An individual based model spatial distribution, production and biomass for Calanus finmarchicus in the Norwegian Sea

The copepod Calanus finmarchicus is the dominant species of the meso-zooplankton in the Norwegian Sea, and constitutes an important link between the phytoplankton and the higher trophic levels in the Norwegian Sea food chain. An individualbased model for C. finmarchicus, based on super-individuals and evolving traits for behaviour, stages, etc., is two-way coupled to the NORWegian ECOlogical Model system (NORWECOM). One year of modelled C. finmarchicus spatial distribution, production and biomass are found to represent observations reasonably well. High C. finmarchicus abundance is found along the Norwegian shelf-break in the early summer, while the overwintering population is found along the slope and in the deeper Norwegian Sea basins. The timing of the spring bloom is generally later than in the observations. Annual Norwegian Sea production is found to be 29 million tonnes of carbon and a production to biomass (P/B) ratio of 4.3 emerges. Sensitivity tests show that the modelling system is robust to initial values of behavioural traits and with regards to the number of super-individuals simulated given that this is above about 50,000 individuals. Experiments with the model system indicate that it provides a valuable tool for studies of ecosystem responses to causative forces such as prey density or overwintering population size. For example, introducing C. finmarchicus food limitations reduces the stock dramatically, but on the other hand, a reduced stock may rebuild in one year under normal conditions. The NetCDF file contains model grid coordinates and bottom topography.

Treeline dynamics in Siberia under changing climates as inferred from an individual-based model for Larix, supplementary material

Siberian boreal forests are expected to expand northwards in the course of global warming. However, processes of the treeline ecotone transition, as well astiming and related climate feedbacks are still not understood. Here, we present 'Larix Vegetation Simulator' LAVESI, an individual-based spatially-explicit model that can simulate Larix gmelinii (RUPR.) RUPR. stand dynamics in an attempt to improve our understanding about past and future treeline movements under changing climates. The relevant processes (growth, seed production and dispersal, establishment and mortality) are incorporated and adjusted to observation data mainly gained from the literature. Results of a local sensitivity analysis support the robustness of the model's parameterization by giving relatively small sensitivity values. We tested the model by simulating tree stands under modern climate across the whole Taymyr Peninsula, north-central Siberia (c. 64-80° N; 92-119° E). We find tree densities similar to observed forests in the northern to mid-treeline areas, but densities are overestimated in the southern parts of the simulated region. Finally, from a temperature-forcing experiment, we detect that the responses of tree stands lag the hypothetical warming by several decades, until the end of 21st century. With our simulation experiments we demonstrate that the newly-developed model captures the dynamics of the Siberian latitudinal treeline.

Medem Channel profiles based on stand-alone model simulation and corrections with nudging

State-of-the-art process-based models have shown to be applicable to the simulation and prediction of coastal morphodynamics. On annual to decadal temporal scales, these models may show limitations in reproducing complex natural morphological evolution patterns, such as the movement of bars and tidal channels, e.g. the observed decadal migration of the Medem Channel in the Elbe Estuary, German Bight. Here a morphodynamic model is shown to simulate the hydrodynamics and sediment budgets of the domain to some extent, but fails to adequately reproduce the pronounced channel migration, due to the insufficient implementation of bank erosion processes. In order to allow for long-term simulations of the domain, a nudging method has been introduced to update the model-predicted bathymetries with observations. The model-predicted bathymetry is nudged towards true states in annual time steps. Sensitivity analysis of a user-defined correlation length scale, for the definition of the background error covariance matrix during the nudging procedure, suggests that the optimal error correlation length is similar to the grid cell size, here 80-90 m. Additionally, spatially heterogeneous correlation lengths produce more realistic channel depths than do spatially homogeneous correlation lengths. Consecutive application of the nudging method compensates for the (stand-alone) model prediction errors and corrects the channel migration pattern, with a Brier skill score of 0.78. The proposed nudging method in this study serves as an analytical approach to update model predictions towards a predefined 'true' state for the spatiotemporal interpolation of incomplete morphological data in long-term simulations.

Water level time series and sediment grain size model

The environment of ebb-tidal deltas between barrier island systems is characterized by a complex morphology with ebb- and flood-dominated channels, shoals and swash bars connecting the ebb-tidal delta platform to the adjacent island. These morphological features reveal characteristic surface sediment grain-size distributions and are subject to a continuous adaptation to the prevailing hydrodynamic forces. The mixed-energy tidal inlet Otzumer Balje between the East Frisian barrier islands of Langeoog and Spiekeroog in the southern North Sea has been chosen here as a model study area for the identification of relevant hydrodynamic drivers of morphology and sedimentology. We compare the effect of high-energy, wave-dominated storm conditions to mid-term, tide-dominated fair-weather conditions on tidal inlet morphology and sedimentology with a process-based numerical model. A multi-fractional approach with five grain-size fractions between 150 and 450 µm allows for the simulation of corresponding surface sediment grain-size distributions. Net sediment fluxes for distinct conditions are identified: during storm conditions, bed load sediment transport is generally onshore directed on the shallower ebb-tidal delta shoals, whereas fine-grained suspended sediment bypasses the tidal inlet by wave-driven currents. During fair weather the sediment transport mainly focuses on the inlet throat and the marginal flood channels. We show how the observed sediment grain-size distribution and the morphological response at mixed-energy tidal inlets are the result of both wave-dominated less frequent storm conditions and mid-term, tide-dominant fair-weather conditions.

Chemical and mineral compositions of basalts and volcanic glasses from DSDP Sites 65-483 and 65-485

Major and rare earth element (REE) data for basalts from Holes 483, 483B, and 485A of DSDP Leg 65, East Pacific Rise, mouth of the Gulf of California, support a simple fractional crystallization model for the genesis of rocks from this suite. The petrography and mineral chemistry (presented in detail elsewhere) provide no evidence for magma mixing, but rather a simple multistage cooling process. Based on its lowest TiO2 content (0.88%), FeO*/MgO ratio (0.95 with total Fe as FeO), and Mg# (100 Mg/Mg + Fe" = 70), sample 483-17-2-(78-83) has been selected as the most primitive primary magma of the samples analyzed. This is supported by the REE data which show this sample has the lowest total REE content, a La/Sm_cn (chondrite-normalized) = 0.36, and Eu/Sm_cn = 1.05. Because other samples analyzed have higher SiO2, lower Mg#, and a negative Eu anomaly (Eu/Sm_cn as low as 0.89), they are most likely derivative magmas. Wright-Doherty and trace element modelling support fractional crystallization of 14.1% plagioclase (An88), 6.7% olivine (Fo86), and 4.7% clinopyroxene (Wo41En49Fs10) from 483-17-2-(78-83) to form the least differentiated sample with Mg# = 63. The La/Sm_cn of this derivative magma is almost identical to the parent magma (0.35 to 0.36), but the other samples have higher La/Sm_cn (0.45 to 0.51), more total REE, and lower Mg# (60 to 56). Both Wright-Doherty and trace element modelling indicate that the primary magma chosen cannot produce these more evolved samples. For the major elements, the TiO2 and P2O5 are too low in the calculated versus the observed (1.38 to 1.90; 0.11 to 0.17, respectively, for example). Rayleigh fractionation calculates a lower La/Sm_cn and requires about 60% crystal removal versus 40% for the Wright-Doherty. These more evolved samples must be derived from a parent magma different from the one selected here and, unfortunately, not sampled in this study. A magma formed by a smaller degree of partial melting with slightly more residual clinopyroxene left in the mantle than for sample 483-17-2-(78-83) is required.

Projecting the fate of fish populations using ecological-economic modeling

Four marine fish species are among the most important on the world market: cod, salmon, tuna, and sea bass. While the supply of North American and European markets for two of these species - Atlantic salmon and European sea bass - mainly comes from fish farming, Atlantic cod and tunas are mainly caught from wild stocks. We address the question what will be the status of these wild stocks in the midterm future, in the year 2048, to be specific. Whereas the effects of climate change and ecological driving forces on fish stocks have already gained much attention, our prime interest is in studying the effects of changing economic drivers, as well as the impact of variable management effectiveness. Using a process-based ecological-economic multispecies optimization model, we assess the future stock status under different scenarios of change. We simulate (i) technological progress in fishing, (ii) increasing demand for fish, and (iii) increasing supply of farmed fish, as well as the interplay of these driving forces under different sce- narios of (limited) fishery management effectiveness. We find that economic change has a substantial effect on fish populations. Increasing aquaculture production can dampen the fishing pressure on wild stocks, but this effect is likely to be overwhelmed by increasing demand and technological progress, both increasing fishing pressure. The only solution to avoid collapse of the majority of stocks is institutional change to improve management effectiveness significantly above the current state. We conclude that full recognition of economic drivers of change will be needed to successfully develop an integrated ecosystem management and to sustain the wild fish stocks until 2048 and beyond.

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.