25th International Meeting on Organic Geochemistry IMOG 2011

P-485
Complications in the interpretation of molecular
paleotemperature reconstructions using isoprenoid and
branched tetraethers: Lessons to be learned
Josef Werne 1 , Beth Bernhardt 1 , Martijn Woltering 1 , Melissa Berke 1 , R. Douglas Ricketts 1 ,
Margarita Caballero 2 , Ellen Hopmans 3 , Stefan Schouten 3 , Jaap Sinninghe Damsté 3,4
1 Large Lakes Observatory, University of Minnesota Duluth, Duluth, United States of America, 2 Institute of
Geophysics, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico, 3 Dept. of Marine Organic
Biogeochemistry, Royal Netherlands Institute for Sea Research (NIOZ), Texel, Netherlands, 4 University of
Utrecht, Utrecht, Netherlands (corresponding author:jwerne@d.umn.edu)
Research efforts over the past decade have
highlighted the potential for new, microbial lipid based
proxies for temperature to be applied in lake
sediments. Schouten et al. (2002) proposed a new
molecular temperature proxy based on the distribution
of specific isoprenoid GDGT (glycerol dialkyl glycerol
tetraether) lipids derived from marine Group I
Crenarchaeota (now Thaumarchaeota) called the
TEX86. More recently, structurally similar branched
GDGT lipids have been identified widespread in soils
and peats. Based on analysis of globally distributed
soils, Weijers et al. (2007) proposed a pair of
molecular proxies, the ―MBT‖ (methylation index of
branched tetraethers) and ―CBT‖ (cyclization index of
branched tetraethers) that can be used in conjunction
to reconstruct the pH and temperature of the soil in
which the bacteria were living.
TheTEX86 and CBT/MBT have been applied in
several lacustrine and marine systems, often
producing robust paleotemperature records. For
example, the TEX86 record from Lake Malawi, in East
Africa, is currently the longest, most high-resolution
temperature record from the African continent
(Woltering et al., 2010), and the MBT/CBT record
from Valles Caldera in New Mexico, USA, provides
realistic temperatures spanning two full glacial/
interglacial cycles, and is one of the few records from
MIS-11 in North America (Fawcett et al., 2011).
Despite, the significant advances derived from these
and other paleotemperature records, not all records
result in the anticipated trends.
Here, we present data from a suite of systems in
which the temperature profiles reconstructed using
the TEX86 or MBT/CBT proxies are not consistent with
known environmental change or with other
temperature reconstructions made in the same
system. In some systems, the poor TEX86 and
MBT/CBT temperature records are due to inputs from
Euryarchaeota, either from soils (Lake Victoria, East
Africa and Lago Verde, Mexico) or from anaerobic
water masses (Cariaco Basin, Venezuela).
Euryarchaeotal contributions of GDGTs, cause a
breakdown between the TEX86 temperature (derived
from Thaumarchaeota) and the annual mean surface
water temperature that we seek to reconstruct. In
contrast, in Lake Superior the TEX86 in fact reflects
the temperature of the mid-water depth of
Thaumarchaeotal growth rather than surface
temperatures – thus it does in fact reflect the
temperature of the growth environment, it is simply
not the temperature that is sought after in most
paleoclimate studies. Similarly, in Issyk-Kul,
Kyrgystan, evidence suggests that the TEX86 is
influenced by depth of Thaumarchaeotal growth, the
unusual circulation patterns in this system, and
possibly by development of a freshwater cap over
brackish bottom waters during glacial melt.
Analysis of small lakes from the USA, including
Deming Lake, MN, Bath Pond, OH, and Lake Tulane,
FL, reveal other complexities. Generally, the
temperatures produced match instrumental
measurements within the error of the calibration, both
in core-top sediments and downcore. However, a
rapid downcore MBT/CBT temperature increase in
surface sediments (e.g. 7ºC in 7 years/5 cm in Bath
Pond) suggests that in situ growth of the source
bacteria and/or diagenesis altering the suite of
GDGTs may influence the MBT/CBT.
This study allows us to provide constraints on the
applicability of these temperature proxies and
indicates the types of environmental data that can be
derived from ―bad‖ GDGT-based temperature profiles.
Schouten et al. (2002) EPSL 204:265-274.
Weijers et al. (2007), GCA, 71:703-713.
Woltering et al. (2010) Palaeogeogr, Palaeoclim,
Palaeoecol. doi:10.1016/j.palaeo.2010.02.013
Fawcett et al. (2011) Nature. In press.
609