Intrinsic temporal structure and lagged environmental effects shape the dynamics of airborne microscopic eukaryotes.

Abstract

Airborne microscopic eukaryotes play important ecological roles, yet their temporal dynamics often appear stochastic and difficult to predict using concurrent meteorological variables. We conducted a high-resolution, 3-year survey of airborne fungi, protists, and metazoa in a temperate urban environment using quantitative PCR and amplicon sequencing. Seasonality varied markedly among groups: fungi and metazoa exhibited distinct annual cycles (peaking in late summer and winter, respectively), while protists displayed stochastic fluctuations. Taxonomically, fungi were dominated by soil- and plant-associated taxa (e.g., Cladosporium), protists by aquatic and terrestrial taxa (e.g., Phytophthora), and metazoa by DNA from mammals and insects. Static (i.e., contemporaneous, non-time lagged) analyses based on correlation and multiple linear regression identified concurrent environmental associations but explained only a limited proportion of the variance (28%, 6%, and 14% for fungi, protists, and metazoa, respectively). In contrast, incorporating time-lagged effects using Granger causality and autoregressive integrated moving average with exogenous variables (ARIMAX) substantially improved explanatory power, accounting for up to 47% of the variance for fungi and ~29% for protists and metazoa. These improvements primarily reflected intrinsic temporal dependence, indicating that antecedent biological states and prior environmental conditions contributed to eukaryotic abundances. Our results suggest that relying solely on concurrent meteorology is insufficient, whereas integrating temporal dependence and lagged environmental effects provides a robust framework for predicting airborne eukaryotic dynamics.IMPORTANCEAirborne microscopic eukaryotes influence ecosystems, agriculture, and human health, yet their temporal behavior in the atmosphere remains poorly understood and difficult to predict. Using a 3-year, high-resolution survey, this study shows that different airborne eukaryotic groups follow fundamentally different temporal rules. Airborne fungi, dominated by plant- and soil-associated taxa such as Cladosporium, and animal-derived metazoan material exhibit clear and contrasting seasonal cycles, whereas protists, including the plant pathogen Phytophthora, fluctuate irregularly. Importantly, models based only on current weather conditions explain little of this variability. By incorporating biological memory and delayed environmental effects, time-series models substantially improve predictability across all groups. These findings demonstrate that airborne eukaryotes respond not only to present conditions but also to prior environmental states, providing a more realistic framework for forecasting bioaerosols relevant to ecosystem connectivity, plant disease spread, and air-quality risk assessment.