Lake Floor Morphology and Sediment Architecture of Lake Torneträsk, Northern Sweden

ABSTRACT. Here we present datasets from a hydroacoustic survey in July 2011 at Lake Torneträsk, northern Sweden. Our hydroacoustic data exhibit lake floor morphologies formed by glacial erosion and accumulation processes, insights into lacustrine sediment accumulation since the beginning of deglaciation, and information on seismic activity along the Pärvie Fault. Features of glacial scouring with a high-energy relief, steep slopes, and relative reliefs of more than 50 m are observed in the large W-basin. The remainder of the lacustrine subsurface appears to host a broad variety of well preserved formations from glacial accumulation related to the last retreat of the Fennoscandian ice sheet. Deposition of glaciolacustrine and lacustrine sediments is focused in areas situated in proximity to major inlets. Sediment accumulation in distal areas of the lake seldom exceeds 2 m or is not observable. We assume that lack of sediment deposition in the lake is a result of different factors, including low rates of erosion in the catchment, a previously high lake level leading to deposition of sediments in higher elevated paleodeltas, tributaries carrying low suspension loads as a result of sedimentation in upstream lakes, and an overall low productivity in the lake. A clear off-shore trace of the Pärvie Fault could not be detected from our hydroacoustic data. However, an absence of sediment disturbance in close proximity to the presumed fault trace implies minimal seismic activity since deposition of the glaciolacustrine and lacustrine sediments.

Rolling stones and tree rings: A state of research on dendrogeomorphic reconstructions of rockfall

This progress report focuses on the contribution of tree-ring series to rockfall research and on recent development and challenges in the field. Dendrogeomorphic techniques have been used extensively since the early 2000s and several approaches have been developed to extract rockfall signals from tree-ring records of conifer trees. The reconstruction of rockfall chronologies has been hampered in the past by sample sizes that decrease as one goes back in time, as well as by a paucity of studies that include broadleaved tree species, which are in fact quite common in rockfall-prone environments. In this report, we propose a new approach considering impact probability and quantification of uncertainty in the reconstruction of rockfall time series as well as a quantitative estimate of presumably missed events. In addition, we outline new approaches and future perspectives for the inclusion of woody vegetation in hazard assessment procedures, and end with future thematic perspectives.

A Bayesian analysis for spatial processes with application to mapping

In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease etiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. Empirical Bayesian (EB) methods have been used to spatially smooth the estimates by permitting an area estimate to "borrow strength" from its neighbors. Such EB methods include the use of a Gamma model, of a James-Stein estimator, and of a conditional autoregressive (CAR) process. A fully Bayesian analysis of the CAR process is proposed. One advantage of this fully Bayesian analysis is that it can be implemented simply by using repeated sampling from the posterior densities. Use of a Markov chain Monte Carlo technique such as Gibbs sampler was not necessary. Direct resampling from the posterior densities provides exact small sample inferences instead of the approximate asymptotic analyses of maximum likelihood methods (Clayton & Kaldor, 1987). Further, the proposed CAR model provides for covariates to be included in the model. A simulation demonstrates the effect of sample size on the fully Bayesian analysis of the CAR process. The methods are applied to lip cancer data from Scotland, and the results are compared. ^