available for phytoplankton growth or consumption by the heterotrophic community and is a rate (generally expressed in units of carbon production per unit time).
Variability in basin-scale marine NPP is clearly associated with climate fluctuations
that are expressed as interannual changes in the environment, periodic phenomena
such as El Niño/La Niña cycles, and glacial-interglacial transitions. However,
ocean NPP is not simply forced by climate, but also participates in complex
feedbacks governing climate (e.g., Falkowski et al. 1998a). Understanding the
distribution of NPP and its environmental dependencies is thus critical for evaluating ocean biogeochemical cycles and climate change. In addition, NPP is the
foundation of nearly all marine food webs. Organic matter produced through
photosynthesis supports grazing by zooplankton and other herbivorous organisms
and ultimately all carnivorous invertebrates and vertebrate fish and mammals.
Although quantitative links between NPP and higher trophic levels have been
difficult to establish (Friedland et al. 2012), NPP is a critical input variable for many
types of fisheries models and is used as a constraint when evaluating harvestable
catches (Sherman et al. 2009; Chassot et al. 2010; Pauly and Christensen 1995).
Assessment of NPP rates has relied primarily on traditional shipboard sampling
which is costly, laborious, and provides coarse spatial and temporal resolution.
The only viable approach for basin or global scale assessments has been through
the use of airborne or satellite platforms. Radiometric measurements from early
aircraft efforts provided the seed for remotely detecting phytoplankton, with an
initial focus on assessing pigment (chlorophyll) concentration (Clarke et al. 1970).
A first-order correlation exists between chlorophyll concentration and NPP,
implying that successful remote sensing retrieval of the former property could
yield estimates of the latter rate. In 1978, the Coastal Zone Color Scanner (CZCS)
was launched and represented the first dedicated satellite ocean color sensor for
estimating pigment concentrations, and subsequently NPP (Gordon et al. 1980;
Hovis et al. 1980). The CZCS effort was very successful and its data are still used
in contemporary investigations for multi-decadal studies of ocean color (e.g.,
Martinez et al. 2009; Antoine et al. 2005). Linking a fundamental radiometric
quantity (satellite radiance) to a high-level rate process (NPP) has remained a key
justification for modern ocean color satellite missions (e.g., SeaWiFS, MODIS).
Pre-launch documents for these missions have explicitly identified NPP as a Level
4 product calculable from a combination of lower level products (Falkowski et al.
1998b; Esaias 1996). Even today, NPP remains a key ocean biological rate process
targeted by all active satellite ocean color missions.
Accurate assessment of global ocean NPP is a daunting task. Much of the
phytoplankton community contributing to production lies ‘hidden’ below the
shallow surface layer detected by satellite sensors. The conversion of detected
standing stocks to a rate processes remains a major challenge and is complicated
by a variety of phytoplankton physiological attributes. Nevertheless, significant
progress has been made since the launch of the CZCS with respect to evaluating
ocean NPP and detecting its dependency on climate forcings. In this review, we
begin with a general overview of the theoretical basis for remote sensing NPP
algorithms, describe contemporary approaches, and discuss the validation of
206
T. K. Westberry and M. J. Behrenfeld
Variability in basin-scale marine NPP is clearly associated with climate fluctuations
that are expressed as interannual changes in the environment, periodic phenomena
such as El Niño/La Niña cycles, and glacial-interglacial transitions. However,
ocean NPP is not simply forced by climate, but also participates in complex
feedbacks governing climate (e.g., Falkowski et al. 1998a). Understanding the
distribution of NPP and its environmental dependencies is thus critical for evaluating ocean biogeochemical cycles and climate change. In addition, NPP is the
foundation of nearly all marine food webs. Organic matter produced through
photosynthesis supports grazing by zooplankton and other herbivorous organisms
and ultimately all carnivorous invertebrates and vertebrate fish and mammals.
Although quantitative links between NPP and higher trophic levels have been
difficult to establish (Friedland et al. 2012), NPP is a critical input variable for many
types of fisheries models and is used as a constraint when evaluating harvestable
catches (Sherman et al. 2009; Chassot et al. 2010; Pauly and Christensen 1995).
Assessment of NPP rates has relied primarily on traditional shipboard sampling
which is costly, laborious, and provides coarse spatial and temporal resolution.
The only viable approach for basin or global scale assessments has been through
the use of airborne or satellite platforms. Radiometric measurements from early
aircraft efforts provided the seed for remotely detecting phytoplankton, with an
initial focus on assessing pigment (chlorophyll) concentration (Clarke et al. 1970).
A first-order correlation exists between chlorophyll concentration and NPP,
implying that successful remote sensing retrieval of the former property could
yield estimates of the latter rate. In 1978, the Coastal Zone Color Scanner (CZCS)
was launched and represented the first dedicated satellite ocean color sensor for
estimating pigment concentrations, and subsequently NPP (Gordon et al. 1980;
Hovis et al. 1980). The CZCS effort was very successful and its data are still used
in contemporary investigations for multi-decadal studies of ocean color (e.g.,
Martinez et al. 2009; Antoine et al. 2005). Linking a fundamental radiometric
quantity (satellite radiance) to a high-level rate process (NPP) has remained a key
justification for modern ocean color satellite missions (e.g., SeaWiFS, MODIS).
Pre-launch documents for these missions have explicitly identified NPP as a Level
4 product calculable from a combination of lower level products (Falkowski et al.
1998b; Esaias 1996). Even today, NPP remains a key ocean biological rate process
targeted by all active satellite ocean color missions.
Accurate assessment of global ocean NPP is a daunting task. Much of the
phytoplankton community contributing to production lies ‘hidden’ below the
shallow surface layer detected by satellite sensors. The conversion of detected
standing stocks to a rate processes remains a major challenge and is complicated
by a variety of phytoplankton physiological attributes. Nevertheless, significant
progress has been made since the launch of the CZCS with respect to evaluating
ocean NPP and detecting its dependency on climate forcings. In this review, we
begin with a general overview of the theoretical basis for remote sensing NPP
algorithms, describe contemporary approaches, and discuss the validation of
206
T. K. Westberry and M. J. Behrenfeld