Nutrient Improvements in Chesapeake Bay: Direct Effect of Load Reductions and Implications for Coastal Management.

In Chesapeake Bay in the United States, decades of management efforts have resulted in modest reductions of nutrient loads from the watershed, but the corresponding improvements in estuarine water quality have not consistently followed. Generalized additive models were used to directly link river flows and nutrient loads from the watershed to nutrient trends in the estuary on a station-by-station basis, which allowed for identification of exactly when and where responses are happening. Results show that Chesapeake Bay's total nitrogen and total phosphorus conditions are mostly improving after accounting for variation in freshwater flow. Almost all of these improving nutrient concentrations in the estuary can be explained by reductions in watershed loads entering through 16 rivers and 145 nearby point sources, with the nearby point source reductions being slightly more effective at explaining estuarine nutrient trends. Overall, these two major types of loads from multiple locations across the watershed are together necessary and responsible for the improving estuarine nutrient conditions, a finding that is highly relevant to managing valuable estuarine resources worldwide.

Seasonal to Inter-Annual Variability of Primary Production in Chesapeake Bay: Prospects to Reverse Eutrophication and Change Trophic Classification.

Estuarine-coastal ecosystems are rich areas of the global ocean with elevated rates of organic matter production supporting major fisheries. Net and gross primary production (NPP, GPP) are essential properties of these ecosystems, characterized by high spatial, seasonal, and inter-annual variability associated with climatic effects on hydrology. Over 20 years ago, Nixon defined the trophic classification of marine ecosystems based on annual phytoplankton primary production (APPP), with categories ranging from "oligotrophic" to "hypertrophic". Source data consisting of shipboard measurements of NPP and GPP from 1982 to 2004 for Chesapeake Bay in the mid-Atlantic region of the United States supported estimates of APPP from 300 to 500 g C m-2 yr-1, corresponding to "eutrophic" to "hypertrophic" categories. Here, we developed generalized additive models (GAM) to interpolate the limited spatio-temporal resolution of source data. Principal goals were: (1) to develop predictive models of NPP and GPP calibrated to source data (1982 to 2004); (2) to apply the models to historical (1960s, 1970s) and monitoring (1985 to 2015) data with adjustments for nutrient loadings and climatic effects; (3) to estimate APPP from model predictions of NPP; (4) to test effects of simulated reductions of phytoplankton biomass or nutrient loadings on trophic classification based on APPP. Simulated 40% decreases of euphotic-layer chl-a or TN and NO2 + NO3 loadings led to decreasing APPP sufficient to change trophic classification from "eutrophic' to "mesotrophic" for oligohaline (OH) and polyhaline (PH) salinity zones, and from "hypertrophic" to "eutrophic" for the mesohaline (MH) salinity zone of the bay. These findings show that improved water quality is attainable with sustained reversal of nutrient over-enrichment sufficient to decrease phytoplankton biomass and APPP.

Long-term trends, current status, and transitions of water quality in Chesapeake Bay.

Coincident climatic and human effects strongly influence water-quality properties in estuarine-coastal ecosystems around the world. Time-series data for a number of ecosystems reveal high spatio-temporal variability superimposed on secular trends traceable to nutrient over-enrichment. In this paper, we present new analyses of long-term data for Chesapeake Bay directed at several goals: (1) to distinguish trends from spatio-temporal variability imposed by climatic effects; (2) to assess long-term trends of water-quality properties reflecting degradation and recovery; (3) to propose numerical water-quality criteria as targets for restoration; (4) to assess progress toward attainment of these targets. The bay has experienced multiple impairments associated with nutrient over-enrichment since World War II, e.g., low dissolved oxygen (DO), decreased water clarity, and harmful algal blooms (HAB). Anthropogenic eutrophication has been expressed as increased chlorophyll-a (chl-a) driven by accelerated nutrient loading from 1945 to 1980. Management intervention led to decreased loading thereafter, but deleterious symptoms of excess nutrients persist. Climatic effects exemplified by irregular "dry" and "wet" periods in the last 30+ years largely explain high inter-annual variability of water-quality properties, requiring adjustments to resolve long-term trends. Here, we extend these analyses at a finer temporal scale to six decades of chl-a, Secchi depth, and nitrite plus nitrate (NO2 + NO3) data to support trend analyses and the development of numerical water-quality criteria. The proposed criteria build on a conceptual model emphasizing the need to distinguish climatic and human effects in gauging progress to reverse eutrophication in estuarine-coastal ecosystems.

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay.

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km(2) watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945-1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981-2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries.

Enumerating sparse organisms in ships' ballast water: why counting to 10 is not so easy.

To reduce ballast water-borne aquatic invasions worldwide, the International Maritime Organization and United States Coast Guard have each proposed discharge standards specifying maximum concentrations of living biota that may be released in ships' ballast water (BW), but these regulations still lack guidance for standardized type approval and compliance testing of treatment systems. Verifying whether BW meets a discharge standard poses significant challenges. Properly treated BW will contain extremely sparse numbers of live organisms, and robust estimates of rare events require extensive sampling efforts. A balance of analytical rigor and practicality is essential to determine the volume of BW that can be reasonably sampled and processed, yet yield accurate live counts. We applied statistical modeling to a range of sample volumes, plankton concentrations, and regulatory scenarios (i.e., levels of type I and type II errors), and calculated the statistical power of each combination to detect noncompliant discharge concentrations. The model expressly addresses the roles of sampling error, BW volume, and burden of proof on the detection of noncompliant discharges in order to establish a rigorous lower limit of sampling volume. The potential effects of recovery errors (i.e., incomplete recovery and detection of live biota) in relation to sample volume are also discussed.

Development of a provisional physical habitat index for Maryland freshwater streams.

Provisional physical habitat indices were developed and validated for Maryland Coastal and Non-Coastal Plain streams using variables (commonly called metrics) that best discriminated reference and degraded conditions based on biological, chemical and land use data from the 1994-97 Maryland Biological Stream Survey (MBSS). These habitat indices contained variables that described structural, hydrological, vegetative and aesthetic components of stream habitat. Variables with the best discriminatory power for Coastal Plain streams were: instream habitat, velocity/depth diversity, pool/glide/eddy quality, embeddedness, maximum depth and aesthetic rating. Physical habitat variables with the best discriminatory power for Non-Coastal Plain sites were: instream habitat, velocity/depth diversity, riffle/run quality, embeddedness, number of rootwads and aesthetic rating. The overall classification efficiency for index validation was 76% for both indices pooled over both strata. Scaled physical habitat index values (0-100) for both strata identified nearly twice as many good sites (31%) as very poor sites (16%). More than half the Maryland sites were in the poor to fair range (53%).