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S. Bernard et al.
nature imprecise by comparison with the species-level in situ data typically used to
determine HAB assemblage characteristics and potentially harmful impacts.
Ocean colour application to HABs is therefore most valuable when contextualised from an ecosystem-specific perspective. Of particular importance is the need
to contextualise observations from an ecosystem understanding of phytoplankton
succession; to utilise satellite derived information through time and space to identify and understand the competitive success of a particular phytoplankton species or
functional type in a given ecological niche. Conceptual succession schemes (Margalef 1978, Smayda 2002) provide a useful framework for ocean colour application
in upwelling systems in ecological space: a key aspect is the distinction between
diatom and dinoflagellate dominance, primarily controlled by turbulence and nutrient availability (Margalef 1978). Upwelling systems are physically driven, but
with a somewhat stochastic determination of phytoplankton functional type dominance within a given ecological niche (Kudela et al. 2010). Beyond the obvious
need to detect the magnitude, extent and transport of blooms, one of the key aims
of ocean colour application should thus be to elucidate assemblage structure within
an environmentally determined ecological niche. HAB application of ocean colour
radiometry therefore necessarily introduces the need for a species or at least phytoplankton functional type identifier from ocean colour: a bloom cannot be identified
as potentially harmful without some form of phytoplankton assemblage information,
even if indirectly derived or highly probabilistic in nature.
Such identifiers can be as simple as an ecosystem-contextualised threshold for
phytoplankton abundance, typically determined using chlorophyll a concentration
as a biomass proxy: such an approach has been successfully used in the Gulf of
Florida for the operational detection of blooms of the toxic dinoflagellate Karenia
brevis using commonly available ocean colour products (Tomlinson et al. 2009).
The southern Benguela system is highly productive; diatom blooms of up to 20 mg
m
−3 chlorophyll a are not uncommon in inshore waters (Barlow 1982, Brown and
Hutchings 1987), with diatom-dominated biomass occasionally reaching values of
> 50 mg m
−3 (Mitchell Innes and Walker 1991; Fawcett et al. 2007). However, typically the majority of reported blooms displaying enhanced biomass concentrations
of > 30–50 mg m
−3 are dinoflagellate dominated (Fawcett et al. 2007; Pitcher et al.
2008a, b; Pitcher and Probyn 2011; Pitcher and Weeks 2006), and thus more likely
to result in a harmful impact. Such enhanced biomass is associated with cellular
motility and the ability to regulate position in the water column, resulting in enhanced near-surface aggregation of flagellated cells (Franks 1992; Smayda 1997).
The biomass range threshold of 30–50 mg m
−3 chlorophyll a can be used as a probabilistic first-order identifier of bloom type: it is likely that a bloom with biomass
above this range is dinoflagellate dominated. However, the accurate determination
of chlorophyll a concentrations > 20 mg m
−3 is well outside the scope of commonly
available algorithms for the Medium Resolution Imaging Spectrometer (MERIS),
both for Case 1 waters (Morel et al. 2007), and Case 2 waters (Schiller and Doerffer
1999, 2005), and the demonstration of new empirical and semi-analytical algorithms
designed for such high biomass application is a primary aim of this study.
The provision of some form of direct assemblage description from ocean colour
measurements offers significant advantages over descriptors derived indirectly from
abundance estimates; namely an ability to distinguish a greater variety of assemblage
S. Bernard et al.
nature imprecise by comparison with the species-level in situ data typically used to
determine HAB assemblage characteristics and potentially harmful impacts.
Ocean colour application to HABs is therefore most valuable when contextualised from an ecosystem-specific perspective. Of particular importance is the need
to contextualise observations from an ecosystem understanding of phytoplankton
succession; to utilise satellite derived information through time and space to identify and understand the competitive success of a particular phytoplankton species or
functional type in a given ecological niche. Conceptual succession schemes (Margalef 1978, Smayda 2002) provide a useful framework for ocean colour application
in upwelling systems in ecological space: a key aspect is the distinction between
diatom and dinoflagellate dominance, primarily controlled by turbulence and nutrient availability (Margalef 1978). Upwelling systems are physically driven, but
with a somewhat stochastic determination of phytoplankton functional type dominance within a given ecological niche (Kudela et al. 2010). Beyond the obvious
need to detect the magnitude, extent and transport of blooms, one of the key aims
of ocean colour application should thus be to elucidate assemblage structure within
an environmentally determined ecological niche. HAB application of ocean colour
radiometry therefore necessarily introduces the need for a species or at least phytoplankton functional type identifier from ocean colour: a bloom cannot be identified
as potentially harmful without some form of phytoplankton assemblage information,
even if indirectly derived or highly probabilistic in nature.
Such identifiers can be as simple as an ecosystem-contextualised threshold for
phytoplankton abundance, typically determined using chlorophyll a concentration
as a biomass proxy: such an approach has been successfully used in the Gulf of
Florida for the operational detection of blooms of the toxic dinoflagellate Karenia
brevis using commonly available ocean colour products (Tomlinson et al. 2009).
The southern Benguela system is highly productive; diatom blooms of up to 20 mg
m
−3 chlorophyll a are not uncommon in inshore waters (Barlow 1982, Brown and
Hutchings 1987), with diatom-dominated biomass occasionally reaching values of
> 50 mg m
−3 (Mitchell Innes and Walker 1991; Fawcett et al. 2007). However, typically the majority of reported blooms displaying enhanced biomass concentrations
of > 30–50 mg m
−3 are dinoflagellate dominated (Fawcett et al. 2007; Pitcher et al.
2008a, b; Pitcher and Probyn 2011; Pitcher and Weeks 2006), and thus more likely
to result in a harmful impact. Such enhanced biomass is associated with cellular
motility and the ability to regulate position in the water column, resulting in enhanced near-surface aggregation of flagellated cells (Franks 1992; Smayda 1997).
The biomass range threshold of 30–50 mg m
−3 chlorophyll a can be used as a probabilistic first-order identifier of bloom type: it is likely that a bloom with biomass
above this range is dinoflagellate dominated. However, the accurate determination
of chlorophyll a concentrations > 20 mg m
−3 is well outside the scope of commonly
available algorithms for the Medium Resolution Imaging Spectrometer (MERIS),
both for Case 1 waters (Morel et al. 2007), and Case 2 waters (Schiller and Doerffer
1999, 2005), and the demonstration of new empirical and semi-analytical algorithms
designed for such high biomass application is a primary aim of this study.
The provision of some form of direct assemblage description from ocean colour
measurements offers significant advantages over descriptors derived indirectly from
abundance estimates; namely an ability to distinguish a greater variety of assemblage