Results of wave modelling for Moreton Bay, Southeast Queensland, and a reef lagoon off Lizard Island, Great Barrier Reef, Australia

The distribution, abundance, behaviour, and morphology of marine species is affected by spatial variability in the wave environment. Maps of wave metrics (e.g. significant wave height Hs, peak energy wave period Tp, and benthic wave orbital velocity URMS) are therefore useful for predictive ecological models of marine species and ecosystems. A number of techniques are available to generate maps of wave metrics, with varying levels of complexity in terms of input data requirements, operator knowledge, and computation time. Relatively simple "fetch-based" models are generated using geographic information system (GIS) layers of bathymetry and dominant wind speed and direction. More complex, but computationally expensive, "process-based" models are generated using numerical models such as the Simulating Waves Nearshore (SWAN) model. We generated maps of wave metrics based on both fetch-based and process-based models and asked whether predictive performance in models of benthic marine habitats differed. Predictive models of seagrass distribution for Moreton Bay, Southeast Queensland, and Lizard Island, Great Barrier Reef, Australia, were generated using maps based on each type of wave model. For Lizard Island, performance of the process-based wave maps was significantly better for describing the presence of seagrass, based on Hs, Tp, and URMS. Conversely, for the predictive model of seagrass in Moreton Bay, based on benthic light availability and Hs, there was no difference in performance using the maps of the different wave metrics. For predictive models where wave metrics are the dominant factor determining ecological processes it is recommended that process-based models be used. Our results suggest that for models where wave metrics provide secondarily useful information, either fetch- or process-based models may be equally useful.

(Table 3) Interannual variability of total mass flux at the deep sediment trap site CBmeso between 1988 and 2006

This article will review major features of the 'giant' Cape Blanc filament off Mauritania with regard to the transport of chlorophyll and organic carbon from the shelf to the open ocean. Within the filament, chlorophyll is transported about 400 km offshore. Modelled particle distributions along a zonal transect at 21°N showed that particles with a sinking velocity of 5 m d**-1 are advected offshore by up to 600 km in subsurface particle clouds generally located between 400 m and 800 m water depth, forming an Intermediate Nepheloid Layer (INL). It corresponds to the depth of the oxygen minimum zone. Heavier particles with a sinking velocity of 30 m d**-1 are transported from the shelf within the Bottom Layer (BL) of more than 1000 m thickness, largely following the topography of the bottom slope. The particles advected within the BL contribute to the enhanced winter-spring mass fluxes collected at the open-ocean mesotrophic sediment trap site CB-13 (200 nm offshore), due to a long distance advection in deeper waters. The lateral contribution to the deep sediment trap in winter-spring is estimated to be 63% and 72% for organic carbon and total mass, respectively, whereas the lateral input for both components on an annual basis is estimated to be in the order of 15%. Biogenic opal increases almost fivefold from the upper to the lower mesotrophic CB-13 trap, also pointing to an additional source for biogenic silica from eutrophic coastal waters. Blooms obviously sink in smaller, probably mesoscale-sized patches with variable settling rates, depending on the type of aggregated particles and their ballast content. Generally, particle sinking rates are exceptionally high off NW Africa. Very high chlorophyll values and a large size of the Cape Blanc filament in 1998-1999 are also documented in enhanced total mass and organic carbon fluxes. An increasing trend in satellite chlorophyll concentrations and the size of the Cape Blanc filament between 1997 and 2008 as observed for other coastal upwelling areas is not documented.

Transferability of Regional Permafrost Disturbance Susceptibility Modelling Using Generalized Linear and Generalized Additive Models

To effectively assess and mitigate risk of permafrost disturbance, disturbance-p rone areas can be predicted through the application of susceptibility models. In this study we developed regional susceptibility models for permafrost disturbances using a field disturbance inventory to test the transferability of the model to a broader region in the Canadian High Arctic. Resulting maps of susceptibility were then used to explore the effect of terrain variables on the occurrence of disturbances within this region. To account for a large range of landscape charac- teristics, the model was calibrated using two locations: Sabine Peninsula, Melville Island, NU, and Fosheim Pen- insula, Ellesmere Island, NU. Spatial patterns of disturbance were predicted with a generalized linear model (GLM) and generalized additive model (GAM), each calibrated using disturbed and randomized undisturbed lo- cations from both locations and GIS-derived terrain predictor variables including slope, potential incoming solar radiation, wetness index, topographic position index, elevation, and distance to water. Each model was validated for the Sabine and Fosheim Peninsulas using independent data sets while the transferability of the model to an independent site was assessed at Cape Bounty, Melville Island, NU. The regional GLM and GAM validated well for both calibration sites (Sabine and Fosheim) with the area under the receiver operating curves (AUROC) N 0.79. Both models were applied directly to Cape Bounty without calibration and validated equally with AUROC's of 0.76; however, each model predicted disturbed and undisturbed samples differently. Addition- ally, the sensitivity of the transferred model was assessed using data sets with different sample sizes. Results in- dicated that models based on larger sample sizes transferred more consistently and captured the variability within the terrain attributes in the respective study areas. Terrain attributes associated with the initiation of dis- turbances were similar regardless of the location. Disturbances commonly occurred on slopes between 4 and 15°, below Holocene marine limit, and in areas with low potential incoming solar radiation

Competition for Cooperation: variability, benefits and heritability of relational wealth in hunter-gatherers

Many defining human characteristics including theory of mind, culture and language relate to our sociality, and facilitate the formation and maintenance of cooperative relationships. Therefore, deciphering the context in which our sociality evolved is invaluable in understanding what makes us unique as a species. Much work has emphasised group-level competition, such as warfare, in moulding human cooperation and sociality. However, competition and cooperation also occur within groups; and inter-individual differences in sociality have reported fitness implications in numerous non-human taxa. Here we investigate whether differential access to cooperation (relational wealth) is likely to lead to variation in fitness at the individual level among BaYaka hunter-gatherers. Using economic gift games we find that relational wealth: a) displays individual-level variation; b) provides advantages in buffering food risk, and is positively associated with body mass index (BMI) and female fertility; c) is partially heritable. These results highlight that individual-level processes may have been fundamental in the extension of human cooperation beyond small units of related individuals, and in shaping our sociality. Additionally, the findings offer insight in to trends related to human sociality found from research in other fields such as psychology and epidemiology.

Spatio-temporal characteristics of Agulhas leakage: a model inter-comparison study

Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

Spatio-temporal characteristics of Agulhas leakage: a model inter-comparison study

Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

Linking environmental variables with regional- scale variability in ecological structure and standing stock of carbon within UK kelp forests

Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.

Linking environmental variables with regional- scale variability in ecological structure and standing stock of carbon within UK kelp forests

Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.

Exploring the joint compositional variability of major components and trace elements in the Tellus soil geochemistry survey (Northern Ireland)

The complexity of modern geochemical data sets is increasing in several aspects (number of available samples, number of elements measured, number of matrices analysed, geological-environmental variability covered, etc), hence it is becoming increasingly necessary to apply statistical methods to elucidate their structure. This paper presents an exploratory analysis of one such complex data set, the Tellus geochemical soil survey of Northern Ireland (NI). This exploratory analysis is based on one of the most fundamental exploratory tools, principal component analysis (PCA) and its graphical representation as a biplot, albeit in several variations: the set of elements included (only major oxides vs. all observed elements), the prior transformation applied to the data (none, a standardization or a logratio transformation) and the way the covariance matrix between components is estimated (classical estimation vs. robust estimation). Results show that a log-ratio PCA (robust or classical) of all available elements is the most powerful exploratory setting, providing the following insights: the first two processes controlling the whole geochemical variation in NI soils are peat coverage and a contrast between “mafic” and “felsic” background lithologies; peat covered areas are detected as outliers by a robust analysis, and can be then filtered out if required for further modelling; and peat coverage intensity can be quantified with the %Br in the subcomposition (Br, Rb, Ni).

Compositional data analysis of Holocene sediments from the West Bengal Sundarbans, India: Geochemical proxies for grain-size variability in a delta environment

This paper is part of a special issue of Applied Geochemistry focusing on reliable applications of compositional multivariate statistical methods. This study outlines the application of compositional data analysis (CoDa) to calibration of geochemical data and multivariate statistical modelling of geochemistry and grain-size data from a set of Holocene sedimentary cores from the Ganges-Brahmaputra (G-B) delta. Over the last two decades, understanding near-continuous records of sedimentary sequences has required the use of core-scanning X-ray fluorescence (XRF) spectrometry, for both terrestrial and marine sedimentary sequences. Initial XRF data are generally unusable in ‘raw-format’, requiring data processing in order to remove instrument bias, as well as informed sequence interpretation. The applicability of these conventional calibration equations to core-scanning XRF data are further limited by the constraints posed by unknown measurement geometry and specimen homogeneity, as well as matrix effects. Log-ratio based calibration schemes have been developed and applied to clastic sedimentary sequences focusing mainly on energy dispersive-XRF (ED-XRF) core-scanning. This study has applied high resolution core-scanning XRF to Holocene sedimentary sequences from the tidal-dominated Indian Sundarbans, (Ganges-Brahmaputra delta plain). The Log-Ratio Calibration Equation (LRCE) was applied to a sub-set of core-scan and conventional ED-XRF data to quantify elemental composition. This provides a robust calibration scheme using reduced major axis regression of log-ratio transformed geochemical data. Through partial least squares (PLS) modelling of geochemical and grain-size data, it is possible to derive robust proxy information for the Sundarbans depositional environment. The application of these techniques to Holocene sedimentary data offers an improved methodological framework for unravelling Holocene sedimentation patterns.

Inter-Laboratory Evaluation of a Next-Generation Sequencing Panel for Acute Myeloid Leukemia

INTRODUCTION: Acute myeloid leukemia (AML) is a heterogeneous clonal disorder often associated with dismal overall survival. The clinical diversity of AML is reflected in the range of recurrent somatic mutations in several genes, many of which have a prognostic and therapeutic value. Targeted next-generation sequencing (NGS) of these genes has the potential for translation into clinical practice. In order to assess this potential, an inter-laboratory evaluation of a commercially available AML gene panel across three diagnostic centres in the UK and Ireland was performed.

METHODS: DNA from six AML patient samples was distributed to each centre and processed using a standardised workflow, including a common sequencing platform, sequencing chips and bioinformatics pipeline. A duplicate sample in each centre was run to assess inter- and intra-laboratory performance.

RESULTS: An average sample read depth of 2725X (range 629-5600) was achieved using six samples per chip, with some variability observed in the depth of coverage generated for individual samples and between centres. A total of 16 somatic mutations were detected in the six AML samples, with a mean of 2.7 mutations per sample (range 1-4) representing nine genes on the panel. 15/16 mutations were identified by all three centres. Allelic frequencies of the mutations ranged from 5.6 to 53.3 % (median 44.4 %), with a high level of concordance of these frequencies between centres, for mutations detected.

CONCLUSION: In this inter-laboratory comparison, a high concordance, reproducibility and robustness was demonstrated using a commercially available NGS AML gene panel and platform.

End-to-end modelling for an ecosystem approach to fisheries in the Northern Humboldt Current Ecosystem

This work represents an original contribution to the methodology for ecosystem models' development as well as the rst attempt of an end-to-end (E2E) model of the Northern Humboldt Current Ecosystem (NHCE). The main purpose of the developed model is to build a tool for ecosystem-based management and decision making, reason why the credibility of the model is essential, and this can be assessed through confrontation to data. Additionally, the NHCE exhibits a high climatic and oceanographic variability at several scales, the major source of interannual variability being the interruption of the upwelling seasonality by the El Niño Southern Oscillation, which has direct e ects on larval survival and sh recruitment success. Fishing activity can also be highly variable, depending on the abundance and accessibility of the main shery resources. This context brings the two main methodological questions addressed in this thesis, through the development of an end-to-end model coupling the high trophic level model OSMOSE to the hydrodynamics and biogeochemical model ROMS-PISCES: i) how to calibrate ecosystem models using time series data and ii) how to incorporate the impact of the interannual variability of the environment and shing. First, this thesis highlights some issues related to the confrontation of complex ecosystem models to data and proposes a methodology for a sequential multi-phases calibration of ecosystem models. We propose two criteria to classify the parameters of a model: the model dependency and the time variability of the parameters. Then, these criteria along with the availability of approximate initial estimates are used as decision rules to determine which parameters need to be estimated, and their precedence order in the sequential calibration process. Additionally, a new Evolutionary Algorithm designed for the calibration of stochastic models (e.g Individual Based Model) and optimized for maximum likelihood estimation has been developed and applied to the calibration of the OSMOSE model to time series data. The environmental variability is explicit in the model: the ROMS-PISCES model forces the OSMOSE model and drives potential bottom-up e ects up the foodweb through plankton and sh trophic interactions, as well as through changes in the spatial distribution of sh. The latter e ect was taken into account using presence/ absence species distribution models which are traditionally assessed through a confusion matrix and the statistical metrics associated to it. However, when considering the prediction of the habitat against time, the variability in the spatial distribution of the habitat can be summarized and validated using the emerging patterns from the shape of the spatial distributions. We modeled the potential habitat of the main species of the Humboldt Current Ecosystem using several sources of information ( sheries, scienti c surveys and satellite monitoring of vessels) jointly with environmental data from remote sensing and in situ observations, from 1992 to 2008. The potential habitat was predicted over the study period with monthly resolution, and the model was validated using quantitative and qualitative information of the system using a pattern oriented approach. The nal ROMS-PISCES-OSMOSE E2E ecosystem model for the NHCE was calibrated using our evolutionary algorithm and a likelihood approach to t monthly time series data of landings, abundance indices and catch at length distributions from 1992 to 2008. To conclude, some potential applications of the model for shery management are presented and their limitations and perspectives discussed.

Air Temperature Distribution and Energy-balance Modelling of a Debris-covered Glacier

Near-surface air temperature is an important determinant of the surface energy balance of glaciers and is often represented by a constant linear temperature gradients (TGs) in models. Spatiotemporal variability in 2 m air temperature was measured across the debris-covered Miage Glacier, Italy, over an 89 d period during the 2014 ablation season using a network of 19 stations. Air temperature was found to be strongly dependent upon elevation for most stations, even under varying meteorological conditions and at different times of day, and its spatial variability was well explained by a locally derived mean linear TG (MG–TG) of −0.0088°C m−1. However, local temperature depressions occurred over areas of very thin or patchy debris cover. The MG–TG, together with other air TGs, extrapolated from both on- and off-glacier sites, were applied in a distributed energy-balance model. Compared with piecewise air temperature extrapolation from all on-glacier stations, modelled ablation, using the MG–TG, increased by <1%, increasing to >4% using the environmental ‘lapse rate’. Ice melt under thick debris was relatively insensitive to air temperature, while the effects of different temperature extrapolation methods were strongest at high elevation sites of thin and patchy debris cover.

Partition alignment in three dimensional unstructured mesh multi-physics modelling

Unstructured mesh codes for modelling continuum physics phenomena have evolved to provide the facility to model complex interacting systems. Parallelisation of such codes using single Program Multi Data (SPMD) domain decomposition techniques implemented with message passing has been demonstrated to provide high parallel efficiency, scalability to large numbers of processors P and portability across a wide range of parallel platforms. High efficiency, especially for large P requires that load balance is achieved in each parallel loop. For a code in which loops span a variety of mesh entity types, for example, elements, faces and vertices, some compromise is required between load balance for each entity type and the quantity of inter-processor communication required to satisfy data dependence between processors.