More than 100 aquatic-science societies sound climate alarm

Nature ◽  
2021 ◽  
Vol 589 (7842) ◽  
pp. 352-352
Author(s):  
Scott A. Bonar
Keyword(s):  
2016 ◽  
Vol 25 (4) ◽  
pp. 134-135 ◽  
Author(s):  
Michelle McCrackin ◽  
Lesley Smith ◽  
Adrienne Sponberg

2019 ◽  
Vol 7 (2) ◽  
pp. 71
Author(s):  
Maggie Liu

Aquatic Science and Technology (AST) would like to acknowledge the following reviewers for their assistance with peer review of manuscripts for this issue. Many authors, regardless of whether AST publishes their work, appreciate the helpful feedback provided by the reviewers. Their comments and suggestions were of great help to the authors in improving the quality of their papers. Each of the reviewers listed below returned at least one review for this issue.Reviewers for Volume 7, Number 2 Augusto E. Serrano, University of the Philippines Visayas, PhilippinesAyman El-Gamal, Coastal Research Institute, EgyptDavid Kerstetter, Nova Southeastern University Oceanographic Center, USALevent BAT, Sinop University Fisheries Faculty, TurkeyLuciana Mastrantuono, Department of Environmental Biology, ItalyTai-Sheng Cheng, National University of Taiwan, TaiwanMaggie LiuAquatic Science and TechnologyMacrothink Institute*************************************5348 Vegas Dr.#825Las Vegas, Nevada 89108United StatesTel: 1-702-953-1852 ext. 524Fax: 1-702-420-2900E-mail: [email protected]: http://ast.macrothink.org


2018 ◽  
Vol 27 (4) ◽  
pp. 103-109 ◽  
Author(s):  
Micah G. Bennett ◽  
Sylvia S. Lee ◽  
Kate A. Schofield ◽  
Caroline Ridley ◽  
Susan B. Norton ◽  
...  

2018 ◽  
Author(s):  
Geoffrey Timms

We analyzed serial citations in 72 marine biology master’s theses as well as the ranking data of aquatic science serials from six global serial citation metrics, to assess serial use by marine biology graduate students from two perspectives. From 1,035 unique serials, a core of 123 titles was identified and evaluated for access. Citation ages averaged 13.5 years, with 27% of serial citations dated prior to 1996. Students cited serials from disciplines beyond marine biology, demonstrating broad title dispersion compared to several other studies. Recommendations are offered for future investigation to develop a stronger understanding of graduate students’ use of the library’s serial collection.


2021 ◽  
Vol 890 (1) ◽  
pp. 012010
Author(s):  
R T A Pertiwi ◽  
K H Iksan ◽  
D Ariyanto

Abstract Heavy metals have a relationship with fish organs. The aim of this study was to determine the distribution of heavy metals in various organs of Gerres abbreviatus and Parastromateus niger. The research was conducted in Kao Bay waters from April to September 2019. Samples obtained were prepared at the aquatic science laboratory of Khairun University and were analyzed at the Environmental Productivity Laboratory of IPB University Bogor using the AAS instrument to determine heavy metals concentrations. The result of the heavy metals accumulation in Gerres abbreviatus meat was Zn > Cu > Pb > Ni > Hg > Mn > Cd. Meanwhile, the heavy metals accumulation in Roi fish (Parastromateus niger) meat was Zn > Mn > Ni > Hg > Pb > Cd > Cu.


Circular ◽  
2012 ◽  
pp. 7-22 ◽  
Author(s):  
Kent Turner ◽  
Michael R. Rosen ◽  
G. Chris Holdren ◽  
Steven L. Goodbred ◽  
David C. Twichell

Circular ◽  
2012 ◽  
pp. 105-138
Author(s):  
Michael R. Rosen ◽  
Steven L. Goodbred ◽  
Wai Hing Wong ◽  
Reynaldo Patiño ◽  
Kent Turner ◽  
...  
Keyword(s):  

2001 ◽  
Vol 58 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Michael L Pace

The need for prediction is now widely recognized and frequently articulated as an objective of research programs in aquatic science. This recognition is partly the legacy of earlier advocacy by the school of empirical limnologists. This school, however, presented prediction narrowly and failed to account for the diversity of predictive approaches as well to set prediction within the proper scientific context. Examples from time series analysis and probabilistic models oriented toward management provide an expanded view of approaches and prospects for prediction. The context and rationale for prediction is enhanced understanding. Thus, prediction is correctly viewed as an aid to building scientific knowledge with better understanding leading to improved predictions. Experience, however, suggests that the most effective predictive models represent condensed models of key features in aquatic systems. Prediction remains important for the future of aquatic sciences. Predictions are required in the assessment of environmental concerns and for testing scientific fundamentals. Technology is driving enormous advances in the ability to study aquatic systems. If these advances are not accompanied by improvements in predictive capability, aquatic research will have failed in delivering on promised objectives. This situation should spark discomfort in aquatic scientists and foster creative approaches toward prediction.


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