Exploring effects of hypoxia on fish and fisheries in the northern Gulf of Mexico using a dynamic spatially explicit ecosystem model

Mutsert, Kim de; Steenbeek, Jeroen; Lewis, Kristy A.; Buszowski, Joe; Cowan, James H.; Christensen, Villy

doi:10.1016/j.ecolmodel.2015.10.013

Cited by 74 publications

(56 citation statements)

References 24 publications

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“…Q was set to 1000 (about 40 days), which was a representative of the times to 50% mortality for prey types eaten by croaker (Fig. 3 in VaquerSunyer and Duarte 2008), and γ was set to 3.47 × 10 −4 based on production to biomass ratio value of 2 year −1 (ArrequinSanchez et al 2002;de Mutsert et al 2016) and assuming the production occurs for 240 days of the year. We also included an unrealistic simulation of 50% mortality occurring after only 4 days (Q = 100 h) to demonstrate that the model could predict a croaker population response.…”

Section: Simulation Set 2: Hypoxia-induced Benthic Mortalitymentioning

confidence: 99%

Modeling the Population Effects of Hypoxia on Atlantic Croaker (Micropogonias undulatus) in the Northwestern Gulf of Mexico: Part 2—Realistic Hypoxia and Eutrophication

Rose

Creekmore

Justić

et al. 2017

Estuaries and Coasts

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Quantifying the population-level effects of hypoxia on coastal fish species has been challenging. In the companion paper (part 1), we described an individual-based population model (IBM) for Atlantic croaker in the northwestern Gulf of Mexico (NWGOM) designed to quantify the long-term population responses to low dissolved oxygen (DO) concentrations during the summer. Here in part 2, we replace the idealized hypoxia conditions with realistic DO concentrations generated from a 3-dimensional water quality model. Three years were used and randomly arranged into a time series based on the historical occurrence of mild, intermediate, and severe hypoxia year types. We also used another water quality model to generate multipliers of the chlorophyll concentrations to reflect that croaker food can be correlated to the severity of hypoxia. Simulations used 100 years under normoxia and hypoxia conditions to examine croaker population responses to the following: (1) hypoxia with food uncoupled and coupled to the severity of hypoxia, (2) hypoxia reducing benthos due to direct mortality, (3) how much hypoxia would need to be reduced to offset decreased croaker food expected under 25 and 50% reduction in nutrient loadings, and (4) key assumptions about avoidance movement. Direct mortality on benthos had no effect on long-term simulated croaker abundance, and the effect of hypoxia (about a 25% reduction in abundance) was consistent whether chlorophyll (food) varied with hypoxia or not. Reductions in hypoxia needed with a 25% reduction in nutrient loadings to result in minimal loss of croaker is feasible, and the croaker population will likely do as well as possible (approach abundance under normoxia) under the 50% reduction in nutrient loadings. We conclude with a discussion of why we consider our simulation-based estimates of hypoxia causing a 25% reduction the long-term population abundance of croaker in the NWGOM to be realistic and robust.

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Section: Simulation Set 2: Hypoxia-induced Benthic Mortalitymentioning

confidence: 99%

Modeling the Population Effects of Hypoxia on Atlantic Croaker (Micropogonias undulatus) in the Northwestern Gulf of Mexico: Part 2—Realistic Hypoxia and Eutrophication

Rose

Creekmore

Justić

et al. 2017

Estuaries and Coasts

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“…The model fit was performed using the sum of squares (SS) formula:

SS = {false\sum}_{i}^{normalnts} ({false\sum}_{i}^{{nob}_{s}} w_{i} log {(\frac{o_{it}}{p_{it}})}^{2})

where SS is the sum of squares, nts is the number of time series loaded, nob s is the number of observations in time series

i

, and

o_{italicit}

is the observed value in time series

i

at time step t (De Mutsert et al. ).…”

Section: Methodsmentioning

confidence: 99%

“…, De Mutsert et al. ) using ecological information of depth tolerance range for each functional group based on data obtained from Amire (), FishBase, and SeaLifeBase (Fig. ).…”

Section: Methodsmentioning

confidence: 99%

“…where SS is the sum of squares, nts is the number of time series loaded, nob s is the number of observations in time series i, and o it is the observed value in time series i at time step t (De Mutsert et al 2016).…”

Section: Model Calibration In Ecopath and Ecosimmentioning

confidence: 99%

“…The distribution maps used were drawn in ESRI ArcMaps 10.3, by using map data obtained from AquaMaps as templates on which EwE input maps were traced. In the habitat-based foraging interfaces, foraging response curves of groups based on their depth tolerance ranges were then defined with a variety of functional response curves (Romagnoni et al 2015, De Mutsert et al 2016) using ecological information of depth tolerance range for each functional group based on data obtained from Amire (2003), FishBase, and SeaLifeBase (Fig. 2).…”

Section: Ecospace Setupmentioning

confidence: 99%

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Spatial simulation of redistribution of fishing effort in Nigerian coastal waters using Ecospace

Adebola

Mutsert

2019

Ecosphere

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In the late 1990s, depletion of the target species Penaeus notialis (Pink Shrimp) in deeper waters (50 m) of the Nigerian coast resulted in a change of target species from P. notialis (Pink Shrimp) to shallower water species such as Penaeus monodon (Brown Shrimp). This study investigates the hypothesis that ecosystem impacts increased as industrial fleets increased fishing in shallower areas of the Nigerian coast by comparing the state of the ecosystem before and 20 yr after commercial shrimping commenced in Nigerian coastal waters (NCW). Two fishing scenarios were developed in Ecospace, the spatial modeling module of Ecopath with Ecosim software (Ecopath with Ecosim is a mass balanced trophic model that accounts for fishing impacts on food webs), with one having trawlers fishing everywhere beginning at the turn of the century (year 2000) and the other with no trawling in the first 5 nautical miles off the Nigerian coast through the entire period of model simulation (1985–2004). Modeling results showed increases in catch for some fisheries during the study period. In addition, estimated biomass for some functional groups increased especially for Small Pelagic fishes along with Rays, Reef fishes, Large Pelagics, and shallow water shrimps. All other exploited species in our modeling scenarios were estimated to have declining biomasses. Our expectation that redistribution of fishing effort in NCW will increase negative impacts of fishing the nearshore ecosystem was not supported by model results. This counterintuitive result may be because fishing effort on average was mostly distributed in the deeper areas of the inshore waters. Although specie such as Reef fishes appear to benefit from closure of the first 5 NM to fishing, the benefits appear to be negligible. We present the first ecosystem model developed for NCW, and our research contributes to fisheries ecology by furthering understanding of tropical coastal food webs and ecological response to fishing, especially in highly perturbed ecosystems like NCW.

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Key taxa in food web responses to stressors: the Deepwater Horizon oil spill

McCann

Able

Christian

et al. 2017

Frontiers in Ecol & Environ

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Identifying key taxa in the response of ecosystems to perturbations relies on quantifying both their sensitivity to stressors and their importance in the overall web of interactions. If sensitive taxa occupy key network positions, then they may decrease the capacity of ecosystems to resist perturbations. Despite widespread concern for coastal marshes after the 2010 Deepwater Horizon oil spill in the Gulf of Mexico, impacts on individual taxa were variable, and the effects on the overall marsh food web have not been assessed. Here, we synthesize published studies on trophic relationships and oil sensitivity to identify critical taxa in the response of marsh food webs to the oil spill. Taxa such as carnivorous marsh fishes are expected to enhance resilience, while gulls, terns, and omnivorous snails may destabilize the food web. Our framework for identifying key taxa can be applied to other environmental stressors or ecosystems if both the sensitivity of individual taxa to a stressor and the food web structure are known.

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Exploring effects of hypoxia on fish and fisheries in the northern Gulf of Mexico using a dynamic spatially explicit ecosystem model

Cited by 74 publications

References 24 publications

Modeling the Population Effects of Hypoxia on Atlantic Croaker (Micropogonias undulatus) in the Northwestern Gulf of Mexico: Part 2—Realistic Hypoxia and Eutrophication

Modeling the Population Effects of Hypoxia on Atlantic Croaker (Micropogonias undulatus) in the Northwestern Gulf of Mexico: Part 2—Realistic Hypoxia and Eutrophication

Spatial simulation of redistribution of fishing effort in Nigerian coastal waters using Ecospace

Key taxa in food web responses to stressors: the Deepwater Horizon oil spill

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