Phytoplankton regulation in a eutrophic tidal river (San ... · The tidal San Joaquin River is located in the upper part of the estuary known as the Delta, a mosaic of water-ways

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Peer ReviewedTitle:Phytoplankton Regulation in a Eutrophic Tidal River (San Joaquin River, California)Journal Issue:San Francisco Estuary and Watershed Science, 3(1)Author:Jassby, Alan D., University of California, DavisPublication Date:2005Permalink:http://escholarship.org/uc/item/9jb2t96dKeywords:blooms, climate, dams, estuary, light, nutrients, phytoplankton, rivers, streamflow, turbidityLocal Identifier:jmie_sfews_10964Abstract:As in many U.S. estuaries, the tidal San Joaquin River exhibits elevated organic matter productionthat interferes with beneficial uses of the river, including fish spawning and migration. Highphytoplankton biomass in the tidal river is consequently a focus of management strategies. Anunusually long and comprehensive monitoring dataset enabled identification of the determinantsof phytoplankton biomass. Phytoplankton carrying capacity may be set by nitrogen or phosphorusduring extreme drought years but, in most years, growth rate is light-limited. The size of the annualphytoplankton bloom depends primarily on river discharge during late spring and early summer,which determines the cumulative light exposure in transit downstream. The biomass-dischargerelationship has shifted over the years, for reasons as yet unknown. Water diversions from thetidal San Joaquin River also affect residence time during passage downstream and may haveresulted in more than a doubling of peak concentration in some years. Dam construction andaccompanying changes in storage-and-release patterns from upstream reservoirs have caused along-term decrease in the frequency of large blooms since the early 1980s, but projected climatechange favors a future increase. Only large decreases in nonpoint nutrient sources will limitphytoplankton biomass reliably. Growth rate and concentration could increase if nonpoint sourcemanagement decreases mineral suspensoid load but does not decrease nutrient load sufficiently.Small changes in water storage and release patterns due to dam operation have a major influenceon peak phytoplankton biomass, and offer a near-term approach for management of nuisancealgal blooms.Copyright Information:

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SAN FRANCISCO ESTUARY & WATERSHED SCIENCE

ABSTRACTAs in many U.S. estuaries, the tidal San Joaquin Riverexhibits elevated organic matter production that inter-feres with beneficial uses of the river, including fishspawning and migration. High phytoplankton biomassin the tidal river is consequently a focus of manage-ment strategies. An unusually long and comprehen-sive monitoring dataset enabled identification of thedeterminants of phytoplankton biomass.Phytoplankton carrying capacity may be set by nitro-gen or phosphorus during extreme drought years but,in most years, growth rate is light-limited. The size ofthe annual phytoplankton bloom depends primarilyon river discharge during late spring and early sum-mer, which determines the cumulative light exposurein transit downstream. The biomass-discharge rela-tionship has shifted over the years, for reasons as yetunknown. Water diversions from the tidal SanJoaquin River also affect residence time during pas-sage downstream and may have resulted in more thana doubling of peak concentration in some years. Damconstruction and accompanying changes in storage-and-release patterns from upstream reservoirs havecaused a long-term decrease in the frequency of large

blooms since the early 1980s, but projected climatechange favors a future increase. Only large decreasesin nonpoint nutrient sources will limit phytoplanktonbiomass reliably. Growth rate and concentration couldincrease if nonpoint source management decreasesmineral suspensoid load but does not decrease nutri-ent load sufficiently. Small changes in water storageand release patterns due to dam operation have amajor influence on peak phytoplankton biomass, andoffer a near-term approach for management of nui-sance algal blooms.

KEYWORDSblooms, climate, dams, estuary, light, nutrients, phyto-plankton, rivers, streamflow, turbidity

SUGGESTED CITATIONJassby AD. 2005. Phytoplankton regulation in aeutrophic tidal river (San Joaquin River, California).San Francisco Estuary and Watershed Science. Vol. 3, Issue 1 (March 2005), Article 3. http://repositories.cdlib.org/jmie/sfews/vol3/iss1/art3

Phytoplankton Regulation in a Eutrophic Tidal River (San Joaquin River, California)Alan D. JassbyUniversity of California, [email protected]

Jassby: Phytoplankton Regulation in a Eutrophic Tidal River (San Joaquin River, California...

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INTRODUCTIONMost estuaries in the U.S. exhibit moderate to higheutrophic conditions and elevated macronutrient con-centrations (Bricker et al. 1999). Increased organicmatter production and depleted dissolved oxygen arecommon symptoms, resulting in habitat loss, fish kills,and sometimes offensive odors. The tidal San JoaquinRiver, one of two major rivers draining into the SanFrancisco Estuary, is representative of this general pat-tern. Phytoplankton chlorophyll a concentrationssometimes exceed 400 µg L-1 in summer and, down-stream, the river frequently exhibits low dissolvedoxygen conditions, annually violating regional waterquality objectives. This chronichypoxia interferes with several bene-ficial uses of the river, includingspawning and migration of warm(striped bass, sturgeon, and shad)and cold (Chinook salmon and steel-head) freshwater fishes, as well aswarm and cold freshwater specieshabitat (CVRWQCB 1998, 2003).Phytoplankton biomass transportedfrom upstream of low dissolved oxy-gen locations is considered to be amajor source of oxygen-demandingmaterials and has been the focus ofmanagement activities.

Most estuaries exhibiting eutrophicconditions are also moderately tohighly influenced by anthropogenicnutrient inputs (e.g., wastewatertreatment plant effluent and agricul-tural drainage), which have thereforebeen identified as the most impor-tant management targets on anational basis. It is natural toassume that such a course is alsowarranted for the San Joaquin Riverbecause of intense agriculture andanimal husbandry throughout itswatershed, resulting in nutrientinputs within and upstream of theestuary. However, many uncertain-ties surround the regulation of phy-toplankton biomass in tidal rivers,

and regional differences in nutrient sources and estu-arine functioning are significant. Cloern (2001) hasemphasized the spectrum of estuarine responses toincreased nutrient loading—from resistant to highlysensitive. He showed that a variety of attributes canact as a filter to modify effects of excessive nutrients,including strength of tidal mixing, magnitude of hori-zontal transport, water clarity, and abundance of ben-thic suspension-feeders. The early conceptual modellinking nutrient loading inexorably to biomass accu-mulation, derived largely from experience with lakes,is now understood to be inadequate for understandingestuarine systems, including their tidal river reaches.

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Figure 1. Map of the San Joaquin Basin and River, including a portion of the Delta(modified from Figure 1 of Kratzer et al. 2004, with permission).

San Francisco Estuary and Watershed Science, 3(1) (2005)

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What, then, controls phytoplankton biomass in thetidal San Joaquin River upstream of major diversionsand low dissolved oxygen conditions; how will reduc-tion in nutrient loading affect existing phytoplanktonlevels; and what other opportunities exist to managephytoplankton in this river reach? Strategies for phy-toplankton regulation in this subregion of the estuarymust also consider the negative consequences of lowphytoplankton biomass. The tidal river is one of thefew productive habitats for an estuarine food web thatotherwise appears to be relatively unproductive andfood-limited (Sobczak et al. 2002), and the small cen-tric diatoms that dominate the reach are a highlynutritious base for the food web supporting higherorganisms. The goal, then, should not be to aim forarbitrarily low levels, but rather to explore ways inwhich phytoplankton biomass can be regulated morefinely, if possible.

The large collection of retrospective data for the upperestuary is a useful resource for understanding phyto-plankton regulation in the San Joaquin River. Severalgovernment agencies have maintained monitoringprograms for decades, mostly for determining compli-ance with water quality objectives. This dataset—theresult of a sustained commitment to environmentalmonitoring by the California departments of WaterResources and Fish and Game and the U.S. Bureau ofReclamation—is exceptional in its spatial coverage, itsduration, and its multiplicity of measured variables. Ithas proven useful for analyses of long-term trendsand interannual variability in primary productivity,phytoplankton biomass, and phytoplankton communi-ty composition in various subregions of the Delta(Lehman 2000, Jassby et al. 2002). Particularly impor-tant for the San Francisco Estuary is a dataset thatencompasses drought and flood years. Interannualvariability in freshwater flow to this estuary is high,and the biota show one of the strongest and broadestresponses to flow among large estuaries (Kimmerer2002). Conclusions from a single year or a small sub-set of climatic conditions are likely to be misleading.Here, the Delta dataset is used to evaluate the regulat-ing factors for phytoplankton biomass in a turbid,nutrient-enriched tidal river and, more specifically, toimprove understanding of the lower San JoaquinRiver system.

Study areaThe tidal San Joaquin River is located in the upper partof the estuary known as the Delta, a mosaic of water-ways linking the Sacramento and San Joaquin rivers ofnorthern California to the downstream embaymentscomprising San Francisco Bay; together, the Delta andBay form the San Francisco Estuary. The San JoaquinRiver extends from the westernmost Delta upstreampast the city of Fresno, draining a watershed area ofabout 19,000 km2 (Kratzer et al. 2004; Figure 1). Itsriver valley is a major center of agricultural production.Despite the loss of most of its wetlands, it also remainsa critical habitat for fish and wildlife, including manyfederally-listed threatened and endangered plants andanimals (CVRWQCB 2003). Hydrology of the river andits major tributaries—the Merced, Tuolumne, andStanislaus rivers—upstream of the Delta is highly man-aged through dams, diversions, and artificial con-veyances. The river reaches the southern boundary ofthe Delta near the town of Vernalis, where estuarinetides begin to affect its flow (Figure 2). The long-term(1956-2002) mean flow at Vernalis is about 130 m3 s-1,with annual means ranging from 13 m3 s-1 in 1961 to650 m3 s-1 in 1983 (IEP 2003). Further downstream, aportion of the water is diverted down Old River to largepumping facilities feeding the State Water Project andfederal Central Valley Project, where it is exported foragricultural, industrial, and domestic use. Annually,temporary barriers have been placed at the head of OldRiver to increase flows down the mainstem, with theintention of alleviating low dissolved oxygen condi-tions downstream and facilitating Chinook salmonmigration (see Methods). Water is also diverted for irri-gation in the Delta by more than 2000 siphons; muchof this water is lost to evapotranspiration, althoughsome returns through many agricultural return flows.The river averages about 3 m in depth and 50 m inwidth between the Vernalis station and the StocktonDeep Water Ship Channel (Ship Channel), a portion ofthe river between San Francisco Bay and the city thathas been dredged to allow the passage of ocean-goingvessels to the Port of Stockton. Just upstream of theShip Channel, the Regional Wastewater Control Facility(RWCF) discharges its effluent into the river. The riverenters the Ship Channel at the eastern point of Roughand Ready Island. River width increases to about 75 m


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in the Ship Channel, and the Channel is dredged to adepth of about 11 m between the Port of Stockton andthe Bay. The tidal range is about 1.5 m in this region.Low dissolved oxygen conditions occur in the ShipChannel approximately from the Turning Basin at thePort of Stockton downstream to Turner Cut.

METHODS

Data sourcesA variety of data sources was used in this study. Of par-ticular note is the discrete water quality monitoring pro-gram originally started by the U.S. Bureau ofReclamation in the late 1960s. It is now carried out

jointly with the California Department of WaterResources, assisted by the California Department of Fishand Game and the U.S. Geological Survey, under theauspices of the Interagency Ecological Program'sEnvironmental Monitoring Program (EMP). Data arecollected from throughout the Delta on an approximatemonthly basis. The number of monitoring stations hasranged from a high of 26 to the current 11 stations. Theprogram's primary purpose is to provide information forcompliance with flow-related water quality standardsspecified in water rights permits that allow export bythe state and federal water projects. This data set,unusual in its spatial and temporal coverage, as well asthe variety of variables considered, is the main evidenceused in this analysis of water quality in the San JoaquinRiver upstream of the Ship Channel. The two stationsrelevant to this study are the Vernalis and Mossdale sta-tions (Figure 2) on the tidal river upstream of the ShipChannel. Samples are collected from about 1 m belowthe surface only, which necessitates the assumption thatthis shallow river reach is well-mixed vertically. Waterquality variables utilized here include chlorophyll a,phytoplankton taxa, total suspended solids and turbidi-ty, vertical light attenuation, total nitrogen and phos-phorus, silica, and temperature. A description of thesampling and analytical methods is available (IEP 2004).Triboli et al. (2004) examine in detail the methodologyfor chlorophyll, the most important measurement con-sidered in this study. The longest record for chlorophylla is at Vernalis, where it has been measured regularlysince 1969. The time series for Mossdale began in 1975and was stopped in 1995. Within each time series, thedata gaps are few.

Phytoplankton and optical parametersThe long-term dataset indexes phytoplankton biomass interms of chlorophyll a. Chlorophyll a must be convertedto organic carbon in order to estimate nutrient content ofphytoplankton cells. Cloern et al. (1995) developed anempirical expression for the chlorophyll a to carbon ratio(Chl:C) in terms of temperature, mean water column irra-diance, and nutrientconcentration:

(1)

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Figure 2. The San Joaquin River from Vernalis through theStockton Deep Water Ship Channel. The locations of the Vernalisand Mossdale long-term monitoring stations are indicated, aswell as the Regional Wastewater Control Facility effluent (RWCF)and tidal velocity station (UVM). Green line, tidal portion of theriver upstream of the Ship Channel.


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where T (°C) is water column temperature, Iav (mol m-

2 d-1) is daily photosynthetically active radiation (PAR)averaged over the mixed layer, N (mg L-1) representsthe concentration of the growth-limiting nutrient, andkn (mg L-1) the half-saturation constant that definessensitivity of growth to changes in nutrient concen-tration. The equation was based on 12 published stud-ies involving 219 different growth conditions forunialgal cultures, mostly of coastal and estuarinediatoms. As discussed below, nutrient limitation rarelyoccurs in the Delta and especially the San JoaquinRiver upstream of the Ship Channel. The assumptionthat N/(kn + N) = 1 is therefore made in this study.Assuming an exponential decline of PAR with depthand a well-mixed water column, average PAR can bedescribed by

(2)

where I0 (mol m-2 d-1) is PAR just below the watersurface, Kd (m-1) is the vertical attenuation coefficientfor downwelling PAR, and H (m) is average waterdepth. I0 values were based on daily irradiance forDavis, California, the nearest location for which acomplete irradiance record is available (CDWR 2004a).A factor of 0.18 was used to convert daily mean irra-diance (W m-2) to PAR quantum irradiance (mol quan-ta m-2 d-1), assuming PAR is 45% of total irradianceand a conversion of 2.77 x 1018 quanta s-1 W-1 forPAR (Morel and Smith 1974). Because Kd measure-ments are available for only a portion of the record(1975-1979 at Vernalis and 1975-1986 at Mossdale),Kd was estimated using combined data from Mossdaleand Vernalis (R2 = 0.65, n = 296, P < 0.001):

(3)

where M (mg L-1) refers to particulate matter as esti-mated by total suspended solids, and coefficient val-ues ± standard errors are shown explicitly. Thus, Kd isapproximately proportional to M0.5.

Instantaneous values of average water column PAR

also must be estimated in order to assess light limita-tion. Daylength Γ (h) was determined from latitude(Forsythe et al. 1995), and mean daily irradiance wasconverted to mean daylight irradiance based ondaylength. Maximum irradiance Imax (µmol m-2 s-1)was estimated based on the ratio of maximum tomean daylight, using a simple sinusoidal light curveto describe diurnal surface irradiance (Platt et al.1990). Average water column values were thenobtained from Equation 2.

The general procedure of Reynolds and Maberly(2002) was used to estimate the phytoplankton carry-ing capacity from macronutrient availability. Totalnitrogen (Ntot) and total phosphorus (Ptot) were usedto calculate carrying capacities for nitrogen and phos-phorus, in order to determine maximum values and toavoid the uncertainty in estimating the bioavailablefraction of nutrients. Carrying capacities are thereforeoverestimates. The theoretical stoichiometric yield ofphytoplankton cell carbon is C:N = 5.7 and C:P = 41(Stumm and Morgan 1981). The carrying capacity inchlorophyll a units for nitrogen is then simplyNtot(C:N)(Chl:C), and for phosphorus, Ptot(C:P)(Chl:C).This approach differs from Reynolds and Maberly's,however, in that the Chl:C ratio was not considered tobe constant. Rather, Equation 1 was used. Because theC:Si ratio for diatoms is highly variable among taxa, acarrying capacity for silicon was not estimated.

The derived equation of Reynolds (Reynolds andMaberly 2002) was used to estimate the supportivecapacity of light, Bmax (µg chlorophyll a L-1):

(4)

where Pr is the dimensionless ratio of maximum pho-tosynthetic rate to basal respiration rate at the sametemperature, Ik (µmol m-2 s-1) is PAR at the onset oflight saturation. κ [m2 (mg chlorophyll a)-1] is the ver-tical light attenuation due to chlorophyll a, and K (m-

1) is the non-phytoplankton-associated vertical lightattenuation. By definition, they are related to the ver-tical attenuation coefficient Kd as follows:


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(5)

The parameter values suggested by Reynolds andMaberly (2002) were also used: κ = 0.01, Pr = 15, andIk = 20. Γ and Imax were determined as above. K wasestimated from Equation 5. There is much uncertaintyin the parameter values chosen by Reynolds andMaberly (2002), and therefore corresponding uncer-tainty in the estimates of Bmax. Although there areother ways to arrive at maximum biomass estimates,they all suffer from similar uncertainties.

Growth rate estimates are required to understand thedemands on nutrient resources in transit to the ShipChannel. Daily gross primary production P (mg C m-2

d-1) is described well in the Delta by

(6)

where Ψ [mg C (mg chlorophyll a)-1 (mol m-2)-1] is thewater column light utilization efficiency and B (µg L-1)is chlorophyll a concentration. This relationship isbased on theoretical considerations for low light con-ditions and has been shown experimentally to apply toDelta primary productivity (Cole and Cloern 1987). Itfollows that growth rate r (d-1) can be expressed interms of P by

(7)

where respiratory losses are divided into a photosyn-thesis-dependent fractional loss ρ0 and a basal meta-bolic loss ρ1 (d-1). The term (Chl:C)/H simply convertsvolumetric chlorophyll a concentrations B into arealcarbon concentrations. The right-hand side has beenwritten to emphasize the physical interpretation:Ψ(Chl:C) is the efficiency with which light is manifest-ed as growth rate, and I0/KdH is the mean light in thewater column assuming, as in the San Joaquin River,that essentially all light is absorbed before the bottom.The efficiency Ψ is taken to be 0.73 (Jassby et al.2002). Values for the respiration parameters are basedon the study of Cloern et al. (1995), who summarizedempirically the results of many experiments in the lit-

erature in which both photosynthesis and growth rateswere measured: ρ0 = 0.15 and ρ1 = 0.015. The estima-tion of Chl:C is also based on the latter study, asdescribed above.

Hydrological estimatesValues of net discharge into the Ship Channel are alsonecessary to estimate phytoplankton demands on rivernutrients. The U.S. Geological Survey has operated anUltrasonic Velocity Meter (UVM) station in the SanJoaquin River just upstream of the Ship Channel sinceAugust 1995(http://sfbay.wr.usgs.gov/access/delta/tidalflow; Figure 2).A 15-minute interval UVM tidal flow record is com-puted and converted to discharge using water-surfaceelevation, channel geometry survey data, and AcousticDoppler Current Profiler measurements.

The best estimate of historical mean daily flows in theDelta is obtained with Dayflow, a computer programdeveloped in 1978 as an accounting tool for determininghistorical Delta boundary hydrology (IEP 2003). Inputdata include monitored and estimated values of the prin-cipal stream inflows, precipitation, exports from theDelta, and diversions and drainage within the Delta.Output data include discharge rates at important loca-tions throughout the Delta, based on input data andmass balance calculations. Dayflow output itself does notcontain estimates of discharge into the Ship Channel, butthe question naturally arises as to whether a surrogatenet flow series can be constructed by determining a rela-tionship between net discharge measurements andDayflow variables. The largest effects on tidally-averagednet flow should be the upstream flow in the San JoaquinRiver and the split in flow taking place at the head ofOld River. The latter is driven by exports from the Deltainto the federal Central Valley Project and State WaterProject. Estimates of San Joaquin River discharge atVernalis and of exports are available from Dayflow out-put (http://iep.water.ca.gov/dayflow).

Net flow is also affected by the presence of a tempo-rary rock barrier—the Head of Old River barrier—con-structed annually at the confluence of the Old and SanJoaquin rivers to protect migrating Chinook salmonfrom the federal and state pumping plants(http://sdelta.water.ca.gov/web_pg/tempmesr.html). The


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barrier has been in place most years since 1963 forsome portion of the period September 15-November30. It was also installed in 1992, 1994, 1996, 1997,2000, 2001, 2002, and 2003 for some portion of theperiod April 15-May 30. A monthly variable Bhor wasdefined equal to the actual proportion of the entiremonth during which the barrier was in place. Becauseinstallation and removal take more than one day, thebarrier was assumed to be in place from the installationcompletion date until the removal completion date.

Net flow was estimated by

(8)

where Qnet (m3 s-1) is monthly mean net flow into theShip Channel, Qvern (m3 s-1) is monthly mean flow atVernalis, and Qexp (m3 s-1) is monthly mean waterexport from the Delta. The effect of the barrier iscomplicated by the addition of culverts in recent yearsthat allow some flow through the barrier, and by tem-porary rock barriers installed further downstream onOld River to increase water levels in south Deltasloughs, primarily for agriculture diversions. Neithercomplication is reflected in Bhor.

Unimpaired discharge or full natural flow representsthe natural water production of a river basin, unal-tered by upstream diversions, storage, or by export orimport of water to or from other watersheds. We esti-mated monthly unimpaired runoff at Vernalis fromthe sum of estimates for the Stanislaus, Tuolumne,Merced, and San Joaquin rivers. These flows are basedon calculations done by project operators on therespective rivers, the U.S. Army Corps of Engineers,and/or California Cooperative Snow Surveys. The SanJoaquin Valley Water Year Hydrologic Classificationidentifies each water year (extending from October 1of the previous calendar year through September 30)as one of five types, depending on unimpaired dis-charge: critical, dry, below normal, above normal, andwet. Exact definitions and data for unimpaired dis-charges and water year type are available at theCalifornia Data Exchange Center (CDWR 2004b).

Data analysesUnless otherwise stated, replicate samples for all vari-ables have been averaged and data within the samemonth aggregated by their median, in order to avoidbias when comparing seasons with different amountsof raw data. When necessary, small gaps in monthlytime series were imputed using a time series modelingprocedure known as TRAMO (Time series Regressionwith ARIMA noise, Missing observations, and Outliers;Gómez and Maravall 2002), which retains the auto-correlation structure in the series. When assessingtrends by month in time series, a robust measure—sometimes known as the Theil trend—is used. This issimply the median slope of the lines joining all pairsof points in the series. The Kendall-tau test can beused to determine the significance of the trend (Helseland Hirsch 1992).

Principal component analysis (PCA) of monthly timeseries was used to investigate interannual variability(Jassby 1999). PCA in this context of time seriesanalysis reveals the number of independent underly-ing mechanisms, sometimes called modes of variabili-ty, that together combine to produce the overall inter-annual variability. Consider, for example, a hypotheti-cal case in which the year-to-year variability of riverphytoplankton is due to both discharge variabilityduring May-August and grazing variability in July-October. As long as the two mechanisms are not high-ly correlated among years, PCA will identify thatthere are two mechanisms; the importance of eachmechanism seasonally; and their strength from oneyear to the next. These features often provide strongconstraints on the underlying mechanisms while alsoproviding clues for their identity. The time series isfirst reshaped into a years × months data matrix.Principal components (PCs) were estimated by singu-lar value decomposition of the covariance matrix ofthe data matrix. The number of significant PCs wasdetermined using used a Monte Carlo procedureknown as Rule N (Overland and Preisendorfer 1982).

Restricted cubic splines were used as transforms forpredictors in regression relationships (Harrell 2001). Acubic spline is a piecewise polynomial of order threethat is smooth (specifically, it has continuous first andsecond derivatives) at the knots (i.e., points joining the


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different polynomial pieces). A restricted cubic spline ornatural spline is further constrained by being linearbeyond the outer knots. The use of splines in generaland restricted cubic splines in particular has manyadvantages over other methods in representing nonlin-ear functions in a regression model when the exactform of the nonlinearity is unknown. To minimize thenumber of parameter estimates, a restricted cubic splinewith only three knots was used, requiring only twoparameters. The knot positions—at the 0.1, 0.5, and 0.9quantiles—were chosen based on general recommenda-tions from simulation studies, and were not tailored inany way for the current data set. The spline functionscan therefore be described in general by

(9)

where b1 and b2 are constant coefficients, the ki arethe 0.1, 0.5, and 0.9 quantiles of x, and

(10)

Multivariate regression model results are illustrated aspartial residual plots, which attempt to show the rela-tionship between a given independent variable and theresponse variable, while accounting for the other inde-pendent variables in the model. Specifically, a partialresidual plot here refers to a plot of ri + bkxik versus xik,where ri is the ordinary residual for the i-th observation,xik is the i-th observation of the k-th predictor, and bk isthe regression coefficient for the k-th predictor.

RESULTS

Historical time seriesInterannual variability in chlorophyll a is strong(Figure 3A and B). Phytoplankton at both Vernalis andMossdale can reach very high concentrations. Monthlymedians reached 337 µg/L in August 1977 during theextreme dry El Niño-Southern Oscillation event (ENSO)of 1976-1977. The record individual measurement of499 µg/L was taken on 18 June 1992 during the lastyear of a six-year drought. At the other extreme, con-centrations remained below 10 µg/L the entire year

during the extreme wet event of 1983. A principalcomponent analysis of the Vernalis time series demon-strated that there was only one significant mode ofinterannual variability, accounting for 72% of theoverall variability (Figure 4A). This mode was centeredin June-August, the period when phytoplankton almostalways reaches its annual maximum (Figure 4B),although there is one case each of the annual chloro-phyll maximum occurring in May (1983), September(2000), and October (1991). Interannual variability isthus determined by the size of the annual chlorophylla peak, and the time series of maximum annualchlorophyll a concentrations contains almost as muchinformation as the time series of monthly values.Regulation of the annual chlorophyll a peaks is there-fore the relevant focus for understanding interannualvariability.

The seasonal pattern also reflects precipitation andrunoff, with lowest values of chlorophyll a typically inDecember-January during the wet season, and highestvalues typically in July-August during the dry season(Figure 3C). The maximum biomass at Mossdale wastypically higher than at Vernalis by a mean of 32 ±8% (standard error). Only 4 of 21 years showed adownstream decrease: 2 of these were the extreme dry

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years 1977 and 1992, and all 4 showed a decrease ofless than 5%. The phytoplankton is thus usually in its(longitudinal) increasing phase in this reach. The sum-mer biomass peaks at the Vernalis and Mossdale sta-tions were almost always dominated by small centricdiatoms characteristic of turbid, well-mixed rivers,most commonly of the genera Cyclotella andThalassiosira (20 of 27 years, 1975-2001). Leland et al.(2001) found similar dominants in their four-yearstudy of algal species composition in the San JoaquinRiver upstream of Vernalis, implying a continuity ofthe main populations along the mainstem.

Resource constraints on carrying capacity and growth ratesTo determine if resource availability controlled phyto-plankton biomass, the carrying capacity for eachmacronutrient and for incident light was estimated forthe time when annual peak chlorophyll a occurred.Data for Mossdale were used, because biomass usuallyincreases between Vernalis and Mossdale andapproaches carrying capacity more closely at the latterstation. Carrying capacities are surprisingly similar for

macronutrients and light (Figure 5). On average,observed peak chlorophyll a values reach only a smallpercentage of the carrying capacity, from 10% (light)to 13% (phosphorus). They are also less than 50% ofthe carrying capacity in almost all years for eachresource. In the extreme dry years such as 1976-77and 1991-92, however, they can be more than 50% ofcarrying capacity: The maximum percentages are 59%for light (1977), and 69% for nitrogen (1977) and 66%for phosphorus (1991). The latter two percentages showthat at least two-thirds of the total nitrogen or phos-phorus was actually available for phytoplanktongrowth in these years.

Phosphorus carrying capacity was lower than nitrogencarrying capacity in 15 of 20 years, and the relativesensitivity to phosphorus limitation appears to beincreasing. There is no overall upward or downwardtrend over the whole record for either total nitrogen orphosphorus (not shown). Indeed, although the trendsfor total nitrogen by month are mostly upward, andfor total phosphorus mostly downward, only in one

1 2 3 4 5 6 7 8 9 10 11 12

00004

00001

Principal component

ecnairaV

004

08)

%(ecnairav

evitalumu

C

A

J F M A M J J A S O N D

0.02.0

4.0tneiciffeoctnenop

moC

B

Month

Figure 4. Principal component analysis of the chlorophyll amonthly time series. (A) Variance (bars) and cumulative vari-ance (circles) corresponding to each principal component.Shading, statistically significant according to Rule N (P < 0.05).(B) Coefficients for the first principal component.

1975 1980 1985 1990 1995

0.04.0

8.0

ChlLight

A

1975 1980 1985 1990 1995

0.04.0

8.0

ChlNP

B

)L/gm(

yticapacgniyrra

C

Figure 5. Estimated carrying capacities of available resources atMossdale for phytoplankton, compared with actual chlorophyll avalues. (A) Light carrying capacity. (B) Nitrogen and phosphoruscarrying capacities.


9

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MARCH 2005

month each were the trends significant (P < 0.05):+0.050 mg L-1 yr-1 nitrogen in June, and -0.019 mg L-1 yr-1 phosphorus in September. In contrast, the totalnitrogen to phosphorus ratio exhibits a clear rise overtime, at least since the 1976-77 ENSO (Figure 6A),and the monthly trends are significant for most ofMarch-October, covering the main growth period forphytoplankton (Figure 6B). Values early in the recordare close to the Redfield ratio of 16, typical of phyto-plankton. In the last decade, however, this ratio hasbeen exceeded almost every month.

Resource constraints on growth rate, as opposed tocarrying capacity, were also investigated. Nutrientlimitation of phytoplankton growth typically becomessignificant only when dissolved nutrient concentra-tions fall below about 0.07 mg L-1 nitrogen and 0.03 mg L-1 phosphorus; these values are at least five

times typical half-saturation constants for uptake(Fisher et al. 1995). Nutrient concentrations wereexamined for those months in which the peak annualbiomass occurred. At Vernalis, the minimum nutrientconcentrations at those times were 0.30 mg L-1 dis-solved inorganic nitrogen and 0.040 mg L-1 solublereactive phosphorus, i.e., above the threshold fornutrient limitation of growth rate. Median values were1.67 and 0.090 mg L-1, respectively. At Mossdale, themedians were similar—1.42 and 0.085 mg L-1, respec-tively—but soluble reactive phosphorus decreased to0.010 mg L-1 in the dry years of 1976, 1977, and

1991, and dissolved inorganic nitrogen was as low as0.110 mg L-1 in both 1991 and 1992. It is thereforepossible that nutrient limitation occurs at Mossdale inextreme dry years. But this must be more the excep-tion than the rule because nutrient levels are usuallymuch higher than the thresholds for limitation even atMossdale. Moreover, soluble reactive phosphorus mayunderestimate available phosphorus because of uncer-tainty about intracellular storage and other dissolvedfractions (Bradford and Peters 1987).

Although carrying capacities for silicon cannot beestimated with any certainty, the dissolved concentra-tions are informative. The median value for silicon atMossdale during 1975-1995 was 15 mg L-1 and theabsolute minimum (1977) was 1.2 mg L-1 silica. Inlakes, silicon limitation does not occur until silicaconcentrations drop well below 1 mg L-1 (Lund 1964).In marine diatoms, Azam and Chisolm (1976) foundhalf-saturation constants of 0.15 mg L-1 silica or lessfor silicic acid uptake. Kilham and Kilham (1975)argued on the basis of distributional data thatAulacoseira granulata grows best where silicon is notlimiting, and this species is often abundant in the SanJoaquin River. Silicon limitation of growth rate is thusunlikely. Even if diatom biomass at Mossdale didbecome limited by silicon availability in extremedroughts, non-diatoms would then simply have theadvantage and in principle would play the dominantrole at those times. Nitrogen and phosphorus aretherefore the focus in what follows.

Light conditions in the water column were examinedat the time of peak biomass each year. Average watercolumn irradiance at the time of maximum daily irra-diance ranged from 53 to 195 µmol m-2 s-1 over theyears, with a median of 91. In comparison, character-istic values for the irradiance level promoting maxi-mum primary productivity are usually in the range200-800 µmol m-2 s-1, even taking into account pho-toadaptation (Padisák 2004). Phytoplankton growthrate in the San Joaquin River is therefore probablylight-limited at the time of the annual phytoplanktonpeak. Growth rates at Mossdale during times of peakphytoplankton biomass were estimated using Equation 7.Growth rates are mostly in the range 0.3-0.6 d-1

(Figure 7). As pointed out above, nutrient limitationmay have been present at Mossdale in 1976-77 and

Tota

l N:P

(mol

ar ra

tio)

01020304050

1975 1980 1985 1990 1995 2000

A

J F M A M J J A S O N D

0.0

0.2

0.4

0.6 B

Tot

alN

:Ptr

end

(yr-1

)

Figure 6. (A) Molar ratio of total nitrogen to phosphorus atVernalis. Dashed line, ratio = 16, characteristic of phytoplankton.(B) Long-term (Theil) trends by month for the molar ratio of totalnitrogen to phosphorus at Vernalis, 1975-2002. Shading, signifi-cantly different from zero (P < 0.05), according to the Kendall-tautest.


10

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1991-92, in which case N/(kn + N) < 1 in Equation 1and growth rates would have been lower.

Note that light attenuation is usually due mostly tomineral suspensoids, as opposed to phytoplankton.Phytoplankton contributes little, on average, to totalsuspended matter at Mossdale, even at peak annualbiomass. For example, assuming a Chl:C ratio givenby Equation 1 and a carbon to dry weight ratio of 0.3for diatoms (based on data from Lund 1964), themedian contribution during the annual peak was 12%(1975-1995). Contributions during extreme dry yearscan be much higher, though, as high as 45% in 1977.Using a typical value of 0.01 m2 (mg chlorophyll a)-1for PAR attenuation, the chlorophyll a contribution toobserved Kd at Mossdale was a median of only 14%but reached as high as 82% in 1977 (1975-1985). Thevery dry years thus favor high chlorophyll a concen-tration even more than high total suspended solids.

Phytoplankton biomass and river dischargeSan Joaquin River discharge appears to be a dominantcontrolling factor for chlorophyll a concentrations atVernalis and Mossdale. This can be appreciated bycomparing monthly chlorophyll a concentrations withdischarge rates (Figure 3). Peak annual values ofchlorophyll a appear to be determined by dischargerates during early summer. For example, the twopeaks over 300 µg/L in 1977 and 1992 correspond tothe two lowest discharge values. In the early years ofthe 1987-1992 drought, summer discharge remained

relatively high and peak chlorophyll a values corre-spondingly low. As summer discharge declinedthroughout the drought, summer chlorophyll aincreased. In fact, the disappearance of high chloro-phyll a values after 1977 until the early 1990s can beunderstood based on early summer discharge ratesalone. Figure 8 illustrates the relationship betweenannual maximum chlorophyll a at Vernalis and dis-charge during the same month. Peak chlorophyll aincreases dramatically as concurrent dischargedecreases. There is some indication of a rapid risebelow about 50 m3 s-1, and a (weak) suggestion ofsaturation at the highest chlorophyll a level in 1977.

The frequency of large blooms appears to have declinedsince the late 1970s (Figure 3A). The dependence ofbloom size on discharge (Figure 8) naturally leads tothe question: Has early-summer discharge changed insome systematic way since the 1970s? Flow in the tidalSan Joaquin River is highly managed, responding to

storage-and-release patterns from upstream reservoirson the mainstem and three tributaries: the Merced,Tuolumne, and Stanislaus rivers. Construction of FriantDam on the mainstem was completed in 1942. The sea-sonal flow pattern at Vernalis has since changedmarkedly, typically with lower flows during March-Julyand higher during September-December (Figure 9A).Combined with high agricultural nutrient sources, lowerflows during March-July made possible the large phy-toplankton blooms observable in the historical record

Gro

wth

rate

(d-1

)

1975 1980 1985 1990 1995

0.3

0.4

0.5

0.6

Figure 7. Estimated phytoplankton community growth rates atMossdale during the time of annual peak biomass, based onequations 1 and 7.

Discharge (m /s)

Annu

al b

loom

siz

e(µ

g/L

chl

orop

hyll

a)

5 10 50 1003

500 1000

050

150

250

1969-19771978-2002

Figure 8. Annual peaks of median monthly chlorophyll a atVernalis versus mean river discharge during the same month inwhich the peak occurred, 1969-2002. Filled circles, observationsbefore 1978.


11

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MARCH 2005

(Figure 3A). The last of the large reservoirs, the NewMelones on the Stanislaus, was constructed in 1979(Figure 1), although full dam operations did not beginuntil 1982 because of public opposition. One of thedam's functions is to decrease Delta salinity intrusionsduring summer by providing auxiliary flow to the SanJoaquin River. The Stanislaus has contributed a medianof about 35% of the San Joaquin discharge in Julysince dam construction, compared to 21% before. About7.1% of the total annual Stanislaus discharge nowoccurs in July, compared to only 2.7% before the damwas built. The result of changed storage-and-releasepatterns from the New Melones and other reservoirssince the early 1980s has been almost a doubling ofmedian July flow at Vernalis, and in some years Julyflow has exceeded the unimpaired level (Figure 9B).During 1982-2002, July flow exceeded the 50 m3 s-1

threshold 11 times, whereas during the prior 21 years, it

exceeded the threshold only 6 times (Figure 10). Evenduring dry and critically dry years, flow now approach-es the threshold. This alone is sufficient to explain thelong-term change in bloom magnitude.

There is much variability in the relationship betweenbloom size and flow at intermediate discharge values.Much of this variability appears to be due to a changein the relationship over the years, with earlier chloro-phyll a observations tending to be higher for a givendischarge level. The different behavior in early com-

pared to later years was explored by modeling chloro-phyll a as a function of discharge and time. Based onFigure 8, a power relationship between chlorophyll aand discharge was assumed, with the addition of atime trend. In order to allow the data themselves todetermine the form of the trend, the trend was mod-eled as a restricted cubic spline transform of time.Only three knots were used for the spline, requiringonly two additional coefficients to be estimated:

(11)

where B is chlorophyll a, Qvern is discharge at Vernalis,Y is the year, f is the spline-estimated transform ofyear, a1 and a2 are constant coefficients; and εt is anindependent normal process. The spline function isgiven by Equation 9.

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Flow

(act

ual:u

nim

paire

d)

0.1

1.0

10.0 A

0.0

0.4

0.8

1.2

1.6

2.0

1960 1970 1980 1990 2000

B

Jassby Phyto Figure 9 2004-1

Figure 9. Ratio of actual to unimpaired flow at Vernalis. (A)Monthly boxplots of the ratio for 1956-2003 (whiskers extend to fullrange of data). (B) Time series of the ratio for July. Horizontallines, median values for 1956-1981 and 1982-2003, respectively.

)s/(m

3egrahcsi

D

1960 1970 1980 1990 2000

002

0406

08001

W

BN

DC

C

BN

AN

D

W

BN D

AN

BN

D

AN

WW

C

C

W

AN

W

D

AN

D

W

C

C C

C

CC

W

C

W

W

ANAN

DD

Figure 10. San Joaquin River discharge near Vernalis during July,including the water year type for each year. C, critical (criticallydry). D, dry. BN, below normal. AN, above normal. W, wet.Horizontal solid lines, range in which bloom size is sensitive todischarge (10-50 m3 s-1).


12

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Parameters of Equation 11 were determined usingordinary least-squares regression. The residuals arefree of serial correlation and approximately normal.All variables are important according to the partial F tests, including the nonlinearity in the trend (Table 1), and the adjusted R2 = 0.83.

Table 1. Partial F tests for the Vernalis chlorophyll a model ofEquation 11.

Partial MeanFactor d.f. Sum Sq. Sq. F-statistic Probability

Discharge 1 15 15 110 <0.001Trend 2 2.4 1.2 9.0 <0.001Trend nonlinearity 1 1.5 1.5 12 0.002Regression 3 22 7.2 55 <0.001Error 30 3.9 0.13

The results indicate an approximate power relationbetween chlorophyll a and river discharge (B ∝ Q-0.76),with the effect of a given discharge value less in laterversus early years (Figure 11). Although there is somehint of an upturn in recent years, the standard errorsindicate that it lacks statistical significance. The trendis constrained to be smooth because the data allowonly one interior knot, but the partial residuals for thetrend suggest that an abrupt drop may have occurredaround the 1976-77 ENSO.

Discharge affects phytoplankton biomass not onlythrough transit time but also through growth rate,because of changes in light attenuation due to dischargeimpacts on suspended matter. The relationship betweensuspended matter and discharge depends on the season.Suspended matter decreases with flow for any givenmonth from late winter to early fall, but not during theremaining months (Figure 12). April and Decembershow strongly opposite relationships with discharge.Although the correlation with discharge is significantfor March-July and December, most of the variabilityappears to be due to other factors. The variabilityexplained by discharge in July, for example, is only R2

= 0.29. The dependence of suspended matter on dis-charge is also much weaker than the inverse depend-ence of transit time on discharge: The exponent of thepower relationship in July is only -0.23.

Net river discharge and export effectsMossdale is 26 km from the entrance to the ShipChannel, so there is further opportunity for phyto-plankton growth between Mossdale and the ShipChannel. Water exports via Old River, however,decrease river discharge and increase travel time fromMossdale to the Ship Channel. It is interesting to con-sider the impact of flows down Old River on traveltime and subsequent phytoplankton growth betweenMossdale and the Ship Channel.

Net discharge Qnet into the Ship Channel was estimat-ed using Equation 8. This model describes the overalldata well, and is also well-behaved statistically (Figure 13, Table 2). The adjusted R2 = 0.93, and theresiduals are not serially correlated. The modeldescribes the low-flow data less well than the entiredataset. The model was refit using only data for

0 200 400 600 800Qvern (m3/s )

-2-1

01

2

ln(Q

vern

)pa

rtia

lres

idua

l A

1970 1980 1990 2000

-0.5

0.0

0.5

1.0

f(Y

)pa

rtia

l res

idua

l

B

Figure 11. Partial residual plots for the Vernalis peak chlorophyll amodel (Equation 11). (A) Partial residuals for discharge. (B) Partialresiduals for the time trend. Solid lines, partial fit. Dashed lines,standard errors. Circles, partial residuals.


13

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MARCH 2005

Qnet <85 m3 s-1. The overall fit was, of course, poorer,but the fit for low-flow data also did not improve. Thelack of fit for low values probably represents physicalprocesses missing from the model and cannot be cor-rected solely through statistical means. The overesti-mation of low flows by the model could possibly beremedied by the inclusion of a term representing cul-verts through the Head of Old River barrier. Diversion

of water for irrigation downstream of the OldRiver branch may also play a role. In anycase, the model was considered adequate forthe application at hand. As net dischargeshould be less than or equal to discharge atVernalis, the smaller of Qnet and Qvern wasused to represent net discharge.

Travel times between Mossdale and the ShipChannel were estimated from net dischargeusing a relationship developed by Jones &Stokes (2002) for this reach of the river.Travel time estimates assume zero tidal dis-persion but, in reality, transit times will besomewhat shorter or longer in the tidal river.At the time of peak phytoplankton biomass,travel times averaged 2.1 ± 0.4 days during1975-1995, ranging from 0.099 in 1983 to8.4 days in 1977. If the barrier at the head ofOld River had been in place and completelyeffective during this time, travel times wouldhave averaged 1.4 ± 0.4 days.

Table 2. Coefficient values for the model of Equation 8 describ-ing average monthly net discharge into the Ship Channel (n = 71).

Variable Coefficient Std. Error t-Statistic Prob.

Intercept 20 5 4.2 <0.001

Qvern 0.40 0.01 30 <0.001

Qexp(1-Bhor) -0.081 0.019 -4.3 <0.001

Some idea of the potential effects on phytoplanktonbiomass can be obtained by combining transit timeswith the growth rates estimated for Mossdale, althoughthe latter could change on the way downstream andnutrient or light resources could become limitingbefore phytoplankton reached the Ship Channel. Notealso that water within a few kilometers upstream ofthe Ship Channel is subject to mixing with ShipChannel water because of tidal dispersion, so that con-centrations in this region do not reflect the true netincrease in biomass of a population starting out atMossdale. In any case, calculations imply that watermovement down Old River could have increased peakbiomass during 1975-1995 at the Ship Channel by a

10

100

Jan

100 1000 10000

Feb Mar

100 1000 10000

Apr

May Jun Jul

10

100

Aug

10

100

100 1000 10000

Sep Oct

100 1000 10000

Nov Dec

Discharge (m3/s)

)L/gm(

SS

T

Figure 12. Total suspended solids versus discharge by month at Vernalis, 1969-2002. Straight lines, power relation between suspended matter and discharge.

-100

-50

0

50

0

100

200

300

400

1996 1997 1998 1999 2000 2001 2002

ResidualActualFitted

)s/(m

3egrahcsidte

N

Figure 13. Fitted values and actual observations of net dischargeinto the Ship Channel. Fitted values are based on the modeldescribed by Equation 8. Horizontal dashed lines, standard errorof residuals.


14

DWR-714


mean of 38 ± 10%. In three of the driest years—1977,1991, and 1992—exports were negligible. In otheryears, however, diversions down Old River could havecaused a notable increase in phytoplankton biomassdownstream. In 1989, for example, potential down-stream concentrations at the time of the peak wouldhave been only 73 µg L-1, instead of 177 µg L-1

(potential concentrations assume no dilution of thebiomass with Ship Channel water).

DISCUSSION

Nutrient management and phytoplanktonThe concentrations of dissolved inorganic nitrogen,soluble reactive phosphorus, and dissolved silica indi-cate that macronutrient limitation is unlikely atVernalis or Mossdale, except perhaps during extremedrought years (such as 1976-77 and 1991-92). Apartfrom these extreme years, though, nutrient concentra-tions do not appear to restrict either phytoplanktongrowth rate or biomass. There is much uncertainty inthe estimates made here. For example, chlorophyll aconcentrations can exhibit more than a two-fold dielvariation in the Delta (Schraga et al. 2003). In addi-tion, total elemental concentrations overestimate car-rying capacity. Yet Figure 5 illustrates a sufficientlylarge difference between estimated biomass and carry-ing capacities that macronutrient limitation is proba-bly rare, despite the uncertainty. Whether the situationchanges in transit to the Ship Channel, i.e., whetherphytoplankton achieve carrying capacity in more thanjust extreme dry years, remains in question because ofprobable changes in growth rate, losses to primaryconsumers, and downstream losses or gains in totalelemental concentrations. There are insufficient long-term data between Mossdale and the Ship Channel toaddress the question. Moreover, water just a few kilo-meters upstream of the Ship Channel is subject todilution because of tidal dispersion. For measurementsmade in the vicinity of the Channel, the effects ofphytoplankton growth in transit downstream couldtherefore easily be swamped by dilution with muchlower phytoplankton biomass from the Channel.

Which of nitrogen or phosphorus would require thesmaller percentage reduction to achieve nutrient limi-

tation, i.e., which nutrient is more liable to be limitingin the San Joaquin River? The N:P molar ratio forphytoplankton averages 16, but Downing andMcCauley (1992) found that nitrogen rather thanphosphorus limitation (albeit in lakes) was more fre-quent until total N:P exceeded 31. The ratio atVernalis is typically below this threshold (median 18)and sometimes even below 16. Dissolved inorganicN:P values are substantially higher (median 27), but itis difficult to interpret this ratio in the San JoaquinRiver: The true availability of phosphorus, for exam-ple, can be underestimated because of internal cellularstorage. The ratios are therefore in a band whereinterpretation is uncertain and we cannot concludedefinitely that the river is more prone to either nitro-gen or phosphorus limitation. It is not uncommon forestuarine phytoplankton communities to be prone tocolimitation by nitrogen and phosphorus (Conley2000), and the same tendency may characterize thistidal reach of the San Joaquin River. In any case, thelong-term trend for both total N:P (Figure 6) andinorganic N:P values since 1980 has been in thedirection of higher ratios and more susceptibility tophosphorus limitation.

Kratzer and Shelton (1998), in their study of 1972-1990 water quality, noted a long-term increase innitrate concentration in the San Joaquin River, whichthey attributed to native soil nitrogen from expandingsubsurface agricultural drainage. Other changes possi-bly affecting the nitrogen and phosphorus balanceover time included an increase in aeration of munici-pal wastewater ponds and land application of domes-tic wastewater. More recently, Kratzer et al. (2004)observed that all but a few δ15N and δ18O values ofnitrate measured in the San Joaquin River fell withinthe range of animal waste and sewage. They conclud-ed that animal waste or sewage now represented asignificant source of nitrate in the San Joaquin Riverat the time of their sampling. During the summer andearly autumn when their study took place, highertemperatures and longer travel times from sourcesfavor conversion of dissolved organic nitrogen andammonium to nitrate. Consistent with these observa-tions, Kratzer and Shelton (1998) reported that about53% of total nitrogen sources in the drainage basinfor the San Joaquin River near Vernalis were of ani-


15

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MARCH 2005

mal origin. The nitrate increase could therefore bedue, at least in part, to an increase in animal wasteand sewage sources.

How much reduction in nitrogen or phosphorus isrequired to limit phytoplankton bloom size to accept-able levels? It is difficult to provide a general answerto this question, because nutrient and suspended sedi-ment loading is year-dependent, and peak biomassdepends on water year type and seasonal patterns ofstorage and release from upstream impoundments.Downstream of Old River, it also depends on waterexports. The monitoring data, however, can providean answer from a historical perspective. Consider, fordiscussion purposes, the OECD (1982) boundarybetween mesotrophy and eutrophy of 25 µg L-1 maxi-mum annual chlorophyll a as an acceptable level.Reductions of this amount probably would not affectthe algal food supply to planktonic food webs, whichmay be saturated at a level of about 10 µg L-1 chloro-phyll a in the Delta (Müller-Solger et al. 2002). Recallalso that as much as two-thirds of total nitrogen orphosphorus can be available for growth, based on thehigh chlorophyll a concentrations attained in dryyears. Depending on the year, the 25 µg L-1 goalwould have required reductions at Mossdale of 61 to95% for nitrogen or 72 to 95% for phosphorus, underthe assumption that two-thirds of the nitrogen andphosphorus were available for growth. These are verychallenging goals to achieve. Moreover, under thesame assumptions, an average nutrient reduction ofmore than 50% would be required to have any effecton the annual bloom size. Therefore, although it ispossible that even moderate nutrient control wouldhave some beneficial effect in the driest years, levelsof nutrient reduction attainable in the short term willprobably leave peak phytoplankton biomassunchanged in many years.

Light-attenuating materials

Historical year-to-year changes in mineral suspensoidconcentrations in the San Joaquin River, unlikemacronutrient changes, probably had importanteffects on phytoplankton growth and biomass.Average light levels experienced by phytoplankton arerelatively low and neither photosynthesis nor growthrate are proceeding at maximum attainable levels.

Total suspended solids concentrations in July haveranged from 38 mg L-1 in 1998 to 226 mg L-1 in1976. Even considering that Kd ∝ M0.5, this representsabout a 2.4-fold change in growth rate, according toEquation 7. Although this includes year-to-year vari-ability in the phytoplankton as well as the mineralsuspensoid portion, the latter must still be consider-able given that the phytoplankton accounts for aminority of suspended matter during the annual peak.The implication is that watershed or river manage-ment actions must reflect an understanding of theconsequences for mineral suspensoids in the river. Forexample, dam removal may decrease transparency andreduce growth rate by eliminating the trapping of sus-pended matter that occurs in reservoirs. Conversely,erosion control measures for fine-grained soils in theCoast Range on the west side of the Valley or for agri-cultural lands on the east side may increase trans-parency. Growth rate and even biomass could increaseif nonpoint source pollution management decreasesmineral suspensoid load but does not decrease nutri-ent load sufficiently. The effects can be very large:Reservoirs in Germany and Austria decreased sus-pended matter and improved water clarity in theDanube River during the 1970s, resulting in a ten-foldincrease in phytoplankton with no change in nutrientsupply (Kiss 1994). Transparency responses thereforeshould be an explicit component of models intendedfor assessing different strategies to manage loads tothe Ship Channel.

Effects of river discharge on biomass

River discharge during June-August has the strongestidentifiable effect on peak phytoplankton biomass atVernalis. Although phytoplankton may reach the car-rying capacity set by macronutrients during extremedrought years, phytoplankton is usually well belowthis level. Growth rate is light-limited due to high lev-els of mineral suspensoids, compounded by highnutrient levels that have permitted phytoplankton toreach values near the top of the range found in rivers.Maximum phytoplankton biomass in most yearstherefore depends primarily on river discharge, whichdetermines the cumulative light exposure in passageto Vernalis. Based on historical evidence, maintainingriver discharge above 50 m3 s-1 during late spring andearly summer could eliminate nuisance algal blooms


16

DWR-714


at Vernalis. Downstream of Mossdale, however, exportflows down Old River can further reduce mainstemriver discharge, and further increase the cumulativelight exposure in passage to the Ship Channel. Theseexport flows may result in more than a doubling ofpeak biomass at the entrance to the Ship Channel inspecific years.

Because of impoundment patterns of water storage andrelease, the seasonal hydrograph has shifted to lowerdischarge in late spring and early summer relative topre-impoundment conditions (Knowles 2002; Figure 9A),allowing development of the massive blooms observ-able since routine monitoring began in the 1960s.During the early years of the 1986-1992 drought, peakbiomass remained relatively low, despite the overalldry conditions. This change from earlier drought yearssuch as 1976-77 appears to be due simply to the factthat discharge remained elevated and residence timesaccordingly low during early summer. The change inmedian July discharge during critical and dry yearssince the early 1980s falls mostly within 10-50 m3 s-1,the most sensitive portion of the biomass-dischargerelationship (Figure 8 and Figure 10). This increase canbe attributed to the changed pattern of storage-and-release from major upstream reservoirs, including thenewest one created by the New Melones Dam on theStanislaus River.

Climate change may mean future long-term shifts inbloom size as well. Knowles and Cayan (2002) usedprojected temperature anomalies from a global climatemodel to drive a model of watershed hydrology for theSan Francisco Estuary. They estimated that, by 2090,spring runoff could be reduced by 20% compared tohistorical annual runoff, with associated increases inwinter flood peaks. According to Figure 8, largeincreases in bloom size would be expected for flowdecreases within the range of 10-50 m3 s-1.

Discharge controls cumulative light exposure, not onlythrough residence time, but also through mean lightavailability in the water column. Light availability inthe water column depends on optical depth, a dimen-sionless term equal to KdH in the case of an opticallyhomogeneous water column (Equation 2). Dischargeaffects optical depth through both Kd and H. In partic-ular, higher discharge causes both a decrease in Kd and

an increase in H. The effect on Kd appears to be a neg-ligible one compared to the effect on residence time.As pointed out in the Results, total suspended solids Mis approximately proportional to Q-0.2 during June-August (Figure 12). Because Kd is approximately pro-portional to M0.5 (Equation 3), a doubling of dischargethus leads to an increase of only about 7% in growthrate, according to Equation 7. Consider a biomass of100 µg L-1 chlorophyll a, a growth rate of 0.4 d-1, anda transit time of 2 days to some second locationdownstream. The net affect of doubling discharge is todecrease biomass at the downstream location from 196to 143 µg L-1. Without any effect on growth rate, finalbiomass would have been 140 µg L-1, a negligible dif-ference, and so effects of discharge on water trans-parency can probably be ignored.

The same cannot be said of water depth, however,because the relationship between discharge and meanwater depth over this reach of the river is unknown.The necessary data are available only for Vernalis anddo not apply for the reach as a whole. As a result, ithas been necessary to conduct the analyses under theassumption of a constant depth, a source of bias anduncertainty in many of the quantitative results pre-sented in this analysis. The increase in H with dis-charge offsets to some extent the decrease in Kd, buteven the sign of the net effect of discharge on opticaldepth is not known for sure.

Long-term shift in biomass-discharge relationship

Although most of the interannual variability in bio-mass is directly attributable to differences in earlysummer discharge, a long-term shift in the relationshipbetween biomass and discharge can also be observed(Figure 11B). The shift accounts for relatively little ofthe overall year-to-year variability but is statisticallysignificant (Table 1), as well as ecologically significantfor intermediate discharges of 30-50 m3 s-1 (Figure 8).What is the mechanism behind this shift? It is possiblethat operation of the New Melones Dam has an effecton bloom size apart from the impact of concurrent dis-charge. This is especially true if lagged dischargeeffects are also important, because winter and springdischarge was generally much higher prior to 1980.Abundances of planktonic grazers with generation


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times longer than planktonic algae are likely to bedependent on these earlier discharges. Pace et al.(1992), for example, found that advective transportregulates zooplankton biomass in the Hudson Riverand in other tidal rivers, estuaries, and lakes where theappropriate data could be found. Gosselain et al.(1998), however, maintain that planktonic grazingpressure on phytoplankton is unlikely to be importantduring low river residence times, such as in spring. Inany case, no convincing statistical evidence for laggedeffects could be found, and zooplankton data are notroutinely collected in this reach.

A climate regime shift in the eastern Pacific and con-tiguous Americas occurred around 1976 (Trenburthand Hurrell 1994), coincident with major step-likechanges in chlorophyll, salmon, crabs, and many otherenvironmental variables (Ebbesmeyer et al. 1991). Themain effect of climate change on the San JoaquinRiver, however, is a change in the discharge hydro-graph, which should already be accounted for by thedischarge term in Equation 11. As we have seen, thedisappearance of large blooms in dry years after 1976-77 appears to have nothing to do with a climateregime shift, but rather with changes in water manage-ment. Nonetheless, this part of the estuary is relativelypoorly studied in terms of metazoa, and it is possiblethat the 1976-77 ENSO event itself had unobservedimpacts on primary consumers, especially benthicmacroinvertebrates. River depths of several meters inthis reach are compatible with intense benthic-pelagiccoupling and major impacts of benthic suspensionfeeders on planktonic communities. Given the continu-ity of the Vernalis with the upstream phytoplankton,based on taxonomic composition and chlorophyll aconcentrations, the impact could have been on theupstream community. Elsewhere in the estuary, persist-ent (multi-year) low flows have allowed upstream col-onization by marine benthic macroinvertebrates, suchas Mya arenaria during the 1976-77 drought (Nichols1985). The drought beginning in 1986 allowed inva-sion of Suisun Bay by an Asian corbulid clam, result-ing in persistently lower phytoplankton and primaryproduction in Suisun Bay and the western Delta(Alpine and Cloern 1992, Jassby et al. 2002). Relevantlong-term data, however, are not available for thisreach of the San Joaquin River, and the few recent

surveys suggest that freshwater clams such asCorbicula fluminea are currently not abundant enoughto control phytoplankton biomass here (J. Thompson,USGS, pers. comm.).

Concluding remarksThe observations and analyses in this study lead to aspecific conception of bloom control in this criticalreach of the tidal San Joaquin River, summarized bythe cause-and-effect diagram of Figure 14. It is a min-imal conception in the sense that there were insuffi-cient data to include primary consumer effects in ourstudy, and these may play a big role. Nor werechanges in phytoplankton species community compo-sition considered, which may determine, among otherthings, the magnitude of light-limited growth rates.Climate, water management, and watershed materialinputs are the ultimate causes in the conception illus-trated here. The amount of water available in springand early summer depends on winter precipitation, butthe temporal pattern depends on dam operations,

biomass

opticaldepth

macronutrients

+ +

-

± -

+ +

-

+

- ±

watershedinput

++

+

-

+

wateramount

waterseasonality

watershedinput

climateexportsreservoirs

early summerdischarge

carryingcapacity

residence time

growth rate

Figure 14. Cause-and-effect diagram summarizing the linkagesdescribed in this study for regulation of peak annual phyto-plankton biomass.


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which are operated in a manner that suppresses histor-ical seasonality and enhances early summer flows rela-tive to spring flows. Combined, these two factorsdetermine the actual magnitude of early summer dis-charge. Discharge then affects another hydrologicalproperty, average residence time in any given reach ofthe river; average residence time downstream is furtheraffected by water exports down Old River. Dischargealso affects two water quality properties, optical depthand the concentrations of macronutrients. Both arealso affected by variable watershed inputs, and opticaldepth in addition can be affected by feedback fromphytoplankton biomass in dry years when biomass isvery high. Optical depth in turn affects growth rate,which is usually light- but not nutrient-limited.Macronutrients determine the carrying capacity ormaximum possible phytoplankton biomass, which maybe attained during extremely dry years. For mostyears, however, bloom size is set by residence time andspecific growth rate. Reductions of macronutrientinputs from the watershed would increase the percent-age of years in which blooms are limited by carryingcapacity, but order-of-magnitude reductions arerequired and these would probably not be obtainablein the near-term for social as well as logistical reasons.Moreover, strategies for macronutrient reduction fromthe watershed must consider accompanying impacts onoptical depth via reduced suspended matter inputsfrom the watershed, which could result in highergrowth rates and larger blooms during years when car-rying capacity is not reached. In contrast, the sensitivi-ty of bloom size at Vernalis to early summer discharge,and the effect of water exports on phytoplankton bio-mass as it moves downstream, offer effective, near-term management tools. In both cases, modification ofthe seasonal pattern rather than changes in the overallannual amount may be sufficient to control largeblooms.

ACKNOWLEDGMENTSI gratefully acknowledge support for this research fromthe California Bay-Delta Authority (4600001642 andERP-02-P33). I also thank Randy Brown, Lisa Lucas,and Erwin Van Nieuwenhuyse for many helpful com-ments on the manuscript; Cathy Ruhl and Peter Smithfor providing essential information on river flows; andCharles Kratzer for permission to use and modify theSan Joaquin Basin map. Three anonymous reviewersoffered many useful suggestions that have been incor-porated into this article.

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Phytoplankton regulation in a eutrophic tidal river (San ... · The tidal San Joaquin River is located in the upper part of the estuary known as the Delta, a mosaic of water-ways