Linking population dynamics models with empirically derived models through phytoplankton primary production

Area of Science:

• Aquatic Ecology
• Limnology
• Biogeochemistry

Background:

• Phytoplankton primary production (PP) is crucial for aquatic ecosystems.
• Existing models for estimating PP differ in their calculation approaches.
• Process-oriented models use photosynthesis-light relationships, while population dynamics models use population data.

Purpose of the Study:

• To compare process-oriented and population dynamics-based PP estimation methods.
• To identify factors influencing PP estimates in various lake types.
• To enhance population dynamics models using insights from process-oriented models.

Main Methods:

• Comparison of two fundamentally different PP estimation methods: process-oriented and population dynamics-based.
• Analysis of sensitivity to phytoplankton sinking, zooplankton grazing, and light parameters (e.g., day length).
• Inclusion of parasite-related loss terms for cyanobacterial blooms to resolve model discrepancies.

Main Results:

• Both PP estimation methods are sensitive to phytoplankton sinking and zooplankton grazing rates.
• Process-oriented models are sensitive to light parameters like day length.
• Discrepancies between methods, especially during cyanobacterial blooms, were resolved by incorporating parasite-related mortality (19%-33% loss).

Conclusions:

• Parasitism plays a critical role in aquatic ecosystem metabolism, particularly in regulating cyanobacterial populations.
• Accounting for parasite-induced mortality is essential for accurate PP estimation, especially during blooms.
• Integrating insights from different PP models enhances our understanding of aquatic ecosystem functioning.