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ONLINE COURSE – Movement Ecology (MOVE04) This course will be delivered live
23 May 2022 - 27 May 2022
£450.00
Event Date
Monday, May 23rd, 2022
Course Format
This is a ‘LIVE COURSE’ – the instructors will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
Time Zone
TIME ZONE – GMT+1 – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you.
About This Course
The course will cover the concepts, technology and software tools that can be used to analyse movement data (from ringing/CMR to VHF/GPS) in ecology and evolution. We will cover elementary and advanced analysis and modelling techniques broadly applicable across taxa, from micro-organisms to vertebrates, highlighting the advantages of a unified Movement Ecology framework. We will provide the necessary bases in ecology (especially behavioural ecology), physics and mathematics/statistics, to be able to identify for any specific research question the most appropriate study species, logging technology (incl. attachment methods), and statistical/mathematical modelling approach. We will specifically address the challenges and opportunities at each of the steps of the proposed ‘question-driven approach’, combining theory with computer-based practicals in R. We will also address the challenges of applying the results of the analyses to applied management problems and communicate the findings to non-experts.
Intended Audiences
Research postgraduates, practicing academics and primary investigators in ecology and management and environmental professionals in government and industry. The course will also be of interest to researchers in geography, mathematics and computer science working on movement analyses.
Venue
Delivered remotely
Course Details
Availability – TBC
Duration – 5 days
Contact hours – Approx. 37 hours
ECT’s – Equal to 3 ECT’s
Language – English
Teaching Format
Assumed quantitative knowledge
A basic understanding of statistical, mathematical and physical concepts. Specifically, generalised linear regression models, including mixed models; basic knowledge of trigonometry, basic knowledge of calculus; basic knowledge of physics as relevant for biological systems.
Assumed computer background
Good familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models (up to GLM); generate simple exploratory and diagnostic plots. Knowledge of more advanced models, such as mixed models, will be helpful, as will a basic recollection of mathematical analysis.
Equipment and software requirements
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.
All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.
A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.
Although not strictly required, using a large monitor or preferably even a second monitor will improve he learning experience
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
COURSE PROGRAMME
Monday 23rd
Classes from 12:00 to 20:30
Movement Fundamentals
Conceptual component: Introduction to movement ecology, movement and behaviour, spatial and movement path analysis.
Practical component: Movement path analysis I – from steps and turns to movement path segmentation; Movement path analysis II – movement modes (home rage, dispersal, migration, nomadism) and the squared displacement method.
Tuesday 24th
Classes from 12:00 – 20:30
Home Range Analysis
Conceptual component: Ecological definitions and interpretations of home ranges, home range estimation, comparisons between estimators and the question-driven approach.
Practical component: Utilization distribution; comparison of contrasting kernel home range estimation methods, isopleth creation, core area & home range overlap.
Wednesday 24th
Classes from 12:00 – 20:30
Dynamic Interactions and Temporal Metrics of Movement
Conceptual component: Movements of interacting animals – static and dynamic interactions; scales of movement – first-passage and residence time analysis.
Practical component: Static and dynamic interaction indices; estimation of first-passage and residence time metrics
Thursday 26th
Classes from 12:00 – 20:30
Introduction to Resource Selection, and Effects of Scale
Conceptual component: Theories of resource and habitat selection, history of approaches, and current methodologies and caveats including definitions of availability and scale effects for RSF and other movement metrics
Practical component: Data projections and R as a GIS; Scale-integrated models of movement, availability sampling, and RSF estimation and interpretation
Friday 27th
Classes from 12:00 – 20:30
Step-Selection Functions and Instantaneous Availability
Conceptual component: Introduction to step selection, decision-making processes, null and alternative models for definitions of availability within SSF, movement-integrated step-selection analysis
Practical component: Creation of available step data, estimation of SSF using multiple packages and approaches, simulation of utilization and occurrence distributions.
Course Instructor
Prof. Luca Borger
Coming Soon
Dr. Jarrett Street
Coming Soon