The impact of natural mortality variations on the performance of management procedures for Spanish mackerel (Scomberomorus niphonius) in the Yellow Sea, China

Abstract Fisheries managers use biological reference points (BRPs) as targets or limits on fishing and biomass to maintain productive levels of fish stock biomass. There are multiple ways to calculate BRPs when biological parameters are time varying. Using summer flounder (Paralichthys dentatus) as a case study, we investigated time-varying approaches in concert with climate-linked population models to understand the impact of environmentally driven variability in natural mortality, recruitment, and size-at-age on two commonly used BRPs [B0(t) and F35%(t)]. We used the following two approaches to calculate time-varying BRPs: dynamic-BRP and moving-average-BRP. We quantified the variability and uncertainty of different climate dependencies and estimation approaches, attributed BRP variation to variation in life-history processes, and evaluated how using different approaches impacts estimates of stock status. Results indicate that the dynamic-BRP approach using the climate-linked natural mortality model produced the least variable reference points compared to others calculated. Summer flounder stock status depended on the estimation approach and climate model used. These results emphasize that understanding climate dependencies is important for summer flounder reference points and perhaps other species, and careful consideration is warranted when considering what time-varying approach to use, ideally based upon simulation studies within a proposed set of management procedures.

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The Use of Remote Sensing Analysis for Evaluating the Impact of Development Projects in the Yellow Sea Large Marine Ecosystem

Sustainability ◽

10.3390/su12093628 ◽

2020 ◽

Vol 12 (9) ◽

pp. 3628

Author(s):

Gabriel Sidman ◽

Sydney Fuhrig ◽

Geeta Batra

Keyword(s):

Remote Sensing ◽

Time Series ◽

Yellow Sea ◽

Marine Pollution ◽

Marine Ecosystem ◽

Environmental Indicators ◽

The Yellow Sea ◽

Series Data ◽

Large Marine Ecosystem ◽

The Impact

Remote sensing has long been valued as a data source for monitoring environmental indicators and detecting trends in ecosystem stress from anthropogenic causes such as deforestation, river dams and air and water pollution. More recently, remote sensing analyses have been applied to evaluate the impacts of environmental projects and programs on reducing environmental stresses. Such evaluation has focused primarily on the change in above-surface vegetation such as forests. This study uses remote sensing ocean color products to evaluate the impact on reducing marine pollution of the Global Environment Facility’s (GEF) portfolio of projects in the Yellow Sea Large Marine Ecosystem. Chlorophyll concentration was derived from satellite images over a time series from the 1990s, when GEF projects began, until the present. Results show a 50% increase in chlorophyll until 2011 followed by a 34% decrease until 2019, showing a potential delayed effect of pollution control efforts. The rich time series data is a major advantage to using geospatial analysis for evaluating the impacts of environmental interventions on marine pollution. However, one drawback to the method is that it provides insights into correlations but cannot attribute the results to any particular cause, such as GEF interventions.

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Combining otolith elemental signatures with multivariate analytical models to verify the migratory pattern of Japanese Spanish mackerel (Scomberomorus niphonius) in the southern Yellow Sea

Acta Oceanologica Sinica ◽

10.1007/s13131-020-1606-0 ◽

2020 ◽

Vol 39 (12) ◽

pp. 54-64

Author(s):

Xindong Pan ◽

Zhenjiang Ye ◽

Binduo Xu ◽

Tao Jiang ◽

Jian Yang ◽

...

Keyword(s):

Yellow Sea ◽

Analytical Models ◽

Southern Yellow Sea ◽

Spanish Mackerel ◽

The Southern Yellow Sea ◽

Migratory Pattern ◽

Scomberomorus Niphonius

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Dissolved silicate in coastal marine rainwaters: Comparison between the Yellow Sea and the East China Sea on the impact and potential link with primary production

Journal of Geophysical Research Atmospheres ◽

10.1029/2004jd005411 ◽

2005 ◽

Vol 110 (D16) ◽

Cited By ~ 19

Author(s):

J. Zhang

Keyword(s):

Primary Production ◽

East China Sea ◽

Yellow Sea ◽

The Yellow Sea ◽

East China ◽

The East China Sea ◽

Coastal Marine ◽

Potential Link ◽

The Impact ◽

Dissolved Silicate

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Assessment of fish vulnerability to climate change in the Yellow Sea and Bohai Sea

Marine and Freshwater Research ◽

10.1071/mf19101 ◽

2020 ◽

Vol 71 (7) ◽

pp. 729

Author(s):

Yunlong Chen ◽

Xiujuan Shan ◽

Ning Wang ◽

Xianshi Jin ◽

Lisha Guan ◽

...

Keyword(s):

Climate Change ◽

Fish Species ◽

Yellow Sea ◽

Bohai Sea ◽

Fish Assemblages ◽

The Yellow Sea ◽

Risk Indices ◽

Vulnerability To Climate Change ◽

Impact Risk ◽

The Impact

Vulnerability assessments provide a feasible yet infrequently used approach to expanding our understanding and evaluating the effects of climate change on fish assemblages. Here, we first used a fuzzy-logic expert system to quantitatively estimate the vulnerability and potential impact risks of climate change for fish species in the Bohai Sea and Yellow Sea (BSYS). The mean (±s.d.) vulnerability and the impact-risk indices for 25 dominant fish species were 51±22 and 62±12 respectively (with the highest possible value being 100 under the Representative Concentration Pathway 8.5 scenario). Miiuy croaker (Miichthys miiuy) was found to have the highest impact risk, whereas the glowbelly (Acropoma japonicum) had the lowest. Demersal fishes tended to be more vulnerable than pelagic fishes, whereas the opposite was found for impact risks. No significant correlation was found between species biomass and vulnerability (P>0.05). The assessment provided a comprehensive framework for evaluating climate effects in the BSYS and suggested that interspecific and habitat group differences should be considered when developing future climate-adaptive fishery policies and management measures in this region, as well as similar systems elsewhere in the world.

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Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas

Scientific Reports ◽

10.1038/s41598-021-98994-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kun Liu ◽

Wuhong Guo ◽

Lianglong Da ◽

Jingyi Liu ◽

Huiqin Hu ◽

...

Keyword(s):

Data Assimilation ◽

Yellow Sea ◽

Thermal Structure ◽

The Yellow Sea ◽

Perturbation Approach ◽

Optimal Perturbation ◽

Sensitive Areas ◽

Targeted Observations ◽

Targeted Observation ◽

The Impact

AbstractTargeted observation is an appealing procedure for improving model predictions. However, studies on oceanic targeted observations have been largely based on modeling efforts, and there is a need for field validating operations. Here, we report the results of a field targeted observation that is designed based on the sensitive areas identified by the Conditional Nonlinear Optimal Perturbation approach to improve the 7th day thermal structure prediction in the Yellow Sea. By introducing the technique of cycle data assimilation and the new concept of time-varying sensitive areas, an observing strategy is designed and validated by a set of Observing System Simulation Experiments. Then, the impact of targeted observations was investigated by a choreographed field campaign in the summer of 2019. The results of the in-field Observing System Experiments show that, compared to conventional local data assimilation, conducting targeted observations in the sensitive areas can yield more benefit at the verification time. Furthermore, dynamic analysis demonstrates that the refinement of vertical thermal structures is mainly caused by the changes in the upstream horizontal temperature advection driven by the Yellow Sea Cold Water Mass circulation. This study highlights the effectiveness of targeted observations on reducing the forecast uncertainty in the ocean.

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