2004 Progress Report: Trophic Indicators of Ecosystem Health in Chesapeake BayEPA 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: Boicourt, William C. , Houde, Edward D. , Mallonee, Michael E. , Gallegos, Charles L. , McClain, Charles R. , Roman, Michael R. , Harding Jr., Lawrence W.
Current Investigators: Houde, Edward D. , Boicourt, William C. , Miller, W. David , Kimmel, David G. , Gallegos, Charles L. , Roman, Michael R. , Harding Jr., Lawrence W. , Magnuson, Andrea , Rakocinski, Chet , Jordan, Christy , Adolf, Jason , Jung, Sukgeun , Connelly, W.
Institution: University of Maryland
Current Institution: University of Maryland Center for Environmental Science , University of Maryland , University of Mississippi Main Campus
EPA Project Officer: Packard, Benjamin H
Project Period: March 1, 2001 through February 28, 2003
Project Period Covered by this Report: March 1, 2003 through February 28, 2004
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text | Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Water , Ecosystems
The objectives of this research project are to:
- develop indicators capable of determining structure and function of plankton and fish communities(i.e., indices of trophic transfer);
- derive these indicators from in situ and remote sensing assessments of ecosystem condition;
- explicitly evaluate roles of climate, environmental factors, dissolved oxygen, and nutrient loading on community structure;
- and develop predictive models of ecosystem state, based on the trophic indicators, to forecast future conditions.
The Chesapeake Bay subproject of the Atlantic Coast Environmental Indicators Consortium (ACE INC) was initiated in 2001. Four principal scientists are developing indicators of estuarine stress and condition, with an emphasis on trophic ecology in estuarine ecosystems. Field, laboratory, remote-sensing, and modeling approaches are included in the research program. Indicators are being developed based on the state of phytoplankton, zooplankton, and fish communities in Chesapeake Bay and in collaborations with scientists from other ACE INC subprojects. Broadly integrative indicators also are being developed and evaluated in relation to environmental and climatic factors. In addition, dissolved oxygen and residence time have been proposed as component variables for incorporation into indicators of estuarine health. Statistical modeling has proven effective in describing biological communities and responses, in terms of quantity and quality, with respect to freshwater flow and nutrient loading. Levels of biological productivity and dominant taxa at all trophic levels vary in relation to flow characteristics. For example, high-flow years and associated high nutrient loads are characterized by a dominance 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. Several candidate indicators have been developed. Biomass size spectra are being evaluated as an integrative indicator of the trophic status of Chesapeake Bay. The long time series of monitoring and survey data available for the Chesapeake Bay ecosystem has benefited the indicators research.
Phytoplankton, Remote Sensing, and Bio-Optics
Phytoplankton indicators include floral composition, biomass as chlorophyll-α (Chl-α), and primary productivity (PP) as daily and annual rates. Bio-optical indicators of relevance to remote sensing retrievals include water absorption properties, in-water reflectance profiles, and remotely sensed reflectances. Climate indicators include 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. SAS III flights on the mainstem of Chesapeake Bay were conducted through 2004 to measure Chl-α and sea surface temperature (SST) distributions. We fielded 22 flights in the Chesapeake Bay Remote Sensing Program (CBRSP; http://www.cbrsp.org) last year with support from the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration.
Figure 1. Conceptual Model of the Effect of Freshwater Flow From the Susquehanna River on the Spring Bloom in Chesapeake Bay.
This work continues a 15-year time series that has generated data of high spatial and temporal resolution for Chl-α and PP. Examples of a spring series of Chl-α distributions from aircraft remote sensing for 2004 reveal the development of phytoplankton biomass in a year of low to moderate flow, whereas Chl-α maxima occurred in the upper, oligohaline Bay, consistent with the conceptual model.
One of the principal advantages of remote sensing for developing an indicator of phytoplankton biomass is the high spatial and temporal resolution of Chl-α we have been able to attain from aircraft and satellite sensors. The Chesapeake Bay is characterized by highly variable Chl-α as an indicator that integrates nutrient loading and eutrophication on a range of scales. Shipboard data alone are insufficient to quantify the annual cycle of Chl-α or the interannual variability that are strongly coupled to climate. Remote sensing gives data on Chl-α at a frequency and resolution that improve our characterizations of the ecosystem with respect to this press physical forcing and overenrichment and to separate variability from trends.
Research cruises in support of ACE INC to characterize phytoplankton dynamics and bio-optical parameters of the water column were conducted on ten occasions during Year 4 of the project, focusing on the mesohaline Chesapeake Bay and the Choptank River. Three cruises (April, July, September-October) were conducted on the mainstem Chesapeake Bay in conjunction with the National Science Foundation Biocomplexity Project in collaboration with Bess Ward. The mesohaline and Choptank cruises was conducted concurrent with surveys of physical properties (Boicourt), zooplankton sampling (Roman), and fish trawls (Houde); the second set gave access to the mainstem Chesapeake Bay and adjacent coastal waters. Bio-optical measurements on all cruises supported the remote sensing efforts and included:
- particulate absorption;
- colored, dissolved organic matter absorption and fluorescence;
- HPLC pigment determinations;
- and in-water profiles of downwelling irradiance and upwelling radiance from a suite of instruments to recover remote sensing reflectance.
The optical instruments for profiles included a Satlantic hyperspectral tethered radiometer buoy and two profilers, a Biospherical Instruments MER-2040 and a Satlantic MicroPro. Deployment of these instruments is supporting QA/QC of radiometry for AINC and comparisons with satellite and aircraft recoveries of key ecosystem properties.
We have used Chl-α biomass (mg m -3), floral composition (as fraction of Chl-α- attributable to specific taxonomic groups), and community size structure as phytoplankton indicators, each of which conveys an independent aspect of phytoplankton dynamics. The mainstem Chesapeake 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. Particular combinations of floral composition, Chl-α, and PP are characterized during each season. In our analysis of a 6-year dataset, regional blooms of recurring taxa were related to trophic gradients in the mainstem Chesapeake 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 Chesapeake Bay in the summer when high SRF precipitated a floral shift from picoplanktonic (< 3 µm) cyanobacteria to larger diatoms.
We applied recently published models of PP to the complete time-series of remote sensing data to generate spatially explicit outputs of PP for the mainstem Chesapeake Bay. These data support predictive capabilities for this integrative indicator of ecosystem function. 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 the joint meeting of the American Society of Limnology and Oceanography and the Oceanography Society (ASLO/TOS) in Honolulu, Hawaii, in February, 2004, and the results are being prepared for publication.
Measurements of primary productivity on the mainstem Chesapeake Bay and tributary cruises were conducted throughout 2002 to obtain validation data for model outputs and the data are now being processed and analyzed. Progress on this aspect of work supported presentations at the Estuarine and Great Lakes (EaGLe) meeting in Bodega Bay, California, in December 2003, and at the ASLO/TOS meeting in February 2004.
ACE INC sampling has compared phytoplankton indicators in the Choptank and Patuxent Rivers using flow cytometric measurements of the size structure of the phytoplankton community. Relative size distribution was measured with a Becton Dickinson FACSCalibur flow cytometer, using an empirical algorithm developed in an REU Fellowship project (Miranda Hoover, Wittenburg University) to relate side-scatter to cell size. 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 quantify relationships between phytoplankton and higher trophic levels, drawing on biomass, floral composition, and size distribution data measured in this study.
We examined the role of synoptic scale weather patterns as a driver of indicator variability across all trophic levels. Most of the indicators that have been identified for the Chesapeake Bay exhibit strong seasonal to interannual variability associated with environmental forcing. On those seasonal to interannual time scales, much of the environmental variability is related to differences in regional-scale weather patterns. By quantifying the variability of atmospheric circulation and its associated influence on environmental variables, we hope to quantify the variability of identified indicators associated with climate variability and, by difference, relate the remaining variability changes in the ecosystem structure and function.
Recent work has focused on developing a water balance model for the Susquehanna River basin, the primary freshwater source for the Chesapeake Bay. Variability of freshwater flow from Susquehanna influences phytoplankton biomass, particularly in the spring when nutrients and sediments associated with flow largely determine the light and nutrient conditions of the Chesapeake Bay. 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. Synoptic climatology is a statistical approach to classifying and quantifying variability in atmospheric circulation at a regional spatial scale. Each day’s weather is clustered into 1 of 10 dominant patterns. These weather patterns have distinct meteorological conditions associated with them, including probability and amount of precipitation, temperature, and wind speed and direction. These parameters then are used in a water balance model to estimate freshwater flow from the river basin. This approach allows us to predict monthly to seasonal freshwater flow based on earlier months’ atmospheric circulation and thereby predict phytoplankton biomass on seasonal and regional time and space scales.
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 in relation to 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-α and related properties from sensors such as Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectrodiometer (MODIS).
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-α 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-α show good agreement for the mesohaline and polyhaline regions of the Chesapeake Bay. These comparisons used the operational SeaWiFS Chl-α algorithm, OC4v.4, that overestimates Chl-α in estuarine and coastal waters. Additional work drawing on the extensive bio-optical measurements we have made in Chesapeake Bay and the mid-Atlantic bight supported an alternative approach to quantify Chl-α 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 overenrichment.
Oxygen and Residence Time Component Indicators
We have been working with dissolved oxygen and residence time as two key indicators of estuarine health. These have been labeled component indicators rather than stand-alone indicators because additional information, such as nutrient loading, stratification, or channel depth must be combined with these parameters to produce a meaningful gauge.
Both field and analytical modeling efforts have been employed in the attempt to formulate and evaluate effective indicators that incorporate dissolved oxygen and residence time. As reported in previous annual summaries, field efforts have been concentrated on the exchange dynamics and short-term oxygen variability of the Patuxent River and Choptank River tributary estuaries, in conjunction with the fish, zooplankton, and phytoplankton components of the ACE Chesapeake Bay program. Measurements from moored instrumentation and high-resolution surveys via a towed undulating vehicle (Acrobat) are supporting a variety of analytical efforts. Of recent note are the dissolved oxygen records from an instrument moored in the mainstem Chesapeake Bay off the Choptank and Patuxent tributaries, as part of the ACE Chesapeake Bay effort to explore high-frequency variations in oxygen while evaluating sensors in the hostile environment of high biofouling and anoxia. An Aanderaa/PerSens Optode oxygen sensor was placed below the pycnocline (12 m) and recorded conditions prior to and during the passage of Hurricane Isabel. The sensor successfully recorded the change from anoxia to saturation resulting from the destratifying mixing of Hurricane Isabel. A Bay-wide survey days later revealed a restratification and return to hypoxic conditions in the lower layers. The details of the oxygen dynamics and physical response of the estuary to Hurricane Isabel were reported at the Hurricane Isabel Symposium in December 2004. In addition, two manuscripts (Roman, et al., 2005; Boicourt, 2005) were submitted.
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 estuaries and, finally, to the global collection. A simple advection-diffusion model has been constructed successfully and tested for two of the three tributaries. This model has provided exchange coefficients that delineate circulation provinces and, from which, residence times can be calculated. The longitudinal structure of the exchange coefficients show 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. We are now in the process of spinning the model up for the Patuxent River, where we expect a more typical exchange associated with a gravitational circulation that increases monotonically seaward.
Three additional analytical efforts are underway to construct meaningful physical indicators. Edgar Davis is developing one-layer and two-layer box models for the Pocomoke River and for the Choptank and Patuxent Rivers. These models yield residence time estimates for both the entire estuary and for scalable subregion. Two-layer box models become unstable in well-mixed estuaries, therefore 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, gravitational circulation, and vertical mixing. For estuaries exhibiting hypoxia, residence time estimates for the lower layers show 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 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 were not successful.
To aid in testing this suite of indicators, a catalog of estuarine characteristics is being prepared that includes relevant physical and water-quality variables. This effort is expected to benefit from a combined, ACE-wide focus.
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 indicator that captures the aerating effect of horizontal advection and the effect of stratification on suppressing vertical exchange provides a more useful guide.
Environmental Application. The physical indicators developed through this effort provide characteristics of an estuary and its ability to resist reaeration of its lower layer. As such, they are applicable, not only with oxygen depletion, but also to the ability of the estuary to dilute the concentration of any introduced pollutant. Ideally, residence-time and oxygen indicators would be most useful for resource management in estuaries if they required a minimum of input data and a simplicity in formulation. The bulk indicators developed so far meet the first requirement, although nutrient loading information may not be easily forthcoming for all estuaries. A minimum of monitoring survey data on salinity and oxygen combined with readily accessible geometric and freshwater inflow data provide the basis for these indicators. Formulating these indicators is conceptually straightforward, although sometimes time consuming if geometric data has not been previously assembled; however, because the sensitivity of these indicators for distinguishing differences among estuaries is expected to depend on careful, standard application, operational procedures need to be documented for each calculation. As with other indicators, choices of spatial and temporal domains and of input data can significantly affect the outcomes, therefore 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.
Zooplankton As Indicators of Change In Estuaries
Zooplankton abundance is currently being monitored in the Chesapeake Bay and its tributaries and in many estuaries around the country. We believe these data may be effectively mined to assess ecosystem condition. Changes or shifts in zooplankton distribution, abundance, and species composition are analyzed and modeled in response to environmental factors, especially human-induced changes in the estuary resulting from eutrophication, climate change, and inter-annual weather patterns.
Ecological Effect/Impact. We examined the long-term changes and possible drivers of zooplankton abundance changes for Chesapeake Bay. We developed models that correlated zooplankton abundance with estuarine water quality and biological parameters. Significant deviations from the models were found for particular time periods and correlated with water quality conditions. Time periods showing the strongest deviations from the model were typically wet or dry years. Therefore, we believe that zooplankton may be used as indicators of changes in estuarine condition that relate to freshwater discharge (Kimmel and Roman, 2004).
Environmental Application. Zooplankton may be used as indicators of trophic condition. The distribution of zooplankton biomass in Chesapeake Bay appears to vary significantly throughout the year. The slope of the size spectra appears to vary with hydrologic conditions, including nutrient inputs and may serve as a tool to assess the efficacy of nutrient reduction efforts. The zooplankton size spectra will be combined with phytoplankton and fish size spectra to create a whole ecosystem-based indicator. In a broader sense, zooplankton community structure, trends, and dynamics are being analyzed with respect to primary producer (bottom-up) and fish (top-down) controllers in estuarine ecosystems.
Zooplankton and Climate
We are examining the daily, monthly, and interannual variability in weather patterns in the Chesapeake Bay region and linking this variability to ecosystem effects. We are developing the weather pattern indicator in an ecosystem that is strongly affected by freshwater input and have linked winter climate to the spring freshet, a major driver of ecosystem function and structure.
Ecological Effect/Impact. Climate may be used as an indicator of future changes in various properties of the ecosystem in question or can be used to evaluate the susceptibility of indicators to potential effects of climate change or variability. We believe that this is a major benefit of developing indicators in the context of climate variability (i.e., the natural variability of the system is quantified). Indicators of estuarine condition may be assessed in relation to environmental perturbations with a higher degree of confidence. Climate classification can be carried out in any defined region, thus this indicator is applicable to a wide variety of ecosystems.
Environmental Application. Climate analysis has a variety of applications. It can be used to predict future ecosystem condition, as we have done by predicting spring freshwater input from winter climate (Miller, et al., in preparation). It also may be used to examine changes in timing of peak abundance, location of peak abundance, and changes in species composition of phytoplankton and zooplankton (Kimmel, et al., in review).
Biomass Size Structure: An Indicator of Trophic State in Estuarine Ecosystems
A biomass size spectrum (BSS) depicts the abundance and distribution of organisms by size classes in an ecosystem. Properties of BSS in the Chesapeake Bay are being analyzed to determine their efficacy as indicators of food-chain relationships and effects of stress on food webs. Metrics that quantify the statistical properties of a normalized BSS may serve as indicators. The metrics are derived from regression models (simple or complex) fit to biomass and size data, usually expressed on a log 2 scale. Scaling of these relationships primarily occurs at two levels in a normalized biomass size spectrum. The overall relationship (integral spectrum) between abundance and size should have a theoretical slope of approximately negative one when plotted on log 2 transformed axes (primary scaling). Parabolic deviations (secondary scaling—biomass domes) from the integral spectrum may occur at the 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:
- biological community structure;
- biological productivity;
- food-chain efficiency;
- predator-prey relationships;
- effects of environmental factors;
- effects of nutrient or contaminant loading;
- effects of fishing;
- and habitat.
Effects of stressors on biological communities in aquatic ecosystems are complex and not easily described by a few select indicators. In this respect, a BSS approach is advantageous because its metrics are broadly integrative across trophic (food-chain) 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; BSS, therefore, is broadly applicable to other estuarine systems.
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 (Kimmel, et al., in review). The importance of bottom-up versus top-down control may be indicated in a size-spectra analysis, thus clarifying how the structure of individual trophic levels is controlled and regulated. Parameters of BSS models can be analyzed with respect to monitored environmental variables. For example, in the case of zooplankton BSS in the Chesapeake Bay, freshwater flow was found to be significantly related to BSS parameters.
BSS of fishes collected in the Trophic Interactions in Estuarine Systems Program (1995-2000) have been modeled and analyzed. The spectra are multi-modal and distinguish 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 variability in biomass modes and the slopes of normalized BSS (abundance-at-size relative to size) are the parameters that are indicators of fish community structure. Normalized spectra for components of the fish community that include only zooplanktivorous and piscivorous fishes (direct trophic link) have a slope coefficient near a theoretical negative one. Spectral slopes and intercepts of BSS for fishes differ among years, mostly from variability in the first dome of the spectrum, which primarily indicates variable bay anchovy recruitment and biomass levels that respond dynamically to environmental conditions (e.g., freshwater flow, dissolved oxygen). Parameters describing the second dome (larger fishes) are relatively constant, but the dominant species that contribute to biomass in this dome varied among years.
The parameters of BSS and their statistical properties may vary in response to stress on the ecosystem. For example, 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 greatly reduced in number and biomass. Or, in highly eutrophic ecosystems, blooms of phytoplankton can greatly increase the abundance and biomass of small organisms, leading to stressful conditions such as hypoxia and mortality of larger organisms (e.g., crabs, fish). 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. Changes in the levels or spacing in dome structure of secondary scaling (parabolas within trophic levels; Figure 2) may signal shifts in predator-prey relationships.
Figure 2. An Integrated Biomass Size Spectrum for Chesapeake Bay, Based on Data Combined from 1997 and 1999 Surveys That Include Phytoplankton, Zooplankton, Fish Larvae, and Juvenile/Adult Fishes. The backbone slope of this linear BSS model is approximately -1.0, a value that characterizes most aquatic ecosystems. More complex models can fit the detailed trophic structure that is represented by BSS data and provide additional parameter estimates.
Environmental Application. Trends in metrics that are calculated in a BSS analysis could 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 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 management. 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.
We will make a dedicated effort in 2005 to deliver products and results of our ACE INC research to stakeholders in the Chesapeake Bay Program (CBP). Presentations of our indicators research will be made to the Scientific and Technical Advisory Committee and Living Resources Subcommittee of the CBP, and to EPA managers who are charged with evaluating status of the Bay and protecting its resources. Our trophic state, climatology, and dissolved oxygen indicators will provide new tools to evaluate status of resources and need for restoration efforts.
Phytoplankton, Remote Sensing, and Bio-Optics
We are implementing the procedures developed in ACE INC into data processing for SeaWiFS and Aqua-MODIS, including semi-analytical models for the retrieval of Chl-α and depth-integrated PP models to generate time-series of these indicators for the lower two-thirds of the mainstem Chesapeake Bay and the nearshore shelf. Future research will center on compiling these outputs with concurrently collected in situ observations for validating, linking satellite-derived phytoplankton indicators to those developed more traditionally, and coupling these several sources of high-resolution data to climate analysis directed at improving our ability to predict ecosystem responses to nutrient overenrichment.
Oxygen and Residence Time Component Indicators
The next step for the physical indicators is to test these formulations over as wide a range of estuaries as possible. We expect to complete the Chesapeake Bay and ACE-wide assessment in 2005. 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 application.
Zooplankton and Climate
In ACE INC, we are evaluating the structure and dynamics of zooplankton communities as an indicator of trophic and climate change in estuaries. Climate variability is a long-term driver of zooplankton variability in the Chesapeake Bay and a major forcing function that affects zooplankton abundance. We will use this knowledge to build upon and link weather pattern anomalies to shifts in mesozooplankton abundance and community composition (Kimmel, et al., in review).
Biomass Size Structure: An Indicator of Trophic State in Estuarine Ecosystems
A detailed analysis of integrated size spectra in the Choptank and Patuxent Rivers tidal tributaries of Chesapeake Bay is underway. A comparison of BSS properties and environmental conditions will be conducted to determine how stressful nutrient loading from agricultural (Choptank) and urban/suburban (Patuxent) watersheds translates into BSS parameters that have utility as indicators of estuarine condition. For the fish component of BSS, we will initiate comparison research in North Carolina estuaries during 2005. In another new component of the trophic indicators research, we will investigate effects of a hurricane (Hurricane Isabel) on BSS, specifically for the fish community and potentially for other trophic levels, in the Chesapeake Bay.
We will emphasize evaluation of statistical properties of BSS in 2005. This emphasis will lead to better understanding of how to apply BSS model parameters as indicators of estuarine condition. In addition, we will explore possibilities of relating BSS parameters to environmental conditions in multivariate analyses such as Principal Component Analysis and other ordination methods. In this way, we will gain a better knowledge of processes that control BSS properties, which will improve the use of BSS models and parameters as indicators of ecosystem state. Our preliminary analysis indicates that the slope parameter of the BSS is strongly correlated with principal components that consist of environmental correlates. Ultimately, we hope to convert complex statistical relationships into simple indicators, and perhaps predictors, of trophic state of Chesapeake Bay biological communities.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
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||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.||
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
Progress and Final Reports:Original Abstract
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