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The inference of past temperatures from a sedimentary pollen record depends upon the stationarity of the pollen-climate relationship. However, humans have altered vegetation independent of changes to climate, and consequently modern pollen deposition is a product of landscape disturbance and climate, which is different from the dominance of climate-derived processes in the past. This problem could cause serious signal distortion in pollen-based reconstructions. In the north-central United States, direct human impacts have strongly altered the modern vegetation and hence the pollen rain since Euro-American settlement in the mid-19th century. Using instrumental temperature data from the early 1800s from Fort Snelling (Minnesota), we assessed the signal distortion and bias introduced by using the conventional method of inferring temperature from pollen assemblages in comparison to a calibration set from pre-settlement pollen assemblages and the earliest instrumental climate data. The early post-settlement calibration set provides more accurate reconstructions of the 19th century instrumental record, with less bias, than the modern set does. When both modern and pre-industrial calibration sets are used to reconstruct past temperatures since AD 1116 from pollen counts from a varve-dated record from Lake Mina, Minnesota, the conventional inference method produces significant low-frequency (centennial-scale) signal attenuation and positive bias of 0.8-1.7°C, resulting in an overestimation of Little Ice Age temperature and likely an underestimation of the extent and rate of anthropogenic warming in this region. However, high-frequency (annual-scale) signal attenuation exists with both methods. Hence, we conclude that any past pollen spectra from before Euro-American settlement in this region should be interpreted using a pre-Euro-American settlement pollen set, paired to the earliest instrumental climate records. It remains to be explored how widespread this problem is when conventional pollen-based inference methods are used, and consequently how seriously regional manifestations of global warming have been underestimated with traditional pollen-based techniques. [ABSTRACT FROM AUTHOR]

A high-resolution, independent pollen-inferred paleoclimate record and direct algal seasonality data from the actual time of sediment deposition are used to interpret the high-resolution diatom and chrysophyte record of varved Lake Mina, west-central Minnesota, USA during AD 1116-2002. This direct algal seasonality information was obtained by splitting varves into constituent winter-spring and summer lamina, and separately analyzing the siliceous algae in each layer. Analyses of integrated, continuous four-year diatom and chrysophyte samples from a sedimentary sequence show that the time period AD 1116-1478 (ie, the Atlantic-centered 'Medieval Climate Anomaly' (MCA)) was characterized by periods of vigorous and prolonged spring mixing, suggesting that ice-out occurred early. However, the warm summer temperatures in the MCA, particularly in a massive drought spanning AD 1300-1400, frequently caused the lake to stratify strongly, leading to nutrient depletion. During AD 1478-1870 (ie, the Atlantic-centered 'Little IceAge' (LIA)), Lake Mina was characterized by weak spring circulation and increasing nutrient depletion, suggesting late ice-out conditions. Strong summer stratification and/or nutrient depletion in both time periods is shown by the occurrence of the nutrient-poor oligotrophic taxon Cyclotella pseudostelligera. The diatom and chrysophyte assemblages of the period of Euro- American settlement AD 1870-2002 show higher nutrient availability and increased spring mixing intensity, as a result of forest clearance and increasingly earlier ice-out (documented in regional historical records). [ABSTRACT FROM AUTHOR]

Aim The bias in modern North American pollen assemblages by landscape disturbance from Euro-American settlement has long been overlooked in the construction of pollen–climate transfer functions. Our aim is to examine this problem and to develop an unbiased pre-settlement pollen–climate transfer function, and to test its performance and inference power in comparison with commonly used techniques. Location Minnesota, USA, is of palaeoclimatic interest because within the state are located two continental-scale ecotones, controlled by temperature and available moisture. Shifts of these ecotones can be tracked using palaeoecological techniques. Methods Using a data set of pre-settlement pollen assemblages from 133 lakes, which were coupled to climate data from the earliest instrumental records (i.e. 1895–1924), a pre-settlement pollen–climate data set was developed that lacked the influence of anthropogenic landscape disturbance. A corresponding modern pollen data set (from lake sediment core tops) and a modern climate (i.e. 1961–90) data set were also developed. The two pollen sets were compared to demonstrate the effects of landscape disturbance from human activities. Ordination (redundancy analysis with Monte Carlo permutation tests) and regression techniques (generalized linear modelling) were used to establish the relationships between the early instrumental climate variables and pre-settlement pollen assemblages and individual taxa, respectively. Transfer functions for the most suitable climate variables (i.e. those forming a minimal set of non-collinear climate variables that explained the greatest amount of pollen variance) were developed from the pre-settlement data set using bootstrapping. Results Comparison of pre-settlement pollen and modern pollen showed an over-representation of Ambrosia, Chenopodiaceae and Poaceae, and an under-representation of arboreal taxa (e.g. Pinus, Quercus, Ostrya) in the modern assemblages. Not surprisingly, ordination and regression techniques showed a strong relationship between the early instrumental climate variables and pre-settlement pollen assemblages and taxa. Transfer functions were developed for May and February mean temperature and available moisture. Pre-settlement transfer functions substantially improved the root mean squared error by 37–72% in comparison with modern transfer functions inferring pre-settlement conditions, suggesting that the modern transfer functions have poorer predictive abilities. Main conclusions For climatic reconstructions, there can be a serious distortion of inferences based solely on modern pollen–climate data sets in regions where anthropogenic landscape disturbance has occurred. By using historical climate data, coupled with pre-disturbance pollen assemblages, robust transfer functions for temperature and effective moisture were developed. [ABSTRACT FROM AUTHOR]