Biogeosciences (Jun 2021)

Revised fractional abundances and warm-season temperatures substantially improve brGDGT calibrations in lake sediments

  • J. H. Raberg,
  • J. H. Raberg,
  • D. J. Harning,
  • D. J. Harning,
  • S. E. Crump,
  • S. E. Crump,
  • G. de Wet,
  • G. de Wet,
  • A. Blumm,
  • A. Blumm,
  • S. Kopf,
  • Á. Geirsdóttir,
  • G. H. Miller,
  • J. Sepúlveda

DOI
https://doi.org/10.5194/bg-18-3579-2021
Journal volume & issue
Vol. 18
pp. 3579 – 3603

Abstract

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Distributions of branched glycerol dialkyl glycerol tetraethers (brGDGTs) are frequently employed for reconstructing terrestrial paleotemperatures from lake sediment archives. Although brGDGTs are globally ubiquitous, the microbial producers of these membrane lipids remain unknown, precluding a full understanding of the ways in which environmental parameters control their production and distribution. Here, we advance this understanding in three ways. First, we present 43 new high-latitude lake sites characterized by low mean annual air temperatures (MATs) and high seasonality, filling an important gap in the global dataset. Second, we introduce a new approach for analyzing brGDGT data in which compound fractional abundances (FAs) are calculated within structural groups based on methylation number, methylation position, and cyclization number. Finally, we perform linear and nonlinear regressions of the resulting FAs against a suite of environmental parameters in a compiled global lake sediment dataset (n = 182). We find that our approach deconvolves temperature, conductivity, and pH trends in brGDGTs without increasing calibration errors from the standard approach. We also find that it reveals novel patterns in brGDGT distributions and provides a methodology for investigating the biological underpinnings of their structural diversity. Warm-season temperature indices outperformed MAT in our regressions, with the mean temperature of months above freezing yielding the highest-performing model (adjusted R2 = 0.91, RMSE = 1.97 ∘C, n = 182). The natural logarithm of conductivity had the second-strongest relationship to brGDGT distributions (adjusted R2 = 0.83, RMSE = 0.66, n = 143), notably outperforming pH in our dataset (adjusted R2 = 0.73, RMSE = 0.57, n = 154) and providing a potential new proxy for paleohydrology applications. We recommend these calibrations for use in lake sediments globally, including at high latitudes, and detail the advantages and disadvantages of each.