Parameter optimization and analysis of ecosystem models using simulated annealing: A case study at Station P

A simulated annealing optimization algorithm is formulated to optimize parameters of ecosystem models. The optimization is used to directly determine the model parameters required to reproduce the observed data. The optimization routine is formulated in a general manner and is easily modified to include additional information on both the desired model output and the model parameters. From the optimization routine, error analysis of the optimal parameters is provided by the error-covariance matrix which gives both the sensitivity of the model to each model parameter and the correlation coefficients between all pairs of model parameters. In addition, the optimization analysis provides a means of assessing the necessary model complexity required to model the available data. To demonstrate the technique, optimal parameters of three different ecosystem model configurations are determined from nitrate, phytoplankton, mesozooplankton and net phytoplankton productivity measurements at Station P. At Station P, error analysis of the optimal parameters indicates that the data are able to resolve up to 10 independent model parameters. This is always less than the number of unknown model parameters indicating that the optimal solutions are not unique. A simple nitrate-phosphate-zooplankton ecosystem is successful at reproducing the observations. To justify the use of a more complicated model at Station P requires additional data to constrain the optimization routine. Although there is evidence supporting the importance of the microbial loop at Station P, without additional ammonium and bacteria measurements one cannot validate a more complicated model that includes these processes

Quantifying the influence of sub-mesoscale dynamics on the supply of iron to Southern Ocean phytoplankton blooms

Southern Ocean phytoplankton growth is limited by iron. Episodes of natural iron fertilisation are pivotalto triggering phytoplankton blooms in this region, the Kerguelen Plateau bloom being one prominentexample. Numerous physical mechanisms that may supply iron to the euphotic zone in the KerguelenPlateau region, and hence trigger a phytoplankton bloom, have been identified. However, the impact ofsub-mesoscaleflows in delivering iron has been omitted. With a scale of order 10 km, sub-mesoscalefilaments and fronts can dramatically increase vertical velocities and iron transport.An innovative technique is developed to investigate the role of vertical advection associated with sub-mesoscale features on the supply of iron to the photic zone. First, Lagrangian trajectories are calculatedusing three dimensional velocityfields from high resolution numerical simulations; iron concentration isthen computed along these Lagrangian trajectories. The contribution of mesoscale- (1/20°resolution)and sub-mesoscale-resolving models (1/80°resolution) is compared, thereby revealing the sensitivity ofiron supply to horizontal resolution. Ironfluxes are clearly enhanced by a factor of 2 with the resolution,thus showing that the vertical motion induced by the sub-mesoscales represents a previously neglectedprocess to drive iron into the photic waters of the Kerguelen Plateau.A. Hogg was supported by Australian Research Council Future Fellowship FT120100842. We want to express our thanks to A. Bowie for constructive discussions

Implications of climate change for Australian fisheries and aquaculture: a preliminary assessment

This review finds that there are likely to be significant climate change impacts on the biological, economic, and social aspects of Australian fisheries and that there is little consolidated knowledge of the potential impacts of climate change. Both positive and negative impacts are expected, and impacts will vary according to changes in the regional environment: south-east fisheries are most likely to be affected by changes in water temperature, northern fisheries by changes in precipitation, and western fisheries by changes in the Leeuwin Current. There may be new opportunities for some wild fisheries where tropical species shift southward. There will also be many challenges, such as that faced by the Tasmanian salmon aquaculture industry due to Atlantic salmon being cultivated close to their upper thermal limits of optimal growth. Nevertheless, the report also highlights that there is potential for adaptation measures to be employed by the industry. The report also notes the need for fisheries and aquaculture management policies to better integrate the effects of climate variability and climate change in establishing harvest levels and developing future strategies. This will enhance the resilience of marine biodiversity and the adaptive capacity of the fisheries and aquaculture industries

Key drivers of seasonal plankton dynamics in cyclonic and anticyclonic eddies off East Australia

© 2016 Laiolo, McInnes, Matear and Doblin. Mesoscale eddies in the south west Pacific region are prominent ocean features that represent distinctive environments for phytoplankton. Here, we examine the seasonal plankton dynamics associated with averaged cyclonic and anticyclonic eddies (CE and ACE, respectively) off eastern Australia. We do this through building seasonal climatologies of mixed layer depth (MLD) and surface chlorophyll-a for both CE and ACE by combining remotely sensed sea surface height (TOPEX/Poseidon, Envisat, Jason-1, and OSTM/Jason-2), remotely sensed ocean color (GlobColour) and in situ profiles of temperature, salinity and pressure from Argo floats. Using the CE and ACE seasonal climatologies, we assimilate the surface chlorophyll-a data into both a single (WOMBAT), and multi-phytoplankton class (EMS) biogeochemical model to investigate the level of complexity required to simulate the phytoplankton chlorophyll-a. For the two eddy types, the data assimilation showed both biogeochemical models only needed one set of parameters to represent phytoplankton but needed different parameters for zooplankton. To assess the simulated phytoplankton behavior we compared EMS model simulations with a ship-based experiment that involved incubating a winter phytoplankton community sampled from below the mixed layer under ambient and two higher light intensities with and without nutrient enrichment. By the end of the 5-day field experiment, large diatom abundance was four times greater in all treatments compared to the initial community, with a corresponding decline in pico-cyanobacteria. The experimental results were consistent with the simulated behavior in CE and ACE, where the seasonal deepening of the mixed layer during winter produced a rapid increase in large phytoplankton. Our model simulations suggest that CE off East Australia are not only characterized by a higher chlorophyll-a concentration compared to ACE, but also by a higher concentration of large phytoplankton (i.e., diatoms) due to the shallower CE mixed layer. The model simulations also suggest the zooplankton community is different in the two eddy types and this behavior needs further investigation

Optimal parameters for the ocean's nutrient, carbon, and oxygen cycles compensate for circulation biases but replumb the biological pump

Accurate predictive modelling of the ocean's global carbon and oxygen cycles is challenging because of uncertainties in both biogeochemistry and ocean circulation. Advances over the last decade have made parameter optimization feasible, allowing models to better match observed biogeochemical fields. However, does fitting a biogeochemical model to observed tracers using a circulation with known biases robustly capture the inner workings of the biological pump? Here we embed a mechanistic model of the ocean's coupled nutrient, carbon, and oxygen cycles into two circulations for the current climate. To assess the effects of biases, one circulation (ACCESS-M) is derived from a climate model and the other from data assimilation of observations (OCIM2). We find that parameter optimization compensates for circulation biases at the expense of altering how the biological pump operates. Tracer observations constrain pump strength and regenerated inventories for both circulations, but ACCESS-M export production optimizes to twice that of OCIM2 to compensate for ACCESS-M having lower sequestration efficiencies driven by less efficient particle transfer and shorter residence times. Idealized simulations forcing complete Southern Ocean nutrient utilization show that the response of the optimized system is sensitive to the embedding circulation. In ACCESS-M, Southern Ocean nutrient and DIC trapping is partially short-circuited by unrealistically deep mixed layers. For both circulations, intense Southern Ocean production deoxygenates Southern-Ocean-sourced deep waters, muting the imprint of circulation biases on oxygen. Our findings highlight that the biological pump's plumbing needs careful assessment to predict the biogeochemical response to environmental changes, even when optimally matching observations.</p

Nitrate Sources, Supply, and Phytoplankton Growth in the Great Australian Bight: An Eulerian-Lagrangian Modeling Approach

The Great Australian Bight (GAB), a coastal sea bordered by the Pacific, Southern, and Indian Oceans, sustains one of the largest fisheries in Australia but the geographical origin of nutrients that maintain its productivity is not fully known. We use 12 years of modeled data from a coupled hydrodynamic and biogeochemical model and an Eulerian-Lagrangian approach to quantify nitrate supply to the GAB and the region between the GAB and the Subantarctic Australian Front (GAB-SAFn), identify phytoplankton growth within the GAB, and ascertain the source of nitrate that fuels it. We find that nitrate concentrations have a decorrelation timescale of ∼60 days; since most of the water from surrounding oceans takes longer than 60 days to reach the GAB, 23% and 75% of nitrate used by phytoplankton to grow are sourced within the GAB and from the GAB-SAFn, respectively. Thus, most of the nitrate is recycled locally. Although nitrate concentrations and fluxes into the GAB are greater below 100 m than above, 79% of the nitrate fueling phytoplankton growth is sourced from above 100 m. Our findings suggest that topographical uplift and stratification erosion are key mechanisms delivering nutrients from below the nutricline into the euphotic zone and triggering large phytoplankton growth. We find annual and semiannual periodicities in phytoplankton growth, peaking in the austral spring and autumn when the mixed layer deepens leading to a subsurface maximum of phytoplankton growth. This study highlights the importance of examining phytoplankton growth at depth and the utility of Lagrangian approaches

Marine nitrogen fixers mediate a low latitude pathway for atmospheric CO2 drawdown

Roughly a third (~30 ppm) of the carbon dioxide (CO2) that entered the ocean during ice ages is attributed to biological mechanisms. A leading hypothesis for the biological drawdown of CO2 is iron (Fe) fertilisation of the high latitudes, but modelling efforts attribute at most 10 ppm to this mechanism, leaving ~20 ppm unexplained. We show that an Fe-induced stimulation of dinitrogen (N2) fixation can induce a low latitude drawdown of 7–16 ppm CO2. This mechanism involves a closer coupling between N2 fixers and denitrifiers that alleviates widespread nitrate limitation. Consequently, phosphate utilisation and carbon export increase near upwelling zones, causing deoxygenation and deeper carbon injection. Furthermore, this low latitude mechanism reproduces the regional patterns of organic δ15N deposited in glacial sediments. The positive response of marine N2 fixation to dusty ice age conditions, first proposed twenty years ago, therefore compliments high latitude changes to amplify CO2 drawdown

Integrating biogeochemistry and ecology into ocean data assimilation systems

Monitoring and predicting the biogeochemical state of the ocean and marine ecosystems is an important application of operational oceanography that needs to be expanded. The accurate depiction of the ocean's physical environment enabled by Global Ocean Data Assimilation Experiment (GODAE) systems, in both real-time and reanalysis modes, is already valuable for various for various applications, such as the fishing industry and fisheries management. However, most of these applications require accurate estimates of both physical and biogeochemical ocean conditions over a wide range of spatial and temporal scales. In this paper, we discuss recent developments that enable coupling new biogeochemical models and assimilation components with the existing GODAE systems, and we examine the potential of such systems in several areas of interest: phytoplankton biomass monitoring in the open ocean, ocean carbon cycle monitoring and assessment, marine ecosystem management at seasonal and longer time scales, and downscaling in coastal areas. A number of key requirements and research priorities are then identified for the future, GODAE systems will need to improve their representation of physical variables that are not yet considered essential, such as upper-ocean vertical fluxes that are critically important to biological activity. Further, the observing systems will need to be expanded in terms of in situ platforms (with intensified deployments of sensors for O-2 and chlorophyll, and inclusion of new sensors for nutrients, zooplankton, micronekton biomass, and others), satellite missions (e.g., hyperspectral instruments for ocean color, lidar systems for mixed-layer depths, and wide-swath altimeters for coastal sea level), and improved methods to assimilate these new measurements

Use of remote-sensing reflectance to constrain a data assimilating marine biogeochemical model of the Great Barrier Reef

Skillful marine biogeochemical (BGC) models are required to understand a range of coastal and global phenomena such as changes in nitrogen and carbon cycles. The refinement of BGC models through the assimilation of variables calculated from observed in-water inherent optical properties (IOPs), such as phytoplankton absorption, is problematic. Empirically derived relationships between IOPs and variables such as chlorophyll-a concentration (Chl a), total suspended solids (TSS) and coloured dissolved organic matter (CDOM) have been shown to have errors that can exceed 100% of the observed quantity. These errors are greatest in shallow coastal regions, such as the Great Barrier Reef (GBR), due to the additional signal from bottom reflectance. Rather than assimilate quantities calculated using IOP algorithms, this study demonstrates the advantages of assimilating quantities calculated directly from the less error-prone satellite remote-sensing reflectance (RSR). To assimilate the observed RSR, we use an in-water optical model to produce an equivalent simulated RSR and calculate the mismatch between the observed and simulated quantities to constrain the BGC model with a deterministic ensemble Kalman filter (DEnKF). The traditional assumption that simulated surface Chl a is equivalent to the remotely sensed OC3M estimate of Chl a resulted in a forecast error of approximately 75 %. We show this error can be halved by instead using simulated RSR to constrain the model via the assimilation system. When the analysis and forecast fields from the RSR-based assimilation system are compared with the non-assimilating model, a comparison against independent in situ observations of Chl a, TSS and dissolved inorganic nutrients (NO3, NH4 and DIP) showed that errors are reduced by up to 90 %. In all cases, the assimilation system improves the simulation compared to the non-assimilating model. Our approach allows for the incorporation of vast quantities of remote-sensing observations that have in the past been discarded due to shallow water and/or artefacts introduced by terrestrially derived TSS and CDOM or the lack of a calibrated regional IOP algorithm

The exposure of the Great Barrier Reef to ocean acidification

The Great Barrier Reef (GBR) is founded on reef-building corals. Corals build their exoskeleton with aragonite, but ocean acidification is lowering the aragonite saturation state of seawater (Omega(a)). The downscaling of ocean acidification projections from global to GBR scales requires the set of regional drivers controlling Omega(a) to be resolved. Here we use a regional coupled circulation-biogeochemical model and observations to estimate the Omega(a) experienced by the 3,581 reefs of the GBR, and to apportion the contributions of the hydrological cycle, regional hydrodynamics and metabolism on Omega(a) variability. We find more detail, and a greater range (1.43), than previously compiled coarse maps of Omega(a) of the region (0.4), or in observations (1.0). Most of the variability in Omega(a) is due to processes upstream of the reef in question. As a result, future decline in Omega(a) is likely to be steeper on the GBR than currently projected by the IPCC assessment report