Marine Research Findings of the VECTORS Project

This website provides access to the research results of the VECTORS project, which can be used to support marine management decisions, policies and governance as well as future research and investment. VECTORS was a large scale project that brought together more than 200 expert researchers from 16 different countries. It examined the significant changes taking place in European seas, their causes, and the impacts they will have on society.

Meteorological data impact assessment on the Catalan beaches’ tourism demand of the Catalan coast

The general objective of this study was to develop a method to predict the variation of the number of beach users based on climate variations of temperature, radiation and wind. With this aim in view, it was determined whether these three factors (temperature, radiation and wind) are significant when predicting the variation of the number of users and a prediction model was developed based on Barcelona beaches available data. The model obtained for the beaches of Barcelona will be extrapolated to other beach typologies recalculating the model parameters using the available data from other beaches.

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The most important factor for users of Catalan beaches in all months, both for weekends and weekdays, is radiation. The other factors are of little significance and very variable from one month to another.

By means of a statistical analysis tool, SPSS, we can determine which of the three factors suggested (temperature, radiation and wind) are significant when predicting the variation of the number of users. A factor analysis tool (Automatic Linear Modelling) included in the SPSS is used, giving as a result a prioritisation of these factors.

The only predictor that is consistently significant besides radiation is the weekend predictor. Its relative weight changes from month to month and that seems logical as we expect the significance of this predictor to decrease when the proportion of potential users that are on holidays increases.  For example, in August, when most people are on holiday, the weekend predictor is less relevant as more people can go to beach on week days.

Temperature, which was the third predictor when analysing the data together, does not appear as a selected predictor for all of the months. This could be explained by saying that the hottest months are also the ones where more people are on holiday. This could lead us to assume that temperature has some prediction capacity. This effect disappears when we analyse months separately.

To conclude, if modelling separately both every month and weekends and weekdays the only meteorological predictor worth considering is the average day radiation.

Relevance for Policy:
  • Convention on Biological Diversity
  • Environmental Impact Assessment Directive
  • Marine Strategy Framework Directive
Data availability:

Data used: See deliverable D3.3.1

Where it is held: LEITAT

Contact: Magí Galindo, mgalindo@lenospamitat.org

Lead Author:

Pau Pérez & Laia Piñol
(magigalindonospam@leitat.org)
LEITAT Technological Centre
Date of research: July 2014

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Economic analysis of offshore wind farms project 

Effect of macroalgal blooms on marine biodiversity

Extreme ecological events and jellyfish outbreaks

Growth model for jellyfish Pelagia noctiluca 

How tourism interacts with other users of the sea?

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This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 266445
© Vectors 2015. Coordinated by Plymouth Marine Laboratory.