scholarly journals Long-Term Variability of Piscivorous Fish in China Seas Under Climate Change With Implication for Fisheries Management

2021 ◽  
Vol 8 ◽  
Author(s):  
Dan Liu ◽  
Yongjun Tian ◽  
Shuyang Ma ◽  
Jianchao Li ◽  
Peng Sun ◽  
...  
Keyword(s):  
Climate Change ◽  
Cold Water ◽  
Principal Component ◽  
Scientific Basis ◽  
Fishing Effort ◽  
China Seas ◽  
Piscivorous Fish ◽  
Fisheries Resources ◽  
The China Seas

Due to persistent fishing expansion in the China Seas over the past six decades, fisheries resources have been over-exploited; as a result, exploited fish have become smaller in size and younger in age. Marine piscivorous fish constituted a large portion of Chinese fisheries catch, long-term variability of which has rarely been investigated despite intense fishing pressure and climate change. In this study, we attempt to identify their responses to climate change and fishing activities and to provide scientific basis for sustainable exploitation of these resources. Seven taxa from pelagic to demersal species inhabiting either cold-water or warm-water were selected to represent the piscivorous fish assemblage in the China Seas. Total catch of these piscivorous fish in the China Seas increased during the early 1990s, stabilizing around 1.2 million tons after 1997. Principal component analysis (PCA) showed evident interannual-decadal variabilities in the catch of these fish with step changes around 1985/86 and 1997/98. Individual taxa, however, showed different trends in catches with sharks, rays, and lizardfishes manifesting downward trends while Pacific cod, eels, and hairtail increasing. Common dolphinfish and Japanese-Spanish mackerel increased largely in the 1990s but declined slightly during the 2000s. Although there were temporal overlaps between climate change and fishing variabilities, results of gradient forest analyses indicated that fishing effort imposed the most important influence on piscivorous fish. And among all climate variables explored in this study, sea surface temperature (SST) especially that of the East China Sea, had greatest impacts on variations in piscivorous fish catch, which may have been gradually exacerbated by the continued high fishing intensity. In addition, significant changes were identified in the life history traits in the species we evaluated, such as reduced average body sizes and truncated age compositions, strongly indicating the effect of fishing. We therefore advocate precautionary fishery practices under climate change.

scholarly journals Prediction of Sea Surface Temperature in the China Seas Based on Long Short-Term Memory Neural Networks

2020 ◽  
Vol 12 (17) ◽  
pp. 2697
Author(s):  
Li Wei ◽  
Lei Guan ◽  
Liqin Qu ◽  
Dongsheng Guo
Keyword(s):  
Spatial Resolution ◽  
Lead Time ◽  
Short Term Memory ◽  
High Spatial Resolution ◽  
Sea Surface ◽  
China Seas ◽  
Short Term ◽  
Long Short Term Memory ◽  
The China Seas

Sea surface temperature (SST) in the China Seas has shown an enhanced response in the accelerated global warming period and the hiatus period, causing local climate changes and affecting the health of coastal marine ecological systems. Therefore, SST distribution prediction in this area, especially seasonal and yearly predictions, could provide information to help understand and assess the future consequences of SST changes. The past few years have witnessed the applications and achievements of neural network technology in SST prediction. Due to the diversity of SST features in the China Seas, long-term and high-spatial-resolution prediction remains a crucial challenge. In this study, we adopted long short-term memory (LSTM)-based deep neural networks for 12-month lead time SST prediction from 2015 to 2018 at a 0.05° spatial resolution. Considering the sub-regional differences in the SST features of the study area, we applied self-organizing feature maps (SOM) to classify the SST data first, and then used the classification results as additional inputs for model training and validation. We selected nine models differing in structure and initial parameters for ensemble to overcome the high variance in the output. The statistics of four years’ SST difference between the predicted SST and Operational SST and Ice Analysis (OSTIA) data shows the average root mean square error (RMSE) is 0.5 °C for a one-month lead time and is 0.66 °C for a 12-month lead time. The southeast of the study area shows the highest predictable accuracy, with an RMSE less than 0.4 °C for a 12-month prediction lead time. The results indicate that our model is feasible and provides accurate long-term and high-spatial-resolution SST prediction. The experiments prove that introducing appropriate class labels as auxiliary information can improve the prediction accuracy, and integrating models with different structures and parameters can increase the stability of the prediction results.

Long-term Projection of Wind Potential in the China Seas

2020 ◽  
Vol 99 (sp1) ◽  
pp. 396
Author(s):  
Cheng-Zhi Gao ◽  
Chong-Wei Zheng ◽  
Guo Zhang ◽  
Yun-Dong Han ◽  
Feng Tian ◽  
...  
Keyword(s):  
China Seas ◽  
Wind Potential ◽  
The China Seas

scholarly journals Multi-Year Monitoring of Ecosystem Metabolism in Two Branches of a Cold-Water Stream

Environments ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 19
Author(s):  
Daniel J. Hornbach
Keyword(s):  
Climate Change ◽  
Cold Water ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Ecosystem Metabolism ◽  
Freshwater Biodiversity ◽  
Water Stream ◽  
Stream Discharge ◽  
Biodiversity And Ecosystem Function

Climate change is likely to have large impacts on freshwater biodiversity and ecosystem function, especially in cold-water streams. Ecosystem metabolism is affected by water temperature and discharge, both of which are expected to be affected by climate change and, thus, require long-term monitoring to assess alterations in stream function. This study examined ecosystem metabolism in two branches of a trout stream in Minnesota, USA over 3 years. One branch was warmer, allowing the examination of elevated temperature on metabolism. Dissolved oxygen levels were assessed every 10 min from spring through fall in 2017–2019. Gross primary production (GPP) was higher in the colder branch in all years. GPP in both branches was highest before leaf-out in the spring. Ecosystem respiration (ER) was greater in the warmer stream in two of three years. Both streams were heterotrophic in all years (net ecosystem production—NEP < 0). There were significant effects of temperature and light on GPP, ER, and NEP. Stream discharge had a significant impact on all GPP, ER, and NEP in the colder stream, but only on ER and NEP in the warmer stream. This study indicated that the impacts of temperature, light, and discharge differ among years, and, at least at the local scale, may not follow expected patterns.

2018 Nobel Economics Prize: Integrating Climate Change Measures into Sustainable Economic Growth

2018 ◽  
Vol 34 (4) ◽  
Author(s):  
Nguyen Thi Thuc An ◽  
Dau Kieu Ngoc Anh
Keyword(s):  
Climate Change ◽  
Economic Growth ◽  
Endogenous Growth ◽  
Environmental Issues ◽  
Growth Theory ◽  
Endogenous Growth Theory ◽  
Technological Advances ◽  
Academy Of Sciences ◽  
Sustainable Economic Growth

The 2018 Nobel Economics Prize was awarded to two American economists - William D. Nordhaus and Paul M. Romer - who designed methods for better assessing environmental issues and technological advances on growth. This year’s Laureates, Nordhaus was the first person to create an intergrated model to assess interactions between society and nature and Romer laid the foundation for what is now called endogenous growth theory. According to the Swedish Royal Academy of Sciences, these two macroeconomists’ research have helped “significantly broaden the scope of economic analysis by constructing models that explain how the market economy interacts with nature and knowledge” which integrates climate change measures into long-term sustainable economic growth. Keywords Nobel in economics, William D. Nordhaus, Paul M. Romer, climate change, endogenous growth theory, economic growth References [1] Y Vân (2018), “Lý lịch 'khủng' của hai nhà khoa học vừa giành giải Nobel Kinh tế 2018”, Vietnambiz, đăng tải ngày 08/10/2018, https://vietnambiz.vn/ly-lich-khung-cua-hai-nha-khoa-hoc-vua-gianh-giai-nobel-kinh-te-2018-95776.html[2] Jonas O. Bergman, Rich Miller (2018), “Nordhaus, Romer Win Nobel for Thinking on Climate, Innovation”, đăng tải ngày 8/10/2018, https://www.bloomberg.com/news/articles/2018-10-08/nordhaus-romer-win-2018-nobel-prize-in-economic-sciences [3] Antonin Pottier (2018), “Giải Nobel” William Nordhaus có thật sự nghiêm túc?”, Nguyễn Đôn Phước dịch, đăng tải ngày 11/10/2018, http://www.phantichkinhte123.com/2018/10/giai-nobel-william-nordhaus-co-that-su.html[4] Thăng Điệp (2018), “Giải Nobel kinh tế 2018 về tay hai người Mỹ”, đăng tải ngày 8/10/2018, http://vneconomy.vn/giai-nobel-kinh-te-2018-ve-tay-hai-nguoi-my-20181008185809239.htm[5] Lars P. Syll (2018), “Cuối cùng - Paul Romer cũng có được giải thưởng Nobel”, Huỳnh Thiện Quốc Việt dịch, đăng tải ngày 14/10/2018, http://www.phantichkinhte123.com/2018/10/cuoi-cung-paul-romer-cung-co-uoc-giai.html[6] Phương Võ (2018), “Nobel Kinh tế 2018: Chạm tới bài toán khó của thời đại”, đăng tải ngày 9/10/2018, https://nld.com.vn/thoi-su-quoc-te/nobel-kinh-te-2018-cham-toi-bai-toan-kho-cua-thoi-dai-20181008221734228.htm[7] Đông Phong (2018), “Nobel Kinh tế cho giải pháp phát triển bền vững và phúc lợi người dân”, đăng tải ngày 8/10/2018, https://news.zing.vn/nobel-kinh-te-cho-giai-phap-phat-trien-ben-vung-va-phuc-loi-nguoi-dan-post882860.html[8] Thanh Trúc (2018), “Giải Nobel kinh tế 2018: Thay đổi tư duy về biến đổi khí hậu”, https://tusach.thuvienkhoahoc.com/wiki/Gi%E1%BA%A3i_Nobel_kinh_t%E1%BA%BF_2018:_Thay_%C4%91%E1%BB%95i_t%C6%B0_duy_v%E1%BB%81_bi%E1%BA%BFn_%C4%91%E1%BB%95i_kh%C3%AD_h%E1%BA%ADu[9] Cẩm Anh (2018), “Nobel kinh tế 2018: Lời giải cho tăng trưởng kinh tế bền vững”, đăng tải ngày 11/10/2018, http://enternews.vn/nobel-kinh-te-2018-loi-giai-cho-tang-truong-kinh-te-ben-vung-137600.html.

Complex study of the fracture processes in materials and structures

2018 ◽  
Vol 84 (11) ◽  
pp. 46-51 ◽  
Author(s):  
N. A. Makhutov
Keyword(s):  
Fracture Mechanics ◽  
Crack Resistance ◽  
Scientific Basis ◽  
Intensity Factors ◽  
Nonlinear Fracture Mechanics ◽  
Nonlinear Fracture ◽  
Linear Fracture ◽  
Science Technology ◽  
Fracture Processes

The results of comprehensive studies of multifactor processes, mechanisms and criteria for fracture at a variation of the crack-like defect state, loading conditions and mechanical properties of structural materials carried out in the 20th - 21st centuries are presented on the basis of monographic publications and articles published in the journal “Zavodskaya Laboratoriya. Diagnostika Materialov.” Crack resistance of materials and structures has become a key problem of the material science, technology, design, manufacture and service of structures. Fracture mechanics including estimation of the stress-strain and limiting states in a cracks tip formed a scientific basis of the crack resistance analysis Stress intensity factors (linear fracture mechanics) and strain intensity factors (nonlinear fracture mechanics) are accepted as the basic criteria of those states. The basic computational relations for construction of the fracture diagrammes which link the cracks growth with conditions of a static, cyclic, long-term, dynamic loading are presented. Parameters of computational relations are put into correspondence with the features of fracture processes on nano-, micro-, meso- and macrolevels. Prospects of the research and guidelines of further studing crack resistance are discussed.

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