Maxent predicts habitat suitability based on collected data (climate change and ecosystems, etc.) on target species and environmental factors to predict habitat and dispersal of species in the area.

To survey changes in habitats for a certain period of time in the past (e.g. 15 years) you can do modeling by defining scenarios in climate change, seasonal variation, and sea surface temperature.

When you defined scenarios and do habitat modeling for species based on them, you can compare changes made in habitats.

Ingo B. Miller ,....... Ingo, my initial suggestion is to do a search in Google and Google Scholar asking “how does maxent account for the time component of each of time occurrences?”…….some of the links below may help you ….

1)__ A statistical explanation of MaxEnt for ecologists

https://hastie.su.domains/Papers/maxent_explained.pdf

2__ MaxEnt’s parameter configuration and small samples: are we paying attention to recommendations? A systematic review

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5354112/

3)__ Use of Maximum Entropy Modeling in Wildlife Research

https://www.mdpi.com/1099-4300/11/4/854

Hi everyone,

I'm trying to run the species distribution model with the the R package 'biomod2'. I'm using the maxent algorithm. However, I'm having issues with model validation.

When I check my metric evaluation (TSS and ROC) I notice that the values ​​for Testing.data are not being generated.

I'm using the following code in R studio to get the model:

model_maxent = BIOMOD_Modeling(back, modeling.id = paste(name), models = c("MAXENT"), bm.options = options, nb.rep = 50, data.split.perc = 70, do.full.models = FALSE, prevalence = 0.5, metric.eval = c("TSS","ROC"), var.import = 100, save.output = TRUE, nb.cpu = 1, do.progress = TRUE) Am I doing something wrong?

The image shows the table resulting from the algorithm get_evaluations(model_maxent)