Assessing phytoplankton structure and spatio-temporal dynamics in a freshwater ecosystem using a powerful multiway...

Area of Science:

• Ecology
• Limnology
• Statistical Modeling

Background:

• Analyzing species-level phytoplankton dynamics is challenging due to high diversity, seasonal variations, and extensive spatial sampling.
• Advanced statistical methods are crucial for detailed spatio-temporal analyses of phytoplankton communities.

Purpose of the Study:

• To apply Partial Triadic Analysis to investigate phytoplankton species dynamics and diversity.
• To identify key seasonal periods and sampling stations within the Reservoir Marne ecosystem.

Main Methods:

• Utilized Partial Triadic Analysis, a STATIS-family method.
• Analyzed a dataset from 6 stations in Reservoir Marne, sampled 22 times over two years (2006-2007) between March and September.

Main Results:

• Unambiguously identified three key seasonal sampling periods: early spring, late spring-early summer, and late summer-early autumn.
• Associated specific phytoplankton species with each identified seasonal period.
• Identified a potential reference sampling station and highlighted three other stations with unique phytoplankton characteristics.

Conclusions:

• Partial Triadic Analysis effectively discerns seasonal phytoplankton patterns and species associations.
• The findings provide valuable insights for scientists and water managers regarding ecosystem monitoring and management strategies in Reservoir Marne.