Analyses of water quality and driving forces in Ningde aquaculture area

Xiaoyan, 汪晓妍 Wang; Ting, 周婷 Zhou; Zimin, 应紫敏 Ying; Jing, 吴静 Wu; Wu, 杨武 Yang

doi:10.5846/stxb201901240180

Cited by 3 publications

(3 citation statements)

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“…Aquaculture has a substantial impact on the water environment of coastal ecosystems (Wu et al, 2022). As an important aquaculture bay, Sansha Bay has been reported in a state of heavy pollution and high eutrophication level after a long-period observation (Wang et al, 2020). The variation of nutrients was controlled by river discharge (Niu et al, 2021;Chen et al, 2022).…”

Section: Effects Of Aquaculture On Environmental Parametersmentioning

confidence: 99%

Spatio-temporal dynamics of the carbonate system during macroalgae farming season in a semi-closed bay in southeast China

Zhang,

Wang,

Lei

et al. 2024

Front. Mar. Sci.

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Ocean Negative Carbon Emission (ONCE) involves utilizing natural marine chemistry and biology, along with mariculture, to achieve carbon sink goals. Growing awareness of the interplay between aquaculture and the coastal carbonate system has drawn researchers’ attention amid ring CO2 concentrations and the negative impacts of aquaculture on the environment. In this study, twelve sites representing different maricultural types were selected, including macroalgae, shellfish, fish, and non-farming areas. The environmental factors, dissolved inorganic carbon (DIC), total alkalinity (TA), and pCO2, were measured monthly during kelp farming periods. Nitrate is a major component of total nitrogen, and the NO3-N concentration in the macroalgal culture zone was lower than others, indicating effective nitrogen removal by macroalgae aquaculture. TA and DIC in non-farmed areas demonstrated larger variation ranges than in farming areas, probably due to the effects of precipitation on salinity. Aquaculture activities effectively maintained TA and DIC, with macroalgae cultivation playing an important role in TA stability, potentially resisting acidification. The pCO2sea-air of macroalgae culture areas in spring was slightly negative, suggesting carbon sink potential. However, further research is needed to assess the full extent of this “fourth type” of blue carbon, including accurate carbon footprint calculation and the contributions of particulate organic carbon and recalcitrant dissolved organic carbon. This study provided insight into the comprehensive contribution of different aquaculture types to the fishery environment and carbonate system, which can help guide aquaculture management and facilitate the carbon-neutral transition of aquaculture.

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Section: Effects Of Aquaculture On Environmental Parametersmentioning

confidence: 99%

Spatio-temporal dynamics of the carbonate system during macroalgae farming season in a semi-closed bay in southeast China

Zhang,

Wang,

Lei

et al. 2024

Front. Mar. Sci.

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“…As shown in Figures 4 and A1, for example, mariculture was eliminated in the west channel of Zhao'an Bay and the north of Bachi Gate. The establishment of new units far from existing mariculture units has been demonstrated to effectively mitigate the negative impacts of a high mariculture density [74]. However, following the introduction of integrated mariculture management by the government in the bay in 2021, the mariculture density increased in some areas because of livelihood pressures (Figures 4 and A1), and these maintained a high pressure on the ecosystem in the bay.…”

Section: Main Drivers Of Mariculture Dynamicsmentioning

confidence: 99%

A Google Earth Engine-Based Framework to Identify Patterns and Drivers of Mariculture Dynamics in an Intensive Aquaculture Bay in China

Wang

Liu

et al. 2023

Remote Sensing

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Although mariculture contributes significantly to regional/local economic development, it also promotes environmental degradation. Therefore, it is essential to understand mariculture dynamics before taking adaptive measures to deal with it. In the present study, a framework that integrates the Google Earth Engine (GEE) based methods and GeoDetector software was developed to identify patterns and drivers of mariculture dynamics. This framework was then applied to Zhao’an Bay, which is an intensive aquaculture bay in Coastal China, based on Landsat 8 OLI (2013–2022) and Sentinel-2 (December 2015–May 2022) data. The results show that the GEE-based method produces acceptable classification accuracy. The overall accuracy values for the interpretation are >85%, where the kappa coefficients are >0.9 for all years, excluding 2015 (0.83). Mariculture increased in the study area from 2013 to 2022, and this is characterised by distinct spatiotemporal variations. Cage mariculture is primarily concentrated around islands, whereas raft mariculture is dominant in bay areas, and pond and mudflat mariculture types are mostly in nearshore areas. The growth of mariculture in Zhao’an Bay is attributed to a combination of geographic and human factors. The initial area associated with mariculture in a grid significantly impacted the expansion of the raft, cage, and mudflat mariculture. The distance to an island, spatial proximity to similar types of mariculture and types of mariculture are the main drivers of change in mariculture. Human activities greatly contribute to the dynamics of mudflat mariculture; regulation regarding the clearing of waterways directly impacts the dynamics of mariculture. The present study demonstrates that the proposed framework facilitates the effective monitoring of the mariculture dynamics and identification of driving factors. These findings can be exploited for the local planning and management of mariculture in similar coastal bays.

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“…In the mariculture process, a large amount of bait is provided, but only a portion of this bait is effectively used, and the rest is discharged into the water column in the form of residual bait and excreta, including feces, forming endogenous pollutants in the water column (Li et al, 2021). Discharging pollutants into the ocean leads to increased nutrient levels in the marine ecosystem, posing a threat to the surrounding ecological environment (Wang et al, 2020;Yuan et al, 2020;.…”

Section: Introductionmentioning

confidence: 99%

Water quality parameters retrieval of coastal mariculture ponds based on UAV multispectral remote sensing

Zhang,

Jing,

Deng

et al. 2023

Front. Environ. Sci.

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The rapid expansion of aquaculture in coastal areas is typically associated with ecological negligence and low water quality owing to the economic exploitation of these areas. However, evaluation of these water bodies tends to be laborious, time-consuming, and costly. Therefore, to overcome the limitations of field surveys, in this study, we evaluated the water quality of the cultured water in the Beibu Gulf of Guangxi, obtained spectral reflectance by unmanned aerial vehicle with multispectral sensors, and constructed inverse models of 11 water quality parameters, namely, ammonia nitrogen (NH3-N), chemical oxygen demand (COD), active phosphate (PO4−), dissolved oxygen, nitrate nitrogen (NO3-N), nitrite nitrogen (NO2-N), inorganic nitrogen, total nitrogen, total phosphorus, suspended solids (SS), and chlorophyll a (chl-a), based on the partial least squares method to invert the water quality distribution of regional aquaculture. Furthermore, we compared the retrieval accuracy of different water quality parameters. The following results were obtained: 1) the constructed model’s results showed that the retrieval models for COD, NO3-N, SS, and chl-a had better accuracy compared with those of other parameters; 2) application of the model to the validation set data yielded a correlation coefficient of 0.93 between the measured and predicted SS values, with a mean absolute error of prediction of 4.65 mg L−1; this parameter constructed the best prediction model. According to the validation set results, the correlation coefficients of chl-a, COD and NO3-N are all greater than 0.8, which had better performance effects compared with the remaining models, which are 0.87, 0.86, and 0.81 respectively. This study provides a reference for remote sensing monitoring of water quality in mariculture in cloudy and rainy areas.

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Analyses of water quality and driving forces in Ningde aquaculture area

Cited by 3 publications

References 0 publications

Spatio-temporal dynamics of the carbonate system during macroalgae farming season in a semi-closed bay in southeast China

Spatio-temporal dynamics of the carbonate system during macroalgae farming season in a semi-closed bay in southeast China

A Google Earth Engine-Based Framework to Identify Patterns and Drivers of Mariculture Dynamics in an Intensive Aquaculture Bay in China

Water quality parameters retrieval of coastal mariculture ponds based on UAV multispectral remote sensing

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