Introduction to the BASIN Special Issue: State of art, past present a view to the future

Marine ecosystems are complex networks of organisms interacting either directly or indirectly while under the influence of the physical and chemical properties of the medium they inhabit. The interplay between these biological agents and their abiotic environment results in complex non-linear responses to individual and multiple stressors, influenced by feedbacks between these organisms and their environment. These ecosystems provide key services that benefit humanity such as food provisioning via the transfer of energy to exploited fish populations or climate regulation via the sinking, subsequent mineralization and ultimately storage of carbon in the ocean interior. These key characteristics or emergent features of marine ecosystems are subject to rapid change (e.g. regime shifts; Alheit et al., 2005 and Scheffer et al., 2009), with outcomes that are largely unpredictable in a deterministic sense. The North Atlantic Ocean is host to a number of such systems which are collectively being influenced by the unique physical and chemical features of this ocean basin, such as the Atlantic Meridional Overturning Circulation (AMOC), the basin’s ventilation with the Arctic Ocean, the dynamics of heat transport via the Gulf Stream and the formation of deep water at high latitudes. These features drive the solubility and biological pumps and support the production and environments that results in large exploited fish stocks. Our knowledge of its functioning as a coupled system, and in particular how it will respond to change, is still limited despite the scientific effort exerted over more than 100 years. This is due in part to the difficulty of providing synoptic overviews of a vast area, and to the fact that most fieldwork provides only snapshots of the complex physical, chemical and biological processes and their interactions. These constraints have in the past limited the development of a mechanistic understanding of the basin as a whole, and thus of the services it provides.

Unbiased Linear Property Estimation For Spheres From Sections Exhibiting Overprojection And Truncation

In the biological sciences, stereological techniques are frequently used to infer changes in structural parameters (volume fraction, for example) between samples from different populations or subject to differing treatment regimes. Non-homogeneity of these parameters is virtually guaranteed, both between experimental animals and within the organ under consideration. A two-stage strategy is then desirable, the first stage involving unbiased estimation of the required parameter, separately for each experimental unit, the latter being defined as a subset of the organ for which homogeneity can reasonably be assumed. In the second stage, these point estimates are used as data inputs to a hierarchical analysis of variance, to distinguish treatment effects from variability between animals, for example. Techniques are therefore required for unbiased estimation of parameters from potentially small numbers of sample profiles. This paper derives unbiased estimates of linear properties in one special case—the sampling of spherical particles by transmission microscopy, when the section thickness is not negligible and the resulting circular profiles are subject to lower truncation. The derivation uses the general integral equation formulation of Nicholson (1970); the resulting formulae are simplified, algebraically, and their efficient computation discussed. Bias arising from variability in slice thickness is shown to be negligible in typical cases. The strategy is illustrated for data examining the effects, on the secondary lysosomes in the digestive cells, of exposure of the common mussel to hydrocarbons. Prolonged exposure, at 30 μg 1−1 total oil-derived hydrocarbons, is seen to increase the average volume of a lysosome, and the volume fraction that lysosomes occupy, but to reduce their number.

A method for semi-automated objective quantification of linear bedforms from multi-scale Digital Elevation Models

The increasing availability of large, detailed digital representations of the Earth’s surface demands the application of objective and quantitative analyses. Given recent advances in the understanding of the mechanisms of formation of linear bedform features from a range of environments, objective measurement of their wavelength, orientation, crest and trough positions, height and asymmetry is highly desirable. These parameters are also of use when determining observation-based parameters for use in many applications such as numerical modelling, surface classification and sediment transport pathway analysis. Here, we (i) adapt and extend extant techniques to provide a suite of semi-automatic tools which calculate crest orientation, wavelength, height, asymmetry direction and asymmetry ratios of bedforms, and then (ii) undertake sensitivity tests on synthetic data, increasingly complex seabeds and a very large-scale (39 000km2) aeolian dune system. The automated results are compared with traditional, manually derived,measurements at each stage. This new approach successfully analyses different types of topographic data (from aeolian and marine environments) from a range of sources, with tens of millions of data points being processed in a semi-automated and objective manner within minutes rather than hours or days. The results from these analyses show there is significant variability in all measurable parameters in what might otherwise be considered uniform bedform fields. For example, the dunes of the Rub’ al Khali on the Arabian peninsula are shown to exhibit deviations in dimensions from global trends. Morphological and dune asymmetry analysis of the Rub’ al Khali suggests parts of the sand sea may be adjusting to a changed wind regime from that during their formation 100 to 10 ka BP.