Measure Of Phytoplankton Biomass Research Articles

Improving Satellite Chlorophyll-a Retrieval in the Turbid Waters of the Bay of Fundy, Canada

AbstractThe Bay of Fundy is a highly productive ecosystem within the Northwest Atlantic where extreme tides and strong currents result in a large gradient of sediment concentrations across and along the bay. We processed daily satellite data from the MODerate resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite from 2003 to 2021 at 300-m resolution to understand and quantify spatial and temporal trends in chlorophyll-a concentration (chl-a, a measure of phytoplankton biomass), and suspended particulate matter concentration (SPM) in the Bay of Fundy surface waters. To account for high sediment loading (up to 100’s g m−3) and moderate chl-a (median in situ chl-a of 1.5 mg m−3 from 2003 to 2021), coefficients of the OC3M chl-a algorithm were regionally tuned using in situ chl-a data, and satellite-derived SPM was incorporated within the chl-a retrieval algorithm to account for possible bias. The updated new algorithm was denoted as OCX-SPMCor. Chl-a computed using OCX-SPMCor showed better performance against in situ chl-a than the generic OC3M with a coefficient of determination that increased from 0.01 to 0.28 and a root mean square logarithmic error that decreased by 35%. Unlike previous remote sensing studies, OCX-SPMCor correctly predicted the particular chl-a seasonality in the Bay of Fundy, which does not follow the typical occurrence of spring/fall blooms as observed in the adjacent Gulf of Maine and Scotian Shelf. For the first time, satellite-predicted chl-a aligned with the phenology of in situ chl-a, where chl-a continually increased from April to June and remained high all summer, with a small secondary summer peak before decreasing in the fall. SPM seasonality followed an opposite trend where SPM reached a maximum in winter and a minimum in summer. A small number of matchups and high temporal variability on the hourly time scale precluded a robust assessment of the satellite-derived SPM. However, comparisons between time series of remotely sensed and in situ SPM demonstrated the ability of the satellite-derived SPM to capture temporal variations, though the absolute values may be slightly underestimated. Accurate maps of phytoplankton biomass and sediment concentrations are essential variables required for effective management and conservation of marine ecosystems in the Bay of Fundy.

Coupling ecological concepts with an ocean-colour model: Phytoplankton size structure

Phytoplankton play a central role in the planetary cycling of important elements and compounds. Understanding how phytoplankton are responding to climate change is consequently a major question in Earth Sciences. Monitoring phytoplankton is key to answering this question. Satellite remote sensing of ocean colour is our only means of monitoring phytoplankton in the entire surface ocean at high temporal and large spatial scales, and the continuous ocean-colour data record is now approaching a length suitable for addressing questions around climate change, at least in some regions. Yet, developing ocean-colour algorithms for climate change studies requires addressing issues of ambiguity in the ocean-colour signal. For example, for the same chlorophyll-a concentration (Chl-a) of phytoplankton, the colour of the ocean can be different depending on the type of phytoplankton present. One route to tackle the issue of ambiguity is by enriching the ocean-colour data with information on sea surface temperature (SST), a good proxy of changes in three phytoplankton size classes (PSCs) independent of changes in total Chl-a, a measure of phytoplankton biomass. Using a global surface in-situ dataset of HPLC (high performance liquid chromatography) pigments, size-fractionated filtration data, and concurrent satellite SST spanning from 1991 to 2021, we re-tuned, validated and advanced an SST-dependent three-component model that quantifies the relationship between total Chl-a and Chl-a associated with the three PSCs (pico-, nano- and microplankton). Similar to previous studies, striking dependencies between model parameters and SST were captured, which were found to improve model performance significantly. These relationships were applied to 40 years of monthly composites of satellite SST, and significant trends in model parameters were observed globally, in response to climate warming. Changes in these parameters highlight issues in estimating long-term trends in phytoplankton biomass (Chl-a) from ocean colour using standard empirical algorithms, which implicitly assume a fixed relationship between total Chl-a and Chl-a of the three size classes. The proposed ecological model will be at the centre of a new ocean-colour modelling framework, designed for investigating the response of phytoplankton to climate change, described in subsequent parts of this series of papers.

Retrieval and Evaluation of Chlorophyll-A Spatiotemporal Variability Using GF-1 Imagery: Case Study of Qinzhou Bay, China

Chlorophyll-a (Chl-a) concentration is a measure of phytoplankton biomass, and has been used to identify ‘red tide’ events. However, nearshore waters are optically complex, making the accurate determination of the chlorophyll-a concentration challenging. Therefore, in this study, a typical area affected by the Phaeocystis ‘red tide’ bloom, Qinzhou Bay, was selected as the study area. Based on the Gaofen-1 remote sensing satellite image and water quality monitoring data, the sensitive bands and band combinations of the nearshore Chl-a concentration of Qinzhou Bay were screened, and a Qinzhou Bay Chl-a retrieval model was constructed through stepwise regression analysis. The main conclusions of this work are as follows: (1) The Chl-a concentration retrieval regression model based on 1/B4 (near-infrared band (NIR)) has the best accuracy (R2 = 0.67, root-mean-square-error = 0.70 μg/L, and mean absolute percentage error = 0.23) for the remote sensing of Chl-a concentration in Qinzhou Bay. (2) The spatiotemporal distribution of Chl-a in Qinzhou Bay is varied, with lower concentrations (0.50 μg/L) observed near the shore and higher concentrations (6.70 μg/L) observed offshore, with a gradual decreasing trend over time (−0.8).

A framework to develop joint nutrient criteria for lake eutrophication management in eutrophic lakes

Nutrient criteria provide the numeric basis for lake eutrophication management. However, there are two obstacles that can hinder the effective application of nutrient criteria, including 1) although total phosphorus (TP) and total nitrogen (TN) might co-limit phytoplankton biomass in eutrophic lakes, their criteria are often developed independently; and 2) the linkage between nutrient criteria and the percentile-based compliance assessment method of chlorophyll a (CHL; as a measure of phytoplankton biomass) has not been well established. To resolve these obstacles, we propose a novel analytical framework of nutrient criteria development, by which joint nutrient criteria are developed using quantile regression (QR). We demonstrated the steps necessary to utilize this novel approach using TP, TN, and CHL data from Lake Dianchi, a hypereutrophic lake located in southwestern China. First, we built candidate QR models to quantify the nutrient-CHL relationship at six regression quantiles. Next, we conducted the sequential Wald test to select the “best” model for each regression quantile. Finally, we visualized the joint nutrient criteria surface using a contour map. The contour map effectively illustrated the joint nutrient criteria by showing the linkage of TP and TN criterion. In addition, based on the QR, it was easy to deduce nutrient criteria which met the requirement of percentile-based compliance assessment. We further found that joint nutrient criteria could help the selection of an efficient load reduction strategy in the watershed. The proposed method can be generalized to other systems and may facilitate site-specific lake eutrophication management.

Factors Regulating the Relationship Between Total and Size-Fractionated Chlorophyll-a in Coastal Waters of the Red Sea

Phytoplankton biomass and size structure are recognized as key ecological indicators. With the aim to quantify the relationship between these two ecological indicators in tropical waters and understand controlling factors, we analyzed the total chlorophyll-a concentration, a measure of phytoplankton biomass, and its partitioning into three size classes of phytoplankton, using a series of observations collected at coastal sites in the central Red Sea. Over a period of 4 years, measurements of flow cytometry, size-fractionated chlorophyll-a concentration, and physical-chemical variables were collected near Thuwal in Saudi Arabia. We fitted a three-component model to the size-fractionated chlorophyll-a data to quantify the relationship between total chlorophyll and that in three size classes of phytoplankton [pico- (<2 μm), nano- (2–20 μm) and micro-phytoplankton (>20 μm)]. The model has an advantage over other more empirical methods in that its parameters are interpretable, expressed as the maximum chlorophyll-a concentration of small phytoplankton (pico- and combined pico-nanophytoplankton, and , respectively) and the fractional contribution of these two size classes to total chlorophyll-a as it tends to zero (Dp and Dp,n). Residuals between the model and the data (model minus data) were compared with a range of other environmental variables available in the dataset. Residuals in pico- and combined pico-nanophytoplankton fractions of total chlorophyll-a were significantly correlated with water temperature (positively) and picoeukaryote cell number (negatively). We conducted a running fit of the model with increasing temperature and found a negative relationship between temperature and parameters and and a positive relationship between temperature and parameters Dp and Dp,n. By harnessing the relative red fluorescence of the flow cytometric data, we show that picoeukaryotes, which are higher in cell number in winter (cold) than summer (warm), contain higher chlorophyll per cell than other picophytoplankton and are slightly larger in size, possibly explaining the temperature shift in model parameters, though further evidence is needed to substantiate this finding. Our results emphasize the importance of knowing the water temperature and taxonomic composition of phytoplankton within each size class when understanding their relative contribution to total chlorophyll. Furthermore, our results have implications for the development of algorithms for inferring size-fractionated chlorophyll from satellite data, and for how the partitioning of total chlorophyll into the three size classes may change in a future ocean.

Assessment of physico‐chemical properties of water and phytoplankton bloom formation in a eutrophic pond using multivariate analysis

AbstractAn investigation of the water chemistry and phytoplankton bloom formation characteristics of a seasonal earthen pond located in the Alappuzha District, Kerala (India) was carried out during November 2011 to May 2012. Twelve important physico‐chemical parameters (temperature, Secchi disc transparency, pH, electrical conductivity EC), dissolved oxygen (DO), biochemical oxygen demand (BOD), ammonia‐nitrogen, nitrite‐nitrogen, nitrate‐nitrogen, total phosphorus (TP), dissolved iron and chlorophyll a related to phytoplankton growth in the pond were the focus of the present study. Chlorophyll a was used as a measure of phytoplankton biomass. The pond developed subsurface phytoplankton blooms of Chlorella vulgaris, Aphanothece sp., Leptosira sp., Lepocinclis globulus and Lepocinclis fusiformis. Visible scums of Lepocinclis globulus and Euglena proxima was also observed during March 2012. Principal component analysis was performed to understand the biochemical processes in the pond ecosystem leading to the Euglena spp. bloom.

Changes in the relationship between zooplankton and phytoplankton biomasses across a eutrophication gradient.

The relationship between zooplankton biomass and phytoplankton biomass can provide insight into the structure and function of lake biological communities. We used a Bayesian network model to analyze a continental-scale data dataset to estimate changes in the relationship between zooplankton (Z) and phytoplankton (P) biomasses along a eutrophication gradient. The Bayesian network model allowed us to combine two different measurements of phytoplankton biomass (chlorophyll a concentration and directly observed biovolume) to improve the precision of estimates of true biomass within each sample. The model also allowed us to estimate separate relationships between P and zooplankton abundance and between P and mean individual zooplankton biomass and then to combine these two relationships into an estimate of seasonal mean zooplankton biomass. The resulting analysis indicated that seasonal mean zooplankton biomass increased proportionally with phytoplankton biomass in oligotrophic lakes, yielding a constant ratio between Z and P and suggested that bottom-up forces determined zooplankton biomass in these systems. In eutrophic lakes, seasonal mean zooplankton biomass was nearly constant with increases in phytoplankton biomass, yielding a decrease in the ratio between Z and P with increasing eutrophication. Bottom-up forces, as quantified by an increase in the proportion of cyanobacteria, accounted for approximately one fifth of the residual variance in the model as the relationship between Z and P changed from direct proportionality in oligotrophic lakes to the nearly constant value of Z observed in eutrophic lakes, suggesting that a combination of both top-down and bottom-up forces likely determined zooplankton biomass in eutrophic lakes.

Structural equation modeling of the influence of environmental factors on summer phytoplankton growth in the Ross Sea

The Ross Sea is a highly productive region of the Southern Ocean, and net phytoplankton growth varies seasonally, ranging from zero to near the temperature-limited maximum. Given that variations in growth can result from a number of factors (such as irradiance and iron concentrations), variability in net growth rate was investigated using structural equation modeling (SEM) and data collected during a January–February 2012 cruise to the Ross Sea. Structural equation modeling indicated that summer growth rates were significantly affected by iron concentrations and particulate organic carbon (POC) levels, the latter which most likely contributed to the seasonal depletion of iron by phytoplankton. Conversely, growth rates did not strongly vary with mixed layer depth (and hence irradiance). SEM indicated that if iron concentrations were increased by 1.0 standard deviation (ca. 0.12 nM), summer growth rates would increase by 0.5 standard deviation (ca. 0.07 day−1). Similarly, if POC (a measure of phytoplankton biomass in this region) was increased by 1.0 standard deviation (from 23.0 to 39.4 µmol L−1), growth rates would decrease by 0.31 standard deviations (~0.04 day−1), which we speculate is likely due to heightened iron limitation via increased total iron uptake. This modeling exercise confirms the dominant role of iron in regulating summer phytoplankton rates over the continental shelf of the Ross Sea.

Seasonal and interannual phytoplankton dynamics and forcing mechanisms in the Northern Benguela upwelling system

Seasonal phytoplankton blooms are one of the key features of the productive northern Benguela upwelling system (nBUS), however they are not well described thus far. In this study twelve years (2000–2012) of in situ chlorophyll-a data from a monitoring transect off the Namibian coast were analysed to assess the long-term and seasonal variability in chlorophyll-a as a measure of phytoplankton biomass and the occurrence of phytoplankton blooms. On the shelf, low chlorophyll-a concentrations were identified in 2001/2002, 2005/2006, and 2011/2012. The concentrations on the shelf were highest in 2008/2009 and 2010/2011. Major phytoplankton blooms defined at chlorophyll-a concentrations >18mgm−3 occurred in five of the 12years (2002/2003, 2004/2005, 2008/2009, 2009/2010 and 2010/2011) while minor blooms (>13mgm−3) occurred in almost every year. The calculated climatology of the chlorophyll-a time series revealed a clear seasonality. Three chlorophyll-a maxima typically develop inshore over the year: an austral winter peak (August), an early austral summer peak (December) and a late summer/autumn peak (April). The analysis of synoptic hydrographic, nutrient and wind data revealed three different forcing mechanisms that all initiate an influx of nutrients into the surface mixed layer.

Phytoplankton Communities in Green Bay, Lake Michigan after Invasion by Dreissenid Mussels: Increased Dominance by Cyanobacteria

Biological invasions of aquatic systems disrupt ecological communities, and cause major changes in diversity and ecosystem function. The Laurentian Great Lakes of North America have been dramatically altered by such invasions, especially zebra (Dreissena polymorpha) and quagga (D. rostriformis bugensis) mussels. Responses to mussel invasions have included increased water clarity, and decreased chlorophyll and phytoplankton abundance. Although not all systems have responded similarly, in general, mussels have changed nutrient dynamics and physical habitat conditions. Therefore examination of different impacts can help us further understand mechanisms that underlie ecosystem responses to biological invasions. To aid our understanding of ecosystem impacts, we sampled established locations along a well-studied trophic gradient in Green Bay, Lake Michigan, after the 1993 zebra mussel invasion. A strong trophic gradient remained during the period sampled after the mussel invasion (2000–2012). However, mean summer chlorophyll increased and other measures of phytoplankton biomass (microscope and electronic cell counting) did not change significantly. Multivariate analyses of phytoplankton community structure demonstrate a significant community shift after the invasion. Cyanobacteria increased in dominance, with Microcystis becoming the major summer taxon in lower Green Bay. Diatom diversity and abundance also increased and Chlorophyta became rare. Phytoplankton responses along the trophic gradient of Green Bay to zebra mussel invasion highlight the importance of mussel effects on nutrient dynamics and phytoplankton diversity and function.

Complementary use of Wave Glider and satellite measurements: Description of spatial decorrelation scales in Chl-a fluorescence across the Pacific basin

A key challenge for ecosystem science in the 21st century is to characterize emerging trends in ecosystem productivity due to climate change and to better predict cycles in ecosystem variability. A first step toward this goal is to be able to characterize phytoplankton variability across a wide range of spatial and temporal scales. In this paper, 15 months of Wave Glider (WG) fluorometer measurements made across the Pacific Ocean were used to understand how WGs complement existing chlorophyll-a-based measurements of phytoplankton biomass from satellite platforms. Extensive analysis of the WG transects demonstrated that WG fluorometer readings reliably characterized similar large-scale variability in satellite Chl-a measurements in four distinct ecosystem types including coastal upwelling, transition zone, oligotrophic and equatorial upwelling regions. Complementary information provided by WG measurements included better resolution of coastal Chl-a patches and prominent diel cycles in the open ocean. The decorrelation scales computed from WG fluorometer measurements in this study provide necessary information for designing observing systems, process experiments, and data assimilation studies. We conclude this paper by suggesting how WGs can be used to anchor satellite measurements and to develop better predictive models.

Long-term seasonal effects of dreissenid mussels on phytoplankton in Lake Simcoe, Ontario, Canada

The invasion of dreissenid mussels to Lake Simcoe coincided with notable changes in the ecosystem, including a period of lower phytoplankton biovolume, particularly at shallower sites. Dreissenid grazing effects are typically most prominent during the summer season in the nearshore areas of lakes. Grazing effects in the winter are small because dreissenid filtration rates, especially those of zebra mussels (Dreissena polymorpha), decrease in cold temperatures. Phytoplankton dynamics in the winter season are poorly characterized, particularly in lakes that experience ice cover. The purpose of this study was to examine the effects of dreissenids on the seasonality of phytoplankton dynamics in the nearshore waters of the lake using long-term monitoring data from unchlorinated water treatment plant (WTP) intake pipes. The long-term dataset from the WTPs showed significant and sustained declines in phytoplankton biovolumes and chlorophyll a (Chl-a) concentrations in the 12-year period following the invasion of dreissenid mussels to Lake Simcoe. The decline was smallest during the ice-covered winter months (Jan–Mar). The fall phytoplankton peak observed in the pre-dreissenid years shifted to a smaller peak during the winter in post-dreissenid years. We hypothesized that reduced dreissenid grazing pressure during the winter, and possible improved under-ice light conditions that we attribute to climate change, may be contributing to this shift. Phytoplankton biovolume data collection continues to be important in Lake Simcoe as a measure of phytoplankton biomass. Our results also indicate that winter phytoplankton biovolumes should be considered when managing lakes experiencing both climate change and dreissenid mussel effects.

Site-specific chlorophyll reference conditions for lakes in Northern and Western Europe

The Water Framework Directive (WFD) requires EU Member States to assess the “ecological status” of surface waters. As a component of ecological status, many European countries are developing a classification scheme for chlorophyll concentrations as a measure of phytoplankton biomass. The chlorophyll classification must be based on the degree of divergence of a water body from an appropriate baseline or ‘reference condition’. This article describes the development of a series of regression models for predicting reference chlorophyll concentrations on a site-specific basis. For model development, a large dataset of European lakes considered to be in reference condition, 466 lakes in total, was assembled. Data were included from 12 European countries, but lakes from Northern and Western Europe dominated and made up 92% of all reference lakes. Data have been collated on chlorophyll concentration, altitude, mean depth, alkalinity, humic type, surface area and geographical region. Regression models were developed for estimating site-specific reference chlorophyll concentrations from significant predictor ‘typology’ variables. Reference chlorophyll concentrations were found to vary along a number of environmental gradients. Concentrations increased with colour and alkalinity and decreased with lake depth and altitude. Forward selection was used to identify independent explanatory variables in regression models for predicting site-specific reference chlorophyll concentrations. Depth was selected as an explanatory variable in all models. Alkalinity was included in models for low colour and humic lakes and altitude was included in models for low colour and very humic lakes. Uncertainty in the models was quite high and arises from errors in the data used to develop the models (including natural temporal and spatial variability in data) and also from additional explanatory variables not considered in the models, particularly nutrient concentrations, retention time and grazing. Despite these uncertainties, site-specific reference conditions are still recommended in preference to type-specific reference conditions, as they use the individual characteristics of a site known to influence phytoplankton biomass, rather than adopt standards set to generally represent a large population of lakes of a particular type. For this reason, site-specific reference conditions should result in reduced error in ecological status classifications, particularly for lakes close to typology boundaries.

Climate forcing of the spring bloom in Chesapeake Bay

Interannual variability of the spring phytoplankton bloom is strongly expressed in estu- arine ecosystems such as Chesapeake Bay. Quantifying this variability is essential to resolve ecosys- tem responses to eutrophication from variability imposed by climate. We developed a 'synoptic clima- tology' from surface sea-level pressure (SLP) maps to categorize and quantify atmospheric circulation patterns and address climate forcing of phytoplankton dynamics in the Bay. The 10 patterns we iden- tified had unique frequencies-of-occurrence and associated meteorological conditions (i.e. precipita- tion, temperature, wind speed and direction). Four measures of phytoplankton biomass, surface chlorophyll a (B), euphotic layer chlorophyll a (Beu), water column chlorophyll a (Bwc), and total bio- mass (Btot), were obtained from remotely sensed ocean color data spanning 16 yr (1989 to 2004) com- bined with concurrent shipboard data. Years with more frequent warm/wet weather patterns had spring blooms that reached peak biomass farther seaward in the estuary, were greater in magnitude, occurred later in the spring, and covered a larger area than years with a predominance of cool/dry weather patterns. Frequencies of winter weather patterns were used to forecast spring B, Beu, Bwc, and Btot, explaining between 23 and 89% of the variance in the regional time-series. Residuals from these models did not show time-trends attributable to either accelerating eutrophication or manage- ment actions intended to decrease nutrient loadings. These findings extend our understanding of cli- matic influences on phytoplankton dynamics in the Bay by quantifying the effects of synoptic climate variability on spring bloom intensity, thereby supporting forecasts of seasonal phytoplankton biomass based on sub-continental scale weather patterns in this mid-Atlantic estuary.

Alterations in Yellowstone Lake Nitrogen Cycling Due to Introduced Lake Trout and Subsquent Decline of Yellowstone Cutthoat Trout

Invasive species may alter processes by indirectly affecting other species in the ecosystem, but indirect affects are difficult to measure and often pre-invasion data were not collected. However, models may be used with empirical relationships and available past data to reconstruct past processes. The introduction of lake trout (Salvelinus namaycush) in Yellowstone Lake may have indirect effects on nitrogen cycling and provide an opportunity to study the effects of an invasive species on lake processes. To estimate how lake trout altered nitrogen cycling in Yellowstone Lake, we measured ammonium (NH4+) uptake by phytoplankton in 2005 and estimate past NH4+ uptake using empirical relationships and past data. Using 1 5N, we measured phytoplankton uptake in 4 areas of Yellowstone Lake. Phytoplankton demanded 4.9 mg N m-2 hr- 1 during the ice-free season of 2005. Uptake was higher at warmer water temperatures and shallower Secchi disk depths (measure of phytoplankton biomass). Using relationships among uptake, water temperature, and Secchi disk depth, we estimated phytoplankton uptake in the past based on historical Secchi disk depths and water temperatures. Water temperatures have increased 0.29.C/decade and Secchi disk depths became 0.53 m/decade deeper over the past 30 years. Using our multiple regression model, phytoplankton uptake did not change between 1976 and 2006. The interaction between warmer water temperatures and deeper Secchi disk depths (a sparser algal assemblage) cancelled out resulting in no changed in modeled uptake. Therefore, when estimating past processes, we should use multiple predictors.

Extending the SeaWiFS chlorophyll data set back 50 years in the northeast Atlantic

Phytoplankton play a key role in biogeochemical cycling and climate processes. Precise quantitative measurements of chlorophyll‐a (Chl‐a), a measure of phytoplankton biomass, have only been available globally since 1997 from the Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS). In the North Atlantic, semi‐quantitative measurements of chlorophyll (Phytoplankton Color Index, PCI) for &gt;50 years have been collected by the Continuous Plankton Recorder. Here we demonstrate a significant correlation between PCI and SeaWiFS Chl‐a from 1997–2002. Combining both time series allows quantification of the stepwise increase in biomass in the mid‐1980s; this regime shift corresponded to a 60% increase in Chl‐a. This was a result of an 80% increase in Chl‐a during winter, alongside a smaller summer increase. This new high‐resolution data set on the monthly variation of Chl‐a in the North Atlantic since 1948 is now available for the development and validation of climate models, and for interpretation of ecological changes related to climate.

Hydrologic variability, water chemistry, and phytoplankton biomass in a large floodplain of the Sacramento River, CA, U.S.A.

The Yolo Bypass, a large, managed floodplain that discharges to the headwaters of the San Francisco Estuary, was studied before, during, and after a single, month-long inundation by the Sacramento River in winter and spring 2000. The primary objective was to identify hydrologic conditions and other factors that enhance production of phytoplankton biomass in the floodplain waters. Recent reductions in phytoplankton have limited secondary production in the river and estuary, and increased phytoplankton biomass is a restoration objective for this system. Chlorophyll a was used as a measure of phytoplankton biomass in this study. Chlorophyll a concentrations were low (<4 μg l−1) during inundation by the river when flow through the floodplain was high, but concentrations rapidly increased as river inflow decreased and the floodplain drained. Therefore, hydrologic conditions in the weeks following inundation by river inflow appeared most important for producing phytoplankton biomass in the floodplain. Discharges from local streams were important sources of water to the floodplain before and after inundation by the river, and they supplied dissolved inorganic nutrients while chlorophyll a was increasing. Discharge from the floodplain was enriched in chlorophyll a relative to downstream locations in the river and estuary during the initial draining and later when local stream inflows produced brief discharge pulses. Based on the observation that phytoplankton biomass peaks during drainage events, we suggest that phytoplankton production in the floodplain and biomass transport to downstream locations would be higher in years with multiple inundation and draining sequences.

Convection and primary production in winter

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 251:1-14 (2003) - doi:10.3354/meps251001 Convection and primary production in winter Jan O. Backhaus1,*, Else Nøst Hegseth2, Henning Wehde1, Xabier Irigoien3, Kerstin Hatten1, Kai Logemann1 1Institute of Oceanography, University of Hamburg, Troplowitzstr.7, 22529 Hamburg, Germany 2The Norwegian College of Fisheries Science, University of Tromsø, 9037 Tromsø, Norway 3Technological Institute for Fisheries and Food AZTI, Herrera Kaia, Portualde z/g, 20110 Pasaia, Spain *Email: backhaus@dkrz.de ABSTRACT: We present observations of temperature, salinity and phytoplankton from late winter of 1999 obtained along a meridional transect running from 52 to 72°N through the northern North Atlantic and Norwegian Sea. The field work was conducted with the intention to find evidence for a postulated relationship between convection and primary production in the open ocean in winter. In the investigated area, convection ventilates water masses in a deep mixed layer which may cover several hundreds of meters, depending on atmospheric forcing and stratification. Inspired by the results of a coupled phytoplankton convection model, we postulated that sinking phytoplankton from the seasonal thermocline in autumn is dispersed within the mixed layer by vertical orbital motions and turbulence induced by convection. Orbital motions allow intermittent visits of plankton to the euphotic layer from much deeper depths. Hence, convection distributes the chance of plankton receiving light over the entire mixed layer. This supports production and allows compensation of losses due to sinking. We hypothesised that a winter stock of living phytoplankton in the open ocean would always coincide with the deep mixed layer formed by convection, irrespective of its depth. Indeed, along the entire meridional transect, living phytoplankton was found within the layer, whereas only marginal amounts or virtually no phytoplankton existed beneath it. The layer extent varied between 300 and 800 m. In the northern North Atlantic, average concentrations of chloro- phyll a (as a measure of phytoplankton biomass) in the mixed layer were about 0.3 mg m-3, and 0.6 mg m-3 in the Norwegian Sea. We concluded that this winter stock forms the inoculum for a spring production in the open ocean. KEY WORDS: Primary production · Winter · Convection · Vertical orbital motions Full text in pdf format NextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 251. Online publication date: April 11, 2003 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2003 Inter-Research.

Changes in shallow lake functioning: response to climate change and nutrient reduction

Nutrient, phytoplankton and zooplankton dynamics have been monitored intensively at Loch Leven for 34 years. The data collected reveal a decline in phosphorus concentrations, following major reductions in external nutrient loading, and large changes in its seasonal availability, particularly in recent years. More striking has been an increasing trend in water temperatures, annual means increasing by about 1 °C over the 34 years, with even greater increases observed for winter and spring periods. In response to these changes, there has been a general pattern of decline in measures of phytoplankton biomass (chlorophylla concentrations). Closer inspection reveals that the detailed response is, however, not so consistent with the environmental trends. A significant decline in chlorophylla concentrations occurred early on in the time series, before major reductions in nutrient availability. Correlation analysis revealed that this decline was associated with the re-appearance of Daphnia grazers. Further declines are only apparent in very recent years; correlation analysis and comparison of trends suggest that these were associated with the observed decline in nutrient concentrations. There was little correlation and no consistent relationship between annual measures of chlorophylla and water temperature, but winter mean values did show a consistent positive relationship. Spring Daphnia densities showed an even stronger, and significant, positive relationship with spring water temperatures. It is clear from this that the scale of climate change predicted in the future will significantly alter the functioning of shallow lakes and seasonal patterns in water quality. This is a particular concern in Europe with the implementation of the EC Water Framework Directive, as if the net effect of global warming on annual measures of water quality is negative, the principle aim of `good status' in all surface waters by 2016 will become even more difficult to achieve.

Bio-optical properties of the subtropical North Atlantic. II. Relevance to models of primary production

. ABSTRACT: Based on measurements of phytoplankton biomass, absorption coefficients and photosynthetic performance obtained from samples collected in the subtropical Atlantic Ocean, standard sets of bio-optical parameters were selected and applied to a spectral model of primary production. Computed profiles of instantaneous production, integrated over the day, and spectral irradiance were compared with measurements of 12 h in situ production and in situ spectral irradiance to assess the model's performance. Although the model performed well for the stations located on the western side of the transect, at the eastern side of the basin the model overestimated both primary production and irradiance below the mixed layer. The modelled irradiance profile was then reconciled with the observations of irradiance by increasing the assumed contribution to absorption by yellow substances. When the production model was re-implemented with the new irradiance values below the mixed layer, the computed and measured production profiles of all the stations were in good agreement. In the spectral model used in this study, the shape of the absorption spectrum of phytoplankton was used as a proxy for the shape of the photosynthetic action spectrum. Because non-photosynthetic pigments (NPPs) were abundant in pigment samples collected in the study region, the influence of NPPs on the shape of the absorption spectrum was examined and its effect on computations of primary production was quantified. When total aPh(z, h) and photosynthetic a,,(z, h) phytoplankton absorption at wavelength h and depth z were used to quantify the error resulting from failure to correct for the influence of NPPs on the shape of the absorption spectra, the results showed small errors in the computation of production at depth (up to 20%) and integrated, water-column primary production (a maximum of 10 %).