Establishing a global climatology of marine phytoplankton phenological characteristics

Abstract

[1] The timing or phenology of the annual cycle of phytoplankton biomass can be monitored to better understand the underpinnings of the marine ecosystem and assess its response to environmental change. Ten-year, global maps of the mean date of bloom onset, peak concentration and termination of bloom duration were constructed by extracting these phenological metrics from Generalized Linear Models (GLM) fit to time series of 1 Â 1 daily estimates of SeaWiFS chlorophyll concentrations dating from September 1997 to December 2007 as well as to MODIS chlorophyll concentrations from July 2002 to July 2010. The fitted models quantitatively define the annual cycle of phytoplankton throughout the global ocean and from which a baseline of phenological characteristics was extracted. The analysis revealed regionally consistent patterns in the shape and timing of the annual cycle of chlorophyll concentration that are broadly consistent with other published studies. The results showed that a single bloom predominates over the global ocean with secondary, autumn blooms being limited in both location and spatial extent. Bloom duration tended to be zonally consistent, but meridionally complex and did not become progressively shorter with increasing latitude as is sometimes depicted. Both the shape of the annual cycle and the phenological climatologies can be used in future studies to detect significant departures over time.

Inter-comparison of phytoplankton functional type phenology metrics derived from ocean color algorithms and Earth System Models

“…2A exhibit strong and reproducible seasonality and are mainly dominated by nano-and microphytoplankton during the bloom months, and by picophytoplankton during the low-biomass summer months . These ensemble mean PFT-based results are consistent with the Chl-based analysis of Sapiano et al (2012) who also determined that the poleward fringes of the subtropical gyres have the best seasonality statistical fits.…”

Seasonality of North Atlantic phytoplankton from space: impact of environmental forcing on a changing phenology (1998–2012)

“…ignoring changes in data availability or in the type of seasonal cycle. Our approach was similar in this aspect to Sapiano et al (2012), although it does not require a nearly constant seasonal cycle year after year at the same location to determine the lack or not of a seasonal cycle (see Vantrepotte & M elin, 2009 for an alternative approach to the analyses of changes in chl a). Instead, we explored each oscillation in posterior simulations of models fitting available seasonal data.…”

“…Limitations and advantages of the methods employed to characterize seasonal changes in chl a concentration A variety of approaches have been proposed to characterize phytoplankton seasonality using remote sensing data (Ueyama & Monger, 2005;Rolinski et al, 2007;Platt & Sathyendranath, 2008;Thomalla et al, 2011;Zhai et al, 2011;Racault et al, 2012;Sapiano et al, (Table 1) was fitted to bloom statistics, although combinations resulting in problems of collinearity were excluded (e.g., those including wind stress and its components). The covariate explaining more deviance was determined by comparing the decline in deviance explained after deleting each covariate one at a time.…”

“…Both approaches assume that a bloom has occurred and thus, that chl a data contain enough information to characterize it. Here, we fitted a model with enough flexibility to characterize different types of seasonal cycles of chl a concentration (see Vargas et al, 2008;Sapiano et al, 2012). Seasonal chl a data were previously subset based on sea surface temperature time series.…”

“…the spring phytoplankton bloom, and have highlighted the great variability in this event and a trend towards an early occurrence of these blooms in northern latitudes in recent years Platt & Sathyendranath, 2008;Henson et al, 2009;Kahru et al, 2011;Zhai et al, 2011), as well as the importance of trophic mismatches (Beaugrand et al, 2003;Platt et al, 2003;Koeller et al, 2009;Kristiansen et al, 2011). Secondary pulses during the fall in temperate latitudes and autumn/winter blooms in subtropical and tropical regions have received in general less attention (but see Ueyama & Monger, 2005;Martinez et al, 2011;Cole et al, 2012;Sapiano et al, 2012).…”