Open Issues Need Help
View All on GitHubAI Summary: The user is encountering an error when using the `BIOMOD_RangeSize` function in the `biomod2` R package. The error message indicates that the input objects (`proj.current` and `proj.future`) must be of the same class (data.frame, SpatRaster, or array), but they are both of class "BIOMOD.projection.out". The task is to determine why the objects are not being correctly recognized as one of the expected classes and to modify the code to resolve the error, allowing the calculation of species range size.
BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships.
AI Summary: The task is to determine the appropriate number of environmental variables to use in species distribution modeling with the biomod2 package in R, given approximately 100 occurrence sites. The user has already performed correlation and VIF filtering, resulting in over 10 variables. The goal is to advise on whether further variable reduction is necessary and to provide guidelines or ratios for the number of sites versus variables in biomod2.
BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships.
AI Summary: The task is to debug a species distribution model built using the `biomod2` R package. The user is encountering an issue where their ensemble model's binary suitability map is entirely unsuitable, despite individual models and continuous ensemble outputs showing suitable areas. The problem likely stems from how the threshold for binarization is applied to the ensemble model's output, potentially due to a misunderstanding of the cutoff value or an unexpected data range in the ensemble predictions. The solution involves analyzing the provided code, evaluation metrics, and output maps to identify the source of the discrepancy and correct the binarization process.
BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships.
AI Summary: The task is to debug a BIOMOD2 R code snippet that produces a "subscript out of bounds" error when using a user-defined cross-validation strategy. The error occurs within the `BIOMOD_Modeling` function, specifically when using the 'user.defined' CV strategy with a custom table (`mySplitTable`). The solution involves investigating the structure and content of `mySplitTable` to ensure it's correctly formatted and compatible with BIOMOD2's expectations for user-defined cross-validation, potentially involving debugging the data preparation steps or the `BIOMOD_Modeling` function call itself.
BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships.
AI Summary: The user needs help normalizing the predicted habitat suitability values from the BIOMOD2 R package's GBM and MAXNET models, and their ensemble, to a 0-1 range. Their current output ranges from 0 to values much higher than 1. The task involves understanding the BIOMOD2 workflow and identifying the appropriate normalization method within the package or through external R functions.
BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships.
AI Summary: The user is experiencing inconsistent model outputs in the `biomod2` R package when rerunning species distribution models. They are using the package to predict current and future species ranges, and the results vary on each run. The task is to debug the provided code to identify why the model outputs are not reproducible and to address the 'no parallel backend registered' warning.
BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships.