Ecosystem service benefits and costs of deep-sea ecosystem restoration.

Deep-sea ecosystems are facing degradation which could have severe consequences for biodiversity and the livelihoods of coastal populations. Ecosystem restoration as a natural based solution has been regarded as a useful means to recover ecosystems. The study provides a social cost-benefit analysis for a proposed project to restore the Dohrn Canyon cold water corals and the deep-sea ecosystem in the Bay of Naples, Italy. By incorporating ecosystem service benefits and uncertainties related to a complex natural-technological-social system surrounding restoration activities, the study demonstrated how to evaluate large-scale ecosystem restoration activities. The results indicate that an ecosystem restoration project can be economic (in terms of welfare improvement) even if the restoration costs are high. Our study shows the uncertainty associated with restoration success rate significantly affects the probability distribution of the expected net present values. Identifying and controlling the underlying factors to improve the restoration successful rate is thus crucial.

Probing the Rare Biosphere of the North-West Mediterranean Sea: An Experiment with High Sequencing Effort.

High-throughput sequencing (HTS) techniques have suggested the existence of a wealth of species with very low relative abundance: the rare biosphere. We attempted to exhaustively map this rare biosphere in two water samples by performing an exceptionally deep pyrosequencing analysis (~500,000 final reads per sample). Species data were derived by a 97% identity criterion and various parametric distributions were fitted to the observed counts. Using the best-fitting Sichel distribution we estimate a total species richness of 1,568-1,669 (95% Credible Interval) and 5,027-5,196 for surface and deep water samples respectively, implying that 84-89% of the total richness in those two samples was sequenced, and we predict that a quadrupling of the present sequencing effort would suffice to observe 90% of the total richness in both samples. Comparing the HTS results with a culturing approach we found that most of the cultured taxa were not obtained by HTS, despite the high sequencing effort. Culturing therefore remains a useful tool for uncovering marine bacterial diversity, in addition to its other uses for studying the ecology of marine bacteria.

Skill Assessment for Coupled Biological/Physical Models of Marine Systems.

Coupled biological/physical models of marine systems serve many purposes including the synthesis of information, hypothesis generation, and as a tool for numerical experimentation. However, marine system models are increasingly used for prediction to support high-stakes decision-making. In such applications it is imperative that a rigorous model skill assessment is conducted so that the model's capabilities are tested and understood. Herein, we review several metrics and approaches useful to evaluate model skill. The definition of skill and the determination of the skill level necessary for a given application is context specific and no single metric is likely to reveal all aspects of model skill. Thus, we recommend the use of several metrics, in concert, to provide a more thorough appraisal. The routine application and presentation of rigorous skill assessment metrics will also serve the broader interests of the modeling community, ultimately resulting in improved forecasting abilities as well as helping us recognize our limitations.

Spatially implicit plankton population models: Transient spatial variability.

Ocean plankton models are useful tools for understanding and predicting the behaviour of planktonic ecosystems. However, when the regions represented by the model grid cells are not well mixed, the population dynamics of grid cell averages may differ from those of smaller scales (such as the laboratory scale). Here, the 'mean field approximation' fails due to 'biological Reynolds fluxes' arising from nonlinearity in the fine-scale biological interactions and unresolved spatial variability. We investigate the domain-scale behaviour of two-component, 2D reaction-diffusion plankton models producing transient dynamics, with spatial variability resulting only from the initial conditions. Failure of the mean field approximation can be quite significant for sub grid-scale mixing rates applicable to practical ocean models. To improve the approximation of domain-scale dynamics, we investigate implicit spatial resolution methods such as spatial moment closure. For weak and moderate strengths of biological nonlinearity, spatial moment closure models generally yield significant improvements on the mean field approximation, especially at low mixing rates. However, they are less accurate given weaker transience and stronger nonlinearity. In the latter case, an alternative 'two-spike' approximation is accurate at low mixing rates. We argue that, after suitable extension, these methods may be useful for understanding and skillfully predicting the large-scale behaviour of marine ecosystems.