Mesoscale survey of western and northwestern Irish lakes--spatial and aestival patterns in trophic status and phytoplankton community structure

Abstract

Inland water bodies are considered as integrated parts of the landscape and the monitoring of water quality and aquatic resources need to be addressed on a regional basis for optimal assessment and management. In this study, a simple stratified sampling scheme was applied to a mesoscale survey of western and northwestern Irish lakes, which was carried out to identify, based on the distribution patterns of phytoplankton biomass, potential associations between lake trophic state and land cover attributes. Phytoplankton community analysis was also performed to determine whether taxa associations reflected meteorology-linked aestival succession or specific spatial distributions. The assessment was based on the typology of hydrogeomorphological and land cover attributes of river catchments through ArcGIS analysis. Sampling was carried out in 50 lakes and during a 15-week period in summer 2009. Results showed a general longitudinal gradient in the trophic status of the lakes sampled, with a greater frequency of mesotrophic lakes in the eastern part of the study area where land cover is dominated by agricultural surfaces. Significant relationships (p < 0.010) were found between chlorophyll-a concentration and the proportion of river catchment surface covered by agriculture land and wetlands, findings which might be considered further as proxies for developing an eutrophication risk index. Multivariate analysis of phytoplankton community data clustered the sampled lakes into three assemblages, with ordination along axis 1 being significantly correlated to time and temperature (p < 0.006). There was greater frequency of occurrence of diatoms in lakes from cluster III (Kruskal-Wallis, p < 0.05, H = 6.34, df = 2, n = 49), concomitant to lower chlorophyll-a concentrations, lake surface temperatures and Secchi depths, reflecting meteorological conditions dominated by precipitations. Those results support the potential of mesoscale surveys to assess water quality variables and detect environmental patterns at regional scales.