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 (T_July) 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. T_July 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 T_July WA-PLS model had the best performance. It produced a strong coefficient of determination (r ² _boot = 0.87), root mean square error of prediction (RMSEP = 1.93), and max bias (max bias_boot = 2.17). For WD, the one-component WA-PLS model had the best performance (r ² _boot = 0.62, RMSEP = 0.35, max bias_boot = 0.47).     

Diatom-environmental relationships in 64 alkaline southeastern Ontario (Canada) lakes: a diatom-based model for water quality reconstructions

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; RMSE_boot = 0.010 mg L^-1). Other variables, including pH (r² = 0.702; RMSE = 0.208; r² _boot = 0.485; RMSE_boot = 0.234), TN (r² = 0.574; RMSE = 0.0899 mg L^-1; r² _boot = 0.380; RMSE_boot = 0.127 mg L^-1) and MaxZ (r² = 0.554; RMSE = 1.05 m; r² _boot = 0.380; RMSE_boot = 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.     

A diatom dataset and diatom-salinity inference model for southeast Australian estuaries and coastal lakes

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.     

Diatom and chrysophyte functions and inferences of post-industrial acidification and recent recovery trends in Killarney lakes (Ontario, Canada)

The surface sediment diatom and chrysophyte assemblages from 33 Sudbury lakes were added to our published 72 lake data set to expand and refine the diatom and chrysophyte-based inference models that we had earlier developed for this region. Our calibration data set now includes 105 lakes, representing gradients for multiple environmental variables (e.g., lakewater pH, metals, and transparency). The revised models are based on the weighted averaging calibration and regression approach and include bootstrap error estimates. The pH model was the strongest (r² _boot = 0.75, RMSE _boot = 0.50). The chrysophyte-inferred pH model (r² _boot = 0.79, RMSE _boot = 0.48) that we developed was as robust as the diatom pH model. Diatom and chrysophyte inferred pH models were then applied to top (surface sediments representing current conditions) and bottom (generally from > 30 cm deep representing pre-industrial conditions) sediment diatom and chrysophyte assemblages of 19 Killarney area lakes near Sudbury. The top and bottom inferred pH results were compared to early-1970s measured pH data. These data suggest that, although many of the poorly buffered Killarney lakes had experienced acidification, marked pH recovery has occurred in many lakes within the last 25 years. Despite the stunning pH recovery, the present-day diatom and chrysophyte assemblages are significantly different from assemblages present during pre-industrial times. Our results suggest that biological recovery may require more time than chemical recovery. It is also likely that these lakes may never recover biologically because other anthropogenic stressors (e.g., climate warming and increased exposure to UV-B radiation) may now have greater influence on biological communities in Killarney/Sudbury area lakes than acidification.     

A northwest North American training set: distribution of freshwater midges in relation to air temperature and lake depth

Freshwater midges, consisting of Chironomidae, Chaoboridae and Ceratopogonidae, were assessed as a biological proxy for palaeoclimate in eastern Beringia. The northwest North American training set consists of midge assemblages and data for 17 environmental variables collected from 145 lakes in Alaska, British Columbia, Yukon, Northwest Territories, and the Canadian Arctic Islands. Canonical correspondence analyses (CCA) revealed that mean July air temperature, lake depth, arctic tundra vegetation, alpine tundra vegetation, pH, dissolved organic carbon, lichen woodland vegetation and surface area contributed significantly to explaining midge distribution. Weighted averaging partial least squares (WA-PLS) was used to develop midge inference models for mean July air temperature (r _boot² = 0.818, RMSEP = 1.46°C), and transformed depth (ln (x+1); r _boot² = 0.38, and RMSEP = 0.58).     

Paleotemperature reconstruction in tropical Africa using fossil Chironomidae (Insecta: Diptera)

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.     

Spatial variability of chironomid death assemblages in the surface sediments of a fluctuating tropical lake (Lake Naivasha,Kenya)

Studies addressing within-lake variability of fossil chironomid assemblages are very few, and all deal with hydrologically stable temperate lakes where the question of spatial integration mostly relates to the mixing of faunal assemblages associated with shallow, warm-water habitat and those associated with deeper, cold-water habitat. Here we study within-lake variability of surface-sediment chironomid assemblages in the fairly large (∼100–170 km² since 1983) and shallow (Z _max = 5–8 m) fluctuating tropical lake basin of Lake Naivasha, Kenya, and compare the patterns observed with those in two smaller adjacent basins, one similarly shallow (Lake Oloidien, 5.1–5.7 km2, 5–8 m), the other deep and stratified (Crescent Island Crater, 1.9 km², 14–17 m). Chironomid assemblages were analysed in core-top samples and surface sediments along inshore to offshore transects, and how well individual samples represented the total (basin-wide mean) subfossil assemblage was considered both in terms of taxon richness and taxon percent composition. Within-lake variability of subfossil chironomid concentrations (with generally higher absolute values in nearshore samples) could be explained by effects of sediment winnowing and focusing, whereas between-lake variability reflected their relative susceptibility to wind-driven sediment disturbance or bottom anoxia. In all study lakes, but most significantly in lakes Naivasha and Oloidien, species distribution in the subfossil chironomid assemblages showed a strong nearshore to offshore gradient, which in these shallow lakes, reflects the dominant control of substrate and food quality on species distribution in the living community. Particularly in the larger basins, nearshore samples better represented the total lake assemblage than offshore samples, because the former always contained a component of mud-dwelling species whereas the latter often lacked a component of macrophyte-dwelling species. Our results show that although sedimentation dynamics in the shallow, wind-stressed Lake Naivasha is dominated by frequent resuspension and random sediment redistribution, the near- to offshore gradient in chironomid habitat remains imprinted on subfossil assemblages. We conclude that also in shallow fluctuating lakes, given sufficient size, incomplete pre-burial spatial integration of habitat-specific chironomid assemblages can be exploited for within-lake calibration of environmental gradients.     

Development of a chironomid-based air temperature inference model for the central Canadian Arctic

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.     

A model for inferring dissolved organic carbon (DOC) in lakewater from visible-near-infrared spectroscopy (VNIRS) measures in lake sediment

We developed an inference model to infer dissolved organic carbon (DOC) in lakewater from lake sediments using visible-near-infrared spectroscopy (VNIRS). The inference model used surface sediment samples collected from 160 Arctic Canada lakes, covering broad latitudinal (60–83°N), longitudinal (71–138°W) and environmental gradients, with a DOC range of 0.6–39.6 mg L⁻¹. The model was applied to Holocene lake sediment cores from Sweden and Canada and our inferences are compared to results from previous multiproxy paleolimnological investigations at these two sites. The inferred Swedish and Canadian DOC profiles are compared, respectively, to inferences from a Swedish-based VNIRS-total organic carbon (TOC) model and a Canadian-based diatom-inferred (Di-DOC) model from the same sediment records. The 5-component Partial Least Squares (PLS) model yields a cross-validated (CV) R_CV² R_{CV}^{2}  = 0.61 and a root mean squared error of prediction (RMSEP _CV ) = 4.4 mg L⁻¹ (11% of DOC gradient). The trends inferred for the two lakes were remarkably similar to the VNIRS-TOC and the Di-DOC inferred profiles and consistent with the other paleolimnological proxies, although absolute values differed. Differences in the calibration set gradients and lack of analogous VNIRS signatures in the modern datasets may explain this discrepancy. Our results corroborate previous geographically independent studies on the potential of using VNIRS to reconstruct past trends in lakewater DOC concentrations rapidly.     

Tracking Holocene environmental changes in an alpine lake sediment core: application of regional diatom calibration, geochemistry, and pollen

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, RMSEP_boot= 0.131), and a thermistor measurements-based PLS model for A _mix (R ² _boot= 0.71, RMSEP_boot= 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.     

Diatom habitats,species diversity and water-depth inference models across surface-sediment transects in Worth Lake,northwest Ontario,Canada

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 - PLS}² = 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.     

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

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

Multi-indicator conductivity transfer functions for Quaternary palaeoclimate reconstruction

Diatoms (Bacillariophyceae; single-celled algae) and ostracods (Ostracoda; shelled microcrustacea) are known for their sensitivity to salinity. In palaeolimnology, the potential has yet to be tested for quantifying past salinity, lake level, and by inference, climate change, by application of multiple-indicator transfer functions. We used weighted averaging techniques to derive diatom (n = 91; r ²  = 0.92) and ostracod (n = 53; r ²  = 0.83) conductivity transfer functions from modern diatom, ostracod and water chemistry data collected in lakes of central, western and northern Turkey. Diatoms were better represented across the full gradient than ostracods, at intermediate levels of conductivity in particular, but both transfer functions were statistically robust. Because transfer functions are not infallible, we further tested the strength and simplicity of salinity response and the potential for identifying characteristic associations of diatom and ostracod taxa in different parts of the salinity gradient, to improve palaeoclimate reconstruction. We identified a subset of 51 samples that contained both diatoms and ostracods, collected at the same time from the same habitat. We used Two-Way Indicator Species Analysis of a combined diatom-ostracod data set, transformed to achieve numerical equivalence, to explore distributions in more detail. A clear ecological threshold was apparent at ~3 g l⁻¹ salinity, rather than at 5 g l⁻¹, the boundary used by some workers, equating to the oligosaline-mesosaline boundary. Other salinity boundaries were poorly defined, indicating lack of a simple, well-defined salinity response. We did, however, define characteristic associations of taxa, to facilitate the distinction to be drawn between a hydrologically open, fresh lake and an oligosaline lake, in palaeoenvironmental reconstruction. Over the rest of the salinity gradient, we highlighted the potential for the multi-proxy approach to strengthen ostracod-based reconstruction in particular, to overcome the problem of broad apparent tolerance ranges in common halophilic taxa such as Limnocythere inopinata, which often dominate in low-diversity fossil assemblages. The combination of multi-proxy quantitative reconstruction, complemented by qualitative understanding of ecological responses generated by the analysis, remains a powerful tool in Quaternary palaeoclimate research.     

Diatom-based total phosphorus (TP) and pH transfer functions for the Irish Ecoregion

A 72-lake diatom training set was developed for the Irish Ecoregion to examine the response of surface sediment diatom assemblages to measured environmental variables. A variety of multivariate data analyses was used to investigate environmental and biological data structure and their inter-relationships. Of the variables used in determining a typology for lakes in the Irish Ecoregion, alkalinity was the only one found to have a significant effect on diatom assemblages. A total of 602 diatom taxa were identified, with 233 recorded at three or more sites with abundances ≥1%. Generally diatom data displayed a high degree of heterogeneity at the species level and non-linear ecological responses. Both pH and total phosphorus (TP) (in the ranges of 5.1–8.5 and 4.0–142.3 μg l⁻¹ respectively) were shown to be the most significant variables in determining the surface sediment diatom assemblages. The calibration models for pH and TP were developed using the weighted averaging (WA) method; data manipulation showed strong influences on model performances. The optima WA models based on 70 lakes produced a jack-knifed coefficient of determination (r ² _jack) of 0.89 with a root mean squared error (RMSEP) of 0.32 for pH and r ² _jack of 0.74 and RMSEP of 0.21 (log₁₀ μg l⁻¹) for TP. Both models showed strong performances in comparison with existing models for Ireland and elsewhere. Application of the pH and TP transfer functions developed here will enable the generation of quantitative water quality data from the expanding number of palaeolimnological records available for the Irish Ecoregion, and thus facilitate the use of palaeolimnological approaches in the reconstruction of past lake water quality, ecological assessment and restoration.     

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

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

Diatom–environment relationships and a transfer function for conductivity in lakes of the Badain Jaran Desert, Inner Mongolia, China

We describe a dataset of 26 modern diatom samples and associated environmental variables from the Badain Jaran Desert, northwest China. The influence of electrical conductivity (EC) and other variables on diatom distribution was explored using multivariate analyses and generalized additive modeling of species response curves. A transfer function was derived for EC, the variable with the largest unique effect on diatom variance, as shown by partial canonical correspondence analysis. Weighted-averaging partial least squares regression and calibration provided the best model, with a high coefficient of determination ( $ {\text{r}}_{\text{boot}}^{2} $  = 0.91) and low prediction error (RMSEP_boot = 0.136 log₁₀ μS cm^?1). To assess its potential for palaeosalinity and palaeoclimate reconstructions, the EC transfer function was applied to fossil diatom assemblages from ²¹⁰Pb-dated short sediment cores collected from two subsaline lakes of the Badain Jaran Desert. The diatom-inferred (DI) EC reconstructions were compared with meteorological data for the past 50 years and with remote sensing data for the period AD 1990–2012. Changes in DI–EC were small and their relationship with climate was weak. Moreover, remote sensing data indicate that the surface areas and water depths of these lakes did not change, which suggests that water loss by evaporation is compensated by groundwater inflow. These results suggest that the response of these lakes to climate change is mediated by non-climatic factors such as the hydrogeological setting, which control recharge from groundwater, and may be non-linear and non-stationary.     

Reconstructing temperature at Egelsee,Switzerland, using North American and Swedish chironomid transfer functions: potential and pitfalls

The temperature reconstruction obtained from chironomids preserved in the sediment of Egelsee, Switzerland, was partially flawed by the low percentages of fossil taxa represented in the Swiss calibration set (Larocque-Tobler et al. 2009a). Transfer functions (TFs) from other regions, which allow a good representation of the fossil taxa (>80%), could be applied to the fossil assemblages of Egelsee. First, the validity of using two (a Swedish and a North American (NA)) TFs was tested by comparing the chironomid-inferred temperatures with instrumental data. Since good relationships (r _Pearson = 0.71 and 0.61, p = 0.001 for the NA and Swedish TFs, respectively) were obtained, these two models were used to reconstruct the Late Glacial and early Holocene periods at Egelsee. Reconstructions using both models showed clear cold periods during the Younger Dryas and the so-called 8,200 calibrated years BP event. However, the amplitude of changes during these periods was higher when the NA transfer function was used, probably due to the fact that 37% of the taxa in the core had temperature optima colder in the NA than in the Swedish and Swiss models. The results indicate that TFs from other regions can be applied when they are based on samples with good modern analogues, however, caution should be taken when the amplitude of temperature changes is considered.     

Diatom-based models for reconstructing past water quality and productivity in New Zealand lakes

The trophic status of lakes in New Zealand is, on average, low compared to more densely populated areas of the globe. Despite this, trends of eutrophication are currently widespread due to recent intensification in agriculture. In order to better identify baseline productivity and establish long-term trends in lake trophic status, diatom-based transfer functions for productivity-related parameters were developed. Water quality data and surface sediment diatom assemblages from 53 lakes across the North and South Islands of New Zealand were analysed to determine species responses to the principal environmental gradients in the data set. Repeat sampling of water chemistry over a 12-month period enabled examination of species responses to annual means as well as means calculated for stratified and mixed periods. Variables found to be most strongly correlated with diatom species distributions were chlorophyll a (Chl a), total phosphorus (TP), dissolved reactive phosphorus (DRP), ionic concentration (measured as electrical conductivity (EC)) and pH. These variables were used to develop diatom-based transfer functions using weighted averaging regression and calibration (simple, tolerance down-weighted and with partial least squares algorithm applied). Overall, models derived for stratified means were weaker than those using annual or isothermal means. For specific variables, the models derived for the isothermal mean of EC (WA-tol r²_jack = 0.79; RMSEP = 0.15 log₁₀ S cm^–1),the annual mean of pH (WA r²_jack = 0.72; RMSEP = 0.25 pH units) and the isothermal mean of Chl a (WA r²_jack = 0.71; RMSEP = 0.18 log₁₀ mg m^–3 Chl a) performed best. The models derived for TP were weak in comparison (for the annual mean of TP: WA r²_jack = 0.50; RMSEP = 0.24 log₁₀ mg m^–3 TP) and residuals on estimates for this model were correlated with several other water quality variables, suggesting confounding of species responses to TP concentrations. The model derived for the isothermal mean of DRP was relatively strong (WA-tol r²_jack = 0.78; RMSEP = 0.17 log₁₀ mg m^–3 DRP); however, residual values for this model were also found to be strongly correlated with several other water quality variables. It is concluded that the poor performance of the TP and DRP transfer functions relative to that of the Chl a model reflects the coexistence of nitrogen and phosphorus limitation within the lakes in the data set. In spite of this, the suite of transfer functions developed from the training set is regarded as a valuable addition to palaeolimnological studies in NewZealand.     

Environmental controls on modern chironomid faunas from NW Iceland and implications for reconstructing climate change

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.     

<Emphasis Type="Italic">Bosmina</Emphasis> remains in lake sediment as indicators of zooplankton community composition

We measured Bosmina spp. mucro and antennule lengths in surface sediment samples from Wisconsin lakes to test whether such measures could be used to reconstruct zooplankton community composition and size structure in paleolimnological studies. Our data set included 58 lakes of various depths, water chemistry, trophic state, macrophyte cover, and zooplankton community composition. We used non-metric multidimensional scaling ordination (NMS) and simple correlation analysis to assess whether mucro and antennule measurements reflect the zooplankton community size structure. Bosmina mucro length (r = 0.727, p < 0.05) and antennule length (r = 0.360, p < 0.05) correlated with the NMS axis, which essentially represents zooplankton community size structure. Bosmina mucro length correlated positively with the abundance of the large-bodied zooplankter Epischura lacustris (r = 0.364, p < 0.01), as well as Diacyclops thomasi (r = 0.256, p < 0.05), and Leptodiaptomus minutus (r = 0.578, p ≤ 0.001), but correlated negatively with the abundance of the small-bodied zooplankter Tropocyclops prasinus (r = −0.385, p < 0.01). Bosmina antennule length correlated positively with the abundance of L. minutus (r = 0.344, p < 0.01) and negatively with T. prasinus (r = −0.258, p < 0.05). This broad, spatial scale assessment supports the use of Bosmina mucro and antennule lengths as a proxy for zooplankton community size structure. Mucro length is a stronger indicator of zooplankton community size structure as seen in its strong correlation with the NMS axis 1 and the significant correlations with abundance of predatory copepods.