Seasonal variation of the water quality of rivers and streams of eastern Mediterranean

Biotic and abiotic data on undisturbed or moderately disturbed lotic sites from a number of studies carried out in northern Greece showed that large rivers differ from small rivers, streams or creeks in terms of diversity, dominant groups and the kind of taxa (concerning the sensitivity of the taxa according to Biological Monitoring Working Party (BMWP) biotic scores). This is mainly due to the differences in their physical characteristics. Correlation of the environmental variables using MDA (multiple discriminant analysis) showed that the chief differentiating factors among the above water bodies are substrate, total suspended solids (TSS), conductivity, slope and temperature. Additionally, there is no clear phenological seasonality in the majority of the dominant benthic macroinvertebrate groups when undisturbed or moderately disturbed sites of mountainous creeks and small rivers are examined. By contrast, in downstream sites of long rivers, seasonality characterizes the dominant benthic macroinvertebrate groups, as it does for other Mediterranean animals

Development of artificial neural network models predicting macroinvertebrate taxa in the river Axios (Northern Greece)

Artificial Neural Network models (ANNs) were used to predict habitat suitability for 12 macroinvertebrate taxa, using environmental input variables. This modelling technique was applied to a dataset of 102 measurement series collected in 31 sampling sites in the Greek river Axios. The database consisted of seven physical-chemical and seven structural variables, as well as abundances of 90 macroinvertebrate taxa. A seasonal variable was included to allow the description of potential temporal changes in the macroinvertebrate communities. The induced models performed well for predicting habitat suitability of the macroinvertebrate taxa. Senso-nets and sensitivity analyses revealed that dissolved oxygen concentration and the substrate composition always played a crucial role in predicting habitat suitability of the macroinvertebrates. Although ANNs are often referred to as black box prediction techniques, it was demonstrated that ANNs combined with sensitivity analyses can provide insight in the relationship between river conditions and the occurrence of macroinvertebrates, and thus deliver new ecological knowledge. Consequently, these models can be useful in decision-making for river restoration and conservation management