The modern distribution of chironomid sub-fossils (Insecta: Diptera) in the Sierra Nevada, California: Potential for paleoclimatic reconstructions

Surface lake sediment was recovered from 57 lakes along an elevation gradient in the central, eastern Sierra Nevada of California. The surface sediment was analysed for subfossil chironomid remains in order to assess the modern distribution of chironomids in the region. The lakes sampled for the calibration dataset were between 2.0 and 40.0 m in depth, spanned an altitudinal gradient of 1360 m and a surface water temperature gradient of approximately 14 °C. Redundancy analysis (RDA) identified that five of the measured environmental variables – surface water temperature, elevation, depth, strontium, particulate organic carbon – accounted for a statistically significant amount of the variance in chironomid community composition. Quantitative transfer functions, based on weighted-averaging (WA), partial least squares (PLS) and weighted-averaging partial least squares (WA-PLS), were developed to estimate surface water temperature from the chironomid assemblages. The best model was a WA model with classical deshrinking, which had a relatively high coefficient of determination (r² = 0.73), low root mean square error of prediction (RMSEP = 1.2 °C) and a low maximum bias (0.90 °C). The results from this study suggest that robust quantitative estimates of past surface water temperature can be derived from the application of these models to fossil chironomid assemblages preserved in late-Quaternary lake sediment in this region.     

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).     

The potential of site-specific and local chironomid-based inference models for reconstructing past lake levels

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.     

Modelling diatom responses to climate induced fluctuations in the moisture balance in continental Antarctic lakes

The water chemistry of lake systems on the edge of the Antarctic continent responds quickly to changes in the moisture balance. This is expressed as increasing salinity and decreasing lake water level during dry periods, and the opposite during wet periods. The diatom composition of the lakes also changes with these fluctuations in salinity and lake water depth. This is important, as their siliceous remains become incorporated into lake sediments and can provide long-term records of past salinity using transfer functions. In order to develop transfer functions, diatoms and water chemistry data were inter-calibrated from five different East Antarctic oases, namely the Larsemann Hills, the Bølingen Islands, the Vestfold Hills, the Rauer Islands and the Windmill Islands. Results indicate that salinity is the most important environmental variable explaining the variance in the diatom flora in East Antarctic lakes. In oligo- saline lakes the variance is mainly explained by lake water depth. This dataset was used to construct a weighted averaging transfer function for salinity in order to infer historical changes in the moisture balance. This model has a jack-knifed r² of 0.83 and a RMSEP of 0.31. The disadvantage of this transfer function is that salinity changes in oligo-saline lakes are reconstructed inaccurately due to the edge effect and due to the low species turnover along the salinity gradient at its lower end. In order to infer changes in the moisture balance in these lakes, a second transfer function using weighted averaging partial least squares (with two components) for depth was constructed. This model has a jack-knifed r² of 0.76 and a RMSEP of 0.22. Both transfer functions can be used to infer climate driven changes in the moisture balance in lake sediment cores from oligo-, hypo-, meso- and hyper-saline lakes in East Antarctic oases between 102–75°E. The transfer function for lake water depth is promising to track trends in the moisture balance of small freshwater lakes, where changes in shallow and deep-water sediments are readily reflected in changing diatom composition.     

Chironomids as indicators of climate change: a 100‐lake training set from a subarctic region of northern Sweden (Lapland)

Multivariate numerical analyses (DCA, CCA) were used to study the distribution of chironomids from surface sediments of 100 lakes spanning broad ecoclimatic conditions in northern Swedish Lapland. The study sites range from boreal forest to alpine tundra and are located in a region of relatively low human impact. Of the 19 environmental variables measured, ordination by CCA identified mean July air temperature as one of the most significant variables explaining the distribution and the abundance of chironomids. Lossonignition (LOI), maximum lake depth and mean January air temperature also accounted for significant variation in chironomid assemblages. A quantitative transfer function was created to estimate mean July air temperature from sedimentary chironomid assemblages using weightedaveraging partial least squares regression (WAPLS). The coefficient of determination was relatively high (r² = 0.65) with root mean squared error of prediction (RMSEP, based on jack-knifing) of 1.13 °C and maximum bias of 2.1 °C, indicating that chironomids can provide useful quantitative estimates of past changes in mean July air temperature. The paper focuses mainly on the relationship between chironomid composition and July air temperature, but the relationship to LOI and depth are also discussed.     

Diatom-based water chemistry reconstructions from northern Sweden: a comparison of reconstruction techniques

The diatom composition in surface sediments from 119 northern Swedish lakes was studied to examine the relationship with lake-water pH, alkalinity, and colour. Diatom-based predictive models, using weighted-averaging (WA) regression and calibration, partial least squares (PLS) regression and calibration, and weighted-averaging partial least squares (WA-PLS) regression and calibration, were developed for inferences of water chemistry conditions. The non-linear response between the diatom assemblages and pH and alkalinity was best modelled by weighted-averaging methods. The lowest prediction error for pH was obtained using weighted averaging, with or without tolerance downweighting. For alkalinity there was still some information in the residual structure after extracting the first weighted-averaging component, which resulted in a slight improvement of predictions when using a two component WA-PLS model. The best colour predictions were obtained using a two component PLS model. Principal component analysis (PCA) of the prediction errors, with some characteristics of the training set included as passive variables, was performed to compare the results for the different alkalinity predictive models. The results indicate that calibration techniques utilizing more than one component (PLS and WA-PLS) can improve the predictions for lakes with diatom taxa that have broad tolerances. Furthermore, we show that WA-PLS performs best compared with the other techniques for those lakes that have a high relative abundance of the most dominant taxa and a corresponding low sample heterogeneity.     

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.     

Recent changes in diatom-inferred pH, heavy metals, and spheroidal carbonaceous particles in lake sediments near an oil refinery at Mongstad, Western Norway

Sediments from two naturally acid lakes have been used to investigate whether there is any local impact of atmospheric pollution from an oil refinery at Mongstad in Western Norway. The refinery started production in 1975 and expanded in 1987. One lake was selected as a reference site as it only receives long-range transported air pollution, whereas a second lake was selected as it was expected to receive both long-range transported and local air pollution from the refinery. Heavy metal (Pb, Ni and Zn) and spheroidal carbonaceous particle (SCP) (> 5 µm in diameter) concentrations and accumulation rates have been estimated and lake-water pH has been reconstructed by weighted averaging and weighted averaging partial least squares regression and calibration from the fossil diatom assemblages.Heavy metals that are in the size range for which atmospheric residence time is greatest do not show any enhanced levels in the sediments after 1975 that could be associated with local impacts from the refinery. SCPs in the sediments that are in the size range thought to be effectively removed by dry deposition, and thus have a more local deposition pattern, show an increase after 1975 and an additional large increase after 1987 that can be explained by impacts from the local oil refinery. After 1975 the SCP diameter distribution changed from being dominated by SCPs with a small diameter in the range 5-10 µm to SCPs with larger diameters. The SO₂ emission from the oil refinery seems to have had no significant effect on lake pH. The reconstructed lake pH history is complex, possibly related to land-use changes and long-range transported air pollution.     

Within-lake variability of subfossil chironomid assemblages in shallow Norwegian lakes

Subfossil chironomids in the surface sediments of five small and shallow Norwegian lakes were studied to determine the within-lake variability of fossil assemblages, changes in chironomid assemblages with respect to water depth, and the representativeness of single samples for the entire chironomid fauna of a lake. In each of the lakes studied, six short sediment cores in the deepest part of the lake basin and two littoral to deep-water transects of seven cores each were obtained using a gravity corer, and chironomid assemblages in the uppermost centimetre of sediment were analysed. In three of the five lakes, chironomid concentrations were highest in the deepest parts of the lake basins. In the remaining two lakes, concentrations were either very variable or, in a lake with clear indications of anoxia in the bottom waters, highest at intermediate water depth. Chironomid assemblages tended to be dominated by the same taxa within a lake basin. However, in each of the lakes studied there was a clear and statistically significant shift in chironomid assemblages with respect to water depth. The organic content of the sediments was statistically significant in explaining the variance in the chironomid assemblages only in lakes where organic matter content was closely related to water depth. Only a few chironomid taxa were restricted to the shallowest parts of the lake basins, whereas a number of chironomids were found exclusively in deep-water sediments. Chironomid head capsules of running water taxa and simuliid remains were generally found in sediments close to lake tributaries and in the deepest parts of the lake basins. Although any individual sample contained only a part of the total subfossil chironomid fauna (21–63% of the total taxa per lake), chironomids dominant in any section of the study lakes were found in most of the transect and mid-lake samples.     

An ostracod-conductivity transfer function for Tibetan lakes

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

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).     

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.     

Quantitative relationship between water-depth and sub-fossil ostracod assemblages in Lake Donggi Cona,Qinghai Province,China

A calibration data set of 51 surface sediment samples from Lake Donggi Cona on the northeastern Tibetan Plateau was investigated to study the relationship between sub-fossil ostracod assemblages and water depth. Samples were collected over a depth range from 0.6 to 80 m. A total of 16 ostracod species was identified from the lake with about half of the species restricted to the Tibetan Plateau and its adjacent mountain ranges and poorly known in terms of ecological preferences, and the other half displaying a mainly Holarctic distribution. Living macrophytes and macroalgae were recorded in Lake Donggi Cona down to a depth of about 30 m, and bivalve (Pisidium cf. zugmayeri) and gastropod (Gyraulus, Radix) shells were found down to depths of 43 and 48 m, respectively. The ostracod-water-depth relationship was assessed by multivariate statistical analysis and ostracod-based transfer functions for water depth were constructed. Weighted averaging partial least squares (WA-PLS) regression provided the best model with a coefficient of determination r ² of 0.91 between measured and ostracod-inferred water depth, a root mean square error of prediction of 8% and a maximum bias of 10.6% of the gradient length, as assessed by leave-one-out cross-validation. Our results show the potential of ostracods as palaeo-depth indicators in appropriate settings. However, transfer-function applications using fossil ostracod assemblages for palaeo-depth estimations require a thorough understanding of the palaeolimnological conditions of lakes and therefore detailed multi-proxy analysis to avoid misinterpretation of ostracod-based inferences.     

Diatom transfer-functions for quantifying past air temperature, pH and total organic carbon concentration from lakes in northern Sweden

The relationships between diatoms (Bacillariophyceae) in surface sediments of lakes and summer air temperature, pH and total organic carbon concentration (TOC) were explored along a steep climatic gradient in northern Sweden to provide a tool to infer past climate conditions from sediment cores. The study sites are in an area with low human impact and range from boreal forest to alpine tundra. Canonical correspondence analysis (CCA) constrained to mean July air temperature and pH clearly showed that diatom community composition was different between lakes situated in conifer-, mountain birch- and alpine-vegetation zones. As a consequence, diatoms and multivariate ordination methods can be used to infer past changes in treeline position and dominant forest type. Quantitative inference models were developed to estimate mean July air temperature, pH and TOC from sedimentary diatom assemblages using weighted averaging (WA) and weighted averaging partial least squares (WA-PLS) regression. Relationships between diatoms and mean July air temperature were independent of lake-water pH, TOC, alkalinity and maximum depth. The results demonstrated that diatoms in lake sediments can provide useful and independent quantitative information for estimating past changes in mean July air temperature (R² _jack = 0.62, RMSEP = 0.86 °C; R² and root mean squared error of prediction (RMSEP) based on jack-knifing), pH (R² _jack = 0.61, RMSEP = 0.30) and TOC (R² _jack = 0.49, RMSEP = 1.33 mg l^-1). The paper focuses mainly on the relationship between diatom community composition and mean July air temperature, but the relationships to pH and TOC are also discussed.     

Holocene climate change and its effect on lake ecosystem production on Northern Victoria Island, Canadian Arctic

A multi-proxy paleoenvironmental study from Lake WB02 (72.29°N, 109.87°W) on Northern Victoria Island, Nunavut, Canada provides an 8.4-ka record of chironomid and ecosystem production. Mean July air temperatures for this region during the Holocene were inferred from the fossil record. The chironomid assemblages contained 33 taxa and were dominated by Paracladius and Heterotrissocladius maeaeri-type. Primary production and chironomid food availability inferred from sediment biogenic silica and loss on ignition at 550°C, and chironomid concentrations, all exhibited synchronous patterns of change through time. Similar to other climate records from across the Arctic, the sediment and fossil data from Lake WB02 support the hypothesis of a warm and productive early to middle Holocene, a cool and generally unproductive middle to late Holocene and a return to a warmer, more productive environment in the past 100 years. Mean July air temperature reconstructions based on both the modern analogue technique (MAT) and weighted averaging partial least squares regression (WAPLS), however, failed to reflect these same changes. The difference between the qualitative and quantitative environmental reconstructions may be due to the restrictions associated with the use of these inference tools, the effects of which are more significant in unproductive ecosystems such as Arctic lakes.     

A chironomid‐based model for inferring late‐summer hypolimnetic oxygen in southeastern Ontario lakes

Hypolimnetic oxygen depletion has been accelerated in many lakes due to cultural eutrophication. However, the extent and magnitude of environmental change is difficult to ascertain due to the lack of historical records. Larval Chironomidae (Diptera) are useful proxy indicators of oxygen, as they show a wide range of tolerances to oxygen conditions and their chitinous head capsules preserve well in lake sediments. Using paleolimnological techniques, chironomid assemblages from the surface sediments of 42 southeastern Ontario lakes were related to environmental conditions. Hypolimnetic oxygen conditions, measured as the average endofsummer hypolimnetic dissolved oxygen (AvgDO_(Summ)), explained the most variation in the chironomid assemblages, whereas dissolved inorganic carbon, the Anoxic Factor, max. depth and total phosphorus concentrations were also correlated with assemblage composition. Based on the relative abundances of 45 chironomid taxa, a robust, partial least squares (PLS) regression transfer function for AvgDO_(Summ) was constructed (r² = 0.74, r² _(jack) = 0.58, n = 40). This new transfer function should allow paleolimnologists to directly track past trends in hypolimnetic oxygen levels.     

Testing intra-site transfer functions: an example using chironomids and water depth

Most calibration data sets used to infer past environmental conditions from biological proxies are derived from many sites. An alternative strategy is to derive the calibration data set from within a single site. Transfer functions derived from such intra-site calibration data sets are usually applied to fossil assemblages from the focal lake, but a recent development has been to apply these transfer functions to other sites. Transfer functions derived from intra-site calibration data sets can have impressive cross-validation performance, but that gives little indication of their performance when applied to other sites. Here, we develop transfer functions for lake depth from intra-lake chironomid calibration data sets in Norway and Alaska and test the resulting models by cross-validation and against known depth in external lakes. Lake depth is a statistically significant predictor of chironomid assemblages at all these lakes, and most intra-lake transfer functions perform reasonably well under cross-validation, but their performance against external data is erratic. Downcore reconstructions from transfer functions developed on different lakes are dissimilar. Ignoring the poorly performing transfer functions, only 3 of 14 downcore reconstructions are statistically significant. Few assemblages downcore had good modern analogues in the calibration data set, even when the core was from the same lake as the calibration data set. We conclude that intra-site calibration data sets can find site-specific rather than general relationships between species and the environment and thus should be applied with care and to external sites only after careful and critical validation.     

Subfossil chironomid variability in surface sediment samples from Icelandic lakes: implications for the development and use of training sets

A suite of surface sediment samples from three Icelandic lakes was analysed for subfossil chironomid head capsules, and a quantitative July air temperature inference model was applied to the data to investigate whether there was significant variability among samples taken from a lake. Ordination and simple regression methods were used to analyse the relationships between environmental and sedimentological variables and the chironomid assemblages and inferred temperature data. Substrate was the most important influence on the chironomid assemblages and inferred temperatures, while water depth at the sampling location had no relationship with the chironomid-inferred temperatures. Within-lake variability of the chironomid assemblages and their inferred temperatures, however, were not significant statistically, suggesting that in lakes of western and northwest Iceland within-lake sampling location has no effect on the data obtained, and therefore on training set samples.     

Sub-fossil chironomids are significant indicators of turbidity in shallow lakes of northeastern USA

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.     

Modern diatom, cladocera, chironomid, and chrysophyte cyst assemblages as quantitative indicators for the reconstruction of past environmental conditions in the Alps. I. Climate

Diatom, chrysophyte cyst, benthic cladocera, planktonic cladocera, and chironomid assemblages were studied in the surface sediments of 68 small lakes along an altitudinal gradient from 300 to 2350 m in Switzerland. In addition, 43 environmental variables relating to the physical limnology, geography, catchment characteristics, climate, and water chemistry were recorded or measured for each lake. The explanatory power of each of these predictor variables for the different biological data-sets was estimated by a series of canonical correspondence analyses (CCA) and the statistical significance of each model was assessed by Monte Carlo permutation tests. A minimal set of environmental variables was found for each biological data-set by a forward-selection procedure within CCA. The unique, independent explanatory power of each set of environmental variables was estimated by a series of CCAs and partial CCAs. Inference models or transfer functions for mean summer (June, July, August) air temperature were developed for each biological data-set using weighted-averaging partial least squares or partial least squares. The final transfer functions, after data screening, have root mean squared errors of prediction, as assessed by leave-one-out cross-validation, of 1.37 °C (chironomids), 1.60 °C (benthic cladocera), 1.62 °C (diatoms), 1.77 °C (planktonic cladocera), and 2.23 °C (chrysophyte cysts).