A chironomid-based mean July temperature inference model from the south-east margin of the Tibetan Plateau, China
A chironomid-based calibration training set comprised of 100 lakes from south-western China was established. Multivariate ordination analyses were used to investigate the relationship between the distribution and abundance of chironomid species and 18 environmental variables from these lakes. Canoni...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-03-01
|
| Series: | Climate of the Past |
| Online Access: | http://www.clim-past.net/13/185/2017/cp-13-185-2017.pdf |
| Summary: | A chironomid-based calibration training set comprised of 100 lakes from
south-western China was established. Multivariate ordination analyses were
used to investigate the relationship between the distribution and abundance
of chironomid species and 18 environmental variables from these lakes.
Canonical correspondence analyses (CCAs) and partial CCAs showed that mean
July temperature is one of the independent and significant variables
explaining the second-largest amount of variance after potassium ions
(K<sup>+</sup>) in 100 south-western Chinese lakes. Quantitative transfer
functions were created using the chironomid assemblages for this calibration
data set. The second component of the weighted-average partial least squares
(WA-PLS) model produced a coefficient of determination
(<i>r</i><sup>2</sup><sub>bootstrap</sub>) of 0.63, maximum bias (bootstrap) of 5.16 and root-mean-square error of prediction (RMSEP) of 2.31 °C. We applied
the transfer functions to a 150-year chironomid record from Tiancai Lake
(26°38′3.8 N, 99°43′ E; 3898 m a.s.l.), Yunnan,
China, to obtain mean July temperature inferences. We validated these results
by applying several reconstruction diagnostics and comparing them to a
50-year instrumental record from the nearest weather station (26°51′29.22′′ N,
100°14′2.34′′ E;
2390 m a.s.l.). The transfer function
performs well in this comparison. We argue that this 100-lake large training
set is suitable for reconstruction work despite the low explanatory power of
mean July temperature because it contains a complete range of modern
temperature and environmental data for the chironomid taxa observed and is
therefore robust. |
|---|---|
| ISSN: | 1814-9324 1814-9332 |