title: The bias and signal attenuation present in conventional pollen-based climate reconstructions as assessed by early climate data from Minnesota, USA.
abstract: 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 1800 s 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.
authors.affiliation: Prairie Adaptation Research Collaborative, University of Regina, Regina, Saskatchewan, Canada, S4S 7H9.
authors.forename: Jeannine-Marie
authors.initials: JM
authors.lastname: St Jacques
authors.affiliation: Paleoecological Environmental Assessment and Research Lab, Department of Biology, Queen's University, Kingston, Ontario, Canada, K7L 3N6.
authors.forename: Brian F
authors.initials: BF
authors.lastname: Cumming
authors.affiliation: Prairie Adaptation Research Collaborative, University of Regina, Regina, Saskatchewan, Canada, S4S 7H9.
authors.forename: David J
authors.initials: DJ
authors.lastname: Sauchyn
authors.affiliation: Paleoecological Environmental Assessment and Research Lab, Department of Biology, Queen's University, Kingston, Ontario, Canada, K7L 3N6.
authors.forename: John P
authors.initials: JP
authors.lastname: Smol
mesh_terms: D002980:Climate; D004777:Environment; D049672:History, 19th Century; D049673:History, 20th Century; D006801:Humans; D008910:Minnesota; D011058:Pollen