Investigating the distribution patterns of phytoplankton primary productivity (PP) and their influencing factors is fundamental for assessing lake ecosystem service functions. Current related studies primarily focus on macro scales (e.g., global and watershed levels), with limited attention to urban lakes.This study analyzed the spatiotemporal distribution patterns of phytoplankton primary productivity in urban lakes using monitoring data from seven urban lakes in Nanjing, China (2021–2022) by developing a Vertically Generalized Production Model (VGPM). A multivariate generalized linear model (GLM) was applied to quantify the relative contributions of influencing factors to phytoplankton primary productivity. Finally, partial least squares structural equation modeling (PLS-SEM) was utilized to interpret the interaction pathways among these influencing factors.
The results indicated that phytoplankton PP in mesotrophic and eutrophic urban lakes was generally higher during spring and summer. In eutrophic urban lakes, except for summer, phytoplankton PP was significantly higher than in mesotrophic lakes in other seasons (p < 0.05). Compared to eutrophic lakes, mesotrophic lakes exhibited more factors influencing phytoplankton PP. In mesotrophic lakes, nutrients (TN and TP) exerted stronger regulatory effects on PP (cumulatively explaining 32.03% of the variability in PP), whereas in eutrophic lakes, underwater light conditions (Secchi depth, suspended solids, and turbidity) showed stronger regulatory effects (cumulatively explaining 12.37% of the variability in PP). Biological factors (represented by Chl-a) exhibited the strongest positive feedback on phytoplankton PP in both mesotrophic and eutrophic urban lakes (path coefficients: 0.842*** and 0.973***, respectively). Chemical factors (TN, TP, and CODMn) demonstrated contrasting feedback mechanisms: positive in mesotrophic lakes (path coefficient: 0.184**) versus negative in eutrophic lakes (path coefficient: -0.241***). Compared to eutrophic lakes, mesotrophic lakes displayed more indirect pathways affecting phytoplankton PP. Physical factors primarily influenced PP through indirect pathways, with "Physical factors→ Biological factors→ PP" being the dominant indirect pathway, particularly stronger in eutrophic lakes. The pathway "Physical factors→ Chemical factors→ PP" exhibited opposite feedback effects in mesotrophic and eutrophic lakes, primarily attributed to differences in underwater light conditions and water temperature.
This study partially addresses the research gap in phytoplankton PP dynamics in urban lakes, provides references for studies on small water bodies, and offers a scientific basis for evaluating lake carbon sink functions.