Since 2006, our team have taught over 60 courses, to more than 1200 participants, all around the globe. In fact, Africa and Antarctica are the only two continents where we haven’t taught a course, so far!
We periodically deliver openly-advertised courses, or can provide in-house training if you prefer. A mix of theory and practice is used in all of our courses to cement understanding on the topic being taught.
We're going online!
Due to the current global situation we're currently developing an online version of the Occupancy Modelling - Beginner/Intermediate course, that will be available from August 2020.
Contact us if you have any questions.
The teaching of in-person courses has been suspended until further notice.
Thank you, your registration has been placed.
You will be contacted by Proteus soon.
You have been sent an email with registration and payment details.
For payment to Proteus' New Zealand bank account (for payments within New Zealand, only the bank account number is required)
Bank Name: Bank of New Zealand, Wellington, New Zealand
SWIFT code: BKNZNZ22
Branch Address: 98 George St, Dunedin
Account Name: Proteus Research and Consulting Ltd
Account Number: 02 0912 0154125 000
Thank you, your waitlisted registration has been placed.
You will be contacted by Proteus if places become available.
You have been sent an email with registration details.
Below is a list of courses that we have taught previously, but we can develop a course to suit your specific requirements. Occupancy modelling courses are our particular specialty, with Darryl MacKenzie having played a key role in the development of the methods.
Species presence/absence is a fundamental concept used in many areas of ecology (e.g., species distributions, habitat modelling, monitoring, and metapopulation studies), however imperfect detection can lead to false absences. Unaccounted for, false absences can lead to misleading inferences about patterns and dynamics of species occurrence, and the factors that influence them.
In this 4.5 day introductory course we cover methods that have been developed to account for imperfect detection with species detection/nondetection data, and also discus important study design considerations. Classroom exercises are completed using the purpose-built software Program PRESENCE, and also R.
This course is targeted at those that have no, or little, experience with occupancy modelling, but more experienced users may also benefit from attending. Familiarity with regression, logistic regression or generalised linear modelling would be an advantage.
There are a number of useful extensions of the basic models that are covered in the beginner/intermediate course, such as multi-scale occupancy models, multi-state models and species co-occurrence model. In this 3-day advanced course, we present the theory of these more complex approaches, along with classroom exercises. All exercises are completed in R.
Participants are expected to well experienced in occupancy modelling, and may have completed the above course (or a similar course) but this is not a requirement. They should also be comfortable in using R, e.g., data input/output, produce plots, understand the formula-based notation frequently used in R for defining models.
Mark-capture studies are widely used to study the demographics of animal and plant populations, e.g., for estimating population size and survival rates. There is a great deal of variety for exactly what type of data may be collected, depending on the questions of interest and resources available. Program MARK is software that has been developed for analysing data from many of these different types of mark-recapture studies.
In this 4-day course we introduce participants to the software, teaching them the basics of how to analyse data with Program MARK. While some of the underlying theory is covered, the focus is on how to use the software. Participants are expected to have a good understanding of the fundamentals of mark-recapture methods (e.g., closed population models, Cormack-Jolly-Seber model, Pollock’s robust design), and familiarity with regression models, logistic regression or generalised linear models.
R is a programming environment that is becoming increasingly popular over time. While often thought of as software for conducting statistical analyses, it is much more than that. This 4-day course is intended to introduce participants to many of the fundamentals of using R for entering and manipulating data, data summaries, conducting basic analyses, creating plots and more.