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 most basic data analysis in biology. Students will receive 8 computer-based workshops/practicals, complemented by short introductory lectures to each workshop. These workshops will cover 5 key themes: 1). Scientific computing, reproducibility and the R Software Environment; 2). Data management; 3). Data visualization; 4). Data analysis - The general linear model; 5). Data analysis - Outline of more advanced methods. The module will be subject to continuous assessment consisting of 8 pieces of computer-based work, 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. There will also be a weekly 1 hour feedback session/lecture.
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 at 1pm, 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 the 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 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 organisms from aphids to eagles. While the module will refer to movement in a wide variety of animals, many strands of behavioural ecology have been developed using birds as model organisms, several themes therefore feature birds (both marine and terrestrial) more than other organisms. Movement will be examined over a range of spatial and temporal scales, as recorded using some of the very latest technologies.
This module extends core knowledge of statistical computing to cover a range of more specialized topics of particular importance to the analysis of real world biological datasets, such as those collected for final year undergraduate research dissertations. We use the R software environment; building on experience of this gained during the core Second Year module, BIB214 – Ecological Data Analysis. Students will be guided through 5 computer-based workshops / practicals, including brief introductory lectures to each topic. Further help will be provided through a series of drop-in sessions and a dedicated module Facebook group. The workshops, and associated additional guidance, will cover 5 key themes: 1) Linear modelling refresher, 2) Generalised Linear Modelling A - Count data, 3) Generalised Linear Modelling B - Proportion data, 4) Non-parametric analysis, 5) Introduction to grouped data. The module will be subject to continuous assessment, consisting of 5 pieces of computer-based work, throughout the course. In addition, students will complete a coursework assignment after the course, where they will gain additional experience of analysis and interpreting biological data.
Students in this course will learn to identify scientific papers of relevance using literature databases, to appraise the results of scientific research and effectively extract information of relevance, and to present the results of a literature search in a clear and logical manner within a correctly structured essay format
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.
Students in this course will learn to (1) identify scientific papers of relevance to their program of study using literature databases, (2) appraise the results of primary research and effectively extract and summarise scientific information, and (3) present the results of a literature search in a clear and logical manner within a correctly structured review format Assessment for this module is 100% through continuous assessment. This module requires the submission of two pieces of work of appropriate standard and according to the format of a peer-review publication. The topic of the first review will be given by the instructor and will be submitted before the end of term 1 (worth 40% of the mark), while the second term review (topic chosen by the student) will be submitted at the end of the term (worth 60% of the mark). There are no examinations for this module