Combining sampling, profiling, remote sensing and modelling to efficiently monitoring estuarine and coastal water quality

Monitoring of coastal and estuarine water quality has been traditionally performed by sampling with subsequent laboratory analysis. This has the disadvantages of low spatial and temporal resolution and high cost. In the last decades two alternative techniques have emerged to overcome this drawback: profiling and remote sensing. Profiling using multi-parameter sensors is now in a commercial stage. It can be used, tied to a boat, to obtain a quick “picture” of the system. The spatial resolution thus increases from single points to a line coincident with the boat track. The temporal resolution however remains unchanged since campaigns and resources involved are basically the same. The need for laboratory analysis was reduced but not eliminated because parameters like nutrients, microbiology or metals are still difficult to obtain with sensors and validation measurements are still needed. In the last years the improvement in satellite resolution has enabled its use for coastal and estuarine water monitoring. Although spatial coverage and resolution of satellite images in the present is already suitable to coastal and estuarine monitoring, temporal resolution is naturally limited to satellite passages and cloud cover. With this panorama the best approach to water monitoring is to integrate and combine data from all these sources. The natural tools to perform this integration are numerical models. Models benefit from the different sources of data to obtain a better calibration. After calibration they can be used to extend spatially and temporally the methods resolution. In Algarve (South of Portugal) a monitoring effort using this approach is being undertaken. The monitoring effort comprises five different locations including coastal waters, estuaries and coastal lagoons. The objective is to establish the base line situation to evaluate the impact of Waste Water Treatment Plants design and retrofitting. The field campaigns include monthly synoptic profiling, using an YSI 6600 multi-parameter system, laboratory analysis and fixed stations. The remote sensing uses ENVISAT\MERIS Level 2 Full Resolution data. This data is combined and used with the MOHID modelling system to obtain an integrate description of the systems. The results show the limitations of each method and the ability of the modelling system to integrate the results and to produce a comprehensive picture of the system.

Prediction of the solar radiation using RBF neural networks and ground-to-sky images

In this study, Artificial Neural Networks are applied to multistep long term solar radiation prediction. The networks are trained as one-step-ahead predictors and iterated over time to obtain multi-step longer term predictions. Auto-regressive and Auto-regressive with exogenous inputs solar radiationmodels are compared, considering cloudiness indices as inputs in the latter case. These indices are obtained through pixel classification of ground-to-sky images. The input-output structure of the neural network models is selected using evolutionary computation methods.

Effect of high CO2 and ocean acidification on photosynthesis and response to oxidative stress in seagrasses

Climate change scenarios comprise significant modifications of the marine realm, notably ocean acidification and temperature increase, both direct consequences of the rising atmospheric CO2 concentration. These changes are likely to impact marine organisms and ecosystems, namely the valuable seagrass-dominated coastal habitats. The main objective of this thesis was to evaluate the photosynthetic and antioxidant responses of seagrasses to climate change, considering CO2, temperature and light as key drivers of these processes. The methodologies used to determine global antioxidant capacity and antioxidant enzymatic activity in seagrasses were optimized for the species Cymodocea nodosa and Posidonia oceanica, revealing identical defence mechanisms to those found in terrestrial plants. The detailed analysis and identification of photosynthetic pigments in Halophila ovalis, H.stipulacea, Zostera noltii, Z marina, Z. capricorni, Cymodocea nodosa and Posidonia oceanica, sampled across different climatic zones and depths, also revealed a similarity with terrestrial plants, both in carotenoid composition and in the pigment-based photoprotection mechanisms. Cymodocea nodosa plants from Ria Formosa were submitted to the combined effect of potentially stressful light and temperature ranges and showed considerable physiological tolerance, due to the combination of changes in the antioxidant system, activation of the VAZ cycle and accumulation of leaf soluble sugars, thus preventing the onset of oxidative stress. Cymodocea nodosa plants living in a naturally acidified environment near submarine volcanic vents in Vulcano Island (Italy) showed to be under oxidative stress despite the enhancement of the antioxidant capacity, phenolics concentration and carotenoids. Posidonia oceanica leaves loaded with epiphytes showed a significant increase in oxidative stress, despite the increase of antioxidant responses and the allocation of energetic resources to these protection mechanisms. Globally, the results show that seagrasses are physiologically able to deal with potentially stressful conditions from different origins, being plastic enough to avoid stress in many situations and to actively promote ulterior defence and repair mechanisms when under effective oxidative stress.

Optimization of molecular dynamics simulation code and applications to biomolecular systems

Tese de doutoramento, Bioquimica, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015