2015
DOI: 10.1007/s10933-015-9848-0
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Chironomid-environment relations in northern North America

Abstract: Chironomid assemblages from the uppermost sediments of 435 lakes spanning northern North America were compared to environmental parameters using direct gradient analysis. This large calibration set was merged from several previously developed regional datasets, and increases the number of modern analogues that are available for use for paleoenvironmental interpretations in this region. Air temperature explained the largest amount of variation in the chironomid assemblages with several other environmental facto… Show more

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Cited by 44 publications
(120 citation statements)
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“…Two, a two-component WA partial-least-squares (WA-PLS) model employing a large northern North American training set, comprising 434 sites representing a July air temperature gradient from 2.0 to 16.3°C and spanning from Alaska, USA, to eastern Canada and from Boreal to High Arctic environments, including the Canadian Arctic islands (Fortin et al 2015; 78 taxa, r 2 boot = 0.72, RMSEP = 1.9°C; hereafter FOR15). Fossil assemblages in East Greenland have much in common with assemblages from the Canadian Arctic at the genus level (Gajewski et al 2005;Francis et al 2006;Fortin et al 2015), but we did find some differences at the sub-genus level, e.g. The Francis et al (2006) training set was used in a previous Holocene study in warmer West Greenland (Axford et al 2013).…”
Section: Study Site and Methodsmentioning
confidence: 99%
“…Two, a two-component WA partial-least-squares (WA-PLS) model employing a large northern North American training set, comprising 434 sites representing a July air temperature gradient from 2.0 to 16.3°C and spanning from Alaska, USA, to eastern Canada and from Boreal to High Arctic environments, including the Canadian Arctic islands (Fortin et al 2015; 78 taxa, r 2 boot = 0.72, RMSEP = 1.9°C; hereafter FOR15). Fossil assemblages in East Greenland have much in common with assemblages from the Canadian Arctic at the genus level (Gajewski et al 2005;Francis et al 2006;Fortin et al 2015), but we did find some differences at the sub-genus level, e.g. The Francis et al (2006) training set was used in a previous Holocene study in warmer West Greenland (Axford et al 2013).…”
Section: Study Site and Methodsmentioning
confidence: 99%
“…Water chemistry variables such as pH and concentration of nutrients, DOC, and ions are well known to have strong influence on diatom assemblage composition in lakes and ponds across the subarctic (Pienitz et al 1995;Rühland and Smol 2002) and Arctic (Smol and Douglas 1996;Bouchard et al 2004). For chironomids, water temperature is often described as the primary factor that governs the community structure of northern and alpine lakes (Walker et al 1991;Lotter et al 1997;Fortin et al 2015). Water chemistry is also known to have some influence (Gajewski et al 2005;Medeiros and Quinlan 2011;Luoto et al 2016).…”
Section: Partitioning Variation In Biological Community Compositionmentioning
confidence: 99%
“…Diatoms, a group of mainly single-celled algae with siliceous cell walls (Chromista: Bacillariophyta), and chironomids, non-biting midges with chitinous exoskeletons (Insecta: Diptera: Chironomidae), are well represented in lake sediments (Birks 1998;Douglas and Smol 1999;Brodersen and Quinlan 2006) because taxonomically diagnostic components are relatively resistant to post-depositional degradation processes (Battarbee 2000;Axford et al 2009). Importantly, they respond sensitively and rapidly to changes in water chemistry (Hall and Smol 1996;Medeiros and Quinlan 2011), climate Fortin et al 2015), and catchment-mediated processes (Thienpont et al 2013;Medeiros et al 2014). Thus, analysis of diatoms and chironomids in lake sediments can serve to improve knowledge of how climate-driven interactions amongst catchment characteristics, hydrology, and limnology affect aquatic biota of shallow northern lakes.…”
Section: Introductionmentioning
confidence: 99%
“…It contains 52 of the 75 lakes in the Eastern Canadian transfer function of Larocque (). The correlation coefficient ( r 2 boot ) is 0.73, the RMSEP is 1.8 °C and the maximum bias is 2.9 °C (Fortin et al ., ).…”
Section: Methodsmentioning
confidence: 99%