r2 boot = 0.69, root mean square error of prediction RMSEP) = 1.8 μg/L); and (2) a regional 33-lake (callibration set from New Jersey and New York (NJ-NY model: r2 boot = 0.54, RMSEP = 1.5 μg/L). The NJ-NY model provided better estimates for modern TP but failed to provide reliable estimates for low TP values and reliable modern analogs for half of the bottom samples. Low TP concentrations were better inferred by the NE-US model, which included a higher number of oligotrophic lakes. Average change for all lakes was an increase of 2 to 7 μg/L TP. Greenwood and Cossayuna lakes inferred TP concentrations have increased up to 21 μg/L, presumably as a result of post-settlement anthropogenic activities. The inferred TP temporal changes provide important insight on the magnitude of cultural eutrophication. The use of 2 different inference models demonstrates the advantage of using a regional versus a larger-scale inference model in estimating the degree of change in historical lake TP. Careful interpretation of TP reconstructions can be used to provide reliable estimates of cost-effective targets for lake restoration programs.

Toward a recovery time: forest herbs insight related to anthropogenic acidification

AbstractAtmospheric deposition is a global concern contributing to soil acidification and biodiversity changes in forest ecosystems. Although acidifying deposition has decreased in the last decades in Europe, few evidence of ecosystem recovery from acidification has been reported until now. The objective of this study was to reconstruct spatiotemporal changes in soil pH across the entire French forest territory over the last 100‐year period through herb species assemblages. Data were collected from floristic databases resulting in a total of 120 216 plots covering French forests and spanning from 1910 to 2010. To define acidity figures, pH values were inferred from herb assemblages for each plot of the prediction dataset based on a weighted averaging partial least squares (WA‐PLS) model (R2 = 0.80, SD = 0.59 for the validation dataset). Spatiotemporal trends of mean pH changes were obtained by comparing plots with respect to the period (mean year of the period = 1933, 1966, 1984, 1997, 2007) and substrate (acidic and nonacidic forest areas). Bioindicated pH highlighted a decrease in soil pH in both acidic and nonacidic forest areas. The sharpest and most significant pH decrease occurred before 1984 in acidic areas, reaching 0.34 pH units. Subsequently, no significant changes were observed, with a tendency toward stabilization. By contrast, the pH decrease reached 0.19 pH units in nonacidic areas, only reaching significance between 1984 and 1997. Thereafter, we observed a slight and significant pH increase. Spatially, pH trends revealed a regionalized character of acidification regarding the substrate, which could not be related to the extent of deposition modeled by the European Monitoring and Evaluation Programme. Both temporal and spatial trends highlight the lagged responses of nonacidic areas compared with acidic areas. Hence, floristic reconstructed pH trends demonstrate a gradual cessation and recovery from acidification of French forests after a period of intense atmospheric pollution.

Comparing different calibration methods (WA/WA-PLS regression and Bayesian modelling) and different-sized calibration sets in pollen-based quantitative climate reconstruction

We compare a Bayesian modelling-based technique with weighted averaging (WA) and weighted averaging-partial least squares (WA-PLS) regression in pollen-based summer temperature transfer function calibration. We test the methods using a new, 113-sample calibration set from Estonia, Lithuania and European Russia, and a Holocene fossil pollen sequence from Lake Kharinei, a previously studied lake in northeast European Russia. We find WA-PLS to outperform WA, probably because of smaller edge-effect biases in the ends of the calibration set gradient. The Bayesian-based calibration models show further improved performance compared with WA-PLS in leave-one-out cross-validation, while additional h-block cross-validation shows the Bayesian method to be little affected by spatial autocorrelation. Comparison with independent climate proxies reveals, however, some clear biases in the Bayesian palaeotemperature reconstructions, likely reflecting in part some specific limitations of our calibration set. As the selected prior parameters can significantly affect both Bayesian cross-validation performance and reconstructions, there is a clear need to further test the Bayesian method in different geographic contexts and over different timescales, with special attention given to the selection of the most realistic priors in each situation. In general, our finding that statistically well-performing transfer functions may produce clearly differing palaeotemperature reconstructions urges caution in transfer function-based inferences. We additionally test a spatially restricted, 58-sample subset of the full 113-sample calibration set. We find some reduced biases with the smaller set, likely because of complex, partially bimodal responses of several taxa along the longer temperature gradient, ill-suited for calibration methods assuming unimodal responses to climate.

A 274-lake calibration data-set and inference model for chironomid-based summer air temperature reconstruction in Europe

A 274-lake calibration data-set for chironomid-based temperature reconstruction is presented which is based on the taxonomic amalgamation of a 117-lake data-set from Switzerland and a 157-lake data-set from Norway and Svalbard. Taxonomic consistency of the two data-sets was ensured by joint microscope sessions by the two involved analysts, re-identifying chironomid assemblages in the Swiss data-set to reach an identical taxonomic resolution as in the Norwegian data, and by double-checking selected samples of the Norwegian calibration data-set. The combined Swiss-Norwegian calibration data-set contains information on the distribution of 154 chironomid taxa over a July air temperature range of 3.5–18.4 °C, a pH range of 4.7–8.8, and an altitudinal range of 5–2815 m asl from lakes in temperate, subarctic, arctic, and alpine environments. Inference models developed based on this data-set using weighted averaging-partial least squares (WA-PLS) regression outperformed inference models based on maximum likelihood regression. After outlier deletion WA-PLS regression predicted July air temperature with a bootstrapped (cross-validated) root mean squared error of prediction (RMSEP) of 1.40 °C. Inference models developed from the separate regional data-sets have an RMSEP of 1.16 and 1.43 °C for the Norwegian and the Swiss calibration data-set, respectively. The WA-PLS inference model based on the Norwegian data-set adequately predicted July air temperature based on chironomid assemblages in the Swiss data-set (RMSEP 2.05 °C; r 2 0.74). In contrast, the WA-PLS model based on the Swiss chironomid assemblages performed poorly in inferring July air temperatures based on the Norwegian chironomid assemblages (RMSEP 2.70 °C; r 2 0.39). We attribute this discrepancy to the large proportion of chironomid taxa in Norwegian samples not represented in the Swiss data-set, the larger range of both pH and lake types included in the Norwegian calibration data-set, and the lack of some chironomid taxa with an arctic and boreal distribution in the Swiss data-set. The WA-PLS inference model based on the combined Swiss-Norwegian calibration data-set is the largest taxonomically consistent chironomid-based inference model available to date and outperforms other existing models if the r 2 and RMSEP relative to the overall temperature gradient are examined. We demonstrate that the combined model can reconstruct a larger range of temperatures when applied to fossil assemblages than models based on the Norwegian or Swiss calibration data-sets only. The combined data-set includes the majority of chironomid taxa expected in late Pleistocene and Holocene sediments of lakes from Northern, Eastern, and Central Europe as well as from southern European mountain lakes. The newly developed WA-PLS inference model is therefore well suited for developing continental-scale reconstructions of late Quaternary temperature change based on chironomid records from different parts of Europe.

Examining 20th century water quality and ecological changes in the Lake of the Woods, Ontario, Canada: A paleolimnological investigation

Comparisons between diatom assemblages preserved in modern and pre-industrial sediments were made to provide a lake-wide paleolimnological assessment of environmental change in 17 sites located throughout the Ontario portion of the Lake of the Woods (LoW). Diatom changes were consistent across all sites, although the magnitude of these changes varied along a trophic gradient (i.e., main channel sites versus isolated bays). The most notable taxonomic shift was towards a higher relative abundance of small, centric Cyclotella taxa and other planktonic, pennate diatoms (e.g., Asterionella formosa, Fragilaria crotonensis) in the modern sediments, with corresponding lower relative abundances of heavily silicified Aulacoseira taxa and small benthic Fragilaria taxa. To aid in determining whether changes in nutrients can explain the diatom trends, weighted-averaging partial-least-squares (WA-PLS) techniques were used to develop a diatom-based inference model to reconstruct changes in total phosphorus (TP) concentrations. Diatom-inferrred TP (DI-TP) reconstructions revealed that 88% of the sites showed either no change or a slight, but not significant decline in DI-TP since pre-industrial times. Diatom-based inferences suggest that TP concentrations at many sites in the Ontario portion of the LoW were moderately elevated in nutrients prior to any major human disturbances (i.e., pre-1850). Results suggest that substantial increases in temperature over the last few decades, and the associated changes to ice cover and water column properties, have likely exacerbated the effects of existing stressors on the system and were key factors influencing a lake-wide restructuring of the diatom communities over the past ca. 150 years.

Paleobathymetric history of the Western Mediterranean Sea shelf during the latest glacial period and the Holocene: Quantitative reconstructions based on foraminiferal transfer functions

We present results of the palaeobathymetric evolution in cool-water shelf carbonate environments of the Western Mediterranean Sea during the latest glacial period and the Holocene. For this quantitative approach, we used the Weighted Averaging-Partial Least Squares (WA-PLS) regression method for the development of benthic foraminifera-based transfer functions, and the Modern Analog Technique (MAT) to test the robustness of the models. Transfer functions were created on the basis of recent benthic foraminiferal assemblages in surface samples (modern data sets), and were then applied to fossil samples in sediment cores from the Alboran Platform, the Oran Bight and the Mallorca Shelf. The performance of the WA-PLS transfer functions suggests a close relationship between the observed and estimated water depths in the modern data sets with a precision of ~ 11 m (Root Mean Squared error of Prediction (RMSEP)) within water depths ranging from 38 to 160 m. The estimated relative sea-level histories of the Alboran Platform and the Mallorca Shelf show a total relative sea-level rise of ~ 50 m with sample-specific errors of approximately ±7 m and generally match the global and regional Mediterranean Sea records. Inconsistencies in the paleobathymetric estimates are strongly attributed to redeposition processes, dating problems and to minor effects of an under-representation of modern samples from shallower water depths.

A modern pollen–temperature calibration data set from Korea and quantitative temperature reconstructions for the Holocene

Modern surface pollen samples from the mountains along the east coast of Korea were used to derive pollen–temperature transfer functions. Detrended correspondence analysis (DCA) and detrended canonical correspondence analysis (DCCA) were performed to test the robustness of the relationship between the modern pollen assemblages and temperatures. The relationship exhibited a high correlation (DCA, r = −0.887; DCCA, r = −0.908). The performance of the best weighted averaging partial least squares (WA-PLS) transfer function was statistically good ([Formula: see text] = 0.74; RMSEP = 1.79°C). In order to quantitatively reconstruct the Holocene temperature changes, the best model was applied to five fossil pollen records produced from four coastal lagoons of the east coast and one high-altitude peat bog. Anomalies calculated from reconstructed paleotemperature data were combined to generate a synthesis temperature reconstruction for the east coast of Korea, in which the ‘Medieval Warm Period’, ‘Little Ice Age’, and ‘Migration Period’ were clearly shown. This study demonstrated the validity of the quantitative reconstruction of paleotemperature using the pollen–climate transfer function, even in heavily human-impacted areas such as the Korean Peninsula.

Chironomid-based inference models for estimating mean July air temperature and water depth from lakes in Yakutia, northeastern Russia

We investigated the subfossil chironomid fauna of 150 lakes situated in Yakutia, northeastern Russia. The objective of this study was to assess the relationship between chironomid assemblage composition and the environment and to develop chironomid inference models for quantifying past regional climate and environmental changes in this poorly investigated area of northern Russia. The environmental data and sediment samples for chironomid analysis were collected in 5 consecutive years, 2003–2007, from several regions of Yakutia. The lakes spanned wide latitudinal and longitudinal ranges and were distributed through several environmental zones (arctic tundra, typical tundra, steppe-tundra, boreal coniferous forest), but all were situated within the zone of continuous permafrost. Mean July temperature (TJuly) varied from 3.4°C in the Laptev Sea region to 18.8°C in central Yakutia near Yakutsk. Water depth (WD) varied from 0.1 to 17.1 m. TJuly and WD were identified as the strongest predictor variables explaining the chironomid communitiy composition and distribution of the taxa in our data set. Quantitative transfer functions were developed using two unimodal regression calibration techniques: simple weighted averaging (WA) and weighted averaging partial least squares (WA-PLS). The two-component TJuly WA-PLS model had the best performance. It produced a strong coefficient of determination (r2boot = 0.87), root mean square error of prediction (RMSEP = 1.93), and max bias (max biasboot = 2.17). For WD, the one-component WA-PLS model had the best performance (r2boot = 0.62, RMSEP = 0.35, max biasboot = 0.47).

Ecology and distribution of diatoms in Biscayne Bay, Florida (USA): Implications for bioassessment and paleoenvironmental studies

The spatial and temporal distribution of planktonic, sediment-associated and epiphytic diatoms among 58 sites in Biscayne Bay, Florida was examined in order to identify diatom taxa indicative of different salinity and water quality conditions, geographic locations and habitat types. Assessments were made in contrasting wet and dry seasons in order to develop robust assessment models for salinity and water quality for this region. We found that diatom assemblages differed between nearshore and offshore locations, especially during the wet season when salinity and nutrient gradients were steepest. In the dry season, habitat structure was primary determinant of diatom assemblage composition. Among a suite of physicochemical variables, water depth and sediment total phosphorus (STP) were most strongly associated with diatom assemblage composition in the dry season, while salinity and water total phosphorus (TP) were more important in the wet season. We used indicator species analysis (ISA) to identify taxa that were most abundant and frequent at nearshore and offshore locations, in planktonic, epiphytic and benthic habitats and in contrasting salinity and water quality regimes. Because surface water concentrations of salts, total phosphorus, nitrogen (TN) and organic carbon (TOC) are partly controlled by water management in this region, diatom-based models were produced to infer these variables in modern and retrospective assessments of management-driven changes. Weighted averaging (WA) and weighted averaging partial least squares (WA-PLS) regressions produced reliable estimates of salinity, TP, TN and TOC from diatoms ( r 2 = 0.92, 0.77, 0.77 and 0.71, respectively). Because of their sensitivity to salinity, nutrient and TOC concentrations diatom assemblages should be useful in developing protective nutrient criteria for estuaries and coastal waters of Florida.

The relationship between water quality and chironomid distribution in Finland—A new assemblage-based tool for assessments of long-term nutrient dynamics

Abstract Relationship between water quality variables and distribution, diversity and abundance of sedimentary chironomids (Diptera: Chironomidae) were examined in 51 limnologically different shallow lakes in Finland. The objective was to identify which of the water quality parameters influenced chironomids the most and to explore the potential of developing a palaeoecological tool to infer past changes in water quality for the use of lake management in conservation, preservation and restoration projects. In addition, taxon-specific optima and tolerances were calculated to identify indicators for ultraoligotrophic–hypereutrophic Finnish lakes. The statistical tests indicated that the chironomid assemblages were closely related to water quality. Of the examined environmental variables total phosphorus (TP), total nitrogen (TN), colour, turbidity and hypolimnetic oxygen were the most important explanatory variables. Because autumnal epilimnetic TP had the highest eigenvalue (λ1:λ2) ratio, which indicates the relative significance of particular variable in explaining the variance in the species data, and lowest statistical significance level, it was considered to have the greatest potential for the development of a calibration model for quantitative inferences of past limnological conditions. In addition to the complete model, a reduced model using 41 lakes was developed that is independent of covariance with temperature. Of the tested model types, weighted averaging-partial least squares (WA-PLS) had the strongest relationship between observed and inferred TP values together with lowest error of prediction and maximum bias showing favourable model performance. In general, the results of taxon-specific indicator value showed close agreement with previous data. The results provided coherent autecological and synecological data that can be used in qualitative assessments of water quality and ecological status of lakes and most importantly as a basis for the new quantitative tool to be used in palaeolimnological studies and evaluations of TP reference conditions.

How does taxonomic resolution affect chironomid-based temperature reconstruction?

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 (r2) between inferred and observed values improved considerably from the lowest taxonomic resolution level (WA: RMSEP 1.91°C, r2 0.78; WA-PLS: RMSEP 1.59°C, r2 0.86) to the highest taxonomic resolution level (WA: RMSEP 1.66°C, r2 0.84; WA-PLS: RMSEP 1.41°C, r2 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.