pinecone/core-2020-05-10-deduplication huggingface dataset:
Geomorphology under ice streams : moving from form to process.

Ice streams are integral components of an ice sheet's mass balance and directly impact on sea level. Their flow is governed by processes at the ice-bed interface which create landforms that, in turn, modulate ice stream dynamics through their influence on bed topography and basal shear stresses. Thus, ice stream geomorphology is critical to understanding and modelling ice streams and ice sheet dynamics. This paper reviews developments in our understanding of ice stream geomorphology from an historical perspective, with a focus on the extent to which studies of modern and palaeo-ice streams have converged to take us from a position of near-complete ignorance to a detailed understanding of their bed morphology. During the 1970s and 1980s, our knowledge was limited and largely gleaned from geophysical investigations of modern ice stream beds in Antarctica. Very few palaeo-ice streams had been identified with any confidence. During the 1990s, however, glacial geomorphologists began to recognise their distinctive geomorphology, which included distinct patterns of highly elongated mega-scale glacial lineations, ice stream shear margin moraines, and major sedimentary depocentres. However, studying relict features could say little about the time-scales over which this geomorphology evolved and under what glaciological conditions. This began to be addressed in the early 2000s, through continued efforts to scrutinise modern ice stream beds at higher resolution, but our current understanding of how landforms relate to processes remains subject to large uncertainties, particularly in relation to the mechanisms and time-scales of sediment erosion, transport and deposition, and how these lead to the growth and decay of subglacial bedforms. This represents the next key challenge and will require even closer cooperation between glaciology, glacial geomorphology, sedimentology, and numerical modelling, together with more sophisticated methods to quantify and analyse the anticipated growth of geomorphological data from beneath active ice streams
Virtual velocity of sand transport in water.

Using the 160-m-long flume at Tsukuba University we undertook an experiment to provide a first estimate of the virtual velocity of sand in the size range 0.5 – 2.0 mm. For the flow velocity used in our experiment this sediment-size range would conventionally be regarded as suspended sediment. The virtual velocity is found to be 37-41 % of the flow velocity. Paradoxically, virtual velocity decreases as particle size decreases. Such a lower virtual velocity of finer sediment is not inconceivable. First, trapping of the sediment appears to be a function of bed roughness, and there is a probable relationship between bed roughness and trapping efficiency for particles of different sizes. Secondly, finer particles are more likely to find sheltered positions on a rough bed and thus experience lower mobility, relative to the more exposed coarser grains, as observed for bedload transport. Thirdly, the virtual velocity of particles undergoing bedload transport has been found, in some instances, to be lower for finer clasts. We combine our data with previous studies of virtual velocity of bedload to develop, for the first time, an hypothesis for an holistic analysis of sediment movement in rivers
From manned to unmanned aircraft : adapting airborne particle size mapping methodologies to the characteristics of sUAS and SfM.

Subaerial particle size data holds a wealth of valuable information for fluvial, coastal, glacial and other sedimentological applications. Recently, we have gained the opportunity to map and quantify surface particle sizes at the mesoscale using data derived from small unmanned aerial system (sUAS) imagery processed using structure from motion (SfM) photogrammetry. Typically, these sUAS-SfM approaches have been based on calibrating orthoimage texture or point cloud roughness with particle size. Variable levels of success are reported and a single, robust method capable of producing consistently accurate and precise results in a range of settings has remained elusive. In this paper, we develop an original method for mapping surface particle size with the specific constraints of sUAS and SfM in mind. This method uses the texture of single sUAS images, rather than orthoimages, calibrated with particle sizes normalised by individual image scale. We compare results against existing orthoimage texture and roughness approaches, and provide a quantitative investigation into the implications of the use of sUAS camera gimbals. Our results indicate that our novel single image method delivers an optimised particle size mapping performance for our study site, outperforming both other methods and delivering residual mean errors of 0.02mm (accuracy), standard deviation of residual errors of 6.90mm (precision) and maximum residual errors of 16.50mm. Accuracy values are more than two orders of magnitude worse when imagery is collected by a similar drone which is not equipped with a camera gimbal, demonstrating the importance of mechanical image stabilisation for particle size mapping using measures of image texture
Robotic photosieving from low-cost multirotor sUAS : a proof-of-concept.

Measurement of riverbed material grainsizes is now a routine part of fieldwork in fluvial geomorphology and lotic ecology. In the last decade, several authors have proposed remote sensing approaches of grain size measurements based on terrestrial and aerial imagery. Given the current rise of small Unmanned Aerial System (sUAS) applications in geomorphology, there is now increasing interest in the application of these remotely sensed grain size mapping methods to sUAS imagery. However, success in this area has been limited due to two fundamental problems: lack of constraint of image scale for sUAS imagery and blurring effects in sUAS images and resulting orthomosaics. In this work, we solve the former by showing that SfM-photogrammetry can be used in a direct georeferencing (DG) workflow (i.e. with no ground validation) in order to predict image scale within margins of 3%. We then propose a novel approach of robotic photosieving of dry exposed riverbed grains that relies on near-ground images acquired from a low-cost sUAS and which does not require the presence of ground control points or visible scale objects. We demonstrate that this absence of scale objects does not affect photosieving outputs thus resulting in a low-cost and efficient sampling method for surficial grains
Better models are more effectively connected models.

Water- and sediment-transfer models are commonly used to explain or predict patterns in the landscape at scales different from those at which observations are available. These patterns are often the result of emergent properties that occur because processes of water and sediment transfer are connected in different ways. Recent advances in geomorphology suggest that it is important to consider, at a specific spatio-temporal scale, the structural connectivity of system properties that control processes, and the functional connectivity resulting from the way those processes operate and evolve through time. We argue that a more careful consideration of how structural and functional connectivity are represented in models should lead to more robust models that are appropriate for the scale of application and provide results that can be upscaled. This approach is necessary because, notwithstanding the significant advances in computer power in recent years, many geomorphic models are still unable to represent the landscape in sufficient detail to allow all connectivity to emerge. It is important to go beyond the simple representation of structural connectivity elements and allow the dynamics of processes to be represented, for example by using a connectivity function. This commentary aims to show how a better representation of connectivity in models can be achieved, by considering the sorts of landscape features present, and whether these features can be represented explicitly in the model spatial structure, or must be represented implicitly at the subgrid scale
Waste dump erosional landform stability – a critical issue for mountain mining

Mining is the largest producer of solid wastes which, when released to land or into waterways, can cause harmful environmental impacts. This is mostly due to fluvial erosion, which is highly increased in mountain areas, due to abrupt slopes. We have analysed this situation at a mountain watershed (192 ha), where steep mined sites and their waste dumps are the main source of sediment in a Natural Park. This problem was tackled by building gabion check dams downstream from the mined sites. We used the DEM of Differences (DoD) method to quantify erosion and sediment yield from three waste dumps (5 ha). Their topography and substrate properties were analysed to understand the erosion problem. The sediment trapped by the check dams was quantified by Electrical Resistivity Tomography. The rainfall characteristics triggering an episode that filled the check dams with sediment in the winter of 2009-2010, were studied to confirm whether it was a case of extreme precipitation conditions. The waste dumps sediment yield (353 ± 95 Mg ha-1 yr-1) suggests severe landform instability. Analysis of topographic and substrate properties confirmed long, steep slopes combined with highly erodible materials. The check dams proved to be inefficient in controlling sediment loads, as they had only functioned for four years of 31 of existence, having trapped 13000 ± 660 m3 of sediment, whereas we estimated that the waste dumps have yielded approximately three times more sediment for the same period. Rainfall analyses showed that neither intense nor extreme conditions (return period of 25-35 years) triggered the mobilization of 37 ± 2 Mg ha-1 in a month. This study highlights the fact that mining operations in similar mountainous settings, with equivalent waste dump construction and reclamation practices, are currently unfeasible. We conclude that landform stability cannot be achieved at this site without landform changes
Microtopography of bare peat : a conceptual model and objective classification from high-resolution topographic survey data.

Peatlands globally are at risk of degradation through increased susceptibility to erosion as a result of climate change. Quantification of peat erosion and an understanding of the processes responsible for their degradation is required if eroded peatlands are to be protected and restored. Owing to the unique material properties of peat, fine‐scale microtopographic expressions of surface processes are especially pronounced and present a potentially rich source of geomorphological information, providing valuable insights into the stability and dominant surface process regimes. We present a new process‐form conceptual framework to rigorously describe bare peat microtopography and use Structure‐from‐Motion (SfM) surveys to quantify roughness for different peat surfaces. Through the first geomorphological application of a survey‐grade structured‐light hand‐held 3D imager (HhI), which can represent sub‐millimetre topographic variability in field conditions, we demonstrate that SfM identifies roughness signatures reliably over bare peat plots (<1 m2), although some smoothing is observed. Across 55 plots, the roughness of microtopographic types is quantified using a suite of roughness metrics and an objective classification system derived from decision tree analysis with 98% success. This objective classification requires just five roughness metrics, each of which quantifies a different aspect of the surface morphology. We show that through a combination of roughness metrics, microtopographic types can be identified objectively from high resolution survey data, providing a much‐needed geomorphological process‐perspective to observations of eroded peat volumes and earth surface change
Sediment and nutrient storage in a beaver engineered wetland

This is the final version of the article.Available from Wiley via the DOI in this record.Beavers, primarily through the building of dams, can deliver significant geomorphic modifications and result in changes to nutrient and sediment fluxes. Research is required to understand the implications and possible benefits of widespread beaver reintroduction across Europe. This study surveyed sediment depth, extent and carbon/nitrogen content in a sequence of beaver pond and dam structures in South West England, where a pair of Eurasian beavers (Castor fiber) were introduced to a controlled 1.8 ha site in 2011. Results showed that the 13 beaver ponds subsequently created hold a total of 101.53 ± 16.24 t of sediment, equating to a normalised average of 71.40 ± 39.65 kg m2. The ponds also hold 15.90 ± 2.50 t of carbon and 0.91 ± 0.15 t of nitrogen within the accumulated pond sediment.

The size of beaver pond appeared to be the main control over sediment storage, with larger ponds holding a greater mass of sediment per unit area. Furthermore, position within the site appeared to play a role with the upper‐middle ponds, nearest to the intensively‐farmed headwaters of the catchment, holding a greater amount of sediment. Carbon and nitrogen concentrations in ponds showed no clear trends, but were significantly higher than in stream bed sediment upstream of the site.

We estimate that >70% of sediment in the ponds is sourced from the intensively managed grassland catchment upstream, with the remainder from in situ redistribution by beaver activity. While further research is required into the long‐term storage and nutrient cycling within beaver ponds, results indicate that beaver ponds may help to mitigate the negative off‐site impacts of accelerated soil erosion and diffuse pollution from agriculturally dominated landscapes such as the intensively managed grassland in this study.The Mid-Devon Beaver Project is led by Mark Elliott from Devon Wildlife Trust, monitored by the University of Exeter,and funded by Devon Wildlife Trust, University of Exeter and Westland Countryside Stewards. Further support came from NERC grant: NERC/PE/2016_087 and the Wellcome Trust
Applying Pattern Oriented Sampling in current fieldwork practice to enable more effective model evaluation in fluvial landscape evolution research

Field geologists and geomorphologists are increasingly looking to numerical modelling to understand landscape change over time, particularly in river catchments. The application of landscape evolution models (LEMs) started with abstract research questions in synthetic landscapes. Now, however, studies using LEMs on real-world catchments are becoming increasingly common. This development has philosophical implications for model specification and evaluation using geological and geomorphological data, besides practical implications for fieldwork targets and strategy. The type of data produced to drive and constrain LEM simulations has very little in common with that used to calibrate and validate models operating over shorter timescales, making a new approach necessary. Here we argue that catchment fieldwork and LEM studies are best synchronized by complementing the Pattern Oriented Modelling (POM) approach of most fluvial LEMs with Pattern Oriented Sampling (POS) fieldwork approaches. POS can embrace a wide range of field data types, without overly increasing the burden of data collection. In our approach, both POM output and POS field data for a specific catchment are used to quantify key characteristics of a catchment. These are then compared to provide an evaluation of the performance of the model. Early identification of these key characteristics should be undertaken to drive focused POS data collection and POM model specification. Once models are evaluated using this POM/POS approach, conclusions drawn from LEM studies can be used with greater confidence to improve understanding of landscape change. © 2018 John Wiley & Sons, Ltd.Peer reviewe
Multiple metals exposure and neurotoxic risk in bald eagles ( Haliaeetus leucocephalus ) from two Great Lakes states

In the present study, the authors determined concentrations of several elements (As, Cd, Co, Cu, Cr, Mn, Pb, Sb, Zn) in the brains and livers of 46 bald eagles ( Haliaeetus leucocephalus ) from two Great Lakes states, Michigan and Minnesota. To explore whether exposures are of neurological concern, the authors assessed their associations with neurochemical receptors ( N ‐methyl‐ D ‐aspartate [NMDA] and γ‐aminobutyric acid A [GABA(A)]) and enzymes (glutamine synthetase [GS] and glutamic acid decarboxylase [GAD]) that play critical roles in vertebrate neurobehavior and reproduction. For most elements, levels in the livers and brains did not differ between region and gender. Hepatic Pb levels averaged 33.1 ppm (dry wt), 30.4% of all carcasses exceeded proposed avian Pb thresholds (>26.4 ppm), and in 30.8% of the birds examined evidence of Pb pellets or fragments was found. Significant changes in the activities of GS and GAD were related to brain concentrations of several metals (Pb, Cd, Co, Cu, Zn). No relationships were found among any of the nine elements and NMDA or GABA(A) receptor levels. When combined with the authors' previous study on these same eagles that showed Hg‐associated alterations in GS, GAD, and NMDA receptor levels, the present research suggests that bald eagles are exposed to various elements, especially Pb and Hg, that are capable of causing changes in GABAergic and glutamatergic neurotransmission. The functional significance of these neurochemical changes warrants attention. Environ. Toxicol. Chem. 2012;31:623–631. © 2011 SETA
Short‐term macroinvertebrate recruitment and sediment accumulation: A novel field chamber approach

Stream‐deposited sediment is one of the major stressors affecting stream biota. Several methods exist to quantify stream sediment embeddedness, but they are relatively qualitative and operationally defined. The authors developed a short‐term in situ embeddedness chamber method to measure aquatic insect recruitment and associated sediment accumulation in a more quantitative, better replicated manner. With sediment accumulation and aquatic insect recruitment as endpoints, three exposure periods were evaluated (4, 7, and 14 d) on a low‐order stream (Honey Creek, New Carlisle, Ohio, USA) and a medium‐order stream (Stillwater River, Covington, Ohio, USA). Chamber results show significant positive correlations between newly deposited fine sediment and insect recruitment. Embeddedness was also measured using the more conventional techniques of the Burns method and the U.S. Geological Survey National Water Quality Assessment Program method. This in situ chamber method allows for increased experimental options for assessing the stress of embeddedness and siltation on benthic communities and may prove useful for investigating the resilience of benthic communities after disturbances. Environ. Toxicol. Chem. 2012; 31: 1098–1106. © 2012 SETA
Toxicity of dietary methylmercury to fish: Derivation of ecologically meaningful threshold concentrations

Threshold concentrations associated with adverse effects of dietary exposure to methylmercury (MeHg) were derived from published results of laboratory studies on a variety of fish species. Adverse effects related to mortality were uncommon, whereas adverse effects related to growth occurred only at dietary MeHg concentrations exceeding 2.5 µg g −1  wet weight. Adverse effects on behavior of fish had a wide range of effective dietary concentrations, but generally occurred above 0.5 µg g −1  wet weight. In contrast, effects on reproduction and other subclinical endpoints occurred at dietary concentrations that were much lower (<0.2 µg g −1  wet wt). Field studies generally lack information on dietary MeHg exposure, yet available data indicate that comparable adverse effects have been observed in wild fish in environments corresponding to high and low MeHg contamination of food webs and are in agreement with the threshold concentrations derived here from laboratory studies. These thresholds indicate that while differences in species sensitivity to MeHg exposure appear considerable, chronic dietary exposure to low concentrations of MeHg may have significant adverse effects on wild fish populations but remain little studied compared to concentrations in mammals or birds. Environ. Toxicol. Chem. 2012; 31: 1536–1547. © 2012 SETA
On the quantification of intertest variability in ecotoxicity data with application to species sensitivity distributions.

Ecotoxicological hazard assessment relies on species effect data to estimate quantities such as the predicted no-effect concentration. While there is a concerted effort to quantify uncertainty in risk assessments, the uncertainty due to intertest variability in species effect measurements is an overlooked component. The European Union Registration, Evaluation, Authorisation, and Restriction of Chemicals (REACH) guidance document suggests that multiple toxicity records for a given chemical–species combination should be aggregated by the geometric mean. Ignoring this issue or applying unjustified so-called harmonization methods weakens the defensibility of uncertainty quantification and interpretation about properties of ecological models, for example, the predicted no-effect concentration. In the present study, the authors propose a simple and broadly theoretically justifiable model to quantify intertest variability and analyze it using Bayesian methods. The value of data in ecotoxicity databases is maximized by using (interval-)censored data. An exploratory analysis is provided to support the model. The authors conclude, based on a large ecotoxicity database of acute effects to aquatic species, that the standard deviation of intertest variability is approximately a factor (or fold-difference) of 3. The consequences for decision makers of (not) adjusting for intertest variability are demonstrated. Environ. Toxicol. Chem. 2012; 31: 1903–1910. © 2012 SETA
Comparison of species sensitivity distributions based on population or individual endpoints

International audienceSpecies sensitivity distributions (SSDs) developed from individual and population endpoints were compared based on simulations and a case study. The simulations were performed with five invertebrate species accounting for the diversity of benthic macroinvertebrate communities in large European lowland rivers and for five benthic invertebrates used as laboratory species. Population growth rate 10% effective concentration (EC10) values were, in most of the simulations, higher than the lowest of the EC10 values at the individual level. However, for the set of ecologically representative species, the fifth percentile level of this distribution (HC5) was more protective for population endpoints than for individual endpoints. This was the opposite for the set of laboratory species. Population and individual SSDs were also compared based on existing data on Cu for the five laboratory invertebrate species. In this case, the calculated population HC5 value was almost twice the individual value, and the authors showed much reduced variability between species sensitivities at population level compared with individual level. They conclude that population-based HC5 would generally be more protective than individual-based HC5. However, the change of level could reveal higher homogeneity at population level than at individual level, supporting the use of population-based HC5 to avoid overprotection. The authors thus advise the derivation of population-based HC5, as soon as it is possible, to derive such value with a relevant panel of species