Advanced monitoring of South Portugal water bodies towards WFD

The challenge on implementation of the EU Water Framework Directive (WFD) fosters the development of new monitoring methods and approaches. It is now commonly accepted that the use of classical monitoring campaigns in discrete point is not sufficient to fully assess and describe a water body. Due to this the WFD promote the use of modelling techniques in surface waters to assist all phases of the process, from characterisation and establishment of reference conditions to identification of pressures and assessment of impact. The work presented in this communication is based on these principles. A classical monitoring of the water status of the main transitional water bodies of Algarve (south of Portugal) is combined with advanced in situ water profiling and hydrodynamic, water quality and ecological modelling of the systems to build a complete description of its state. This approach extends spatially and temporally the resolution of the classical point sampling. The methodology was applied during a 12 month program in Ria Formosa coastal lagoon, the Guadiana estuary and the Arade estuary. The synoptic profiling uses an YSI 6600 EDS multi-parameter system attached to a boat and a GPS receiver to produce monthly synoptic maps of the systems. This data extends the discrete point sampling with laboratory analysis performed monthly in several points of each water body. The point sampling is used to calibrate the profiling system and to include variables, such as nutrients, not measured by the sensors. A total of 1427 samplings were performed for physical and chemical parameters, chlorophyll and microbiologic contamination in the water column. This data is used to drive the hydrodynamic, transport and ecological modules of the MOHID water modelling system (www.mohid.com), enabling an integrate description of the water column.

Assessing the effects of pseudo-absences on predictive distribution model performance

Modelling species distributions with presence data from atlases, museum collections and databases is challenging. In this paper, we compare seven procedures to generate pseudoabsence data, which in turn are used to generate GLM-logistic regressed models when reliable absence data are not available. We use pseudo-absences selected randomly or by means of presence-only methods (ENFA and MDE) to model the distribution of a threatened endemic Iberian moth species (Graellsia isabelae). The results show that the pseudo-absence selection method greatly influences the percentage of explained variability, the scores of the accuracy measures and, most importantly, the degree of constraint in the distribution estimated. As we extract pseudo-absences from environmental regions further from the optimum established by presence data, the models generated obtain better accuracy scores, and over-prediction increases. When variables other than environmental ones influence the distribution of the species (i.e., non-equilibrium state) and precise information on absences is non-existent, the random selection of pseudo-absences or their selection from environmental localities similar to those of species presence data generates the most constrained predictive distribution maps, because pseudo-absences can be located within environmentally suitable areas. This study showsthat ifwe do not have reliable absence data, the method of pseudo-absence selection strongly conditions the obtained model, generating different model predictions in the gradient between potential and realized distributions.

Landscape metrics as indicators of coastal morphology and its use in ecological niche modelling of seagrass species

Dependence of some species on landscape structure has been proved in numerous studies. So far, however, little progress has been made in the integration of landscape metrics in the prediction of species associated with coastal features. Specific landscape metrics were tested as predictors of coastal shape using three coastal features of the Iberian Peninsula (beaches, capes and gulfs) at different scales. We used the landscape metrics in combination with environmental variables to model the niche and find suitable habitats for a seagrass species (Cymodocea nodosa) throughout its entire range of distribution. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. We provided the first global model of the factors that can be shaping the environmental niche and distribution of C. nodosa throughout its range. Sea surface temperature and salinity were the most relevant variables. We identified areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. We also present some preliminary results of testing historical biogeographical hypotheses derived from distribution predictions under Last Glacial Maximum conditions and genetic diversity data.

Hydroinformatics based decision.making integrating modelling, sampling and profiling: the Ria Formosa case

A Waste Water monitoring program aiming to help decision making is presented. The program includes traditional and inboard sensor sampling, hydrodynamic and water quality modeling and a GIS based database to help the decision making of manager authorities. The focus is in the quality of waters receiving discharges from Waste Water Treatment Plants. Data was used to feed model simulations and produce hydrodynamic, effluent dispersion and ecological results. The system was then used to run different scenarios of discharge flow, concentration and location. The results enable to access the current water quality state of the lagoon and are being used as a decision making tool by the waste water managers in the evaluation phase of the treatment plant project to decide the location and the level of treatment of the discharge.

Modelling antropogenic impact on primary production of sado estuary

The assessment of human impact on complex estuarine systems is a multidisciplinary task that is highly demanding in terms of measurements and fieldwork. Nowadays the use of inexpensive and reliably modeling tools can substantially reduce the amount of measurements needed to characterize a system. These tools are also a convenient way to forecast the future evolution of the system and to study the impact of different scenarios of human influence. In this communication a modeling system composed by hydrodynamic, transport and ecological models is used to assess the current trophic state of Sado Estuary (Portugal) and to predict the future trends of the system based on different scenarios of human intervention. Special care is taken to the impact of changing riverine nutrient loads. Sado estuary is a large European estuary that has been considered until now in good trophic conditions with eutrophication appearing only in some isolated spots. Nevertheless in recent years some studies point out that the situation is changing. Sado estuary is a system with strong environmental opposing interests. It hosts a major industrial and urban center around the city of Setúbal and the upper reaches are used to intensive cultures such as rice. On the other hand the estuary possess an important ecological value since it is used by several important species of fish as a spawning and nursery area and it’s wetlands are used by many species of birds as winter shelters. Due to it’s importance the majority of Sado Estuary is considered as Natural Reserve.

Using niche modelling of indicator species to predict the distribution of xerophitic shrub dune communities in South-Western Portugal

Inland sand dune systems are amongst the most threatened habitat types of Europe. Affected by severe conditions, these habitats present distinct community compositions, which makes them excellent for studying possible interactions among their integrating species and the environment. We focus on understanding the distribution and cooccurrence of the species from dune plant assemblages as a key step for the adequate protection of these habitats. Using data from an extensive survey we identified the shrub species that could be considered indicators of the different xerophytic scrub dune communities in South West Portugal. Then, we modelled the responses of these species to the environmental conditions using Ecological Niche Factor Analysis. We present some preliminary results elucidating whether using species distribution models of indicator species at a regional scale is a valid approach to predict the distribution of the different types of communities inhabiting these endangered habitats.