The European Upper Mantle as Seen by Surface Waves

We derive a global, three-dimensional tomographic model of horizontally and vertically polarized shear velocities in the upper mantle. The model is based on a recently updated global database of Love- and Rayleigh-wave fundamental-mode phase-anomaly observations, with a good global coverage and a particularly dense coverage over Europe and the Mediterranean basin (broadband stations from the Swiss and German seismic networks). The model parameterization is accordingly finer within this region than over the rest of the globe. The large-scale, global structure of our model is very well correlated with that of earlier shear-velocity tomography models, based both on body- and surface-wave observations. At the regional scale, within the region of interest, correlation is complicated by the different resolution limits associated to different databases (surface waves, compressional waves, shear waves), and, accordingly, to different models; while a certain agreement appears to exist for what concerns the grand tectonic features in the area, heterogeneities of smaller scale are less robustly determined. Our new model is only one step towards the identification of a consensus model of European/Mediterranean upper-mantle structure: on the basis of the findings discussed here, we expect that important improvements will soon result from the combination, in new tomographic inversions, of fundamental-mode phase-anomaly data like ours with observations of surface-wave overtones, of body-wave travel times, of ambient "noise”, and by accounting for an a-priori model of crustal structure more highly resolved than the one employed her

Natural capital metrics. Phase 1 final report: central components

This is a condensed version of the Natural Capital Metrics (NCMet) project Phase 1 report. It focuses on three key components: i) the conceptual framework, ii) development of six example evidence-chains and their associated data and model inventories, and iii) early development work towards a Natural Capital Portal to provide access to relevant data, models and maps of natural capital. All outputs are preliminary and are undergoing considerable refinement in the second phase of the project. Phase 2 outputs will be available in 2018

Rapid Earthquake Characterization Using MEMS Accelerometers and Volunteer Hosts Following the M 7.2 Darfield, New Zealand, Earthquake

We test the feasibility of rapidly detecting and characterizing earthquakes with the Quake‐Catcher Network (QCN) that connects low‐cost microelectromechanical systems accelerometers to a network of volunteer‐owned, Internet‐connected computers. Following the 3 September 2010 M 7.2 Darfield, New Zealand, earthquake we installed over 180 QCN sensors in the Christchurch region to record the aftershock sequence. The sensors are monitored continuously by the host computer and send trigger reports to the central server. The central server correlates incoming triggers to detect when an earthquake has occurred. The location and magnitude are then rapidly estimated from a minimal set of received ground‐motion parameters. Full seismic time series are typically not retrieved for tens of minutes or even hours after an event. We benchmark the QCN real‐time detection performance against the GNS Science GeoNet earthquake catalog. Under normal network operations, QCN detects and characterizes earthquakes within 9.1 s of the earthquake rupture and determines the magnitude within 1 magnitude unit of that reported in the GNS catalog for 90% of the detections

The northern Hikurangi margin three-dimensional plate interface in New Zealand remains rough 100 km from the trench

At the northern Hikurangi margin (North Island, New Zealand), shallow slow slip events (SSEs) frequently accommodate subduction-interface plate motion from landward of the trench to <20 km depth. SSEs may be spatially related to geometrical interface heterogeneity, though kilometer-scale plate-interface roughness imaged by active-source seismic methods is only constrained offshore at <12 km depth. Onshore constraints are comparatively lacking, but we mapped the Hikurangi margin plate interface using receiver functions from data collected by a dense 22 × 10 km array of 49 broadband seismometers. The plate interface manifests as a positive-amplitude conversion (velocity increase with depth) dipping west from 10 to 17 km depth. This interface corroborates relocated earthquake hypocenters, seismic velocity models, and downdip extrapolation of depth-converted two-dimensional active-source lines. Our mapped plate interface has kilometer-amplitude roughness we interpret as oceanic volcanics or seamounts, and is 1–4 km shallower than the regional-scale plate-interface model used in geodetic inversions. Slip during SSEs may thus have different magnitudes and/or distributions than previously thought. We show interface roughness also leads to shear-strength variability, where slip may nucleate in locally weak areas and propagate across areas of low shear-strength gradient. Heterogeneous shear strength throughout the depth range of the northern Hikurangi margin may govern the nature of plate deformation, including the localization of both slow slip and hazardous earthquakes

ISSN exercise & sport nutrition review: research & recommendations

Sports nutrition is a constantly evolving field with hundreds of research papers published annually. For this reason, keeping up to date with the literature is often difficult. This paper is a five year update of the sports nutrition review article published as the lead paper to launch the JISSN in 2004 and presents a well-referenced overview of the current state of the science related to how to optimize training and athletic performance through nutrition. More specifically, this paper provides an overview of: 1.) The definitional category of ergogenic aids and dietary supplements; 2.) How dietary supplements are legally regulated; 3.) How to evaluate the scientific merit of nutritional supplements; 4.) General nutritional strategies to optimize performance and enhance recovery; and, 5.) An overview of our current understanding of the ergogenic value of nutrition and dietary supplementation in regards to weight gain, weight loss, and performance enhancement. Our hope is that ISSN members and individuals interested in sports nutrition find this review useful in their daily practice and consultation with their clients

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives