China's 13th Five-Year Plan, launched in March 2016, provides a sound policy platform for the protection of marine ecosystems and the restoration of capture fisheries within China's exclusive economic zone. What distinguishes China among many other countries striving for marine fisheries reform is its sizeaccounting for almost one-fifth of global catch volume-and the unique cultural context of its economic and resource management. In this paper, we trace the history of Chinese government priorities, policies, and outcomes related to marine fisheries since the 1978 Economic Reform, and examine how the current leadership's agenda for "ecological civilization" could successfully transform marine resource management in the coming years. We show how China, like many other countries, has experienced a decline in the average trophic level of its capture fisheries during the past few decades, and how its policy design, implementation, and enforcement have influenced the status of its wild fish stocks. To reverse the trend in declining fish stocks, the government is introducing a series of new programs for sustainable fisheries and aquaculture, with greater traceability and accountability in marine resource management and area controls on coastal development. As impressive as these new plans are on paper, we conclude that serious institutional reforms will be needed to achieve a true paradigm shift in marine fisheries management in China. In particular, we recommend new institutions for science-based fisheries management, secure fishing access, policy consistency across provinces, educational programs for fisheries managers, and increasing public access to scientific data. offers for the restoration and enhancement of wild fisheries, the protection of marine ecosystem services, and the amelioration of coastal pollution are momentous. Achieving the Plan's marine protection objectives will be challenging, however, and will require new approaches for state governance of marine resources, data sharing and use for policy implementation, and an expanded public appreciation of marine ecosystem services for sustained economic growth and environmental quality. Without serious institutional adjustments, even the most limited

A survey of the fishing grounds for bigeye tuna, Thunnus obesus, in the Indian Ocean was carried out for a better understanding of the environmental preferences of bigeye tuna in a longline fishery. Catch rates of bigeye tuna were analyzed with respect to the ranges of depth, temperature, salinity, chlorophyll-a, and dissolved oxygen. The optimum capture depth, water temperature, and dissolved oxygen range of bigeye tuna were identified as 240.0 m to 279.9 m, 12.0°C to 13.9°C, and 2.00 mg·L −1 to 2.99 mg·L −1 , respectively, in the study area of Indian Ocean. Neither salinity nor chlorophyll-a had a detectable effect on the vertical distribution of the adult bigeye tuna. The dissolved oxygen is the principal factor limiting the vertical distribution of bigeye tuna.

Survey of yellowfin tuna in the west-central Indian Ocean was conducted on board of Chinese longliners during 2003, 2004 and 2005, which is a part of Chinese Tuna Fishery Scientific Observer Program (CTFSOP).The reproductive biology has been investigated. A total of 1 023 samples are collected including 417 ovaries and 606 testes. Spawning activities of yellowfin tuna have been studied for both male and female from January to June. The data showed that the average monthly sex ratio is 0.59, and the minimum length at sexual maturity is 101 cm for female and 110 cm for male respectively. Length at 50% sexual maturity is estimated at 113.77 cm for female and 120.20 cm for male, whereas maturation rate is 0.066 cm -1 for female and 0.091 cm -1 for male. Sex ratio by length class indicates that the proportion of male is higher than female's along with size increasing; for instance, in the group of the body length longer than 145 cm, some females have their body length from 145 to 160 cm and males have their body length at 160 cm and even longer. Statistically, yellowfin tuna has a significant seasonal reproduction.

While neural machine translation (NMT) achieves remarkable performance on clean, indomain text, performance is known to degrade drastically when facing text which is full of typos, grammatical errors and other varieties of noise. In this work, we propose a multitask learning algorithm for transformer-based MT systems that is more resilient to this noise. We describe our submission to the WMT 2019 Robustness shared task (Li et al., 2019) based on this method. Our model achieves a BLEU score of 32.8 on the shared task French to English dataset, which is 7.1 BLEU points higher than the baseline vanilla transformer trained with clean text 1 .