I am currently using Maxent to model species distribution over time using climate change data and species occurrence. I am working with three environmental variables which are all set to the same geographic projections and dimensions and saved as ascii files. I am also using my species occurrence data, which is displayed in three columns: species, UTME, and UTMN in a CSV file.
I am trying to use a minimum convex hull as a bias file to account for sampling bias in my occurrence data. I created these masks, by using the "Minimum Bounding Geometry" tool in ArcGIS, I input the species occurrence data, which was point data, to create a minimum convex polygon (MCP) mask. The result was a polygon that included all of the species occurrence points. In order to load the minimum convex polygon mask into maxent I had to convert the polygon -> raster, and then raster -> ascii. The aim is to use the MCP mask during Maxent model training, so that all cells that fall within the MCP polygon have equal likelihood of being selected as background locations.
When I plug all of my data into Maxent, I get an error message that says my climate layers (ascii files) and the bias mask have different geographic dimensions. How do I get them into the same geographic dimensions if they are displaying different types of data?
I am not sure on how to fix this problem, and can't move forward with my models until I can fix it. Any thoughts?