1. Maxent interface

2. Maximum Entropy (Maxent)
Deterministic
Precise mathematical definition
Continuous and categorical environmental data
Continuous output

3. Maxent can be downloaded at: http://www. cs. princeton
For this slide ask them to start Maxent to follow the presentation more easily
Note: when downloading Maxent, make sure that maxent.jar is saved as is, and not as a .zip file

4. Input data:
Samples: a .csv file with 3 fields (species label, longitude, latitude) and a header as first line. Can have multiple species in a single file
Environmental layers*: ASCII files (ESRI or DIVA-GIS formats) grouped in a folder. No mask file is needed
* also possible to use SWD format (sample-with-data): a .csv file containing the environmental variables’ values for each occurrence point

5. 2.Quadratic → square of variable 3.Product → product of two variables
Classes of features:
1.Linear* → variable itself
2.Quadratic → square of variable
3.Product → product of two variables
4.Threshold → binary transformation (0, 1) of a continuous variable using a threshold
5.Hinge → like a linear feature, but constant below a threshold
* Categorical data: Binary feature → variable itself

6. What are the features used for?
to constrain the probability distribution of maximum entropy (most spread out) which determines a species probability distribution (output prediction)
Constraints:
Linear* → mean
Quadratic → variance
Product → covariance
Threshold → fit an arbitrary response
Hinge → like linear (but constant below a threshold)
* Categorical data: Binary feature → proportion

7. Auto features setting optimizes the use of a set of features based on the number of presence records for the species
Linear features if <10 presence points available
Linear + quadratic if presence points available
Linear + quadratic + hinge if presence points available
All features if >80 presence points available
In order to override this default setting, it is necessary to use the command line flags described in help menu. However, the beta regularization value has to be adjusted too.

8. Outputs:
SpeciesName.html contains response curves, pictures of predictions and jackknife to measure variable importance if chosen
prediction can be saved as cumulative, logistic, or raw
Output file types available: ASCII grid and DIVA-GIS grid (.mxe is not a grid output)
model can be projected on different climatic datasets (different geographic region or different period of time

9. Examples of response curves (how each environmental variable affects Maxent model)
Picture of Maxent prediction

10. Used to be the default type New default type Raw values (very small)
Cumulative output
Logistic output
Raw output
Used to be the default type New default type Raw values (very small)
Each value is the sum of Non-linear scale up Sum over all cells used
probabilities of cells < the of raw values for training is 1
cell grid, times 100
General notes:
Thresholding (binning) can change the look of the map significantly
Care in interpreting the thresholds (e.g. a cumulative value of 80% doesn’t mean that the probability of a species’ occurrence is 80%)
Grids have floating points values, thus they should be imported as floating point grids this in GIS software in order to preserve the fine details in classifying cells as suitable

11. Lastly... (more) Settings button: opens a new window with more settings
Random test/train partition of occurrence data for each run; same for background data
% of occurrence data randomly set aside as test points (default is 0)
modifies the regularization value (higher value gives a more spread out distribution); works only if auto features option is off.
Sampling is assumed to be biased according to sampling distribution
Occurrence data from a file (rather than a random sample of training data) is used to test AUC, omission, etc

12. To summarize in a few words...
To run Maxent:
Occurrence data in a .csv file
Training environmental dataset (no mask needed) containing ASCII grids
Optional: environmental dataset for projecting models
Maxent outputs (predictions):
ASCII grids, floating point (not integers)
Can be raw, logistic, or cumulative predictions
Additional files, including an .html summary file