MB5370
MB5370: Techniques in Marine Science 1
MB5370: Techniques in Marine Science 1
Overview
Overview
This subject equips students with practical expertise in computing methods essential for understanding and analysing biological and ecological processes in marine and coastal environments. The curriculum is problem-based, with a strong emphasis on hands-on skill development, delivered through a combination of practical and demonstration sessions.
This subject equips students with practical expertise in computing methods essential for understanding and analysing biological and ecological processes in marine and coastal environments. The curriculum is problem-based, with a strong emphasis on hands-on skill development, delivered through a combination of practical and demonstration sessions.
Course Structure
Course Structure
The subject is organised into distinct learning modules, each requiring either 20 and 40 hours of study. The class begins with a compulsory introductory module that builds foundational skills in coding and data manipulation. Following this, students have the flexibility to select from a series of specialised modules, each focusing on different ecological questions and conservation-related analyses. These modules provide the opportunity to gain proficiency in a variety of cutting-edge analytical platforms tailored to marine science.
The subject is organised into distinct learning modules, each requiring either 20 and 40 hours of study. The class begins with a compulsory introductory module that builds foundational skills in coding and data manipulation. Following this, students have the flexibility to select from a series of specialised modules, each focusing on different ecological questions and conservation-related analyses. These modules provide the opportunity to gain proficiency in a variety of cutting-edge analytical platforms tailored to marine science.
The modules have been developed in close collaboration with industry stakeholders, government partners, and academic researchers, ensuring that the knowledge and skills gained are directly relevant to real-world marine science applications. Each module is taught by faculty from the Global Ecology Lab and across JCU's College of Science and Engineering. Guest lectures are also delivered from a range of external world-leading scientists, providing access to a wealth of expertise in the field.
The modules have been developed in close collaboration with industry stakeholders, government partners, and academic researchers, ensuring that the knowledge and skills gained are directly relevant to real-world marine science applications. Each module is taught by faculty from the Global Ecology Lab and across JCU's College of Science and Engineering. Guest lectures are also delivered from a range of external world-leading scientists, providing access to a wealth of expertise in the field.
Detailed Module Overview
Detailed Module Overview
1. Introduction to Programming (Compulsory | 10 hours)
1. Introduction to Programming (Compulsory | 10 hours)
This foundational module introduces students to essential concepts in scientific programming, preparing them for the complexity of marine data science. With marine datasets growing rapidly in size and complexity, reproducibility and collaboration are key in ensuring transparent and robust analyses. Students will develop a structured approach to organizing workflows that integrate data and code to support reproducible research. Upon completion, students will be well-prepared for the subsequent, more specialized modules.
This foundational module introduces students to essential concepts in scientific programming, preparing them for the complexity of marine data science. With marine datasets growing rapidly in size and complexity, reproducibility and collaboration are key in ensuring transparent and robust analyses. Students will develop a structured approach to organizing workflows that integrate data and code to support reproducible research. Upon completion, students will be well-prepared for the subsequent, more specialized modules.
2. Introduction to GIS (Elective | 20 hours)
2. Introduction to GIS (Elective | 20 hours)
This module is specifically designed for students with no prior experience in GIS. Participants will be introduced to fundamental geospatial tools, focusing on widely-used GIS platforms such as ArcGIS. Students will explore different spatial data types (including field and sensor-acquired data), learn to access public spatial data archives, and apply various analytical techniques to marine environmental datasets. This module provides a robust foundation in geospatial analysis, critical for those pursuing further data science modules.
This module is specifically designed for students with no prior experience in GIS. Participants will be introduced to fundamental geospatial tools, focusing on widely-used GIS platforms such as ArcGIS. Students will explore different spatial data types (including field and sensor-acquired data), learn to access public spatial data archives, and apply various analytical techniques to marine environmental datasets. This module provides a robust foundation in geospatial analysis, critical for those pursuing further data science modules.
3. Introduction to Photogrammetry (Elective | 40 hours)
3. Introduction to Photogrammetry (Elective | 40 hours)
In this module, students will explore both established and cutting-edge techniques for creating three-dimensional models of coastal and marine environments. The module emphasizes hands-on learning with off-the-shelf software, allowing students to produce 3D models using tools such as underwater cameras (structure from motion, stereo cameras), drones, and LiDAR. In addition to the technical skills, students will engage with guest lectures delivered by leading researchers, providing insights into how 3D technologies are transforming marine science.
In this module, students will explore both established and cutting-edge techniques for creating three-dimensional models of coastal and marine environments. The module emphasizes hands-on learning with off-the-shelf software, allowing students to produce 3D models using tools such as underwater cameras (structure from motion, stereo cameras), drones, and LiDAR. In addition to the technical skills, students will engage with guest lectures delivered by leading researchers, providing insights into how 3D technologies are transforming marine science.
4. Data Science in R (Elective | 40 hours)
4. Data Science in R (Elective | 40 hours)
This module focuses on the use of R for organising, analysing, and visualising large marine datasets. Students will develop proficiency in manipulating file systems, implementing version control and processing extensive monitoring data, and generating reports on key environmental metrics. Emphasis will be placed on the importance of tidy data management and programmed workflows, ensuring efficient, reproducible scientific analysis. The skills acquired in this module are directly applicable to a wide range of marine data science applications.
This module focuses on the use of R for organising, analysing, and visualising large marine datasets. Students will develop proficiency in manipulating file systems, implementing version control and processing extensive monitoring data, and generating reports on key environmental metrics. Emphasis will be placed on the importance of tidy data management and programmed workflows, ensuring efficient, reproducible scientific analysis. The skills acquired in this module are directly applicable to a wide range of marine data science applications.
5. Data Analysis at the Global Scale (Elective | 20 hours)
5. Data Analysis at the Global Scale (Elective | 20 hours)
This module introduces students to cloud-based geospatial analysis, specifically designed for handling global-scale environmental datasets. Participants will gain foundational skills in JavaScript programming to analyse spatial data in Google Earth Engine. Practical examples will focus on analysing remote sensing data to address global environmental targets. Additionally, students will learn to develop simple web-based geospatial applications to communicate their findings to a broad audience, including stakeholders and decision-makers.
This module introduces students to cloud-based geospatial analysis, specifically designed for handling global-scale environmental datasets. Participants will gain foundational skills in JavaScript programming to analyse spatial data in Google Earth Engine. Practical examples will focus on analysing remote sensing data to address global environmental targets. Additionally, students will learn to develop simple web-based geospatial applications to communicate their findings to a broad audience, including stakeholders and decision-makers.
6. Marine Genomics (Elective | 40 hours)
6. Marine Genomics (Elective | 40 hours)
Students will explore the cutting-edge field of marine genomics, learning how to generate, analyse, and interpret DNA sequencing data. This module covers core principles of modern DNA sequencing technologies and their applications in understanding marine biodiversity and evolutionary processes. Practical workshops will focus on the analysis of long-read sequencing data, with case studies including the microbial communities responsible for coral diseases. This module is designed for those seeking to expand their expertise in bioinformatics and computational biology.
Students will explore the cutting-edge field of marine genomics, learning how to generate, analyse, and interpret DNA sequencing data. This module covers core principles of modern DNA sequencing technologies and their applications in understanding marine biodiversity and evolutionary processes. Practical workshops will focus on the analysis of long-read sequencing data, with case studies including the microbial communities responsible for coral diseases. This module is designed for those seeking to expand their expertise in bioinformatics and computational biology.
7. Self-Led Learning (Elective | 20 hours)
7. Self-Led Learning (Elective | 20 hours)
In this module, students have the flexibility to design their own learning path by selecting an open-access course that aligns with their interests in data science or computing. This independent study component allows students to further develop their computing skills at their own pace. The assessment will require students to create a documented, computer-based analysis workflow, which will be presented in an ePortfolio.
In this module, students have the flexibility to design their own learning path by selecting an open-access course that aligns with their interests in data science or computing. This independent study component allows students to further develop their computing skills at their own pace. The assessment will require students to create a documented, computer-based analysis workflow, which will be presented in an ePortfolio.
8. Practice-Based Learning (Elective | 20 hours)
8. Practice-Based Learning (Elective | 20 hours)
This module allows students to integrate skills learned in the classroom with practical experience gained through volunteering in marine science. Students will work with their volunteer advisors to develop a computer-based analysis project that aligns with their volunteer work. The deliverable will be a documented analysis, which will form the basis of their assessment.
This module allows students to integrate skills learned in the classroom with practical experience gained through volunteering in marine science. Students will work with their volunteer advisors to develop a computer-based analysis project that aligns with their volunteer work. The deliverable will be a documented analysis, which will form the basis of their assessment.
9. Systematic Conservation Planning (Elective | 20 hours)
9. Systematic Conservation Planning (Elective | 20 hours)
This module, developed in collaboration with The Nature Conservancy, provides students with both the theoretical foundations and practical tools for systematic conservation planning. A key focus is the role of conservation planning in achieving the 30x30 Global Biodiversity Framework goals. Students will learn to apply decision-making tools, such as Marxan, to address complex conservation challenges. By the end of the module, students will have the skills necessary to contribute meaningfully to marine biodiversity conservation efforts.
This module, developed in collaboration with The Nature Conservancy, provides students with both the theoretical foundations and practical tools for systematic conservation planning. A key focus is the role of conservation planning in achieving the 30x30 Global Biodiversity Framework goals. Students will learn to apply decision-making tools, such as Marxan, to address complex conservation challenges. By the end of the module, students will have the skills necessary to contribute meaningfully to marine biodiversity conservation efforts.
Subject Learning Outcomes
Subject Learning Outcomes
Upon successful completion of the subject, students will be able to:
Upon successful completion of the subject, students will be able to:
• Retrieve, analyse, synthesise, and evaluate complex information to critically assess the application of contemporary marine biology theories in promoting sustainable environments and communities.
• Retrieve, analyse, synthesise, and evaluate complex information to critically assess the application of contemporary marine biology theories in promoting sustainable environments and communities.
• Organise, analyse, and interpret intricate scientific data using mathematical, statistical, and technological tools, applying an integrated understanding of multiple approaches to select the most appropriate method for various scenarios.
• Organise, analyse, and interpret intricate scientific data using mathematical, statistical, and technological tools, applying an integrated understanding of multiple approaches to select the most appropriate method for various scenarios.
• Demonstrate proficiency in advanced technical and practical skills required for data management, analysis, and communication, which are essential for professional marine science practice.
• Demonstrate proficiency in advanced technical and practical skills required for data management, analysis, and communication, which are essential for professional marine science practice.
More information
More information