Landscape-scale analysis of ecosystem risk and returns: A new tool for ICZM

Management of the coastal zone often focuses on “islands” of high value ecosystems, in terms of economic value or conservation. However, integrated management requires landscape-level analysis of all ecosystem values. The biodiversity portfolio analysis (BPA) method is derived from the logic used in share (equity) portfolio management in terms of balancing within a portfolio the returns with the risks. Optimising the returns from a share portfolio, or a suite of ecosystems in a landscape, is dependent on the relationship between the units in terms of risk and return. Three case studies are then presented to test the applicability of the BPA method at the international (North West Europe), regional (Durham Heritage Coast, UK) and local (part of South Uist, Outer Hebrides, UK) spatial scale. The Biodiversity Portfolio Analysis for NW Europe showed that risk and return were highly correlated in the studied Member States. The ranking of risk and return, with the highest first, was Ireland > UK > France=Netherlands > Belgium. For these Member States the risks to ecosystem service provision were positively correlated with GNI (r=0.97, P<0.01); suggesting that the higher the economic importance of coastal and marine resources in a Member State the more at risk the resources are. The regional and local case studies were more focussed on providing information on which to base Integrated Coastal Zone Management (ICZM) decision making; both case studies used stakeholder participation to determine risks and returns. The conclusions from these two case studies show how the BPA method can be useful in terms of setting ICZM priorities and in addressing local coastal issues. The BPA involves making a number of assumptions, however, it does provide coastal managers with a potential tool to strategically plan due to increased awareness of the interaction between the ecosystems in the portfolio.There is a need for such techniques, which involve stakeholder participation and which create objective outcomes, to support the implementation of ICZM.     

Velocity potential formulations of highly accurate Boussinesq-type models

The highly accurate Boussinesq-type equations of Madsen et al. (Madsen, P.A., Bingham, H.B., Schäffer, H.A., 2003. Boussinesq-type formulations for fully nonlinear and extremely dispersive water waves: Derivation and analysis. Proc. R. Soc. Lond. A 459, 1075–1104; Madsen, P.A., Fuhrman, D.R., Wang, B., 2006. A Boussinesq-type method for fully nonlinear waves interacting with a rapidly varying bathymetry. Coast. Eng. 53, 487–504); Jamois et al. (Jamois, E., Fuhrman, D.R., Bingham, H.B., Molin, B., 2006. Wave-structure interactions and nonlinear wave processes on the weather side of reflective structures. Coast. Eng. 53, 929–945) are re-derived in a more general framework which establishes the correct relationship between the model in a velocity formulation and a velocity potential formulation. Although most work with this model has used the velocity formulation, the potential formulation is of interest because it reduces the computational effort by approximately a factor of two and facilitates a coupling to other potential flow solvers. A new shoaling enhancement operator is introduced to derive new models (in both formulations) with a velocity profile which is always consistent with the kinematic bottom boundary condition. The true behaviour of the velocity potential formulation with respect to linear shoaling is given for the first time, correcting errors made by Jamois et al. (Jamois, E., Fuhrman, D.R., Bingham, H.B., Molin, B., 2006. Wave-structure interactions and nonlinear wave processes on the weather side of reflective structures. Coast. Eng. 53, 929–945). An exact infinite series solution for the potential is obtained via a Taylor expansion about an arbitrary vertical position z = zˆ. For practical implementation however, the solution is expanded based on a slow variation of zˆ and terms are retained to first-order. With shoaling enhancement, the new models obtain a comparable accuracy in linear shoaling to the original velocity formulation. General consistency relations are also derived which are convenient for verifying that the differential operators satisfy a potential flow and/or conserve mass up to the order of truncation of the model. The performance of the new formulation is validated using computations of linear and nonlinear shoaling problems. The behaviour on a rapidly varying bathymetry is also checked using linear wave reflection from a shelf and Bragg scattering from an undulating bottom. Although the new models perform equally well for Bragg scattering they fail earlier than the existing model for reflection/transmission problems in very deep water.     

Quantifying the storm erosion hazard for coastal planning

The quantity of coastline retreat resulting from storm erosion is one of the most important phenomena that needs to be accurately quantified to facilitate effective coastal management strategies. Historically, the volume of storm erosion (and coastline retreat) accommodated for coastal planning decisions has been directly linked to the storm (usually defined by considering wave height and duration only) with a certain pre-defined return period, known as a Synthetic Design Storm (SDS) (e.g. 1 in 100 year storm). The SDS method of estimating storm erosion volumes for coastal planning thus assumes that, for example, the 1 in 100 year storm event also results in a 1 in 100 year erosion event. This communication discusses the physical reality of this assumption and demonstrates the improved performance of a new method, based on Joint Probability Distributions (JPD) for estimating storm erosion volumes proposed by Callaghan et al. [Callaghan, D.P., Nielsen, P., Short, A.D. and Ranasinghe, R., 2008. Statistical simulation of wave climate and extreme beach erosion. Coastal Engineering, 55(5): 375–390] using one of the world's longest beach profile surveys from Sydney, Australia.     

Tsunami generation,propagation, and run-up with a high-order Boussinesq model

In this work we extend a high-order Boussinesq-type (finite difference) model, capable of simulating waves out to wavenumber times depth kh < 25, to include a moving sea-bed, for the simulation of earthquake- and landslide-induced tsunamis. The extension is straight forward, requiring only an additional term within the kinematic bottom condition. As first test cases we simulate linear and nonlinear surface waves generated from both positive and negative impulsive bottom movements. The computed results compare well against earlier theoretical, numerical, and experimental values. Additionally, we show that the long-time (fully nonlinear) evolution of waves resulting from an upthrusted bottom can eventually result in true solitary waves, consistent with theoretical predictions. It is stressed, however, that the nonlinearity used far exceeds that typical of geophysical tsunamis in the open ocean. The Boussinesq-type model is then used to simulate numerous tsunami-type events generated from submerged landslides, in both one and two horizontal dimensions. The results again compare well against previous experiments and/or numerical simulations. The new extension compliments recently developed run-up capabilities within this approach, and as demonstrated, the model can therefore treat tsunami events from their initial generation, through their later propagation, and final run-up phases. The developed model is shown to maintain reasonable computational efficiency, and is therefore attractive for the simulation of such events, especially in cases where dispersion is important.     

The mid-depth circulation of the northwestern tropical Atlantic observed by floats

A comprehensive analysis of velocity data from subsurface floats in the northwestern tropical Atlantic at two depth layers is presented: one representing the Antarctic Intermediate Water (AAIW, pressure range 600–1050 dbar), the other the upper North Atlantic Deep Water (uNADW, pressure range 1200–2050 dbar). New data from three independent research programs are combined with previously available data to achieve blanket coverage in space for the AAIW layer, while coverage in the uNADW remains more intermittent. Results from the AAIW mainly confirm previous studies on the mean flow, namely the equatorial zonal and the boundary currents, but clarify details on pathways, mostly by virtue of the spatial data coverage that sets float observations apart from e.g. shipborne or mooring observations. Mean transports in each of five zonal equatorial current bands is found to be between 2.7 and 4.5 Sv. Pathways carrying AAIW northward beyond the North Brazil Undercurrent are clearly visible in the mean velocity field, in particular a northward transport of 3.7 Sv across 16°N between the Antilles islands and the Mid-Atlantic Ridge. New maps of Lagrangian eddy kinetic energy and integral time scales are presented to quantify mesoscale activity. For the uNADW, mean flow and mesoscale properties are discussed as data availability allows. Trajectories in the uNADW east of the Lesser Antilles reveal interactions between the Deep Western Boundary Current (DWBC) and the basin interior, which can explain recent hydrographic observations of changes in composition of DWBC water along its southward flow.     

Investigating the effect of ballasting by CaCO3 in Emiliania huxleyi, II: Decomposition of particulate organic matter

The quantitative relationship between organic carbon and mineral contents of particles sinking below 1800 m in the ocean indicates that organisms with mineral shells such as coccolithophores are of special importance for transporting carbon into the deep sea. Several hypotheses about the mechanism behind this relationship between minerals and organic matter have been raised, such as mineral protection of organic matter or enhanced sinking rates through ballast addition. We examined organic matter decomposition of calcifying and non-calcifying Emiliania huxleyi cultures in an experiment that allowed aggregation and settling in rotating tanks. Biogenic components such as particulate carbon, particulate nitrogen, particulate volume, pigments, transparent exopolymer particles (TEP), and particulate amino acids in suspended particles and aggregates were followed over a period of 30 d. The overall pattern of decrease in organic matter, the amount of recalcitrant organic matter left after 30 d, and the compositional changes within particulate organic matter indicated that cells without a shell are more subject to loss than calcified cells. It is suggested that biogenic calcite helps in the preservation of particulate organic matter (POM) by offering structural support for organic molecules. Over the course of the experiment, half the particulate organic carbon in both calcifying and non-calcifying cultures was partitioned into aggregates and remained so until the end of the experiment. The partial protection of particulate organic matter from solubilization by biominerals and by aggregation that was observed in our experiment may help explain the robustness of the relationship between organic and mineral matter fluxes in the deep ocean.     

Comparing spatially varying coefficient models: a case study examining violent crime rates and their relationships to alcohol outlets and illegal drug arrests

In this paper, we compare and contrast a Bayesian spatially varying coefficient process (SVCP) model with a geographically weighted regression (GWR) model for the estimation of the potentially spatially varying regression effects of alcohol outlets and illegal drug activity on violent crime in Houston, Texas. In addition, we focus on the inherent coefficient shrinkage properties of the Bayesian SVCP model as a way to address increased coefficient variance that follows from collinearity in GWR models. We outline the advantages of the Bayesian model in terms of reducing inflated coefficient variance, enhanced model flexibility, and more formal measuring of model uncertainty for prediction. We find spatially varying effects for alcohol outlets and drug violations, but the amount of variation depends on the type of model used. For the Bayesian model, this variation is controllable through the amount of prior influence placed on the variance of the coefficients. For example, the spatial pattern of coefficients is similar for the GWR and Bayesian models when a relatively large prior variance is used in the Bayesian model.