S.-i. S. Matsuzaki

This study evaluates early warning signals for ecological regime shifts in lake data and finds few critical transitions, with mixed performance of prediction methods.

The paper examines the relationship between planktonic functional diversity and lake ecosystem state across five lakes, finding that FD synchronizes with state metrics but is not a reliable early indicator.

This paper introduces EcohNet, a machine learning framework for causal inference in complex ecosystems, showing it improves interaction network inference and forecasting of ecosystem components.

This paper develops a multispecies site occupancy model for eDNA metabarcoding to improve study design and species detection efficiency by accounting for workflow variability and detection bias.

This study evaluates how species traits and ecosystem characteristics affect eDNA detection rates in lake fish communities across Japan.

The paper examines how long-term warming reduces the stabilizing role of biodiversity in aquatic ecosystems by analyzing time series data and causal relationships.