In this module you will discover what it takes to be a research scientist and discuss world-leading research with biologists from Universities and research institutes from all over the UK and further afield. You will attend our Biosciences seminar series, generally held every second Thursday, as well as a series of journal clubs and more informal talks, held on the Thursdays in between the biweekly seminars. Following each seminar there will be a group workshop with the speakers where you will to learn to evaluate critically current research and advanced scholarship in the discipline, and gain a practical understanding of how established techniques of research and enquiry are used to create and interpret knowledge in Biosciences. For a selection of seminars, you will summarise the research highlights (3 to 5 bullet points, maximum 85 characters) and write an abstract on the research (max 300 words). You will also produce brief, webinar-style presentations and blogs for Swansea BioTalks, the blog for our seminar and journal club series at the Department of Biosciences. These tasks will allow you to fine-tune your communication skills and increase your depth of understanding of the latest research in Biosciences.
This module introduces students to the basics of analyzing ecological data, using the R Software Environment for Statistical Computing. The topics covered will be also broad enough to be equally applicable to basic data analysis across biology. Students will receive 7 computer-based workshops/practicals, complemented by 7 lectures before each workshop. Furthermore, a weekly drop-in stats help session will be provided, as well as help through a course Facebook page. The module will cover 5 key themes: 1). Data analysis and statistics, reproducibility and the R Software Environment; 2). Data management; 3). Data visualization; 4). Data analysis - The general linear model; 5). Data analysis - Presentation of results and outline of more advanced methods. The module will be subject to continuous assessment consisting of 6 pieces of computer-based work (70% of final mark), which will require the students to carefully complete all course work assigned on a weekly basis ('independent learning'), in order to be able to complete the assignments. A further 30% of the final mark will consist in a data analysis report, to be completed after the end of the course. Weekly readings and non-assessed computer-based exercises will be assigned, too.
This module will examine why, how, where and when organisms move. The lectures will draw on first principles of animal movement in order to examine the costs and benefits of different movement strategies and how they apply to animals from aphids to eagles. While the module will refer to movement in a wide variety of animals, many core elements of behavioural ecology have been developed using birds as model organisms. Consequently, several key module themes are explored using birds as examples. Movement will be examined over a range of spatial and temporal scales, as recorded using some of the very latest technologies.
This module introduces students to the Movement Ecology Framework, a unified conceptual approach for analysing and modelling the movement of organisms, ranging from bacteria, to plants, to animals. Students will receive 10 lectures which introduce specific subject areas, combined with 10 computer-based practicals/workshops and six field-based practicals. The module is assessed by a combination of continuous assessments (40%) and weekly project work (60%), which replaces the end-of-year exam.