Ecoregional assessment of Turkish lakes using phytoplankton metrics and multimetric approaches

Abstract The aim of this study was to investigate how environmental gradients influence the ecological status (ES) of four lake ecosystems located in different ecoregions of Türkiye using integrated physicochemical and multimetric bioassessments. Four lakes differing in salinity, nutrient levels, and morphometric features were sampled across distinct ecological contexts. Canonical correspondence analysis revealed that phytoplankton communities varied significantly among the lakes. Species composition, primarily shaped by key environmental factors such as electrical conductivity (EC), total organic carbon (TOC), total phosphorus (TP), total suspended solids (TSS), pH, nitrate (NO 3 − ), and temperature, had a strong association of 98.8%. Lake Gölbaşı was related to relatively high temperature and NO 3 − levels, conditions which favor species such as Lepocinclis fusiformis , Lepocinclis acus , Euglena agilis , Phacus caudatus , and Dolichospermum sp. Lake Burdur was associated with high EC, TP, TOC, TSS, and pH, supporting taxa like Lagerheimia ciliata , Lagerheimia genevensis, and Microcystis flos-aquae . Lake Dalyan, a brackish ecosystem, was separated in the ordination, with species such as Phacus limnophilus var. 'swirenkoi', Gymnodinium discoidale , and Pseudanabaena sp. preferring relatively high EC levels. According to bio-assessment based on the Modified Phytoplankton Trophic State Index, Lakes Gölbaşı and Dalyan have a good ES while Lakes Salda and Burdur have moderate and poor ES, respectively. Using the Biological Condition Gradient model, Lake Burdur was categorized with a bad ES and the other three studied lakes were categorized with a good ES. The multimetric Aquatic Biotic Omnimetric Zenith Index (chemical assessment) classified Lake Burdur as the most degraded system. These results highlight the value of combining biological and chemical indicators to achieve a more comprehensive understanding of lake health and highlight the need for adaptable assessment frameworks that can account for both local conditions and broader ecological patterns.