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Donald Scavia

Publications and source records attributed to Donald Scavia.

17 recordsLinked to original sources
USGS2021

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-1980s.

Chesapeake Bay↗
USGS2021

Uncertainty in critical source area predictions from watershed-scale hydrologic models

Watershed-scale hydrologic models are frequently used to inform conservation and restoration efforts by identifying critical source areas (CSAs; alternatively 'hotspots'), defined as areas that export relatively greater quantities of nutrients and sediment. The CSAs can then be prioritized or ‘targeted’ for conservation and restoration to ensure efficient use of limited resources. However, CSA simulations from watershed-scale hydrologic models may be uncertain and it is critical that the extent and implications of this uncertainty be conveyed to stakeholders and decision makers. We used an ensemble of four independently developed Soil and Water Assessment Tool (SWAT) models and a SPAtially Referenced Regression On Watershed attributes (SPARROW) model to simulate CSA locations for flow, phosphorus, nitrogen, and sediment within the ~17,000-km 2 Maumee River watershed at the HUC-12 scale. We then assessed uncertainty in CSA simulations determined as the variation in CSA locations across the models. Our application of an ensemble of models - differing with respect to inputs, structure, and parameterization - facilitated an improved accounting of CSA prediction uncertainty. We found that the models agreed on the location of a subset of CSAs, and that these locations may be targeted with relative confidence. However, models more often disagreed on CSA locations. On average, only 16%–46% of HUC-12 subwatersheds simulated as a CSA by one model were also simulated as a CSA by a different model. Our work shows that simulated CSA locations are highly uncertain and may vary substantially across models. Hence, while models may be useful in informing conservation and restoration planning, their application to identify CSA locations would benefit from comprehensive uncertainty analyses to avoid inefficient use of limited resources.

Ohio↗
USGS2021

Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models

Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets.

Michigan↗
USGS2021

Elucidating controls on cyanobacteria bloom timing and intensity via Bayesian mechanistic modeling

The adverse impacts of harmful algal blooms (HABs) are increasing worldwide. Lake Erie is a North American Great Lake highly affected by cultural eutrophication and summer cyanobacterial HABs. While phosphorus loading is a known driver of bloom size, more nuanced yet crucial questions remain. For example, it is unclear what mechanisms are primarily responsible for initiating cyanobacterial dominance and subsequent biomass accumulation. To address these questions, we develop a mechanistic model describing June–October dynamics of chlorophyll a , nitrogen, and phosphorus near the Maumee River outlet, where blooms typically initiate and are most severe. We calibrate the model to a new, geostatistically-derived dataset of daily water quality spanning 2008–2017. A Bayesian framework enables us to embed prior knowledge on system characteristics and test alternative model formulations. Overall, the best model formulation explains 42% of the variability in chlorophyll a and 83% of nitrogen, and better captures bloom timing than previous models. Our results, supported by cross validation, show that onset of the major midsummer bloom is associated with about a month of water temperatures above 20 °C (occurring 19 July to 6 August), consistent with when cyanobacteria dominance is usually reported. Decreased phytoplankton loss rate is the main factor enabling biomass accumulation, consistent with reduced zooplankton grazing on cyanobacteria. The model also shows that phosphorus limitation is most severe in August, and nitrogen limitation tends to occur in early autumn. Our results highlight the role of temperature in regulating bloom initiation and subsequent loss rates, and suggest that a 2 °C increase could lead to blooms that start about 10 days earlier and grow 23% more intense.

Michigan, Ohio↗
USGS2019

A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent

Harmful algal blooms (HABs) have been increasing in intensity across many waterbodies worldwide, including the western basin of Lake Erie. Substantial efforts have been made to track these blooms using in situ sampling and remote sensing. However, such measurements do not fully capture HAB spatial and temporal dynamics due to the limitations of discrete shipboard sampling over large areas and the effects of clouds and winds on remote sensing estimates. To address these limitations, we develop a space-time geostatistical modeling framework to improve estimates of HAB timing, extent, and intensity using five independent sets of chlorophyll a (chl-a) data sampled from June to October, 2008 to 2017. Based on the Bayesian information criterion for model selection, trend variables explain bloom northerly and easterly expansion from Maumee Bay, wind effects over depth, and variability among sampling methods. Cross validation results indicate the model can estimate daily, location-specific chl-a concentrations with reasonable accuracy (R2 = 55%) between monitoring cruises. Conditional simulations provide probabilistic estimates of algal biomass and surface areal extent, which are compared to remote sensing estimates. The simulations also provide, for the first time, comprehensive estimates of overall bloom biomass based on depth-integrated concentrations, with quantified uncertainties. These estimates enhance our understanding of HAB variability and can inform HAB monitoring network design, predictive modeling, and management.

Lake Erie↗
USGS2017

Multiple models guide strategies for agricultural nutrient reductions

In response to degraded water quality, federal policy makers in the US and Canada called for a 40% reduction in phosphorus (P) loads to Lake Erie, and state and provincial policy makers in the Great Lakes region set a load-reduction target for the year 2025. Here, we configured five separate SWAT (US Department of Agriculture's Soil and Water Assessment Tool) models to assess load reduction strategies for the agriculturally dominated Maumee River watershed, the largest P source contributing to toxic algal blooms in Lake Erie. Although several potential pathways may achieve the target loads, our results show that any successful pathway will require large-scale implementation of multiple practices. For example, one successful pathway involved targeting 50% of row cropland that has the highest P loss in the watershed with a combination of three practices: subsurface application of P fertilizers, planting cereal rye as a winter cover crop, and installing buffer strips. Achieving these levels of implementation will require local, state/provincial, and federal agencies to collaborate with the private sector to set shared implementation goals and to demand innovation and honest assessments of water quality-related programs, policies, and partnerships.

Frontiers in Ecology and the Environment↗
USGS2016

Informing Lake Erie agriculture nutrient management via scenario evaluation

Harmful algal blooms (HABs) have been increasing in extent and intensity in the western basin of Lake Erie. The cyanobacteria Microcystis produces toxins that pose serious threats to animal and human health, resulting in beach closures and impaired water supplies, and have even forced a “do not drink” advisory for the City of Toledo water system for several days in the summer of 2014. The main driver of Lake Erie HABs is elevated phosphorus loading from watersheds draining to the western basin, particularly from the Maumee River watershed (Obenour et al. 2014). Through the 2012 Great Lakes Water Quality Agreement (GLWQA), the U.S. and Canadian governments agreed to revise Lake Erie phosphorus loading targets to decrease HAB severity below levels representing a hazard to ecosystem and human health. New targets limit March-July loadings from the Maumee River to 186 metric tonnes of dissolved reactive phosphorus (DRP) and 860 metric tonnes of total phosphorus (TP) – a 40% reduction from 2008 loads (GLWQA 2016). The Great Lakes region must now determine what policy options are most effective and feasible for meeting those targets. While all sources are important, our focus is on agriculture because it overwhelms other sources. In a conservative ballpark estimate we found that 85% of the Maumee River’s load to Lake Erie comes from farm fertilizers and manures, even though this is only 10% of farmland fertilizer applications (Figure 1). Load targets will not be met without reductions from agriculture. Therefore, the overall goal of this study was to identify potential options for agricultural management to reduce phosphorus loads and lessen future HABs in Lake Erie. We applied multiple watershed models to test the ability of a series of land management scenarios, developed in consultation with agricultural and environmental stakeholders, to reach the proposed targets.

Indiana, Michigan, Ohio↗
USGS2014

Assessing and addressing the re-eutrophication of Lake Erie: central basin hypoxia

Relieving phosphorus loading is a key management tool for controlling Lake Erie eutrophication. During the 1960s and 1970s, increased phosphorus inputs degraded water quality and reduced central basin hypolimnetic oxygen levels which, in turn, eliminated thermal habitat vital to cold-water organisms and contributed to the extirpation of important benthic macroinvertebrate prey species for fishes. In response to load reductions initiated in 1972, Lake Erie responded quickly with reduced water-column phosphorus concentrations, phytoplankton biomass, and bottom-water hypoxia (dissolved oxygen < 2 mg/l). Since the mid-1990s, cyanobacteria blooms increased and extensive hypoxia and benthic algae returned. We synthesize recent research leading to guidance for addressing this re-eutrophication, with particular emphasis on central basin hypoxia. We document recent trends in key eutrophication-related properties, assess their likely ecological impacts, and develop load response curves to guide revised hypoxia-based loading targets called for in the 2012 Great Lakes Water Quality Agreement. Reducing central basin hypoxic area to levels observed in the early 1990s (ca. 2000 km 2 ) requires cutting total phosphorus loads by 46% from the 2003–2011 average or reducing dissolved reactive phosphorus loads by 78% from the 2005–2011 average. Reductions to these levels are also protective of fish habitat. We provide potential approaches for achieving those new loading targets, and suggest that recent load reduction recommendations focused on western basin cyanobacteria blooms may not be sufficient to reduce central basin hypoxia to 2000 km 2 .

Great Lakes;Lake Erie↗
USGS2014

2014 Gulf of Mexico Hypoxia Forecast

The Gulf of Mexico annual summer hypoxia forecasts are based on average May total nitrogen loads from the Mississippi River basin for that year. The load estimate, recently released by USGS, is 4,761 metric tons per day. Based on that estimate, we predict the area of this summer’s hypoxic zone to be 14,000 square kilometers (95% credible interval, 8,000 to 20,000) – an “average year”. Our forecast hypoxic volume is 50 km 3 (95% credible interval, 20 to 77).

Gulf Of Mexico↗
USGS2013

A scenario and forecast model for Gulf of Mexico hypoxic area and volume

For almost three decades, the relative size of the hypoxic region on the Louisiana-Texas continental shelf has drawn scientific and policy attention. During that time, both simple and complex models have been used to explore hypoxia dynamics and to provide management guidance relating the size of the hypoxic zone to key drivers. Throughout much of that development, analyses had to accommodate an apparent change in hypoxic sensitivity to loads and often cull observations due to anomalous meteorological conditions. Here, we describe an adaptation of our earlier, simple biophysical model, calibrated to revised hypoxic area estimates and new hypoxic volume estimates through Bayesian estimation. This application eliminates the need to cull observations and provides revised hypoxic extent estimates with uncertainties, corresponding to different nutrient loading reduction scenarios. We compare guidance from this model application, suggesting an approximately 62% nutrient loading reduction is required to reduce Gulf hypoxia to the Action Plan goal of 5,000 km 2 , to that of previous applications. In addition, we describe for the first time, the corresponding response of hypoxic volume. We also analyze model results to test for increasing system sensitivity to hypoxia formation, but find no strong evidence of such change.

Environmental Science & Technology↗
USGS2013

2013 Gulf of Mexico Hypoxia Forecast

The Gulf of Mexico annual summer hypoxia forecasts are based on average May total nitrogen loads from the Mississippi River basin for that year. The load estimate, recently released by USGS, is 7,316 metric tons per day. Based on that estimate, we predict the area of this summer’s hypoxic zone to be 18,900 square kilometers (95% credible interval, 13,400 to 24,200), the 7th largest reported and about the size of New Jersey. Our forecast hypoxic volume is 74.5 km 3 (95% credible interval, 51.5 to 97.0), also the 7th largest on record.

Report↗
USGS2011

Effects of hypoxia on consumption, growth, and RNA:DNA ratios of young Yellow Perch

As in various freshwater and coastal marine ecosystems worldwide, seasonal bottom water hypoxia is a recurring phenomenon in Lake Erie’s central basin. While bottom hypoxia can strongly affect sessile benthic animals, its effects on mobile organisms such as fish are less understood. We evaluated the potential for bottom hypoxia to affect the growth rates of yellow perch Perca flavescens, a species of ecological and economic importance in the lake. To this end, we (1) conducted laboratory experiments to quantify the effects of reduced dissolved oxygen on consumption, somatic growth, and RNA:DNA ratios (an index of short-term growth) of young yellow perch and (2) explored the effects of bottom hypoxia on young yellow perch growth in Lake Erie’s central basin by collecting individuals in hypoxic and normoxic regions of the lake and quantifying their RNA:DNA ratios. Yellow perch consumption and growth in our experiments declined under hypoxic conditions (≤2 mg O2/L). While yellow perch RNA:DNA ratios responded strongly to experimental temperature, nucleic acid ratios were not significantly affected by dissolved oxygen or feeding ration. We did, however, observe a positive correlation between yellow perch growth and RNA:DNA ratios at low temperatures (11◦C). The nucleic acid ratios of yellow perch collected in Lake Erie varied spatiotemporally, but their patterns were not consistent with hypoxia. In short, while yellow perch consumption and growth rates respond directly and negatively to low oxygen conditions, these responses are not necessarily reflected in RNA:DNA ratios. Moreover, in central Lake Erie, where yellow perch can behaviorally avoid hypoxic areas, the RNA:DNA ratios of yellow perch do not respond strongly to bottom hypoxia. Thus, this study suggests that there is no strong negative effect of bottom hypoxia on the growth of young yellow perch in Lake Erie.

Transactions of the American Fisheries Society↗
USGS2010

Seasonal and interannual effects of hypoxia on fish habitat quality in central Lake Erie

1. Hypoxia occurs seasonally in many stratified coastal marine and freshwater ecosystems when bottom dissolved oxygen (DO) concentrations are depleted below 2–3 mg O 2 L -1 . 2. We evaluated the effects of hypoxia on fish habitat quality in the central basin of Lake Erie from 1987 to 2005, using bioenergetic growth rate potential (GRP) as a proxy for habitat quality. We compared the effect of hypoxia on habitat quality of (i) rainbow smelt, Osmerus mordax mordax Mitchill (young-of-year, YOY, and adult), a cold-water planktivore, (ii) emerald shiner, Notropis atherinoides Rafinesque (adult), a warm-water planktivore, (iii) yellow perch, Perca flavescens Mitchill (YOY and adult), a cool-water benthopelagic omnivore and (iv) round goby Neogobius melanostomus Pallas (adult) a eurythermal benthivore. Annual thermal and DO profiles were generated from 1D thermal and DO hydrodynamics models developed for Lake Erie’s central basin. 3. Hypoxia occurred annually, typically from mid-July to mid-October, which spatially and temporally overlaps with otherwise high benthic habitat quality. Hypoxia reduced the habitat quality across fish species and life stages, but the magnitude of the reduction varied both among and within species because of the differences in tolerance to low DO levels and warm-water temperatures. 4. Across years, trends in habitat quality mirrored trends in phosphorus concentration and water column oxygen demand in central Lake Erie. The per cent reduction in habitat quality owing to hypoxia was greatest for adult rainbow smelt and round goby (mean: -35%), followed by adult emerald shiner (mean: -12%), YOY rainbow smelt (mean: -10%) and YOY and adult yellow perch (mean: -8.5%). 5. Our results highlight the importance of differential spatiotemporally interactive effects of DO and temperature on relative fish habitat quality and quantity. These effects have the potential to influence the performance of individual fish species as well as population dynamics, trophic interactions and fish community structure.

Lake Erie↗
USGS2002

Climate change impacts on U.S. coastal and marine ecosystems

Increases in concentrations of greenhouse gases projected for the 21st century are expected to lead to increased mean global air and ocean temperatures. The National Assessment of Potential Consequences of Climate Variability and Change (NAST 2001) was based on a series of regional and sector assessments. This paper is a summary of the coastal and marine resources sector review of potential impacts on shorelines, estuaries, coastal wetlands, coral reefs, and ocean margin ecosystems. The assessment considered the impacts of several key drivers of climate change: sea level change; alterations in precipitation patterns and subsequent delivery of freshwater, nutrients, and sediment; increased ocean temperature; alterations in circulation patterns; changes in frequency and intensity of coastal storms; and increased levels of atmospheric CO 2 . Increasing rates of sea-level rise and intensity and frequency of coastal storms and hurricanes over the next decades will increase threats to shorelines, wetlands, and coastal development. Estuarine productivity will change in response to alteration in the timing and amount of freshwater, nutrients, and sediment delivery. Higher water temperatures and changes in freshwater delivery will alter estuarine stratification, residence time, and eutrophication. Increased ocean temperatures are expected to increase coral bleaching and higher CO 2 levels may reduce coral calcification, making it more difficult for corals to recover from other disturbances, and inhibiting poleward shifts. Ocean warming is expected to cause poleward shifts in the ranges of many other organisms, including commercial species, and these shifts may have secondary effects on their predators and prey. Although these potential impacts of climate change and variability will vary from system to system, it is important to recognize that they will be superimposed upon, and in many cases intensify, other ecosystem stresses (pollution, harvesting, habitat destruction, invasive species, land and resource use, extreme natural events), which may lead to more significant consequences.

Estuaries↗