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Final Call for September courses - Multivariate Analysis Of Ecological Communities Using VEGAN - Bioacoustics For Ecologists: Hardware, Survey design And Data analysis - Species Distribution Modelling With Bayesian Statistics Using R

Oliver Hooker 
We still have places on our 3 September courses.

Details below.

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ONLINE COURSE ? Multivariate Analysis Of Ecological Communities Using R
With The VEGAN package (VGNR04)

https://www.prstatistics.com/course/multivariate-analysis-of-ecological-communities-using-r-with-the-vegan-package-vgnr04/

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ABOUT THIS COURSE

This 5-day course will cover R concepts, methods, and tools that can be
used to analyze community ecology data. The course will review data
processing techniques relevant to multivariate data sets. We will cover
diversity indices, distance measures and distance-based multivariate
methods, clustering, classification and ordination techniques using the R
package VEGAN. We will use real-world empirical data sets to motivate
analyses, such as describing patterns along gradients of environ-mental or
anthropogenic disturbances, quantifying the effects of continuous and
discrete predictors. We will emphasise visualisation and reproducible
workflows as well as good programming practices. The modules will consist
of introductory lectures, guided computer coding, and participant
exercises. The course is intended for intermediate users of R who are
interested in community ecology, particularly in the areas of terrestrial
and wetland ecology, microbial ecology, and natural resource management.
You are strongly encouraged to use your own data sets (they should be clean
and already structured, see the document: ?recommendation if you
participate with your data?.

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ONLINE COURSE ? Bioacoustics For Ecologists: Hardware, Survey design And
Data analysis (BIAC03)

https://www.prstatistics.com/course/bioacoustics-for-ecologists-hardware-survey-design-and-data-analysis-biac03/

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*ABOUT THIS COURSE*

This course will introduce and explain the different applications for
bioacoustics to answer ecological questions. Starting with a detailed
overview of the correct and most efficient methods of data collecting in
the field, this course will then go on to show delegates cutting edge
methods for analysing and interpreting different types of bioacoustic data.

By the end of this 5-day practical course, attendees will have the capacity
to set up and deploy recording devices, download acoustic data, how to
analyse this data and report the results.

Bioacoustic methods are becoming increasingly recognised as a valuable
approach for ecological surveying. Bioacoustics can be used to effectively
replace some current techniques whilst increasing the quality of the data
collected or can be used in unison to compliment them. They are
particularly useful for developing long-term, permanent datasets that can
be independently reviewed, particularly for rare species with low
detectability, or when working in difficult environments.

The course will provide a practical introduction to bioacoustics methods,
with a mix of lectures and practical workshops, and some optional
fieldwork. It will start with a basic introduction to sound and recording
theory, before developing hands-on skills in setting-up and deploying a
range of acoustic and ultrasonic audio recorders. Workshops will then cover
the download and analysis of audio data, mainly using Kaleidoscope Pro and
Audacity software. The processed audio data will then be analysed and
presented using R, the free software environment for statistical computing
and graphics (http://www.r-project.org/).

Example data sets will mostly cover applications for bat and bird surveys,
as well as the use of Acoustic Indices as biodiversity metrics.


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ONLINE COURSE ? Species Distribution Modelling With Bayesian Statistics
Using R (SDMB04)

https://www.prstatistics.com/course/online-course-species-distribution-modelling-with-bayesian-statistics-in-r-sdmb04/

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ABOUT THIS COURSE

Bayesian Additive Regression Trees (BART) are a powerful machine learning
technique with very promising potential applications in ecology and
biogeography in general, and in species distribution modelling (SDM) in
particular. Unlike most other SDM methods, BART models can generally
provide a well-balanced performance regarding both main aspects
of predictive accuracy, namely discrimination (i.e. distinguishing presence
from absence localities) and calibration (i.e., having predicted
probabilities reflect the species' gradual occurrence frequencies).
BART can generate accurate predictions without overfitting to noise or to
particular cases in the data. As it is a cutting-edge technique in this
field, BART is not yet routinely included in SDM workflows or in ensemble
modelling packages. This course will include 1) an introduction or
refresher on the essentials of the R language; 2) an introduction or
refresher on species distribution modelling; 3) an overview of SDM methods
of different complexity, including regression-based and machine-learning
(both Bayesian and non-Bayesian) methods; 4) SDM building and block
cross-validation focused on different aspects of model performance,
including discrimination and calibration or reliability. We will use R
packages 'embarcadero', 'fuzzySim' and 'modEvA' to
see how BART can perform well when all these aspects are equally important,
as well as to identify relevant predictors, map prediction uncertainty,
plot partial dependence curves with Bayesian credible intervals, and map
relative probability of presence regarding particular predictors. Students
will apply all these techniques to their own species distribution data, or
to example data that will be provided during the course.