Author/Authors :
L. W. Harding Jr.، نويسنده , , M. E. Mallonee، نويسنده , , E. S. Perry، نويسنده ,
Abstract :
This paper addresses the development of a predictive understanding of phytoplankton primary productivity (PP) in
estuaries, drawing on an extensive set of observations in Chesapeake Bay and contemporary modeling approaches
coupled to empirical data. PP was measured at 575 stations on 68 cruises, 1982–2000. Descriptions presented here are
based on PP data from 455 stations occupied 1982–1998, and from 120 stations occupied 1999–2000 that were used for
model validation. The nearly two-decade sampling period encompassed a broad range of freshwater flow and nutrient
loading to the Bay. Mean net 14C-PP for 1982–1998 was 1055 mg C m 2 d 1 ( SE=46·0) in the main stem Bay for
all seasons and regions. Phytoplankton dynamics included a spring maximum of biomass, expressed as euphotic-layer
chlorophyll (chl a), and a summer maximum of net 14C-PP displaced by approximately 4 months from the biomass
maximum. The annual maximum of euphotic-layer chl a exceeded 100 mg m 2 in mesohaline and polyhaline regions of
the Bay during April and May, whereas highest net 14C-PP of 1700–2500 mg C m 2 d 1occurred in the mesohaline Bay
in July and August. Euphotic-layer chl a and net 14C-PP were much lower in the light-limited oligohaline Bay and no time
lag was observed. Mean gross 14C-PP was 1564 mg C m 2 d 1 ( SE=85·0) for 1995–1998. Concurrent measurements
using 14C and O2 methods generated estimates of the photosynthetic quotient (PQ) to confirm our interpretation
of net and gross PP from 14C uptake in full- and partial-day incubations, respectively, and allowed us to reconcile
apparent differences in 14C- and O2-determined PP in recent studies. PQ values (=O2 produced/CO2 fixed) were
estimated as 1·48 from regression of stoichiometrically converted net O2-PP on net 14C-PP, and as 1·38 from the
regression of gross O2-PP on gross 14C-PP. PQ values in this range typically correspond to phytoplankton that are using
oxidized nitrogen (NO
3 -N) as the main N source, consistent with the view that N-limitation occurs on an annual scale
in the Bay. We used empirical data for net and gross 14C-PP to estimate annual integrated production (AIP) of 282 to
538 g C m 2 yr 1 (net) and 347 to 662 g C m 2 yr 1 (gross). Simple, linear regression of net AIP on annual, mean
euphotic-layer chl a was significant and explained 62% of the variance. Inter-annual variability of net AIP was related
to the volume of freshwater flow and to total nitrogen (TN) and total phosphorus (TP) loading during February and
March. We tested the performance of published models to estimate PP in Chesapeake Bay. The Vertically Generalized
Productivity Model (VGPM) overestimated net and gross PP, and adjusted forms of VGPM termed VGPM-A for net and
gross PP gave significantly improved performance for Chesapeake Bay. We explored an alternative approach to VGPM
that allowed us to obtain non-unity exponents for independent variables, using step-wise and multiple regressions in
log-space first to identify independent variables that predicted net and gross PP, and subsequently to determine
coefficients of the terms. This approach resulted in the Chesapeake Bay Productivity Model (CBPM-1) that estimated net
and gross PP with root mean square error (RMSE) of 28·3% and 34·9%, respectively. We then developed models of the
physiological input, PB
opt, a variable that expresses optimal photosynthesis in the water column normalized to chl a, using
several independent variables and measured values of PB
opt. Substitution of the models of PB
opt in CBPM-1 resulted in
CBPM-2 that required no explicit input of PB
opt and estimated net and gross PP with RMSE of 120% and 49·8%,
respectively. Lastly, we validated CBPM-1 and CBPM-2 using observations from 1999–2000 not included in
development of the models. CBPM-1 estimated net and gross PP with RMSE of 17·8% and 35·8%, respectively, and
CBPM-2 estimated net and gross PP with RMSE of 80·3% and 47·6%, respectively. We believe the use of contemporary
PP models that require simple inputs amenable to remote sensing, such as the adjusted VGPM, CBPM-1, and CBPM-2,
should permit us to resolve spatial and temporal differences of net and gross PP in estuaries and give improved estimates
of AIP, an essential measure of ecosystem health and productivity.
Keywords :
models , prediction , Time-series , Chesapeake Bay , primary productivity