A Bayesian palaeoenvironmental transfer function model for acidified lakes

A Bayesian approach to palaeoecological environmental reconstruction deriving from the unimodal responses generally exhibited by organisms to an environmental gradient is described. The approach uses Bayesian model selection to calculate a collection of probability-weighted, species-specific response curves (SRCs) for each taxon within a training set, with an explicit treatment for zero abundances. These SRCs are used to reconstruct the environmental variable from sub-fossilised assemblages. The approach enables a substantial increase in computational efficiency (several orders of magnitude) over existing Bayesian methodologies. The model is developed from the Surface Water Acidification Programme (SWAP) training set and is demonstrated to exhibit comparable predictive power to existing Weighted Averaging and Maximum Likelihood methodologies, though with improvements in bias; the additional explanatory power of the Bayesian approach lies in an explicit calculation of uncertainty for each individual reconstruction. The model is applied to reconstruct the Holocene acidification history of the Round Loch of Glenhead, including a reconstruction of recent recovery derived from sediment trap data.The Bayesian reconstructions display similar trends to conventional (Weighted Averaging Partial Least Squares) reconstructions but provide a better reconstruction of extreme pH and are more sensitive to small changes in diatom assemblages. The validity of the posteriors as an apparently meaningful representation of assemblage-specific uncertainty and the high computational efficiency of the approach open up the possibility of highly constrained multiproxy reconstructions

An expanded calibration model for inferring lakewater and air temperatures from fossil chironomid assemblages in northern Fennoscandia

Chironomid-temperature inference models based on an expanded data set of surface-sediment and limnological data from 53 Subarctic lakes in northern Fennoscandia have been developed using eight different numerical techniques, each based on slightly different underlying statistical models or ecological assumptions. The study sites are mostly small, shallow, bathymetrically simple, oligotrophic lakes, with a pH range from 5.0 to 7.8, a total organic carbon range from 2.5 to 12.6 mg l- 1, a mean July lakewater temperature ranging from 6.1 to 15.4°C, and a mean July air temperature ranging from 8.5 to 14.9°C. A series of redundancy analyses (RDA) identified sediment organic content, maximum lake depth, and lakewater temperature as being the most important explanatory variables. Variance partitioning by partial RDAs further suggested that each of these variables accounted for a significant fraction of variance independent from each other. Different cali bration models were assessed on the basis of their statistical performance, with particular reference to prediction errors and the amount of bias along the temperature gradient. Of the eight calibration models, modern analogue techniques, weighted averaging partial least squares, simple weighted averaging with an‘inverse’ deshrinking regression, and linear partial least squares consistently performed best. These methods can all be used to develop transfer functions for surface-water and air July temperatures with a root mean squared error of predic tion (RMSEP) of about 1.5–1.6°C (water temperature) and 0.8–1.1°C (air temperature), as assessed by leave-one-out cross-validation. The resulting models do, however, have relatively high maximum biases (up to 3.9°C) in the lowest segments of the air and water temperature gradients, highlighting the need for enlarging and expanding the calibration data set to include lower temperatures

The development of a diatom-based transfer function along the Pacific coast of eastern Hokkaido, northern Japan—an aid in paleoseismic studies of the Kuril subduction zone

This paper provides a dataset to develop a diatom-based transfer function, which is applicable to paleoseismic studies at southwestern Kuril subduction zone, northern Japan. Modern diatom samples were collected from five transects from saltmarshes of Lakes Akkeshi and Onnetoh along the Pacific coast of eastern Hokkaido. The relationships between diatom species and environmental variables were elucidated by canonical correspondence analysis (CCA) and partial CCAs. Partial CCAs associated with Monte Carlo permutation tests show that elevation accounts for a significant portion of the total variance in the diatom data. Therefore, statistically significant transfer functions quantifying the relationship between modern diatom assemblages and elevation were developed using weighted averaging partial least squares and applied to fossil diatom assemblages from Lake Onnetoh. The reconstructed curve of elevations contains five emergence and four submergence events and the transfer functions calculated the amplitude of four of the emergence events to be at least 1 m. The results are consistent with paleoecological data produced by previous studies. If these events represent uplift associated with interplate earthquake and subsidence during an interseismic period along the Kuril subduction zone, transfer functions of eastern Hokkaido can contribute to reconstruction of the recurrence intervals and the amplitude of earthquakes

Co-correspondence analysis: a new ordination method to relate two community compositions

A new ordination method, called co-correspondence analysis, is developed to relate two types of communities (e.g., a plant community and an animal community) sampled at a common set of sites in a direct way. The method improves the simple, indirect approach of applying correspondence analysis (reciprocal averaging) to the separate species data sets and correlating the resulting ordination axes. Co-correspondence analysis maximizes the weighted covariance between weighted averaged species scores of one community and weighted averaged species scores of the other community. It thus attempts to identify the patterns that are common to both communities. Both a symmetric descriptive and an asymmetric predictive form are developed. The symmetric form relates to co-inertia analysis and the asymmetric, predictive form to partial least-squares regression. In two examples the predictive power of co-correspondence analysis is compared with that of canonical correspondence analyses on syntaxonomic and environmental data. In the first example, carabid beetles in roadside verges are shown to be more closely related to plant species composition than to vegetation structure (biomass, height, roughness, among others), and, in the second example, bryophytes in spring meadows are shown to be more closely related to the species composition of the vascular plants than to the measured water chemistry

Alignment of cryo-EM movies of individual particles by optimization of image translations

Direct detector device (DDD) cameras have revolutionized single particle electron cryomicroscopy (cryo-EM). In addition to an improved camera detective quantum efficiency, acquisition of DDD movies allows for correction of movement of the specimen, due both to instabilities in the microscope specimen stage and electron beam-induced movement. Unlike specimen stage drift, beam-induced movement is not always homogeneous within an image. Local correlation in the trajectories of nearby particles suggests that beam-induced motion is due to deformation of the ice layer. Algorithms have already been described that can correct movement for large regions of frames and for > 1 MDa protein particles. Another algorithm allows individual < 1 MDa protein particle trajectories to be estimated, but requires rolling averages to be calculated from frames and fits linear trajectories for particles. Here we describe an algorithm that allows for individual < 1 MDa particle images to be aligned without frame averaging or linear trajectories. The algorithm maximizes the overall correlation of the shifted frames with the sum of the shifted frames. The optimum in this single objective function is found efficiently by making use of analytically calculated derivatives of the function. To smooth estimates of particle trajectories, rapid changes in particle positions between frames are penalized in the objective function and weighted averaging of nearby trajectories ensures local correlation in trajectories. This individual particle motion correction, in combination with weighting of Fourier components to account for increasing radiation damage in later frames, can be used to improve 3-D maps from single particle cryo-EM.Comment: 11 pages, 4 figure

Testate amoebae as a proxy for reconstructing Holocene water table dynamics in southern Patagonian peat bogs

Funded by Natural Environment Research Council. Grant Numbers: NE/I022809/1, NE/I022981/1, NE/I022833/1, NE/I023104/1 Ricardo Muza and the Wildlife Conservation Society Karukinka Park Acknowledgements This work was supported by the Natural Environment Research Council (grant numbers NE/I022809/1, NE/I022981/1, NE/I022833/1 and NE/I023104/1). We thank Ricardo Muza and the Wildlife Conservation Society (WCS) Karukinka Park rangers for facilitating access to Karukinka Park. We also thank François De Vleeschouwer, Gaël Le Roux, Heleen Vanneste, Sébastien Bertrand, Zakaria Ghazoui and Jean-Yves De Vleeschouwer for fieldwork assistance. Nelson Bahamonde (INIA, Punta Arenas, Chile) and Ernesto Teneb (UMag, Punta Arenas, Chile) provided logistical support for the fieldwork in Chile. Dr Andrea Coronato (CADIC, Ushuaia) kindly provided logistical support for the research in Argentina. Thanks to Jenny Johnston for cartography, David Jolley for assistance in microscopic photography and Audrey Innes for laboratory assistance. We highly appreciate reviews by Matt Amesbury and an anonymous reviewer. R.P. is supported by an Impact Fellowship from the University of Stirling.Peer reviewedPublisher PD