Benthic Carbon Mineralization and Nutrient Turnover in a Scottish Sea Loch: An Integrative In Situ Study

Based on in situ microprofiles, chamber incubations and eddy covariance measurements, we investigated the benthic carbon mineralization and nutrient regeneration in a ~65-m-deep sedimentation basin of Loch Etive, UK. The sediment hosted a considerable amount of infauna that was dominated by the brittle star A. filiformis. The numerous burrows were intensively irrigated enhancing the benthic in situ O₂ uptake by ~50 %, and inducing highly variable redox conditions and O₂ distribution in the surface sediment as also documented by complementary laboratory-based planar optode measurements. The average benthic O₂ exchange as derived by chamber incubations and the eddy covariance approach were similar (14.9 ± 2.5 and 13.1 ± 9.0 mmol m^?2 day^?1) providing confidence in the two measuring approaches. Moreover, the non-invasive eddy approach revealed a flow-dependent benthic O₂ flux that was partly ascribed to enhanced ventilation of infauna burrows during periods of elevated flow rates. The ratio in exchange rates of ΣCO₂ and O₂ was close to unity, confirming that the O₂ uptake was a good proxy for the benthic carbon mineralization in this setting. The infauna activity resulted in highly dynamic redox conditions that presumably facilitated an efficient degradation of both terrestrial and marine-derived organic material. The complex O₂ dynamics of the burrow environment also concurrently stimulated nitrification and coupled denitrification rates making the sediment an efficient sink for bioavailable nitrogen. Furthermore, bioturbation mediated a high efflux of dissolved phosphorus and silicate. The study documents a high spatial and temporal variation in benthic solute exchange with important implications for benthic turnover of organic carbon and nutrients. However, more long-term in situ investigations with like approaches are required to fully understand how environmental events and spatio-temporal variations interrelate to the overall biogeochemical functioning of coastal sediments.     

The Dynamics of Benthic Respiration at a Mid-Shelf Station Off Oregon

Mid-shelf sediments off the Oregon coast are characterized as fine sands that trap and remineralize phytodetritus leading to the consumption of significant quantities of dissolved oxygen. Sediment oxygen consumption (SOC) can be delayed from seasonal organic matter inputs because of a transient buildup of reduced constituents during periods of quiescent physical processes. Between 2009 and 2013, benthic oxygen exchange rates were measured using the noninvasive eddy covariance (EC) method five separate times at a single 80-m station. Ancillary measurements included in situ microprofiles of oxygen at the sediment–water interface, and concentration profiles of pore water nutrients and trace metals, and solid-phase organic C and sulfide minerals from cores. Sediment cores were also incubated to derive anaerobic respiration rates. The EC measurements were made during spring, summer, and fall conditions, and they produced average benthic oxygen flux estimates that varied between ?2 and ?15 mmol m^?2 d^?1. The EC oxygen fluxes were most highly correlated with bottom-sensed, significant wave heights (H _s). The relationship with H _s was used with an annual record of deepwater swell heights to predict an integrated oxygen consumption rate for the mid-shelf of 1.5 mol m^?2 for the upwelling season (May–September) and 6.8 mol m^?2 y^?1. The annual prediction requires that SOC rates are enhanced in the winter because of sand filtering and pore water advection under large waves, and it counters budgets that assume a dominance of organic matter export from the shelf. Refined budgets will require winter flux measurements and observations from cross-shelf transects over multiple years.     

Why GPS makes distances bigger than they are

Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.     

Novel shape indices for vector landscape pattern analysis

The formation of an anisotropic landscape is influenced by natural and/or human processes, which can then be inferred on the basis of geometric indices. In this study, two minimal bounding rectangles in consideration of the principles of mechanics (i.e. minimal width bounding (MWB) box and moment bounding (MB) box) were introduced. Based on these boxes, four novel shape indices, namely MBLW (the length-to-width ratio of MB box), PAMBA (area ratio between patch and MB box), PPMBP (perimeter ratio between patch and MB box) and ODI (orientation difference index between MB and MWB boxes), were introduced to capture multiple aspects of landscape features including patch elongation, patch compactness, patch roughness and patch symmetry. Landscape pattern was, thus, quantified by considering both patch directionality and patch shape simultaneously, which is especially suitable for anisotropic landscape analysis. The effectiveness of the new indices were tested with real landscape data consisting of three kinds of saline soil patches (i.e. the elongated shaped slightly saline soil class, the circular or half-moon shaped moderately saline soil, and the large and complex severely saline soil patches). The resulting classification was found to be more accurate and robust than that based on traditional shape complexity indices.     

Map-Based Web Tools Supporting Climate Change Adaptation

This article discusses the state of the art in geovisualization supporting climate change adaptation. We reviewed twenty selected map-based Web tools, classified by their content and functionality, and assessed them by visual representations, interactive functions, information type, target audience, and how vulnerability and adaptation to climate change are addressed. Our study concludes that the tools (1) can be classified as data viewers with basic functionality and data explorers offering more sophisticated interactive functions; (2) mostly feature moderate or high richness of data content; and (3) predominantly target expert users.     

Spatial Concentration in Australian Regional Development,Exogenous Shocks and Regional Demographic Outcomes: a South Australian case study

ABSTRACT

As a tribute to the massive contribution of our friend and colleague Graeme Hugo to the population and settlement geography of Australian rural areas, this paper presents a longitudinal study from his home State. It forms part of a wider study of the long-term demographic relationships between Australia’s rapidly growing regional cities and their surrounding functional regions. Of particular interest is the question of what effect the accelerating concentration of population and economic activity into a given regional city will have for the longer term demographic sustainability of its functional region as a whole. Taking the case of Port Lincoln, regional capital of most of South Australia’s Eyre Peninsula, it examines the nature of change in the functional region over the period 1947–2011, and investigates the forces feeding, and partly counteracting, the population concentration process, informed by concepts of evolutionary economic geography. In particular it traces the demographic impact (particularly differential migration and ageing trends) of exogenous shocks to the region’s essentially primary productive economic base during the period of major change from 1981 to 2011.     

The sedimentary and tectonic evolution of the Amur River and North Sakhalin Basin: new evidence from seismic stratigraphy and Neogene–Recent sediment budgets

The North Sakhalin Basin in the western Sea of Okhotsk has been the main site of sedimentation from the Amur River since the Early Miocene. In this article, we present regional seismic reflection data and a Neogene–Recent sediment budget to constrain the evolution of the basin and its sedimentary fill, and consider the implications for sediment flux from the Amur River, in particular testing models of continental‐scale Neogene drainage capture. The Amur‐derived basin‐fill history can be divided into five distinct stages: the first Amur‐derived sediments (>21–16.5 Ma) were deposited during a period of transtension along the Sakhalin‐Hokkaido Shear Zone, with moderately high sediment flux to the basin (71 Mt year^?1). The second stage sequence (16.5–10.4 Ma) was deposited following the cessation of transtension, and was characterised by a significant reduction in sediment flux (24 Mt year^?1) and widespread retrogradation of deltaic sediments. The third (10.4–5.3 Ma) and fourth (5.3–2.5 Ma) stages were characterised by progradation of deltaic sediments and an associated increase in sediment flux (48–60 Mt year^?1) to the basin. Significant uplift associated with regional transpression started during this time in southeastern Sakhalin, but the north‐eastward propagating strain did not reach the NE shelf of Sakhalin until the Pleistocene (<2.5 Ma). This uplift event, still ongoing today, resulted in recycling of older deltaic sediments from the island of Sakhalin, and contributed to a substantially increased total sediment flux to the adjacent basinal areas (165 Mt year^?1). Adjusted rates to discount these local erosional products (117 Mt year^?1) imply an Amur catchment‐wide increase in denudation rates during the Late Pliocene–Pleistocene; however, this was likely a result of global climatic and eustatic effects, combined with tectonic processes within the Amur catchment and possibly a smaller drainage capture event by the Sungari tributary, rather than continental‐scale drainage capture involving the entire upper Amur catchment.     

On the simulation of multidimensional cyclic loading with intergranular strain

A sample of soil is subjected to multidimensional cyclic loading when two or three principal components of the stress or strain tensor are simultaneously controlled to perform a repetitive path. These paths are very useful to evaluate the performance of models simulating cyclic loading. In this article, an extension of an existing constitutive model is proposed to capture the behavior of the soil under this type of loading. The reference model is based on the intergranular strain anisotropy concept and therefore incorporates an elastic locus in terms of a strain amplitude. In order to evaluate the model performance, a modified triaxial apparatus able to perform multidimensional cyclic loading has been used to conduct some experiments with a fine sand. Simulations of the extended model with multidimensional loading paths are carefully analyzed. Considering that many cycles are simulated (\(N>30\)), some additional simulations have been performed to quantify and analyze the artificial accumulation generated by the (hypo-)elastic component of the model. At the end, a simple boundary value problem with a cyclic loading as boundary condition is simulated to analyze the model response.     

2D probabilistic prediction of sparsely measured earth properties constrained by geophysical imaging fully accounting for tomographic reconstruction ambiguity

Many hydrological, environmental, or engineering exploration tasks require predicting spatially continuous scenarios of sparsely measured borehole logging data. We present a methodology to probabilistically predict such scenarios constrained by ill-posed geophysical tomography. Our approach allows for transducing tomographic reconstruction ambiguity into the probabilistic prediction of spatially continuous target parameter scenarios. It is even applicable to data sets where petrophysical relations in the survey area are non-unique, i.e., different facies related petrophysical relations may be present. We employ static two-layer artificial neural networks (ANNs) for prediction and additionally evaluate, whether the training performance of the ANNs can be used to rank geophysical tomograms, which are mathematically equal reconstructions of physical parameter distributions in the ground. We illustrate our methodology using a realistic synthetic database for maximal control about the prediction performance and ranking potential of the approach. For doing so, we try to link geophysical radar and seismic tomography as input parameters to porosity of the ground as target parameter of ANN. However, the approach is flexible and can cope with any combination of geophysical tomograms and hydrologic, environmental or engineering target parameters. Ranking of equivalent geophysical tomograms based on additional borehole logging data is found to be generally possible, but risks remain that the ranking based on the ANN training performance does not fully coincide with the closeness of geophysical tomograms to ground truth. Since geophysical field data sets do usually not offer control options similar to those used in our synthetic database, we do not recommend the utilization of recurrent ANNs to learn weights for the individual geophysical tomograms used in the prediction procedure.