scholarly journals Estimating Hypoxic Volume in the Chesapeake Bay Using Two Continuously Sampled Oxygen Profiles

2018 ◽  
Vol 123 (9) ◽  
pp. 6392-6407 ◽  
Author(s):  
Aaron J. Bever ◽  
Marjorie A. M. Friedrichs ◽  
Carl T. Friedrichs ◽  
Malcolm E. Scully
Keyword(s):  
Chesapeake Bay ◽  
Hypoxic Volume ◽  
Oxygen Profiles

scholarly journals The Importance of Climate Variability to Wind-Driven Modulation of Hypoxia in Chesapeake Bay

2010 ◽  
Vol 40 (6) ◽  
pp. 1435-1440 ◽  
Author(s):  
Malcolm E. Scully
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Chesapeake Bay ◽  
Wind Direction ◽  
Large Scale ◽  
Nitrogen Loading ◽  
Nutrient Inputs ◽  
Westerly Direction ◽  
Hypoxic Volume

Abstract Extensive hypoxia remains a problem in Chesapeake Bay, despite some reductions in estimated nutrient inputs. An analysis of a 58-yr time series of summer hypoxia reveals that a significant fraction of the interannual variability observed in Chesapeake Bay is correlated to changes in summertime wind direction that are the result of large-scale climate variability. Beginning around 1980, the surface pressure associated with the summer Bermuda high has weakened, favoring winds from a more westerly direction, the direction most correlated with observed hypoxia. Regression analysis suggests that the long-term increase in hypoxic volume observed in this dataset is only accounted for when both changes in wind direction and nitrogen loading are considered.

scholarly journals Combining observations and numerical model results to improve estimates of hypoxic volume within the Chesapeake Bay, USA

2013 ◽  
Vol 118 (10) ◽  
pp. 4924-4944 ◽  
Author(s):  
Aaron J. Bever ◽  
Marjorie A. M. Friedrichs ◽  
Carl T. Friedrichs ◽  
Malcolm E. Scully ◽  
Lyon W. J. Lanerolle
Keyword(s):  
Numerical Model ◽  
Chesapeake Bay ◽  
Hypoxic Volume

Ranking ecosystem impacts on Chesapeake Bay blue crab (Callinectes sapidus) using empirical Gaussian Graphical Models

2020 ◽  
Author(s):  
Dong Liang ◽  
Geneviève M. Nesslage ◽  
Michael J Wilberg ◽  
Thomas J. Miller
Keyword(s):  
Chesapeake Bay ◽  
Blue Crab ◽  
Graphical Models ◽  
Callinectes Sapidus ◽  
Abiotic Factors ◽  
Multivariate Adaptive Regression Splines ◽  
Catch Per Unit Effort ◽  
Gaussian Graphical Models ◽  
Ecosystem Impacts ◽  
Hypoxic Volume

Moving toward ecosystem-based fisheries management requires integration of biotic and abiotic factors into our understanding of population dynamics. Using blue crab (Callinectes sapidus) in the Chesapeake Bay as a model system, we applied Gaussian Graphical Models (GGMs) to understand the influence of climatic, water quality and biotic variables on estimates of key indices of blue crab recruitment for 1990‐2017. Variables included the North Atlantic Oscillation (NAO), Susquehanna River discharge, wind forcing, hypoxic volume, submerged aquatic vegetation and the catch-per-unit-effort of striped bass (Morone saxatilis). Direct effects of age‐1+ crabs and summer salinity on recruitment were significant. Phase of the NAO in summer and spring, summer and winter discharge, and hypoxic volume indirectly affected the recruitment. A simulation study shows that GGM model selection achieved nominal coverage and outperformed structural equation models (SEM) and Multivariate Adaptive Regression Splines (MARS). GGMs have the potential to improve ecosystem-based management of blue crabs in Chesapeake Bay. Specifically, the approach can be used to examine ecosystem impacts on blue crab productivity and to improve forecasts of blue crab recruitment.

scholarly journals Predicting the Hypoxic-Volume in Chesapeake Bay with the Streeter-Phelps Model: A Bayesian Approach1

2011 ◽  
Vol 47 (6) ◽  
pp. 1348-1363 ◽  
Author(s):  
Yong Liu ◽  
George B. Arhonditsis ◽  
Craig A. Stow ◽  
Donald Scavia
Keyword(s):  
Chesapeake Bay ◽  
Hypoxic Volume

Between ‘Savage Man’ and ‘Most Faithful Englishman’ Manteo and the Early Anglo-Indian Exchange, 1584–1590

Itinerario ◽  
2000 ◽  
Vol 24 (2) ◽  
pp. 146-169 ◽  
Author(s):  
Michael Leroy Oberg
Keyword(s):  
North Carolina ◽  
Chesapeake Bay ◽  
One Year ◽  
Anglo Indian

In August of 1587 Manteo, an Indian from Croatoan Island, joined a group of English settlers in an attack on the native village of Dasemunkepeuc, located on the coast of present-day North Carolina. These colonists, amongst whom Manteo lived, had landed on Roanoke Island less than a month before, dumped there by a pilot more interested in hunting Spanish prize ships than in carrying colonists to their intended place of settlement along the Chesapeake Bay. The colonists had hoped to re-establish peaceful relations with area natives, and for that reason they relied upon Manteo to act as an interpreter, broker, and intercultural diplomat. The legacy of Anglo-Indian bitterness remaining from Ralph Lane's military settlement, however, which had hastily abandoned the island one year before, was too great for Manteo to overcome. The settlers found themselves that summer in the midst of hostile Indians.

Developing TMDLs for Local Impairments Consistent with the Regional Chesapeake Bay TMDL

2012 ◽  
Author(s):  
Gene Yagow ◽  
Brian Benham ◽  
Karen Kline ◽  
Becky Zeckoski ◽  
Carlington Wallace
Keyword(s):  
Chesapeake Bay

Spatial ecology and growth in early life stages of bay anchovy Anchoa mitchilli in Chesapeake Bay (USA)

2020 ◽  
Vol 651 ◽  
pp. 125-143
Author(s):  
TD Auth ◽  
T Arula ◽  
ED Houde ◽  
RJ Woodland
Keyword(s):  
Chesapeake Bay ◽  
Spatial Ecology ◽  
Environmental Variability ◽  
Larval Growth ◽  
Larval Abundance ◽  
Spatial And Temporal Variability ◽  
Estuarine Ecosystem ◽  
Anchoa Mitchilli ◽  
Larval Production ◽  
Bay Anchovy

The bay anchovy Anchoa mitchilli is the most abundant fish in Chesapeake Bay (USA) and is a vital link between plankton and piscivores within the trophic structure of this large estuarine ecosystem. Baywide distributions and abundances of bay anchovy eggs and larvae, and larval growth, were analyzed in a 5 yr program to evaluate temporal and spatial variability based on research surveys in the 1995-1999 spawning seasons. Effects of environmental variability and abundance of zooplankton that serve as prey for larval bay anchovy were analyzed. In the years of these surveys, 97.6% of eggs and 98.8% of larvae occurred in the polyhaline lower bay. Median egg and larval abundances differed more than 10-fold for surveys conducted in the 5 yr and were highest in the lower bay. Within years, median larval abundance (ind. m-2) in the lower bay was generally 1-2 orders of magnitude higher than upper-bay abundance. Salinity, temperature, and dissolved oxygen explained 12% of the spatial and temporal variability in egg abundances and accounted for 27% of the variability in larval abundances. The mean, baywide growth rate for larvae over the 5 yr period was 0.75 ± 0.01 mm d-1, and was best explained by zooplankton concentration and feeding incidence. Among years, mean growth rates ranged from 0.68 (in 1999) to 0.81 (in 1998) mm d-1 and were fastest in the upper bay. We identified environmental factors, especially salinity, that contributed to broadscale variability in egg and larval production.

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