Coupling habitat-specific temperature scenarios with tolerance landscape to predict the impacts of climate change on farmed bivalves.

Due to climate change, heatwaves are likely to become more frequent, prolonged and characterized by higher peak values, compared with climatological averages. However, the thermal tolerance of organisms depends on the actual exposure, which can be modulated by environmental context and microhabitat characteristics. This study investigated the frequency of occurrence of mass mortality events in the next decades for two species of farmed bivalves, the mussel Mytilus galloprovincialis and the clam Ruditapes philippinarum, in a shallow coastal lagoon, characterised by marked diurnal oscillations of water temperature. The effect of heatwaves was estimated by means of tolerance landscape models, which predict the occurrence of 50% mortality based on the exposure intensity and duration. Scenarios of water temperature up to the year 2100 were modelled by combining two mechanistic components, namely: 1) monthly mean water temperatures, simulated using a hydrodynamic model including the heat budget; 2) daily oscillations, estimated from the harmonic analysis of a twenty year-long site-specific time series of water temperature. Scenarios of mean daily sediment temperature were estimated by means of a cross-correlation model, using as input the water temperature one: the model parameters were estimated based on a comprehensive set of site-specific water and sediment temperature observations. The results indicate that for both species the risk of mass mortality rapidly increases starting from the 2060s. Furthermore, the daily patterns of water temperature seemed to be relevant, as overnight it falls below the predicted mortality thresholds for a few hours. These findings suggest that further studies should address: 1) the improvement of tolerance landscape models, in order to take into account the integrated effect of repeated non-lethal stress events on mortality rate; 2) the prediction of environmental temperature in specific habitat, by means of both process-based and data driven models.

How to cope in heterogeneous coastal environments: Spatio-temporally endogenous circadian rhythm of valve gaping by mussels.

Transitional coastal zones are subject to high degrees of temporal fluctuation in environmental conditions, with these patterns varying in space. Gaining an in depth understanding of how sessile organisms cope with and respond to such environmental changes at multiple scales is needed to i) advance fundamental knowledge, ii) predict how organisms may react to stressors and iii) support the management of halieutic resources in transitional coastal areas. We addressed this question using mussels (Mytilus galloprovincialis) as model system. Valve-gaping sensor were deployed at multiple sites within the southern Venice Lagoon over a period of 6 months, to investigate the existence of periodicity in valve-gaping and its relationship with environmental variables, such as temperature and chlorophyll-a. Gaping behaviour was found to have periodic rhythms, of ~12 h and ~ 24 h, which were most pronounced in the inner part of lagoon part and were strongest during summer months. In autumn, the dual periodicity became weaker and mostly the 12 h remained. Gaping was closely linked with tide, but the relationship in terms of phasing varied upon location. Surprisingly, no clear direct relationships were found with chlorophyll-a, but food delivery may be mediated by tide itself. The results highlight the heterogeneity of behaviour and the endogenic nature of circadian rhythms in space and time. These findings have important implications for management of transitional areas where tidal alteration may have impacts on key behaviours, and emphasize the importance of characterizing their rhythms before using these as stress indicator. Moreover, the described tidal relationships should be included in growth models of bivalves in these systems.

Climate change impacts on marine water quality: The case study of the Northern Adriatic sea.

Climate change is posing additional pressures on coastal ecosystems due to variations in water biogeochemical and physico-chemical parameters (e.g., pH, salinity) leading to aquatic ecosystem degradation. With the main aim of analyzing the potential impacts of climate change on marine water quality, a Regional Risk Assessment methodology was developed and applied to coastal marine waters of the North Adriatic. It integrates the outputs of regional biogeochemical and physico-chemical models considering future climate change scenarios (i.e., years 2070 and 2100) with site-specific environmental and socio-economic indicators. Results showed that salinity and temperature will be the main drivers of changes, together with macronutrients, especially in the area of the Po' river delta. The final outputs are exposure, susceptibility and risk maps supporting the communication of the potential consequences of climate change on water quality to decision makers and stakeholders and provide a basis for the definition of adaptation and management strategies.

Linking food web functioning and habitat diversity for an ecosystem based management: a Mediterranean lagoon case-study.

We propose a modelling approach relating the functioning of a transitional ecosystem with the spatial extension of its habitats. A test case is presented for the lagoon of Venice, discussing the results in the context of the application of current EU directives. The effects on food web functioning due to changes related to manageable and unmanageable drivers were investigated. The modelling procedure involved the use of steady-state food web models and network analysis, respectively applied to estimate the fluxes of energy associated with trophic interactions, and to compute indices of food web functioning. On the long term (hundred years) temporal scale, the model indicated that the expected loss of salt marshes will produce further changes at the system level, with a lagoon showing a decrease in the energy processing efficiency. On the short term scale, simulation results indicated that fishery management accompanied by seagrass restoration measures would produce a slight transition towards a more healthy system, with higher energy cycling, and maintaining a good balance between processing efficiency and resilience. Scenarios presented suggest that the effectiveness of short term management strategies can be better evaluated when contextualized in the long term trends of evolution of a system. We also remark the need for further studying the relationship between habitat diversity and indicators of food web functioning.

The seasonal distribution of dissolved inorganic nitrogen and phosphorous in the lagoon of Venice: a numerical analysis.

This paper investigates the seasonal evolution of the spatial distributions of dissolved inorganic nitrogen and phosphorus, in relation to the estimation of the N and P loads, which were obtained in the framework of the DRAIN project. Such investigation is carried out by using a 3D reaction-diffusion model which has been calibrated against salinity data and then used for obtaining the most likely scenario of the spatial and seasonal distribution of DIN and DIP. The consequences of different management policies are also discussed, in relation to the current Italian legislation, which sets quality standards for both DIN and DIP in the lagoon of Venice.

Fault detection in a real-time monitoring network for water quality in the lagoon of Venice (Italy).

In the context of monitoring water quality in natural ecosystems in real time, on-line data quality control is a very important issue for effective system surveillance and for optimizing maintenance of the monitoring network. This paper presents some applications of recursive state-parameter estimation algorithms to real-time detection of signal drift in high-frequency observations. Two continuous-discrete recursive estimation schemes, namely the Extended Kalman Filter and the Recursive Prediction Error algorithm, were applied to assuring the quality of the dissolved oxygen (DO) time series, as obtained from the Lagoon of Venice (Italy) during August 2002, through the real-time monitoring network of the Magistrato alle Acque (the Venice Water Authority). Results demonstrate the effectiveness of the methodology in early detection of a probable drift in the DO signal. Comparison of these results with those obtained from the application of a related recursive scheme (a Dynamic Linear Regression procedure) suggests the strong benefits of approaching the problem of on-line data quality control with several (not merely a single) independent such estimation methods.