spBayes: An R Package for Univariate and Multivariate Hierarchical Point-referenced Spatial Models

Scientists and investigators in such diverse fields as geological and environmental sciences, ecology, forestry, disease mapping, and economics often encounter spatially referenced data collected over a fixed set of locations with coordinates (latitude-longitude, Easting-Northing etc.) in a region of study. Such point-referenced or geostatistical data are often best analyzed with Bayesian hierarchical models. Unfortunately, fitting such models involves computationally intensive Markov chain Monte Carlo (MCMC) methods whose efficiency depends upon the specific problem at hand. This requires extensive coding on the part of the user and the situation is not helped by the lack of available software for such algorithms. Here, we introduce a statistical software package, spBayes, built upon the R statistical computing platform that implements a generalized template encompassing a wide variety of Gaussian spatial process models for univariate as well as multivariate point-referenced data. We discuss the algorithms behind our package and illustrate its use with a synthetic and real data example.     

Sustainable management of Agiasma Lagoon-River Nestos delta—Using R.E.MO.S. daily monitoring data of water quality and quantity parameters : Trends, assessments, and natural hazards for the years 2000-2002

Three R.E.MO.S. (Remote Environmental MOnitoring System) telemetric networks have been installed in the catchment area of River Nestos, by research team PERSEAS. The first network has been installed in Nestos Delta. This network consists of two Remote Stations (R.S.):

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The first one is called R.S. “Nestos” and is settled in Nestos Delta in Chrysoupoli and

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the second one is called R.S “Agiasma” and is settled in the homonymous Lagoon.

This paper deals with R.S. “Agiasma”, which operates in Agiasma Lagoon, an area of great environmental importance in the west part of River Nestos Delta. The gradients of the water quality and quantity monitored parameters are very important for the ecological preservation of the lagoon. Moreover, this case can be an excellent example of how the real-time monitoring data can work as an alarm system to prevent environmental hazards.The scientific issues this paper is focused on are:

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The three years systematic daily electronic monitoring data (1/1/2000-31/12/2002). The monitored parameters are Water level—H (cm), Salinity—Sal (‰), Redox Potential—RP (mV), Dissolved Oxygen—DO (mg/l), Water Temperature—T_w (^oC) and Air Temperature—T_a (^oC).

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The assessment of water quality and quantity parameters and the aquatic environment of Agiasma lagoon.

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The detection of trends, using the non-parametric Spearman's criterion. This trend analysis proved the existence of trends for the parameters H, Sal and RP.

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The necessity of real-time monitoring, which can prevent and confront possible natural hazards and disasters and work as an alarm system for the local authorities.