Forecasting hypoxia in the Chesapeake Bay and Gulf of Mexico: model accuracy, precision, and sensitivity to ecosystem change

Increasing use of ecological models for management and policy requires robust evaluation of model precision, accuracy, and sensitivity to ecosystem change. We conducted such an evaluation of hypoxia models for the northern Gulf of Mexico and Chesapeake Bay using hindcasts of historical data, comparing several approaches to model calibration. For both systems we find that model sensitivity and precision can be optimized and model accuracy maintained within reasonable bounds by calibrating the model to relatively short, recent 3 year datasets. Model accuracy was higher for Chesapeake Bay than for the Gulf of Mexico, potentially indicating the greater importance of unmodeled processes in the latter system. Retrospective analyses demonstrate both directional and variable changes in sensitivity of hypoxia to nutrient loads.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90830/1/1748-9326_6_1_015001.pd

Exploring estuarine eutrophication sensitivity to nutrient loading

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109763/1/lno20135820569.pd

Measuring the ecological significance of microscale nutrient patches

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109789/1/lno19842910214.pd

How climate controls the flux of nitrogen by the Mississippi River and the development of hypoxia in the Gulf of Mexico

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110015/1/lno20075220856.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110015/2/0856a1.pd

Nutrient loading and meteorological conditions explain interannual variability of hypoxia in Chesapeake Bay

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109879/1/lno20145920373.pd

Assessing biophysical controls on Gulf of Mexico hypoxia through probabilistic modeling

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116353/1/eap2015252492.pd

Advancing estuarine ecological forecasts: seasonal hypoxia in Chesapeake Bay

Ecological forecasts are quantitative tools that can guide ecosystem management. The coemergence of extensive environmental monitoring and quantitative frameworks allows for widespread development and continued improvement of ecological forecasting systems. We use a relatively simple estuarine hypoxia model to demonstrate advances in addressing some of the most critical challenges and opportunities of contemporary ecological forecasting, including predictive accuracy, uncertainty characterization, and management relevance. We explore the impacts of different combinations of forecast metrics, drivers, and driver time windows on predictive performance. We also incorporate multiple sets of state-variable observations from different sources and separately quantify model prediction error and measurement uncertainty through a flexible Bayesian hierarchical framework. Results illustrate the benefits of (1) adopting forecast metrics and drivers that strike an optimal balance between predictability and relevance to management, (2) incorporating multiple data sources in the calibration data set to separate and propagate different sources of uncertainty, and (3) using the model in scenario mode to probabilistically evaluate the effects of alternative management decisions on future ecosystem state. In the Chesapeake Bay, the subject of this case study, we find that average summer or total annual hypoxia metrics are more predictable than monthly metrics and that measurement error represents an important source of uncertainty. Application of the model in scenario mode suggests that absent watershed management actions over the past decades, long-term average hypoxia would have increased by 7% compared to 1985. Conversely, the model projects that if management goals currently in place to restore the Bay are met, long-term average hypoxia would eventually decrease by 32% with respect to the mid- 1980

Coastal eutrophication assessment in the United States

Recent national assessments document that nitrogen-driven coastal eutrophication is widespread and increasing in the United States. This significant coastal pollution problem includes impacts including increased areas and severity of hypoxic and anoxic waters; alteration of food webs; degradation and loss of sea grass beds, kelp beds and coral reefs; loss of biodiversity; and increased incidences and duration of harmful algal blooms. In this paper, we review two complementary approaches to assessing the causes and consequences of these trends, as well as potential remedies for them. The first is a national-scale assessment, drawn primarily from expert knowledge of those most familiar with the individual estuaries and integrated into a common analysis framework. The second approach, focused on the Mississippi/Atchafalaya basin – the largest US drainage basin – draws upon both quantitative and qualitative analyses within a comprehensive framework, Integrated Assessment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46795/1/10533_2006_Article_9011.pd

Nutrient Loss Rates in Relation to Transport Time Scales in a Large Shallow Lake (Lake St. Clair, USA—Canada): Insights From a Three‐Dimensional Model

A nutrient mass balance and a three‐dimensional, coupled hydrodynamic‐ecological model, calibrated and validated for Lake St. Clair with observations from 2009 and 2010, were integrated to estimate monthly lake‐scale nutrient loss rates, and to calculate 3 monthly transport time scales: flushing time, water age, and water residence time. While nutrient loss rates had statistically significant relationships with all transport time scale measures, water age had the strongest explanatory power, with water age and nutrient loss rates both smaller in spring and fall and larger in summer. We show that Lake St. Clair is seasonally divided into two discrete regions of contrasting water age and productivity. The north‐western region is dominated by oligotrophic waters from the St. Clair River, and south‐eastern region is dominated by the nutrient enriched, more productive waters from the Thames‐Sydenham River complex. The spatial and temporal variations in local transport scales and nutrient loss rates, coupled with strong seasonal variations in discharge and nutrient loads from the major tributaries, suggest the need for different load reduction strategies for different tributaries.Key PointsWe applied a three‐dimensional ecosystem model to simulate physical, chemical, and biological dynamics in a large shallow lakeWe found that spatially dependent water residence time represents lake flushing better than traditional flushing timeWater age influences the spatial and temporal distribution of nutrient retention, primary production, and algal biomass distributionPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145320/1/wrcr23330.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145320/2/wrcr23330_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145320/3/wrcr23330-sup-0001-2017WR021876-s01.pd