Diatom-based models for inferring past water chemistry in western Ugandan crater lakes

This article was published in the Journal of Paleolimnology [© Springer Science+Business Media B.V.] and the definitive version is available at: http://dx.doi.org/10.1007/s10933-012-9609-2. The repository file contains the paper and supplementary material.Diatom surface sediment samples and corresponding water chemistry were collected from 56 lakes across a natural conductivity gradient in western Uganda (reflecting a regional climatic gradient of effective moisture) to explore factors controlling diatom distribution. Here we develop a regional training set from these crater lakes to test the hypothesis that this approach, by providing more appropriate and closer analogues, can improve the accuracy of palaeo-conductivity reconstructions, and so environmental inferences in these lake systems compared to larger training sets. We compare this output to models based on larger, but geographically and limnologically diverse training sets, using the European Diatom Database Initiative (EDDI) database. The relationships between water chemistry and diatom distributions were explored using canonical correspondence analysis (CCA) and partial CCA. Variance partitioning indicated that conductivity accounted for a significant and independent portion of this variation. A transfer function was developed for conductivity (r jack 2 = 0.74). Prediction errors, estimated using jack-knifing, are low for the conductivity model (0.256 log10 units). The resulting model was applied to a sedimentary sequence from Lake Kasenda, western Uganda. Comparison of conductivity reconstructions using the Ugandan crater lake training set and the East Africa training set (EDDI) highlighted a number of differences in the optima of key diatom taxa, which lead to differences in reconstructed values and could lead to misinterpretation of the fossil record. This study highlights issues of how far transfer functions based on continental-scale lake datasets such as the EDDI pan-African models should be used and the benefits that may be obtained from regional training sets

Uncovering diversity and metabolic spectrum of animals in dead zone sediments

Ocean deoxygenation driven by global warming and eutrophication is a primary concern for marine life. Resistant animals may be present in dead zone sediments, however there is lack of information on their diversity and metabolism. Here we combined geochemistry, microscopy, and RNA-seq for estimating taxonomy and functionality of micrometazoans along an oxygen gradient in the largest dead zone in the world. Nematodes are metabolically active at oxygen concentrations below 1.8μmolL−1, and their diversity and community structure are different between low oxygen areas. This is likely due to toxic hydrogen sulfide and its potential to be oxidized by oxygen or nitrate. Zooplankton resting stages dominate the metazoan community, and these populations possibly use cytochrome c oxidase as an oxygen sensor to exit dormancy. Our study sheds light on mechanisms of animal adaptation to extreme environments. These biological resources can be essential for recolonization of dead zones when oxygen conditions improve