Underestimation of Snow Accumulation Rate in Central Antarctica (Vostok Station) Derived from Stake Measurements

Russian Meteorology and Hydrology - It is shown that the snow stake measurements in central Antarctica systematically underestimate the value of the snow build-up. Two methods for the calculation...     

Responding to change: Using scenarios to understand how socioeconomic factors may influence amplifying or dampening exploitation feedbacks among Tanzanian fishers

Environmental change often requires societies to adapt. In some instances, these adaptations can create feedbacks that amplify the change. Alternatively, other adaptations may dampen the change. We used semi-structured interviews with 240 fishers from nine Tanzanian coastal communities to explore responses to four hypothetical scenarios of increasingly severe declines in their average catch (10%, 20%, 30% and 50%). Overall, a higher proportion of fishers said they would respond to decline using amplifying adaptations (such as fishing harder) than dampening adaptations (such as reducing effort), particularly in the scenarios with lower levels of decline. We used a redundancy analysis to explore whether certain types of responses were related to the fishers’ socioeconomic characteristics. Fishers that would employ amplifying responses had greater economic wealth but lacked options. Fishers who would adopt dampening responses possessed characteristics associated with having livelihood options. Fishers who would adopt neither amplifying nor dampening responses were less likely to belong to community groups and sold the largest proportion of their catch. This study provides novel contributions by differentiating aspects of adaptive capacity that will amplify versus dampen environmental change and by highlighting what the resource users’ themselves say regarding responding to environmental change. Although direct policy application is limited by the study's hypothetical scenario nature, it provides a good beginning to incorporating resource users’ voices into such policy discussions.     

The erosion rates of cohesive sediments in Venice lagoon,Italy

The stability of cohesive sediments from Venice lagoon has been measured in situ using the benthic flume Sea Carousel. Twenty four stations were occupied during summertime, and a sub-set of 13 stations was re-occupied during the following winter. Erosion thresholds and first-order erosion rates were estimated and showed a distinct difference between inter-tidal and sub-tidal stations. The higher values for inter-tidal stations are the result of exposure that influences consolidation, density, and organic adhesion. The thresholds for each state of sediment motion are well established. However, the rate of erosion once the erosion threshold has been exceeded has been poorly treated. This is because normally a time-series of sediment concentration (C) and bed shear stress (τ₀(t)) is used to define threshold stress or cohesion (τ_crit,z) and erosion rate (E). Whilst solution of the onset of erosion, τ_crit,0, is often reported, the evaluation of the erosion threshold variation through the process of erosion (eroded depth) is usually omitted or not estimated. This usually leads to assumptions on the strength profile of the bed which invariably has no credibility within the topmost mm of the bed where most erosion takes place. It is possible to extract this information from a time-series through the addition of a step in data processing. This paper describes how this is done, and the impact of this on the accuracy of estimates of the excess stress (τ₀(t)–τ_crit,z) on E.     

Analyzing spatial ecological data using linear regression and wavelet analysis

Spatial (two-dimensional) distributions in ecology are often influenced by spatial autocorrelation. In standard regression models, however, observations are assumed to be statistically independent. In this paper we present an alternative to other methods that allow for autocorrelation. We show that the theory of wavelets provides an efficient method to remove autocorrelations in regression models using data sampled on a regular grid. Wavelets are particularly suitable for data analysis without any prior knowledge of the underlying correlation structure. We illustrate our new method, called wavelet-revised model, by applying it to multiple regression for both normal linear models and logistic regression. Results are presented for computationally simulated data and real ecological data (distribution of species richness and distribution of the plant species Dianthus carthusianorum throughout Germany). These results are compared to those of generalized linear models and models based on generalized estimating equations. We recommend wavelet-revised models, in particular, as a method for logistic regression using large datasets.