Effect of low count sums on quantitative environmental reconstructions: an example using subfossil chironomids |
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| Authors: | Oliver Heiri André F Lotter |
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| Institution: | (1) Institute of Plant Sciences, University of Bern, Altenbergrain 21, CH 3013 Bern, Switzerland;(2) Laboratorium voor Palaeobotanie en Palynologie, Universiteit Utrecht, Budapestlaan 4, 3584 CD Utrecht, Netherlands |
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| Abstract: | The concentrations of chironomid remains in lake sediments are very variable and, therefore, chironomid stratigraphies often include samples with a low number of counts. Thus, the effect of low count sums on reconstructed temperatures is an important issue when applying chironomid temperature inference models. Using an existing data set, we simulated low count sums by randomly picking subsets of head capsules from surfacesediment samples with a high number of specimens. Subsequently, a chironomidtemperature inference model was used to assess how the inferred temperatures are affected by low counts. The simulations indicate that the variability of inferred temperatures increases progressively with decreasing count sums. At counts below 50 specimens, a further reduction in count sum can cause a disproportionate increase in the variation of inferred temperatures, whereas at higher count sums the inferences are more stable. Furthermore, low count samples may consistently infer too low or too high temperatures and, therefore, produce a systematic error in a reconstruction. Smoothing reconstructed temperatures downcore is proposed as a possible way to compensate for the high variability due to low count sums. By combining adjacent samples in a stratigraphy, to produce samples of a more reliable size, it is possible to assess if low counts cause a systematic error in inferred temperatures. |
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| Keywords: | quantitative temperature reconstruction Chironomidae sample size error estimation palaeolimnology subfossils |
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