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Abstract The timing of biological events, known as phenology, plays a key role in shaping ecosystem dynamics, and climate change can significantly alter these timings. The Gulf of Maine on the Northeast U.S. Shelf is vulnerable to warming temperatures and other climate impacts, which could affect the distribution and production of plankton species sensitive to phenological shifts. In this study, we apply a novel data‐driven modeling approach to long‐term datasets to understand the population variability ofCalanus finmarchicus, a lipid‐rich copepod that is fundamental to the Gulf of Maine food web. Our results reveal how phenology impacts the complex intermingling of top‐down and bottom‐up controls. We find that early initiation of the annual phytoplankton bloom prompts an early start to the reproductive season for populations ofC. finmarchicusin the inner Gulf of Maine, resulting in high spring abundance. This spring condition appears to be conducive to enhanced predation pressure later in the season, consequently resulting in overall lowC. finmarchicusabundance in the fall. These biologically controlled dynamics are less pronounced in the outer Gulf of Maine, where water exchanges near the boundary have a greater influence. Our analysis augments existing hypotheses in fisheries oceanography and classical ecological theory by considering unique plankton life‐history characteristics and shelf sea dynamics, offering new insights into the biological factors drivingC. finmarchicusvariability. 

Abstract Spatial population synchrony, defined as spatial covariation in population density fluctuations, exists across different temporal and spatial scales. Determining the degree of spatial synchrony is useful for inferring environmental drivers of population variability in the wake of climate change. In this study, we applied novel statistical methods to detect spatial synchrony patterns ofCalanus finmarchicuson the Northeast U.S. Shelf at multiple spatiotemporal scales using unevenly distributed data. Our results reveal thatC. finmarchicussubpopulations connected by advection are not necessarily in synchrony, indicating that the degree of synchrony is likely influenced by heterogeneity of local habitats. In addition, regionally synchronous environmental conditions (e.g., sea surface temperature) may not play as significant a role in influencing subregional population dynamics as was previously hypothesized. Overlooking the spatial heterogeneity of synchronous patterns at different time scales could lead to erroneous inferences of potential environmental drivers responsible forC. finmarchicusvariability.