New U.S. Research Ships Named: Aquatic Science Landmark for BIPOC

2021 ◽  
Author(s):  
Phillip R. Taylor
Keyword(s):  
Aquatic Science

scholarly journals Aquatic Science: Informing Policy, Management, and the Public

2016 ◽  
Vol 25 (4) ◽  
pp. 134-135 ◽  
Author(s):  
Michelle McCrackin ◽  
Lesley Smith ◽  
Adrienne Sponberg
Keyword(s):  
Policy Management ◽  
The Public ◽  
Aquatic Science

scholarly journals Reviewer Acknowledgements

2019 ◽  
Vol 7 (2) ◽  
pp. 71
Author(s):  
Maggie Liu
Keyword(s):  
Peer Review ◽  
Science And Technology ◽  
The Philippines ◽  
Environmental Biology ◽  
Aquatic Science ◽  
Nova Southeastern University ◽  
National University ◽  
Coastal Research ◽  
Research Institute

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

scholarly journals Using Systematic Review and Evidence Banking to Increase Uptake and Use of Aquatic Science in Decision-Making

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

scholarly journals Citations and Citation Metrics in a Serial Assessment Using Master’s Theses

2018 ◽  
Author(s):  
Geoffrey Timms
Keyword(s):  
Graduate Students ◽  
Marine Biology ◽  
Ranking Data ◽  
Aquatic Science ◽  
Citation Metrics

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.

scholarly journals Accumulation and distribution of heavy metals in Gerres abbreviatus (Bleeker 1850) and Parastromateus niger (Bloch, 1795) in Kao Bay, North Maluku, Indonesia

2021 ◽  
Vol 890 (1) ◽  
pp. 012010
Author(s):  
R T A Pertiwi ◽  
K H Iksan ◽  
D Ariyanto
Keyword(s):  
Heavy Metals ◽  
Science Laboratory ◽  
Fish Organs ◽  
Heavy Metals Accumulation ◽  
Aquatic Science ◽  
Metals Accumulation ◽  
Parastromateus Niger

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.

scholarly journals Environmental setting of Lake Mead National Recreation Area: Chapter 2 in A synthesis of aquatic science for management of Lakes Mead and Mohave

Circular ◽  
2012 ◽  
pp. 7-22 ◽  
Author(s):  
Kent Turner ◽  
Michael R. Rosen ◽  
G. Chris Holdren ◽  
Steven L. Goodbred ◽  
David C. Twichell
Keyword(s):  
Lake Mead ◽  
Environmental Setting ◽  
Aquatic Science ◽  
Recreation Area

scholarly journals Threats and stressors to the health of the ecosystems of Lakes Mead and Mohave: Chapter 6 in A synthesis of aquatic science for management of Lakes Mead and Mohave

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

Prediction and the aquatic sciences

2001 ◽  
Vol 58 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Michael L Pace
Keyword(s):  
Predictive Models ◽  
Probabilistic Models ◽  
Aquatic Systems ◽  
Environmental Concerns ◽  
Predictive Capability ◽  
Aquatic Science ◽  
Scientific Context ◽  
Key Features ◽  
Predictive Approaches ◽  
Aquatic Sciences

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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