The distribution and abundance of chironomids in high-latitude Eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern Russia

The large landmass of northern Russia has the potential to influence global climate through amplification of climate change. Reconstructing climate in this region over millennial timescales is crucial for understanding the processes that affect the global climate system. Chironomids, preserved in la...

Full description

Bibliographic Details
Main Authors: Self, AE, Brooks, SJ, Birks, HJB, Nazarova, L, Porinchu, D, Odland, A, Yang, H, Jones, VJ
Format: Article in Journal/Newspaper
Language:unknown
Published: PERGAMON-ELSEVIER SCIENCE LTD 2011
Subjects:
Online Access:http://discovery.ucl.ac.uk/1315038/
id ftucl:oai:eprints.ucl.ac.uk.OAI2:1315038
record_format openpolar
spelling ftucl:oai:eprints.ucl.ac.uk.OAI2:1315038 2023-05-15T15:06:53+02:00 The distribution and abundance of chironomids in high-latitude Eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern Russia Self, AE Brooks, SJ Birks, HJB Nazarova, L Porinchu, D Odland, A Yang, H Jones, VJ 2011-05 http://discovery.ucl.ac.uk/1315038/ unknown PERGAMON-ELSEVIER SCIENCE LTD QUATERNARY SCI REV , 30 (9-10) 1122 - 1141. (2011) Chironomids Palaeolimnology Russia Climate change Transfer function Continentality Species responses WA-PLS SURFACE AIR-TEMPERATURE LIMNOLOGICAL CHARACTERISTICS QUANTITATIVE INDICATORS ARCTIC RUSSIA TRAINING SET LENA RIVER DIPTERA HISTORY ASSEMBLAGES TREELINE Article 2011 ftucl 2013-11-10T04:31:45Z The large landmass of northern Russia has the potential to influence global climate through amplification of climate change. Reconstructing climate in this region over millennial timescales is crucial for understanding the processes that affect the global climate system. Chironomids, preserved in lake sediments, have the potential to produce high resolution, low error, quantitative summer air temperature reconstructions. Canonical correspondence analysis of modern surface sediments from high-latitude lakes, located in northern European Russia and central Siberia, suggests that mean July air temperature is the most significant variable explaining chironomid distribution and abundance. This strong relationship enabled the development of a chironomid-based mean July air temperature-inference model based on 81 lakes and 89 taxa which has a r(jack)(2) = 0.92 and RMSEP = 0.89 degrees C. Comparison of taxon responses to July temperature between this Russian and existing Norwegian data-sets shows that the temperature optima of individual taxa were between 1 and 3 degrees C higher in the Russian data regardless of modelling technique. Reconstructions based on fossil assemblages from a Russian tundra lake core (VORK5) using a Norwegian chironomid-based inference model provide mean July air temperature estimates that are 1.0-2.7 degrees C colder than from the 81-lake Russian model and are also lower than the instrumental record from a nearby meteorological station. The Norwegian model also did not reconstruct decadal-scale fluctuations in temperature seen in the instrumental record. These observations suggest that chironomid-based inference models should only be applied to sediment cores which have similar climate regimes to the geographic area of the training set. In addition a 149 lake, 120 taxa chironomid-based continentality inference model was also developed from the modern Norwegian and Russian training sets. A 2-component WA-PLS model was the minimal adequate model with r(jack)(2) = 0.73 and RMSEP = 9.9 using the Gorczynski continentality index. Comparison of reconstructed continentality indices from the tundra lake, VORK5, show close agreement with local instrumental records over the past 70 years and suggest that the model is reliable. Recent warming in the Arctic has been spatially and seasonally heterogeneous; in many areas warming is more pronounced in the spring and autumn leading to a lengthening of the summer, while summer temperatures have remained relatively stable. A continentality inference model has the potential to detect these seasonal changes in climate. (C) 2011 Elsevier Ltd. All rights reserved. Article in Journal/Newspaper Arctic Climate change lena river Tundra Siberia University College London: UCL Discovery Arctic
institution Open Polar
collection University College London: UCL Discovery
op_collection_id ftucl
language unknown
topic Chironomids
Palaeolimnology
Russia
Climate change
Transfer function
Continentality
Species responses
WA-PLS
SURFACE AIR-TEMPERATURE
LIMNOLOGICAL CHARACTERISTICS
QUANTITATIVE INDICATORS
ARCTIC RUSSIA
TRAINING SET
LENA RIVER
DIPTERA
HISTORY
ASSEMBLAGES
TREELINE
spellingShingle Chironomids
Palaeolimnology
Russia
Climate change
Transfer function
Continentality
Species responses
WA-PLS
SURFACE AIR-TEMPERATURE
LIMNOLOGICAL CHARACTERISTICS
QUANTITATIVE INDICATORS
ARCTIC RUSSIA
TRAINING SET
LENA RIVER
DIPTERA
HISTORY
ASSEMBLAGES
TREELINE
Self, AE
Brooks, SJ
Birks, HJB
Nazarova, L
Porinchu, D
Odland, A
Yang, H
Jones, VJ
The distribution and abundance of chironomids in high-latitude Eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern Russia
topic_facet Chironomids
Palaeolimnology
Russia
Climate change
Transfer function
Continentality
Species responses
WA-PLS
SURFACE AIR-TEMPERATURE
LIMNOLOGICAL CHARACTERISTICS
QUANTITATIVE INDICATORS
ARCTIC RUSSIA
TRAINING SET
LENA RIVER
DIPTERA
HISTORY
ASSEMBLAGES
TREELINE
description The large landmass of northern Russia has the potential to influence global climate through amplification of climate change. Reconstructing climate in this region over millennial timescales is crucial for understanding the processes that affect the global climate system. Chironomids, preserved in lake sediments, have the potential to produce high resolution, low error, quantitative summer air temperature reconstructions. Canonical correspondence analysis of modern surface sediments from high-latitude lakes, located in northern European Russia and central Siberia, suggests that mean July air temperature is the most significant variable explaining chironomid distribution and abundance. This strong relationship enabled the development of a chironomid-based mean July air temperature-inference model based on 81 lakes and 89 taxa which has a r(jack)(2) = 0.92 and RMSEP = 0.89 degrees C. Comparison of taxon responses to July temperature between this Russian and existing Norwegian data-sets shows that the temperature optima of individual taxa were between 1 and 3 degrees C higher in the Russian data regardless of modelling technique. Reconstructions based on fossil assemblages from a Russian tundra lake core (VORK5) using a Norwegian chironomid-based inference model provide mean July air temperature estimates that are 1.0-2.7 degrees C colder than from the 81-lake Russian model and are also lower than the instrumental record from a nearby meteorological station. The Norwegian model also did not reconstruct decadal-scale fluctuations in temperature seen in the instrumental record. These observations suggest that chironomid-based inference models should only be applied to sediment cores which have similar climate regimes to the geographic area of the training set. In addition a 149 lake, 120 taxa chironomid-based continentality inference model was also developed from the modern Norwegian and Russian training sets. A 2-component WA-PLS model was the minimal adequate model with r(jack)(2) = 0.73 and RMSEP = 9.9 using the Gorczynski continentality index. Comparison of reconstructed continentality indices from the tundra lake, VORK5, show close agreement with local instrumental records over the past 70 years and suggest that the model is reliable. Recent warming in the Arctic has been spatially and seasonally heterogeneous; in many areas warming is more pronounced in the spring and autumn leading to a lengthening of the summer, while summer temperatures have remained relatively stable. A continentality inference model has the potential to detect these seasonal changes in climate. (C) 2011 Elsevier Ltd. All rights reserved.
format Article in Journal/Newspaper
author Self, AE
Brooks, SJ
Birks, HJB
Nazarova, L
Porinchu, D
Odland, A
Yang, H
Jones, VJ
author_facet Self, AE
Brooks, SJ
Birks, HJB
Nazarova, L
Porinchu, D
Odland, A
Yang, H
Jones, VJ
author_sort Self, AE
title The distribution and abundance of chironomids in high-latitude Eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern Russia
title_short The distribution and abundance of chironomids in high-latitude Eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern Russia
title_full The distribution and abundance of chironomids in high-latitude Eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern Russia
title_fullStr The distribution and abundance of chironomids in high-latitude Eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern Russia
title_full_unstemmed The distribution and abundance of chironomids in high-latitude Eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern Russia
title_sort distribution and abundance of chironomids in high-latitude eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern russia
publisher PERGAMON-ELSEVIER SCIENCE LTD
publishDate 2011
url http://discovery.ucl.ac.uk/1315038/
geographic Arctic
geographic_facet Arctic
genre Arctic
Climate change
lena river
Tundra
Siberia
genre_facet Arctic
Climate change
lena river
Tundra
Siberia
op_source QUATERNARY SCI REV , 30 (9-10) 1122 - 1141. (2011)
_version_ 1766338450826461184