Module OSX-4000:
Marine Ecology Skills
Module Facts
Run by School of Ocean Sciences
20.000 Credits or 10.000 ECTS Credits
Semester 1
Organiser: Dr Adel Heenan
Overall aims and purpose
The aim of this module is to give students a high level introduction to the entire process of the scientific method, from project inception, sampling design and data analysis through to development of a summary scientific report. Students will be introduced to and have opportunities to practice a number of skills, from ship-based data collection, taxonomic identification, statistical analysis and programming, report writing and map making using GIS. Students will have further opportunities to practice and master the variety of marine ecology skills introduced in this module throughout their Masters program.
Course content
The module provides an introduction to the scientific method and an overview of approaches to experimental and survey sampling design, data analysis and interpretation and report writing. Learning will be enhanced through ship-based sampling and laboratory analysis of samples, and students will collaborate to produce a dataset which they will independently analyse to practice statistical and data communication skills. Students will learn about and practice scientific writing and develop introductory map making skills. More specifically the module includes:
- A description of the scientific process with a particular focus on null hypothesis significance testing and revising univariate statistical tests.
- Ideas surrounding statistical sampling design from an observational and empirical perspective
- Data exploration and univariate analysis in the statistical programming environment R
- Introduction to multivariate statistical methods commonly used by marine ecologists and working in the software Primer
- Ship-based benthic grab sampling
- Taxonomic identification of benthic organisms and laboratory processing to collaboratively produce a class dataset
- Independent analysis of the class dataset
- Scientific research and report writing skills
- Mapping and spatial analysis techniques in ArcGIS
Assessment Criteria
threshold
A threshold student will have a basic knowledge of the scientific method and hypothesis driven framework, a basic ability to identify benthic organisms as well as a basic ability to quantitatively manipulate and investigate datasets using a range of fundamental approaches using appropriate computer software (R, Primer and ArcGIS). The student will be able to apply and interpret statistical tests and create an evidence based scientific reporting summarizing their work.
good
A good student will have a thorough understanding of the scientific method and hypothesis driven framework, and a solid ability to identify benthic organisms as well as be competent in quantitatively manipulating datasets using a range of fundamental mathematical tools, have a good ability to interpret datasets and be able to confidently use and interpret statistical tests using appropriate computer software. The student will be able to concisely present and interpret their analytical findings in the context of the wider literature to create a compelling evidence based scientific report summarizing their work.
excellent
An excellent student will have a high-level understanding of the scientific method and ability to present testable hypotheses. They will have advanced benthic taxonomy identification skills, as well as have a sophisticated knowledge of quantitatively manipulating datasets using a range of fundamental mathematical tools. Their ability to interpret datasets will be advanced and they be highly skilled in the use and interpretation of statistical tests using appropriate computer software. The student will create a scientific report that has high level understanding of the ecological concepts, as well as a mature interpretation of the results presenting them in the context of wider literature. Their written and presentation style will be highly skilled, concise, clear and compelling.
Learning outcomes
-
Knowledge:
- recognise sampling design issues (like statistical power and pseudo-replication) that relate to large-scale biological surveys, to experimental field studies and controlled laboratory studies
- identify a variety of common UK benthic organisms with the correct nomenclature using taxonomic keys and identification methods
- demonstrate an understanding of the scientific method from a null hypothesis significance testing framework
-
Comprehension:
- explain situations in which the following univariate statistical tests would be used: t-tests, Mann-Whitney, ANOVA, Kruskal-Wallis, correlation, regression
- explain the basic principles underlying multivariate methods including SIMPER, ANOSIM and MDS.
- summarize key findings from independent desk based literature search on the environmental drivers of variability in benthic community structure
-
Analyse:
- apply univariate and multivariate methods to a multi-species dataset combined with environmental driver data
-
Synthesis:
- organize key findings from independent desk-based research and data analysis to generate a benthic report written in IMRAD (introduction, methods, results and discussion) format
-
Application:
- ship-based biological data collection (benthic grab samples)
- laboratory based taxonomic identification of benthic grab samples
- programming for data exploration and univariate statistical methods in R
- multivariate methods for community analyses in Primer
- acquire the fundamentals of GIS and apply these to analyze spatial data using ArcGIS
Assessment Methods
Type | Name | Description | Weight |
---|---|---|---|
Benthic survey data collection and analysis scientific report | 70.00 | ||
Predictive modelling GIS Exercise | 30.00 |
Teaching and Learning Strategy
Hours | ||
---|---|---|
Practical classes and workshops | 1 x 3 hour benthic taxonomy training and 3 x 7 hrs taxonomic practice and processing of benthic grabs. |
24 |
Lecture | 1 hour introductory GIS, 1.5 scientific writing process, 1 hour introduction to benthic assignment, 1 hour sampling design, 1 hour introduction to multivariate, 5 hours lecture univariate and R overview |
12 |
Practical classes and workshops | Computer practicals (Primer, R and GIS) - students work through materials independently with staff available for questions |
26 |
Fieldwork | Sea-going field trip to survey benthos aboard the RV Prince Madog |
8 |
Private study | 115 | |
Supervised time in studio/workshop | Help sessions (open Q&A) for benthic report analysis (7 hours) , benthic report writing (2 hours) and GIS assignment (6 hours) |
15 |
Transferable skills
- Literacy - Proficiency in reading and writing through a variety of media
- Numeracy - Proficiency in using numbers at appropriate levels of accuracy
- Computer Literacy - Proficiency in using a varied range of computer software
- Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
- Exploring - Able to investigate, research and consider alternatives
- Information retrieval - Able to access different and multiple sources of information
- Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
- Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
- Safety-Consciousness - Having an awareness of your immediate environment, and confidence in adhering to health and safety regulations
- Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
- Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
- Mentoring - Able to support, help, guide, inspire and/or coach others
- Management - Able to utilise, coordinate and control resources (human, physical and/or financial)
- Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
- Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others
- Leadership - Able to lead and manage, develop action plans and objectives, offer guidance and direction to others, and cope with the related pressures such authority can result in
Courses including this module
Compulsory in courses:
- C1AF: MSc Marine Biology year 1 (MSC/MB)
- F7AD: MSc Marine Environmental Protection year 1 (MSC/MEP)