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

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Abstract

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.

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Acknowledgements

This work was funded by a NSF Paleoclimate award (ATM-0442177) to D.F.P and K.A.M. We are grateful to NSF, VECO, the Polar Continental Shelf Project (PCSP) and the Nunavut Research Institute (NRI) for field and logistical support. We are also grateful to Glen MacDonald and two anonymous reviewers for detailed, constructive criticism of this paper. We thank Derek Muir, Xiaowa Wang and their colleagues at the water chemistry lab in the National Laboratory for Environmental Testing (NLET), Water Science and Technology Directorate of Environment Canada (Burlington, ON) for water chemistry analyses. We also thank Ken Clogg-Wright and Glen MacDonald for their help in the field and Lori Miller and Russ Brandenburg for sediment processing.

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  1. Department of Geography, The Ohio State University, 1036 Derby Hall, 154 North Oval Mall, Columbus, OH, 43210-1361, USA

    David Porinchu & Nicolas Rolland

  2. Department of Geography, Social Science Building, University of Western Ontario, 1151 Richmond Street North, London, ON, Canada, N6A 5C2

    Katrina Moser

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  1. David Porinchu
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  2. Nicolas Rolland
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  3. Katrina Moser
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Correspondence to David Porinchu.

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David Porinchu and Nicolas Rolland contributed equally to the work.

Appendix 1

Appendix 1

Fig. 6
figure 6

Photos of the mentum of 4 morpho-types of Corynocera oliveri present in the central Canadian Arctic training set

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Porinchu, D., Rolland, N. & Moser, K. Development of a chironomid-based air temperature inference model for the central Canadian Arctic. J Paleolimnol 41, 349–368 (2009). https://doi.org/10.1007/s10933-008-9233-3

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