Final Report: Trophic Indicators of Ecosystem Health in Chesapeake Bay

EPA Grant Number: R828677C002
Subproject: this is subproject number 002 , established and managed by the Center Director under grant R828677
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: EAGLES - Atlantic Coast Environmental Indicators Consortium
Center Director: Paerl, Hans
Title: Trophic Indicators of Ecosystem Health in Chesapeake Bay
Investigators: Houde, Edward D. , Adolf, Jason , Boicourt, William C. , Connelly, W. , Gallegos, Charles L. , Harding Jr., Lawrence W. , Jordan, Christy , Jung, Sukgeun , Kimmel, David G. , Magnuson, Andrea , Miller, W. David , Rakocinski, Chet , Roman, Michael R.
Institution: University of Maryland Center for Environmental Science , University of Maryland , University of Mississippi Main Campus
EPA Project Officer: Hiscock, Michael
Project Period: March 1, 2001 through February 28, 2003
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text |  Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Water , Ecosystems

Objective:

The objectives of this research project were to:  (1) develop indicators capable of determining structure and function of plankton and fish communities (i.e., indices of trophic transfer); (2)  derive these indicators from in situ and remote sensing assessments of biological communities and environmental conditions in the Chesapeake Bay; (3) evaluate explicitly the roles of climate, environmental factors, dissolved oxygen, and nutrient loading on community structure; and (4) develop predictive models of ecosystem state, based on the trophic indicators, to forecast future conditions.

Summary/Accomplishments (Outputs/Outcomes):

The Chesapeake Bay Atlantic Coast Environmental Indicators Consortium (ACE INC) was initiated in 2001.  Four principal scientists have worked to develop indicators of estuarine stress and condition, with an emphasis on the trophic ecology of estuarine ecosystems.  Field, laboratory, remote sensing, and modeling approaches have been included in the research program.  Indicators have been developed based on the state of phytoplankton, zooplankton, and fish communities in the Chesapeake Bay, and in collaborations with scientists from other ACE INC component projects.  We have undertaken extensive analyses of broadly integrative indicators in the contexts of hydrographic, environmental, and climatic factors.  The climate context that underlies trophic indicators was an essential emphasis, given the strong forcing of plankton and fish tropho dynamics by regional meteorological conditions, expressed as high seasonal to interannual variability.  We also explored dissolved oxygen and estuarine residence time as component variables for incorporation into indicators of estuarine health.  Statistical modeling proved to be effective in describing quantitative and qualitative attributes of biological communities and responses, particularly as affected by freshwater flow and nutrient loading.  Levels of biological productivity and dominant taxa at all trophic levels var ied in relation to flow and its effects on residence time and dissolved oxygen dynamics in the Chesapeake Bay.  For example, high-flow years and associated high nutrient loads are characterized by a predominance of diatoms at the primary producer level and by high abundances of the copepod Eurytemora affinis in the zooplankton, whereas anadromous fishes experience high recruitment levels under such conditions.  Extending our analyses of climate forcing beyond flow relationships by using synoptic climatology has been a fruitful approach.  We also have developed several novel candidate indicators, notably biomass size spectra (BSS), as integrative indicators of the trophic status of the Bay.  Although ACE INC has terminated, analysis and modeling are continuing on many components of the Chesapeake Bay indicators research.  Lastly, the extensive long-term data holdings we have developed and analyzed in partnerships with state and federal agencies will benefit future indicators research and resource management applications.

Phytoplankton/ Bio optical Indicators

Ecological Indicators.  Phytoplankton indicators included floral composition, biomass as chlorophyll a (chl a), and primary productivity (PP) as daily and annual rates.  Bio optical indicators of relevance to remote sensing retrievals included water absorption properties, in-water reflectance profiles, and remotely sensed reflectances.  Climate indicators included seasonal to interannual variability of predominant weather patterns derived from synoptic climatology, precipitation, and freshwater flow.

Ecological Effect/Impact.  Our analysis of ecological effect/impact has relied on a combination of shipboard, aircraft, and satellite methodologies to provide data of high spatial and temporal resolution, essential in an ecosystem characterized by strong physical forcing from the landscape.   Sea- Viewing Wide Field-of-View Sensor (Sea WiFS) Aircraft Simulator (SAS III) flights on the main stem of the Chesapeake Bay were conducted through 2005 to measure chl a and sea surface temperature (SST) distributions.  This remote sensing and bio optics component of ACE INC focused on floral composition, biomass (chl a), and PP of phytoplankton with analyses of climate forcing in the mid-Atlantic region to develop indicators of primary producers.  We worked in the Chesapeake Bay where freshwater flow is the predominant physical force that structures the ecosystem, whereby seasonal to interannual variability of flow imposed by climate is expressed in the phytoplankton signature.  We developed a conceptual model of the effect of flow on the position and magnitude of the spring diatom bloom, arguably the single most important feature in the annual cycle of phytoplankton in the Bay.

Biomass.  Aircraft remote sensing was the predominant sampling approach we used to detail spatial and temporal variability of phytoplankton biomass in the Bay.  This program commenced in 1989 and provides long-term data on chl a and SST spanning a wide range of hydrologic conditions.  The instruments used during ACE INC were the SAS III manufactured by Satlantic, Inc., to measure ocean color, retrieve chl a, and measure SST by using a commercial infrared temperature sensor by Heimann Instruments .  We continued flights with the SAS III package on the main stem of the Chesapeake Bay through 2005 as part of the Chesapeake Bay Remote Sensing Program (CBRSP, http://www.cbrsp.org Exit ) with support from the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration .  This work has resulted in a 17-year time -series for chl a and PP that is unique for estuaries.  Examples of a spring series of chl a distributions from aircraft remote sensing revealed the development of phytoplankton biomass in a year of low to moderate flow wherein chl a maxima occurred in the upper, oligohaline Bay, consistent with the conceptual model presented above.

A series of research cruises has been conducted as part of Chesapeake Bay-ACE INC to characterize phytoplankton dynamics and bio optical parameters of the water column.  These cruises occupied stations in the Choptank and Patuxent R ivers and were complemented by seasonal cruises on the main stem Bay (April, August, October, and November) in conjunction with related projects, including National Science Foundation (NSF) Biocomplexity with Bess Ward, NSF Microbial Observatory for Virioplankton Ecology with Eric Wommack and Wayne Coats, and NSF Small Grants Emergency Response that supported a post- Hurricane Isabel cruise by our Chesapeake Bay-ACE INC group.  The first set provided coverage of the main stem Bay and adjacent coastal waters; the second set gave coverage of the Choptank and Patuxent Rivers concurrent with surveys of physical properties (Boicourt), zooplankton sampling (Roman), and fish (Houde); and a third set sampled the Bay before and after passage of Hurricane Isabel in fall 2003 to measure changes in plankton and fish communities associated with this strong storm.  Bio optical measurements on all cruises supported the remote sensing efforts and included:  (1) chl a; (2) particulate absorption; (3) chromophoric dissolved organic matter absorption and fluorescence; (4) seston; (5) high-performance liquid chromatography pigment determinations; (6) in-water profiles of downwelling irradiance and upwelling radiance from a suite of instruments to recover remote sensing reflectance; and (7) sun photometer measurements for atmospheric turbidity.  The optical instruments for profiles included a Satlantic tethered hyperspectral radiometer buoy (TSRB) and two profilers, a Biospherical Instruments MER-2040 and a Satlantic MicroPro.  Deployment of these instruments is supporting quality assurance/quality control of radiometry for ACE INC and comparisons with satellite and aircraft recoveries of key ecosystem properties.

Primary Productivity.  The Chesapeake Bay group published models of PP (Harding, et al., 2002) that have been applied to the complete time-series of remote sensing data to generate spatially explicit outputs of PP for the main Bay.  These data now are being analyzed to develop predictive capabilities for this integrative indicator of ecosystem function for the Bay.  The specific approach combines data on freshwater input and nutrient loading to the estuary with the greater than 400 time -point data set developed from the remotely sensed data and models applied thereto.  We reported on progress at an international symposium on primary productivity in the oceans in Bangor, Wales, in March, 2002.  Measurements of PP on the main stem Bay and tributary cruises were conducted throughout 2002 to obtain validation data for model outputs, and the data now are being processed and analyzed.  Progress on this aspect of our work supported presentations at an Estuarine and Great Lakes Meeting in Bodega Bay in December 2003, and at an American Society of Limnology and Oceanography/The Oceanography Society meeting in Honolulu in February 2005, and the results now are being prepared for publication .

Floral Composition.  We have used chl a biomass (mg/m3), floral composition (as fraction of chl a - f_chl a: attributable to specific taxonomic groups), and community size structure as phytoplankton indicators, each of which conveys an independent aspect of phytoplankton dynamics.  The major goals of our work were to:  (1) quantify the responsiveness of these indicators to environmental variability, focusing on freshwater flow and nutrient loading from the watershed; (2) quantify the relationships among these indicators (i.e., how floral composition, biomass, cell size distribution, and PP co-vary and are forced by similar environmental drivers); and (3) detail the ramifications for ecosystem function.  Chl a biomass generally is regarded as a good indicator of trophic status, as chl a tends to increase as a function of nutrient loading.  Floral composition and cell -size distribution serve as qualitative descriptors of the phytoplankton biomass captured in chl a measurements, which may impact the fate of phytoplankton biomass captured in our chl a measurements.  Furthermore, floral composition and size structure of the phytoplankton potentially can respond to environmental forces that do not affect chl a biomass.  Consideration of combinations of chl a biomass, floral composition, and size structure can be used to estimate fates of phytoplankton, such as sedimentation (i.e., high biomass, large diatoms) or harmful algal blooms formation (i.e., high biomass, high percentage of dinoflagellates).

Coincident Forcing.  We have undertaken a statistical study of physical forcing of phytoplankton floral composition, biomass, and PP :  three important indicators of eutrophication in the main stem of the Chesapeake Bay that was published in Estuarine, Coastal and Shelf Science this winter (Adolf, et al., 2006).  The Bay is a diatom-dominated system wherein seasonal variability of temperature and Susquehanna River flow (SRF) explains most of the annual variability of floral composition.  Seasons are characterized by particular combinations of floral composition, chl a biomass, and PP.  In an analysis of a 6-year dataset, each season was characterized by regional blooms of recurring taxa related to trophic gradients in the main stem of the Bay.  Interannual variability of phytoplankton dynamics in spring and summer was driven primarily by freshwater input that stimulated diatoms.  Thus, diatoms were highly responsive to large-scale nutrient inputs such as those that attended freshwater inputs.  These responses were most pronounced in the lower Bay in summer where high SRF precipitated a floral shift from picoplanktonic (< 3 mm) cyanobacteria to larger diatoms.

ACE INC sampling from 2002- 2005 compared phytoplankton indicators in the Choptank and Patuxent Rivers.  In 2003, flow cytometric measurements of phytoplankton community size distribution were added to core measurements of biomass and floral composition.  Seasonal relationships exist among floral composition, chl a biomass, and cell size distribution.  Relative size distribution was measured with a Becton Dickinson FACSCalibur flow cytometer, using an empirical algorithm developed in a Research Experiences for Undergraduates Fellowship project (Miranda Hoover, Wittenburg University) to relate side-scatter to cell -size.  Here, the size distribution is scaled between 0 and 1 for presentation.  High -flow in spring 2003 pushed biomass distributions toward the mouths of each river where phytoplankton were characterized by relatively large diatoms.  The average cell size of phytoplankton was smaller in summer than in spring.  The advantage of combining these different phytoplankton indicators is that community size distribution associated with diatom assemblages in spring (i.e., large cells) and summer (i.e., small cells) carries different ecological ramifications for the fate of algal biomass.  Future studies will attempt to quantify relationships between phytoplankton and higher trophic levels, drawing on biomass, floral composition, and size distribution data measured in this study.

A recent focus of our research in ACE INC has used synoptic climatology as an analytical approach to study environmental forcing of spatial and temporal variability of phytoplankton biomass in the Chesapeake Bay.   Briefly, synoptic climatology is a statistical approach to classify and quantify variability of atmospheric circulation on a regional scale.  Each day’s weather is clustered into 1 of 10 dominant weather patterns.  These weather patterns have distinct meteorological conditions including probability and amount of precipitation, temperature, wind speed, and wind direction.  These parameters then are used in a water balance model to estimate freshwater flow from the river basin.  W. David Miller, a graduate student working in ACE INC, has developed a water balance model for the Susquehanna River basin in collaboration with Dave Kimmel and Larry Harding that will appear in Water Resources Research this spring (Miller, et al., 2006).

The Susquehanna River is the primary source of freshwater to the Bay, and variability of flow from this river influences phytoplankton biomass, particularly in the spring when nutrients and sediments associated with flow determine the light and nutrient conditions of the Bay .  On seasonal to interannual time scales, phytoplankton indicators (floral composition, biomass, and PP) are responsive to variability of freshwater flow that ultimately traces to regional-scale weather patterns quantified using the synoptic climatology.  By developing a water balance model that is forced by synoptic-scale weather patterns, we have been able to identify and quantify the type of weather that most strongly influences phytoplankton dynamics.  This approach allows us to predict monthly to seasonal freshwater flow based on earlier months’ atmospheric circulation and thereby predict phytoplankton biomass on seasonal, regional time, and space scales.  Surface chl a values collected as part of CBRSP from 1989-2004 have been used to calculate monthly average chl a for various regions of the Bay that experience similar salinity, nutrient, and light attenuation conditions .  Chl a is expressed as anomalies from long-term monthly mean conditions by region to determine the response of the ecosystem to the various synoptic-scale weather patterns. A synoptic climatology provides a mechanism to classify and quantify weather variability on smaller spatial and temporal scales than basin-scale climate indices such as the North Atlantic Oscillation or El Niňo-Southern Oscillation that do not have a proximate influence in the Chesapeake Bay region.  Each of the predominant weather patterns has a relatively consistent set of conditions associated with it (i.e., cloud cover, temperature, wind speed and direction, and precipitation).  The frequency of occurrence of certain weather patterns in a given month and deviations from the normal condition are being related to the chl a anomalies to detect weather patterns that most influence surface chl a and the quantify magnitude of the response.

Environmental Application

One of the main applications of our intensive bio optical sampling and climate analysis is to make data from satellite remote usable for this ecosystem.  Case 2 waters of estuarine and coastal waters are problematic vis-à-vis retrieving useful information on phytoplankton dynamics because of the complex mix of bio optically active constituents that influence the spectral signature.  This has required the application of data from ACE INC to develop workable alternatives to retrieve chl a and related properties from sensors such as SeaWiFS and the Moderate Resolution Imaging Spectroradiometer.

We consolidated progress in the use of satellite ocean color sensors for estuarine and coastal waters with a pair of publications on bio optical modeling and chl a retrievals from the SeaWiFS .  Satellite remote sensing has the advantage of regular coverage provided that atmospheric correction and the complex bio optical properties typical of Case 2 waters are taken into account in processing the data.  Our work in ACE INC has led to improvements in the usefulness of SeaWiFS data.  Comparisons of in situ and remotely sensed chl a showed good agreement for the mesohaline and polyhaline regions of the Bay.  These comparisons used the operational SeaWiFS chl a algorithm, OC4v.4, that overestimates chl a in estuarine and coastal waters.  Additional work drawing on the extensive bio optical measurements we have made in the Chesapeake Bay and the mid-Atlantic bight supported an alternative approach to quantify chl a using a semi-analytical model.  This application supports the development of long time-series of observations spanning a broad range of environmental conditions enabling us to sort change from variability, a key element in establishing and interpreting phytoplankton indicators of nutrient over enrichment.

Residence -Time and Dissolved Oxygen

Ecological Indicators.  We started our search for meaningful physical-process indicators of water quality in estuaries with the evidence that the proportion of introduced nutrients exported to the ocean is related clearly to the estuary’s flushing characteristics.  It appeared as if the estuary were like an industrial, chemical-reaction vat, where the uptake and reaction processes within the system occurred at a comparatively constant rate (perhaps set by temperature and vat geometry), such that the longer the water was retained in the system, the further the reaction proceeded.  This observation led directly to the idea that residence -time would not only be a good component indicator, allowing a first-level screening in a decision tree or a multi-input indicator when combined with indicators of other key processes such as system metabolism,  but we also realized that the Nixon, et al. (1996) relationship also might argue for residence -time as a stand-alone indicator of estuarine water quality.

A primary driver of residence -time in estuaries is fresh water input.  In well-mixed estuaries, such as Delaware Bay or the Columbia River at spring tide, the role of fresh water input is comparatively simple, where this flow acts like a hose to flush materials from the system.  For partially mixed and salt-wedge estuaries, fresh water acts to drive the classical, two-layer estuarine circulation, which is the dominant flushing mechanism for these kinds of systems.

In addition to residence -time, we have been exploring an effect-based indicator:   dissolved oxygen.  Dissolved oxygen is related to residence -time, in that longer residence -times lead to stagnation and oxygen sags.  In estuaries, fresh water input not only contributes to the circulation, but it also increases stratification.  Stratification suppresses vertical exchange, leading to oxygen depletion in summer months.  In the Chesapeake Bay, this process has been exacerbated under increasing eutrophication pressures.  Dissolved oxygen recently has been established by the EPA Chesapeake Bay Program as one of the key indicators of Bay health. Specific target criteria have been established for geographic zones of the Bay ranging from nearshore to the deep channel.

We have separated our indicators into stand-alone and component indicators.  We have termed some of the uses of these measures as component indicators because additional information, such as nutrient loading, stratification, or channel depth, must be combined with these parameters to produce a meaningful gauge.  Stand-alone indicators are intended to serve as gauges of estuarine health on their own.

In the ACE INC Chesapeake Bay Program, both field and analytical modeling efforts were employed in the attempt to formulate and evaluate effective indicators that incorporate dissolved oxygen and residence -time.  Field efforts were concentrated on the exchange dynamics and short-term oxygen variability of the Patuxent River, Choptank River, and Pocomoke tributary estuaries, in conjunction with the fish, zooplankton, and phytoplankton components of the ACE INC Chesapeake Bay program.  Measurements from moored instrumentation and high-resolution surveys via towed undulating vehicle (Acrobat) supported a variety of analytical efforts.  A variety of moored oxygen sensors were deployed on Chesapeake Bay Observing System buoys to both assess their ability to obtain accurate measures in the presence of hypoxia and biofouling (both potentially harmful to moored sensors) and to measure short-term variability of oxygen.

One difficulty in establishing residence -time as an ecological indicator of estuarine health has been the myriad methods for determining this value from measurable parameters.  We decided to use both a standard global estimate based on the fresh-water fraction method (Dyer, 1997 ), and a set of models to explore the utility of spatially explicit residence -time estimates as indicators. Analytical efforts have been centered on developing oxygen and residence -time formulations to test on the three Chesapeake Bay tributaries:   the Choptank, Patuxent, and Pocomoke Rivers and then on the other ACE INC estuaries and finally, to the global collection.  Wh e reas the Choptank and Patuxent Rivers have a similar geometry, with cross-sectional area exponentially expanding toward the sea, the Pocomoke River has an unusual pipe-like geometry for the majority of the estuarine portion, with the cross-sectional area nearly constant until a rapid exponential expansion near the protective entrance sill.

A simple advection-diffusion model has been constructed successfully and tested for all three tributaries.  This model has provided exchange coefficients which delineate circulation provinces and from which residence -times can be calculated.  The longitudinal structure of the exchange coefficients showed a marked maximum in mid estuary, where analysis revealed a confined region of elevated gravitational circulation located between the 1-layer circulation in the upper reaches and the pulsed wind-driven circulation in the lower reaches.

To complement and compare this continuous one-dimensional approach, Edgar Davis (2005) appealed to know discrete one-dimensional and two- dimensional box models for his Master’s research on flushing and residence -time determinations for the Pocomoke, Choptank, and Patuxent Rivers.  He applied Pritchard’s (1969) box models, with guidance from Officer’s (1980) and Hagy’s (1996) applications.  Davis was successful in applying these models to all three estuaries, obtaining both bulk and spatially explicit residence -time estimates.  Residence times varied from hours within individual cells of his two- dimensional models to nearly a year for the entire estuary for low-runoff conditions.  Davis has completed his thesis work and now is producing a manuscript that compares his discrete models to the continuous models for the Pocomoke, Patuxent, and Choptank Rivers.

For estuaries exhibiting hypoxia, specific residence -time estimates for the lower layers showed promise as a component in an indicator that includes nutrient loading.  Bulk residence -time indicators based on the freshwater fraction method have been constructed to complete the suite of candidate indicators.  These indicators have the attraction of their simplicity and integrating power, but they are less sensitive in distinguishing the spectrum of estuaries susceptible to oxygen depletion.  A summer student, Katharine Haberkorn, addressed long-term time -series (ACE INC salinity and oxygen data) from the Chesapeake Bay to explore the effects of winds on both horizontal circulation as well as vertical mixing.   Although these efforts were successful in delineating the wind-driven horizontal motion, attempts at developing a simple wind-mixing formulation have not yet been fruitful.

Ecological Effect/Impact.  We have argued that the inclusion of an indicator that captures the balance between the physical effects of flushing and retention is essential for characterizing the susceptibility of an estuarine ecosystem to pollutant loadings.  For estuaries subject to excess nutrient loading, an additional indicator that captures the aerating effect of horizontal advection and the effect of stratification on suppressing vertical exchange provides a more useful guide.  In the Chesapeake Bay, we have observed a fundamental shift in the relationship between freshwater input (creating stratification) and the volume of hypoxia in the mid-1980s with significantly greater hypoxia occurring per unit inflow following the shift.

Both sets of models yielded residence -time estimates for the entire estuary and for scalable subregions.  Two-layer box models become unstable in well-mixed estuaries, so a screening indicator for determining which model should be applied is part of the stepwise process.  When stratification exists, as it does for the majority of estuaries, two-layer box models are especially useful for indicators because they capture the combined effects of stratification and gravitational circulation, as well as vertical mixing.

For oxygen to be used as a stand-alone indicator, specific statistics are required that relate to the ecological impact of concern.   Although bulk determinations of hypoxic volume have served well in providing indications of long-term trends in the Chesapeake Bay and in the Mississippi River plume, these measures do not provide habitat or exposure impact information for important estuarine species.  For these impacts, measures derived from continuous high-frequency oxygen probes are required.

Environmental Application.  The physical indicators developed through ACE INC provide measures of the flushing characteristics of an estuary and of its ability to resist re aeration of its lower layers.  As such, they are applicable, not only to oxygen depletion, but also the ability of the estuary to dilute the concentration of any introduced pollutant.  Ideally, residence time and oxygen indicators are most useful for resource management in estuaries when they require a minimum of input data and simplicity in formulation.  The bulk indicators developed so far meet the first requirement, although nutrient loading information may not be forthcoming easily for all estuaries.  A minimum of monitoring survey data on salinity and oxygen combined with readily accessible geometric and freshwater inflow data provided the basis for these indicators. Formulating these indicators conceptually is straightforward, although sometimes time-consuming if geometric data has not been assembled previously to support the residence time models.  Because the sensitivity of these indicators for distinguishing differences among estuaries is expected to depend on careful standardized application, operational procedures need to be documented for each calculation.  As with other indicators, choices of spatial domains, temporal domains, and input data can affect significantly the outcomes so that these too must be standardized.  Furthermore, once these procedures have been standardized, a final indicator scale analogous to a litmus test must be established for convenient application to management decisions.  Ultimately, a handbook guiding the operational procedures and providing the calibration scale will aid this process.

Residence -time indicators derived from discrete and continuous models have been developed using known one-dimensional and two-dimensional techniques.  These models have been applied successfully to the Patuxent, Choptank, and Pocomoke River estuaries, estuaries that differ significantly in geometry, freshwater inflow, and circulation.  Their formulation is sufficiently simple that they can be applied readily to other estuaries.  The required inputs are estuarine geometry, freshwater inflow, and a sufficiently long set of salinity measurements to cover both high- and low-flow conditions.

During the ACE INC Chesapeake Bay program, we have assessed the suitability of five oxygen sensors to survive anoxia and biofouling on moorings in the Chesapeake Bay while returning accurate measurements.  With these combined effects of hypoxia and biofouling, the Aanderaa/Per-Sens Optode (a ruthenium quenching technique) probe and the brushed YSI 6000 Extended Deployment Probe proved adequate to the purpose.  Both, however, required significant technician time for preparation, calibration, deployment, and maintenance.

As part of the ACE INC field effort to explore high-frequency variations in oxygen while evaluating sensors in the hostile environment, an instrument was moored in the main stem Bay off the Choptank and Patuxent tributaries, An Aanderaa/PerSens Optode oxygen sensor was placed below the pycnocline (12 m), and the sensor recorded conditions before and during the passage of Hurricane Isabel.  The sensor successfully recorded the change from anoxia to saturation resulting from the destratifying mixing of Isabel.  A Bay-wide survey 18 days later revealed a restratification and return to hypoxic conditions in the lower layers.

We have worked with the EPA Chesapeake Bay Program to develop meaningful criteria for dissolved oxygen to gauge restoration progress in the Bay.  These criteria depend on continuous measurement of dissolved oxygen from observing systems.  From our ACE INC experience, we have shown that two sensor types show promise of surviving the hostile environment of the deep layers of Chesapeake Bay where the hypoxia is most severe.

The next step for the physical indicators is to test these formulations over as wide a range of estuaries as possible.   The statistical strength, however, of even this large a group of estuaries is expected to be limited.  For that reason, a concerted effort to assemble input and assessment data from a broad range of estuaries is deemed essential for refining these indicators and transitioning them into operational applications.

Zooplankton and Climate Indicators

We have been developing zooplankton as an indicator of trophic and climate change in estuaries. We have studied the long-term drivers of zooplankton variability in the Chesapeake Bay, discovering the major forcing functions that affect zooplankton abundance .  We used this knowledge to link weather patterns to spring freshwater input and shifts in mesozooplankton abundance and community composition .  We also have focused on the use of BSS as an indicator of zooplankton response to changes in the Chesapeake Bay ecosystem .

BSS are capable of serving as indicators of multiple stresses to the ecosystem. The individual spectrum for each trophic level may be examined for shape, slope, and intercept and these parameters used to assess the factors shaping the size spectra .  The importance of bottom-up versus top-down control may be elucidated using size spectra, thus pinpointing the most important forcing functions impacting an individual trophic level.  These external forces may be the target of management.  The integrated spectra, consisting of multiple trophic levels, will serve as an indicator of nutrient stress and over fishing in the estuary.  The same parameters as in an individual spectrum may be monitored to assess ecosystem response to these important targets of management.

Environmental Application.  BSS will be used primarily to assess the ecosystem state of estuaries impacted by eutrophication and over fishing.  It also may be used to assess the response of estuaries to management, in particular nutrient reduction.  The size spectra will shift in response to management and thus serve as an effective barometer for ecosystem condition. BSS is also an integrative indicator, capable of measuring ecosystem response to management at multiple trophic levels, thus may be a very effective tool for monitoring purposes.

Biomass Size Spectra, Trophic Indicators

BSS depicts the abundance and distribution of organisms by size classes in an ecosystem.  In aquatic ecosystems, the biomasses (i.e., aggregate weight) of organisms at each level in the food chain from microscopic phytoplankton to the largest vertebrate animals nearly are equal.  Thus, the distribution of organism biomasses across size classes (the spectrum) is said to be flat, with a slope of zero.  Although biomasses are near equal, the numerical abundance of small organisms (referred to as a normalized BSS) greatly exceeds numbers of large organisms.  Rates of physiological and ecological processes, such as metabolism, production, and predator-prey interactions can be derived from BSS, based primarily on allometric relationships.  Parameters of modeled BSS, such as slope, intercept, and shape have potential for use as indicators of anthropogenic impact on estuarine ecosystems from such stresses as eutrophication, contaminant loadings, or fishing.

Traditional measures of community structure rely on measures of abundances, species diversity, and ordination metrics.   Although reliable, these measures may not describe community structure or dynamics in the context of the broader trophic structure of estuarine ecosystems.  Evaluating biomass and size structure across trophic levels is an integrative measure of trophic state that links higher trophic levels in aquatic ecosystems (i.e., fish) to lower trophic levels (i.e., phytoplankton and zooplankton).  The Chesapeake Bay ACE INC developed B S S indicators of fish community structure and of plankton community structure.  The BSS within a trophic component (e.g., zooplankton or fish) describe d the structure and status of that component, whereas BSS integrated across trophic levels offered the possibility of broadly evaluating the state of an estuary from an analysis of its combined trophic constituents.

Predominantly size-specific predation (big organisms eat smaller ones) characterizes aquatic communities, maintains the observed biomass size structure, and has led to theory, methods development, and models that evaluate biomass-size relationships to characterize the structure and state of ecosystems.  A BSS broadly quantifies responses to stress or change in an ecosystem’s structure or carrying capacity and provides metrics to judge the degree of change. Shifts, trends, or anomalies in BSS metrics portray real changes in biological community structure and can serve as indicators of change in the state of estuarine ecosystems.

Ecological Indicator.  Properties of BSS in the Chesapeake Bay were analyzed to determine their efficacy as indicators of food-chain relationships and effects of stress on food webs.  Parameters that quantify the statistical properties of a normalized BSS were calculated and modeled.  These metrics were derived from regression models (simple or complex) fit to biomass and size data expressed on a log2 scale.  Scaling of these relationships primarily occurs at two levels in a normalized BSS .  The overall relationship ( integral spectrum ) between abundance and size has a theoretical slope of approximately -1 when plotted on log2-transformed axes (termed primary scaling).  Parabolic deviations (termed secondary scaling or biomass domes ) from the integral spectrum occur generally at size ranges corresponding to phytoplankton, zooplankton, and fishes. Interannual shifts, long-term trends, or regional differences in BSS metrics, relative to reference levels, historical benchmarks, or standards may be indicative of changes or variability in:  (1) biological community structure, (2) biological productivity , (3) food-chain efficiency, (4) predator-prey relationships , (5) effects of environmental factors , (6) effects of nutrient or contaminant loading , (7) effects of fishing , and (8) habitat.

Effects of stressors on biological communities in aquatic ecosystems are complex and not described easily by a few select indicators.  A BSS approach is advantageous because its metrics are broadly integrative across trophic levels and are indicative of changes in organism abundances and sizes, predator-prey relationships, and trophic efficiencies.  BSS is a conserved property in all aquatic systems; therefore, BSS is broadly applicable in aquatic ecosystems.

Ecological Effect/Impact.  BSS can serve as indicators of multiple stresses to the ecosystem.  The individual spectrum for each trophic level (e.g., phytoplankton, zooplankton, fish) may be examined for shape, slope, and intercept and these parameters then used to evaluate factors shaping the size spectra.  Parameters of BSS models were analyzed with respect to monitored environmental variables.  For example, in the case of zooplankton and fish BSS in the Chesapeake Bay, freshwater flow was found to be significantly related to BSS parameters.  In the case of fish, the biomass level of the dome representing zooplanktivorous fish was high and the slope of the integral spectrum was low in 1996, a near-record wet year in the Chesapeake Bay watershed.

BSS of fishes collected in the Trophic Interactions in Estuarine Systems Program (1995-2000) weremodeled and analyzed.  The spectra are multi modal and distinguished two trophic groups, with major modes that represent:  (1) small forage fishes (e.g., bay anchovy) that feed primarily on zooplankton; and (2) larger carnivorous fishes (e.g., Atlantic croaker and white perch) that forage on benthic invertebrates and smaller fishes.  The structure and interannual or regional variability in biomass modes and slopes of normalized BSS are useful parameters that serve as indicators of fish community structure.  Normalized spectra for components of the fish community that include zooplanktivorous and piscivorous fishes (a direct trophic link) have a slope coefficient near a theoretical -1.0.  Spectral slopes and intercepts of BSS for fishes differed among years, mostly from variability in the first dome of the spectrum, which primarily indicate d variable bay anchovyrecruitment and biomass levels that responded dynamically to environmental conditions (e.g., freshwater flow, dissolved oxygen).  Parameters describing the second dome (larger fishes) were relatively constant, but the dominant species that contributed to biomass in this dome varied among years (e.g., Atlantic croaker and white perch shifted in biomass among years).

The parameters of BSS and their statistical properties may vary in response to stress on the ecosystem.  In an integrated normalized BSS model, the overall (backbone) slope of the decline in abundance can serve as an indicator of changes in abundance and biomass of small or large organisms.  Normalized BSS of stressed ecosystems are hypothesized to have steep negative slopes.  For example, in heavily fished ecosystems larger fish may be reduced greatly in number and biomass; or, in highly eutrophic ecosystems, blooms of phytoplankton can increase greatly the abundance and biomass of small organisms, leading to stressful conditions such as hypoxia and mortality of larger organisms.  In these examples, the net effect of such stresses is a shift in community structure across the food chain, a decline in food-chain efficiency, and steeper slopes in normalized BSS.  Changes in the level of the regression describing a BSS may indicate a shift in carrying capacity of the ecosystem.  Or, changes inthe levels or spacing in the dome structure of secondary scaling (parabolas describing trophic levels) may signal shifts in predator-prey relationships.

In a seasonal and regional analysis of BSS in the Chesapeake Bay (phytoplankton, zooplankton, ichthyoplankton, fish), parameters of the size spectrum, averaged over four years, suggested that Bay-wide biological communities had a BSS structure like that predicted for an unstressed aquatic community (slopes near -1.0).   Two selected regional-seasonal combinations, however, have spectral properties that are indicative of either good or bad conditions.  For the bad conditions of Summer-Middle Bay, the slope (a) is strongly negative and the intercept parameter (H0) is low, indicating low biomass and a relatively inefficient trophic transfer potential.  In contrast, the Fall-Upper Bay spectrum is indicative of good conditions (i.e., relatively high biomass and low spectral slope) indicating efficient trophic transfer.  Our preliminary analysis indicates that the slope parameter of the BSS is strongly correlated with principal components (Principal Components Analysis) that consist of environmental correlates.  We are working to convert complex statistical relationships into simpler indicators, and perhaps predictors, of trophic state of the Chesapeake Bay biological communities.

Environmental Application.  Trends in parameters that are calculated in a BSS analysis can be used as a barometer of the degree of change in biological structure in perturbed estuarine ecosystems.  BSS metrics can be applied to a broad suite of biological communities, not only to selected organisms, and thus can indicate how whole ecosystems are responding to either deteriorating conditions or remediation efforts in resource management.  Integrated spectra, consisting of multiple trophic levels, may serve as indicators of nutrient stress and over fishing in the estuary.  Additionally, contributions of key species to BSS, such as bay anchovy in the Chesapeake Bay, may explain why shifts in BSS properties result in functional shifts in productivity or economic value.

Shifts in size spectra toward a reference condition or historical standard in response to management can serve as an effective measure of the success of resource management actions. Because BSS is a fundamental property of all aquatic ecosystems and is an integrative indicator, it is potentially an effective tool for monitoring in many estuaries or coastal ecosystems that are experiencing change or responding to restoration measures.
                       
ACE INC results suggest that BSS indicators are best to detect multi year or decadal shifts in community structure of estuarine ecosystems, rather than in shorter term applications, although extreme environmental conditions (e.g., wet year 1996) can be detected by shifts in spectral properties.  BSS may have advantages over other indices depicting ecosystem or community status (e.g., indices of biotic integrity ) because it represents an objective, integrative approach with defendable statistical foundations.  Extending the analysis of BSS statistical properties in multivariate statistical models, such as Principal Components Analysis, to evaluate explicitly environmental factors represents a promising future approach.  BSS models can support ecosystem-based simulation models now under development for the Chesapeake Bay, such as Ecopath with Ecosim (http://www.ecopath.org), to diagnose and forecast long-term ecosystem changes.

References:

Dyer KR. Estuaries, a Physical Introduction, 2nd Edition. New York, NY: John Wiley and Sons, 1997.

Hagy JD. Residence times and net ecosystem processes in Patuxent River estuary. M.S. Thesis. University of Maryland at College Park, MD, 1996.

Nixon SW, Ammerman JW, Atkinson LP, Berounsky VM, Billen G, Boicourt WC, Boynton WR, Church TM, DiToro DM, Elmgren R, Garber JH, Giblin AE, Jahnke RA, Owens NJP, Pilson MEQ, Seitzinger SP. The fate of nitrogen and phosphorous at the land-sea margin of the North Atlantic Ocean. Biogeochemistry 1996;35:141-180.

Officer CB. Box models revisited. In: Hamilton P, MacDonald RB, eds. Estuarine and Wetland Processes. Marine Sciences Series. New York, NY: Plenum Press, 1980;11.

Pritchard DW. Dispersion and flushing of pollutants in estuaries. American Society of Civil Engineers 1969HY1:115-124.


Journal Articles on this Report : 15 Displayed | Download in RIS Format

Other subproject views: All 83 publications 18 publications in selected types All 18 journal articles
Other center views: All 383 publications 99 publications in selected types All 88 journal articles
Type Citation Sub Project Document Sources
Journal Article Acker JG, Harding LW, Leptoukh G, Zhu T, Shen S. Remotely-sensed chl a at the Chesapeake Bay mouth is correlated with annual freshwater flow to Chesapeake Bay. Geophysical Research Letters 2005;32(5):L05601, doi:10.1029/2004GL021852. R828677 (Final)
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  • Journal Article Adolf JE, Stoecker DK, Harding Jr. LW. The balance of autotrophy and heterotrophy during mixotrophic growth of Karlodinium micrum (Dinophyceae). Journal of Plankton Research 2006;28(8):737-751. R828677 (Final)
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  • Journal Article Harding Jr. LW, Mallonee ME, Perry ES. Toward a predictive understanding of primary productivity in a temperate, partially stratified estuary. Estuarine, Coastal and Shelf Science 2002;55(3):437-463. R828677 (2001)
    R828677 (Final)
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    R826941 (Final)
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  • Journal Article Harding Jr. LW, Magnuson A, Mallonee ME. SeaWiFS retrievals of chlorophyll in Chesapeake Bay and the mid-Atlantic bight. Estuarine, Coastal and Shelf Science 2005;62(1-2):75-94. R828677 (Final)
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  • Journal Article Jung S, Houde ED. Production of bay anchovy Anchoa mitchilli in Chesapeake Bay: application of size-based theory. Marine Ecology Progress Series 2004;281:217-232. R828677 (Final)
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  • Journal Article Jung S, Houde ED. Fish biomass size spectra in Chesapeake Bay. Estuaries and Coasts 2005;28(2):226-240. R828677 (Final)
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  • Journal Article Kemp WM, Boynton WR, Adolf JE, Boesch DF, Boicourt WC, Brush G, Cornwell JC, Fisher TR, Glibert PM, Hagy JD, Harding LW, Houde ED, Kimmel DG, Miller WD, Newell RIE, Roman MR, Smith EM, Stevenson JC. Eutrophication of Chesapeake Bay:historical trends and ecological interactions. Marine Ecology Progress Series 2005;303:1-29. R828677 (Final)
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  • Journal Article Kimmel DG, Roman MR. Long-term trends in mesozooplankton abundance in Chesapeake Bay, USA:influence of freshwater input. Marine Ecology Progress Series 2004;267:71-83. R828677 (Final)
    R828677C002 (2004)
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  • Journal Article Kimmel DG, Roman MR, Zhang X. Spatial and temporal variability in factors affecting mesozooplankton dynamics in Chesapeake Bay:evidence from biomass size spectra. Limnology and Oceanography 2005;51(1):131-141. R828677 (Final)
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  • Journal Article Kimmel DG, Miller WD, Roman MR. Regional scale climate forcing of mesozooplankton dynamics in Chesapeake Bay. Estuaries and Coasts 2006;29(3):375-387. R828677 (Final)
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  • Journal Article Magnuson A, Harding Jr. LW, Mallonee ME, Adolf JE. Bio-optical model for Chesapeake Bay and the Middle Atlantic Bight. Estuarine, Coastal and Shelf Science 2004;61(3):403-424. R828677 (Final)
    R828677C002 (2003)
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  • Journal Article Miller WD, Kimmel DG, Harding Jr. LW. Predicting spring discharge of the Susquehanna River from a winter synoptic climatology for the eastern United States. Water Resources Research 2006;42(5):W05414, doi:10.1029/2005WR004270. R828677 (Final)
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  • Journal Article Roman MR, Boicourt WC, Kimmel DG, Miller WD, Adolf JE, Bichy J, Harding Jr. LW, Houde ED, Jung S, Zhang JX. Stimulation of plankton and fish abundance in Chesapeake Bay by Hurricane Isabel. Eos, Transactions American Geophysical Union 2005;86(28):261-265. R828677 (Final)
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  • Journal Article Tzortziou M, Herman JR, Gallegos CL, Neale PJ, Subramaniam A, Harding Jr. LW, Ahmad Z. Bio-optics of Chesapeake Bay from measurements and radiative transfer closure. Estuarine, Coastal and Shelf Science 2006;68(1-2):348-362. R828677 (Final)
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  • Journal Article Yeager CLJ, Harding Jr. LW, Mallonee ME. Phytoplankton production, biomass and community structure following a summer nutrient pulse in Chesapeake Bay. Aquatic Ecology 2005;39(2):135-149. R828677 (Final)
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  • Supplemental Keywords:

    phytoplankton, zooplankton, fish, trophodynamics, size spectrum, bio-optics, remote sensing, primary production, HPLC, photopigments, dissolved oxygen, circulation, estuarine management, nutrients, regional scale indicators,, RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, RESEARCH, particulate matter, Air Quality, exploratory research environmental biology, Ecosystem/Assessment/Indicators, Ecosystem Protection, Air Pollutants, Chemistry, climate change, Air Pollution Effects, Monitoring/Modeling, Ecological Effects - Environmental Exposure & Risk, Monitoring, Atmospheric Sciences, Environmental Engineering, Atmosphere, Ecological Indicators, ambient aerosol, environmental monitoring, remote sensing, aquatic ecosystem, anthropogenic stress, atmospheric dispersion models, ecoindicator, aerosol formation, fish habitats, atmospheric particulate matter, climate change effects, assessment models, environmental measurement, meteorology, climatic influence, air quality models, ozone, climate, global change, Choptank River, trophic effects, atmospheric transport, estuarine ecosystems, greenhouse gases, climate models, estuarine ecoindicator, atmospheric aerosol particles, airborne aerosols, environmental stress, water quality, climate model, ecological models, greenhouse gas, aerosols, atmospheric chemistry, climate variability, Global Climate Change, zooplankton, ambient air pollution

    Relevant Websites:

    http://www. aceinc.org/ Exit
    http://www.cbrsp.org Exit
    http://www.cisnet-choptank.org Exit

    Progress and Final Reports:

    Original Abstract
  • 2001

  • Main Center Abstract and Reports:

    R828677    EAGLES - Atlantic Coast Environmental Indicators Consortium

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R828677C001 Phytoplankton Community Structure as an Indicator of Coastal Ecosystem Health
    R828677C002 Trophic Indicators of Ecosystem Health in Chesapeake Bay
    R828677C003 Coastal Wetland Indicators
    R828677C004 Environmental Indicators in the Estuarine Environment: Seagrass Photosynthetic Efficiency as an Indicator of Coastal Ecosystem Health