Artificial Upwelling in Singular and Recurring Mode: Consequences for Net Community Production and Metabolic Balance

Artificial upwelling of nutrient-rich waters and the corresponding boost in primary productivity harbor the potential to enhance marine fishery yields and strengthen the biological pump for sequestration of atmospheric CO2. There is increasing urgency to understand this technology as a “ocean-based solution” for counteracting two major challenges of the 21st century—climate change and overfishing. Yet, little is known about the actual efficacy and/or possible side effects of artificial upwelling. We conducted a large-scale off-shore mesocosm study (∼44 m3) in the oligotrophic waters of the Canary Islands to identify the community-level effects of artificial upwelling on a natural oligotrophic plankton community. Four upwelling intensities were simulated (approx. 1.5/3/5.7/10 μmol L–1 of nitrate plus phosphate and silicate) via two different upwelling modes (a singular deep-water pulse vs. recurring supply every 4 days) for 37 days. Here we present results on the response of net community production (NCP), metabolic balance and phytoplankton community composition (<250 μm). Higher upwelling intensities yielded higher cumulative NCP. Following upwelling onset, the phytoplankton community became dominated by diatoms in all treatments, but other taxa such as Coccolithophores increased later in the experiment. The magnitude of effects on the metabolic balance scaled with the amount of added deep water, leading to (i) a balanced to net-heterotrophic system in the singular and (ii) a net-autotrophic system in the recurring upwelling treatments. Accordingly, the mode in which nutrients are supplied to an oligotrophic system plays a crucial role in the ecosystem response, with recurring upwelling leading to higher long-term positive NCP than singular upwelling. These results highlight the importance of empirically measured local responses to upwelling such as community structure and metabolism, with major implications for the potential employment of artificial upwelling as an ocean-based solution to generate (primary) production.

Linkage mapping and QTL analysis of growth traits in Rhopilema esculentum

R. esculentum is a popular seafood in Asian countries and an economic marine fishery resource in China. However, the genetic linkage map and growth-related molecular markers are still lacking, hindering marker assisted selection (MAS) for genetic improvement of R. esculentum. Therefore, we firstly used 2b-restriction site-associated DNA (2b-RAD) method to sequence 152 R. esculentum specimens and obtained 9100 single nucleotide polymorphism (SNP) markers. A 1456.34 cM linkage map was constructed using 2508 SNP markers with an average interval of 0.58 cM. Then, six quantitative trait loci (QTLs) for umbrella diameter and body weight were detected by QTL analysis based on the new linkage map. The six QTLs are located on four linkage groups (LGs), LG4, LG13, LG14 and LG15, explaining 9.4% to 13.4% of the phenotypic variation. Finally, 27 candidate genes in QTLs regions of LG 14 and 15 were found associated with growth and one gene named RE13670 (sushi, von Willebrand factor type A, EGF and pentraxin domain-containing protein 1-like) may play an important role in controlling the growth of R. esculentum. This study provides valuable information for investigating the growth mechanism and MAS breeding in R. esculentum.

Real-Time Jellyfish Classification and Detection Based on Improved YOLOv3 Algorithm

In recent years, jellyfish outbreaks have frequently occurred in offshore areas worldwide, posing a significant threat to the marine fishery, tourism, coastal industry, and personal safety. Effective monitoring of jellyfish is a vital method to solve the above problems. However, the optical detection method for jellyfish is still in the primary stage. Therefore, this paper studies a jellyfish detection method based on convolution neural network theory and digital image processing technology. This paper studies the underwater image preprocessing algorithm because the quality of underwater images directly affects the detection results. The results show that the image quality is better after applying the three algorithms namely prior defogging, adaptive histogram equalization, and multi-scale retinal enhancement, which is more conducive to detection. We establish a data set containing seven species of jellyfishes and fish. A total of 2141 images are included in the data set. The YOLOv3 algorithm is used to detect jellyfish, and its feature extraction network Darknet53 is optimized to ensure it is conducted in real-time. In addition, we introduce label smoothing and cosine annealing learning rate methods during the training process. The experimental results show that the improved algorithms improve the detection accuracy of jellyfish on the premise of ensuring the detection speed. This paper lays a foundation for the construction of an underwater jellyfish optical imaging real-time monitoring system.

Analysis of the relationship between chlorophyll-a and sea surface temperature on marine capture fisheries production in Indonesia: 2018

Fishery production in Indonesia is still relatively high, dominated by the marine capture fisheries. Oceanographic dynamics can affect the high and low levels of marine fishery production. Sea surface temperature and chlorophyll-a are oceanographic parameters that are often used as indicators for determining fishing areas, especially pelagic fish which are associated with ocean fertility. This study aims to identify the effect of chlorophyll-a and sea surface temperature (SST) on the production of fish catches in Indonesia: 2018. Data on marine capture fisheries production (skipjack, mackerel tuna, tuna and shrimp) in 2018 were obtained from the Ministry of Marine Affairs and Fisheries (KKP). Data of Chlorophyll-a and sea surface temperature (SST) are satellite observations from Marine Copernicus. The relationship between chlorophyll-a and sea surface temperature (SST) with marine capture fisheries production was analyzed using logistic regression analysis. The results showed that chlorophyll-a significantly affected the yield of skipjack and tuna in Indonesia with coefficients of -5.7066 and -4.3760, respectively. A higher concentration of chlorophyll-a had the possibility to produce high fish production of 0.0033 times than an area with a lower concentration of chlorophyll-a.

Analysis on the structure effect of marine fishery total factor productivity under high-quality development in China

Improving total factor productivity (TFP) is the source of power for high-quality development. Industrial structure optimization is an important way to improve TFP. This paper constructed an econometric model of industry structure changes impacting on TFP in the marine fisheries and conducted an empirical test and analysis. The results showed that the industry rationalization, softening and processing coefficient of marine fishery had a significant “structural dividend” for improving its TFP; while the impact of industrial structure advancement and aquaculture-catching structure changes did not have “structural dividend”, but it could be a combination of other factors to reduce these adverse effects.We believe that simply pursuing the advanced evolution of the industrial structure is not conducive to sustainable development of fishery. Under the pursuit of the rationalization of the marine fishery industry structure, by promoting the coordinated evolution of marine fisheries advancement, aquaculture-catching structure and other factors, the "structural dividend" effect can be enhanced and the fishery can achieve sustainable development. Finally, it proposed to promote the development of advancement and rationalization of marine fishery industry structure coordinately, adjust fishery science and technology transformation direction and key points, and accelerate the development of intensive processing industry by cross-border integration.

Methods for Characterizing and Examining Marine Fishery Ecosystems

There are many variables associated with assessing marine fishery ecosystems. These include exploring facets of the living marine resources (LMRs), habitats, oceans, economics, and social considerations associated with marine social-ecological systems. Yet which ones can help track progress toward ecosystem-based fisheries management (EBFM) and, by extension, the efficacy of LMR management? This chapter provides a list of over 90 indicators we will use throughout the regional chapters, with documentation of data sources, time periods, and geographies covered, and the typical caveats associated with these data. This chapter also notes the methodology of how we synthesized all this information across all the regional chapters, noting the appropriate statistical and ranking methods we employed and the benchmarking criteria we considered to ascertain progress toward EBFM.

An Examination of Progress Toward Ecosystem-Based Management of Living Marine Resources in the U.S.

This chapter presents a cumulative examination of socioeconomic, governance, ecological, and environmental indicators among the eight major United States (U.S.) marine fishery ecosystems, 26 U.S. subregions, and 14 U.S. participatory regional fisheries management organization (RFMO) jurisdictions. Based on these indicators and as one might expect, some regions are making greater progress toward ecosystem-based fisheries management (EBFM) than others, but in all U.S. marine ecosystems there has been notable progress toward EBFM, albeit on different facets for different regions. Common areas of notable progress toward EBFM are observed around the nation in areas of implementing ecosystem-level planning and advancing understanding of ecosystem processes. Overall, it appears that more inherently productive marine ecosystems tend to have greater biomass, fisheries landings, proportional LMR-based employments, and fisheries revenue. More work remains in areas of ecosystem and community resilience, as well as broader consideration of more systematic measures for a fisheries ecosystem (especially ecosystem-level reference points). Several areas of common challenges and anticipated concerns are identified, with an eye toward focusing efforts on addressing these issues.