Abstract
Blooms of many dinoflagellates, including several harmful algal bloom (HAB) species, are seeded and revived through the germination of benthic resting cysts. Temperature is a key determinant of cysts' germination rate, and temperature-germination rate relationships are therefore fundamental to understanding species' germling cell production, cyst bed persistence, and resilience to climate warming. This study measured germination by cysts of the HAB dinoflagellate Alexandrium catenella using a growing degree-day (DD) approach that accounts for the time and intensity of warming above a critical temperature. Time courses of germination at different temperatures were fit to lognormal cumulative distribution functions for the estimation of the median days to germination. As temperature increased, germination times decreased hyperbolically. DD scaling collapsed variability in germination times between temperatures after cysts were oxygenated. A parallel experiment demonstrated stable temperature-rate relationships in cysts collected during different phases of seasonal temperature cycles in situ over three years. DD scaling of the results from prior A. catenella germination studies showed consistent differences between populations across a wide range of temperatures and suggests selective pressure for different germination rates. The DD model provides an elegant approach to quantify and compare the temperature dependency of germination among populations, between species, and in response to changing environmental conditions. IMPORTANCE Germination by benthic life history stages is the first step of bloom initiation in many, diverse phytoplankton species. This study outlines a growing degree-day (DD) approach for comparing the temperature dependence of germination rates measured in different populations. Germination by cysts of Alexandrium catenella, a harmful algal bloom dinoflagellate that causes paralytic shellfish poisoning, is shown to require a defined amount of warming, measured in DD after cysts are aerated. Scaling by DD, the time integral of temperature difference from a critical threshold, enabled direct comparison of rates measured at different temperatures and in different studies.