Organic Geochemical Microanalysis by Time‐of‐Flight Secondary Ion Mass Spectrometry (ToF‐SIMS)

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) is a powerful method for the chemical analysis of solid surfaces. In this paper, the capabilities and limitations of this technique and the potential for its use in geochemical research are outlined. Using ToF‐SIMS, the chemical composition of sample structures down to 10–100 μm can be determined, without the need for pre‐selection or labelling of the analysed substances. In addition, the lateral distribution of organic and inorganic compounds can be mapped in geochemical samples at a resolution in the micrometre range. The capabilities of the technique in geochemistry are illustrated by two examples. In the first example, it is shown that ToF‐SIMS can be used to detect biomarkers in oil samples, making it a promising method for the analysis of biomarkers in fluid inclusions. In the second example, a number of specific lipid biomarkers were identified and mapped on the surface of a microbial mat cryosection surface. Post‐measurement optical microscopy correlated the localisation of the lipids with the presence of methanotrophic archaea in the microbial mat.     

Interplay of eustatic,tectonic and autogenic controls on a Late Devonian carbonate platform,northern Canning Basin,Australia

Frasnian reef complexes along the northern margin of the Canning Basin in northwestern Australia evolved during rifting of the Fitzroy Trough. Geological investigations of the Frasnian Hull platform, which developed on an active tilted fault‐block, reveal significant lateral and vertical facies variations superimposed on prominent metre‐scale cyclicity. This study uses numerical analyses of facies and magnetic susceptibility data from three measured sections along the Hull platform to test whether a tectonic signal can be distinguished from eustatic and other signals. Geostatistical analysis of facies variations reveals an exponential distribution of thin (<3 m) facies, characteristic of stochastic depositional processes. Thick subtidal facies predominate in the Guppy Hills (GH) and southeastern Hull Range (SHR) sections near the hangingwall margin, and thick shallow‐subtidal to intertidal facies dominate the Horse Springs drillcore (HD 14) section near the footwall margin. Power and wavelet spectral analyses indicate a strong periodic component; Average Spectral Misfit and spectral optimisation methods confirm the presence of Milankovitch eccentricity signals and suggest the presence of obliquity and precession signals. However, the results also expose strong temporal and spatial variation providing evidence for tectonic control. Spectral analyses show strongest periodicity is recorded in short intervals that are not correlated across the platform and provide evidence of variations in sedimentation rate and hiatuses. Time series for the neighbouring GH and SHR sections show no overall statistical correlation, and Markov analysis indicates weakly ordered vertical facies transitions that do not correlate across the platform. Subtidal to intertidal facies data from HD 14 core suggest that at least 35% of the section is absent, almost obscuring the Milankovitch signal. The results indicate a complex set of controls on deposition on the Hull platform with local tectonic effects having produced spatio‐temporal moderation of the underlying eustatic signals and autogenic processes adding a localised stochastic response.     

Relating Hyperspectral Airborne Data to Ground Measurements in a Complex and Discontinuous Canopy

The work described in this paper is aimed at validating hyperspectral airborne reflectance data collected during the Regional Experiments For Land-atmosphere EXchanges (REFLEX) campaign. Ground reflectance data measured in a vineyard were compared with airborne reflectance data. A sampling strategy and subsequent ground data processing had to be devised so as to capture a representative spectral sample of this complex crop. A linear model between airborne and ground data was tried and statistically tested. Results reveal a sound correspondence between ground and airborne reflectance data (R2 > 0.97), validating the atmospheric correction of the latter.     

Evidence for elevated coastal vulnerability following large‐scale historical oyster bed harvesting

Living coastal barriers, such as coral reefs, tidal marshes, mangroves and shellfish beds are widely recognized for their potential role in mitigating flood risk. Limited data exists, however, for assessing the effectiveness of these natural defenses as forms of flood mitigation. In particular, very few mature shellfish beds exist today for modern study due to their destruction in the past few centuries. As an alternative method of study, we present here sedimentary reconstructions of storm overwash from coastal ponds internal to New York Harbor. We use these reconstructions to show that the initial degradation of oyster beds following European settlement of the area coincides with a significant increase in wave‐derived overwash deposition at all three of our field sites. Numerical simulations of two flood events of record in the harbor (Hurricane Sandy and a severe winter storm in 1992) were run without and with oyster beds of varying heights (1 m above the seafloor‐to‐intertidal). Simulations show that the removal of these oyster beds increases wave energy directly off‐shore of our field sites by between 30% and 200%. Sedimentary reconstructions and wave modeling experiments therefore both support oyster beds serving as a significant form of coastal protection prior to European disturbance. Copyright © 2016 John Wiley & Sons, Ltd.     

How does forest structure affect root reinforcement and susceptibility to shallow landslides?

Forests can decrease the risk of shallow landslides by mechanically reinforcing the soil and positively influencing its water balance. However, little is known about the effect of different forest structures on slope stability. In the study area in St Antönien, Switzerland, we applied statistical prediction models and a physically‐based model for spatial distribution of root reinforcement in order to quantify the influence of forest structure on slope stability. We designed a generalized linear regression model and a random forest model including variables describing forest structure along with terrain parameters for a set of landslide and control points facing similar slope angle and tree coverage. The root distribution measured at regular distances from seven trees in the same study area was used to calibrate a root distribution model. The root reinforcement was calculated as a function of tree dimension and distance from tree with the root bundle model (RBMw). Based on the modelled values of root reinforcement, we introduced a proxy‐variable for root reinforcement of the nearest tree using a gamma distribution. The results of the statistical analysis show that variables related to forest structure significantly influence landslide susceptibility along with terrain parameters. Significant effects were found for gap length, the distance to the nearest trees and the proxy‐variable for root reinforcement of the nearest tree. Gaps longer than 20 m critically increased the susceptibility to landslides. Root reinforcement decreased with increasing distance from trees and is smaller in landslide plots compared to control plots. Furthermore, the influence of forest structure strongly depends on geomorphological and hydrological conditions. Our results enhance the quantitative knowledge about the influence of forest structure on root reinforcement and landslide susceptibility and support existing management recommendations for protection against gravitational natural hazards. Copyright © 2015 John Wiley & Sons, Ltd.     

Metazooplankton communities in the Ahe atoll lagoon (Tuamotu Archipelago, French Polynesia): Spatiotemporal variations and trophic relationships

Metazooplankton abundance, biomass (<80μm, 200-500μm and >500μm) and community structure in the Ahe atoll were studied together with their relationships with environmental factors (temperature, salinity, wind) and trophic factors (phytoplankton, bacteria, heterotrophic nanoflagellates (HNF) and ciliates) during three periods in 2008-2009. Meroplankton, mainly bivalve and gastropod larvae, was dominant. Holoplankton was dominated by copepods, the main species being Oithona spp., Paracalanus parvus, Clausocalanus spp., Corycaeus spp., Acartia fossae and Undinula vulgaris. The results suggest a clear wind influence on the structure and horizontal distribution of the zooplankton communities. The metazooplankton appeared to be controlled mainly by food resources, suggesting a bottom-up control. The low nanophytoplankton biomass in contrast to the high abundance of picophytoplankton, HNF and nano-particle grazers (mainly Oithona spp., Paracalanus and bivalve larvae) highlighted the importance of the microbial loop in the food web.     

The added value of participatory modelling in fisheries management – what has been learnt?

How can uncertain fisheries science be linked with good governance processes, thereby increasing fisheries management legitimacy and effectiveness? Reducing the uncertainties around scientific models has long been perceived as the cure of the fisheries management problem. There is however increasing recognition that uncertainty in the numbers will remain. A lack of transparency with respect to these uncertainties can damage the credibility of science. The EU Commission's proposal for a reformed Common Fisheries Policy calls for more self-management for the fishing industry by increasing fishers' involvement in the planning and execution of policies and boosting the role of fishers' organisations. One way of higher transparency and improved participation is to include stakeholders in the modelling process itself. The JAKFISH project (Judgment And Knowledge in Fisheries Involving StakeHolders) invited fisheries stakeholders to participate in the process of framing the management problem, and to give input and evaluate the scientific models that are used to provide fisheries management advice. JAKFISH investigated various tools to assess and communicate uncertainty around fish stock assessments and fisheries management. Here, a synthesis is presented of the participatory work carried out in four European fishery case studies (Western Baltic herring, North Sea Nephrops, Central Baltic Herring and Mediterranean swordfish), focussing on the uncertainty tools used, the stakeholders' responses to these, and the lessons learnt. It is concluded that participatory modelling has the potential to facilitate and structure discussions between scientists and stakeholders about uncertainties and the quality of the knowledge base. It can also contribute to collective learning, increase legitimacy, and advance scientific understanding. However, when approaching real-life situations, modelling should not be seen as the priority objective. Rather, the crucial step in a science–stakeholder collaboration is the joint problem framing in an open, transparent way.     

Effects of sampling microhabitats with low coverage within the STAR/AQEM macroinvertebrate sampling protocol on stream assessment

In the STAR/AQEM protocol microhabitats covering less than 5% of the sampling area were neglected. Driven by an ongoing discussion on the importance of these underrepresented microhabitats we tested the influence of sampling them. We investigated 48 streams representing 14 different stream types from all over Germany. Macroinvertebrates of underrepresented microhabitats were sampled in addition to the STAR/AQEM protocol. To ensure the method remains feasible in routine monitoring programmes the total sampling and sorting effort of additional sampling was limited to 20 min. Particularly those taxa were picked, which were not recognised during the routine STAR/AQEM sorting.To identify the effect of additional sampling on stream assessment results, we calculated the stream type-specific Multimetric Index (MMI) with the “main” and the “main+additional” data for each sample. The mean and median difference in MMI values between “main” and “main+additional” samples was 0.02 and 0.01, respectively. In seven of 48 samples (14.6%) a different ecological quality class was calculated with the “main+additional” dataset. Regarding common metrics within the MMI as well as intercalibration metrics differences between “main” and “main+additional” samples were analysed. The values differed most in richness metrics (e.g., number of EPTCBO Taxa, number of Trichoptera Taxa). The results of the present study show that additional sampling of underrepresented microhabitats could alter multimetric assessment results.