Hi there,
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: mean summer, mean winter, and annual precipitation, 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 bias mask 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 the MCP mask. The result was a polygon that included all of the species occurrence points. In order to get the MCP mask into maxent I had to convert the polygon -> raster, and then raster -> ascii. The bias masks were created using the species occurrence data, and simply present a repeatable way of limiting the extent of the study area. 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.
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?
Thanks,
Caroline