Dataset of how animal movement paths in a landscape vary due to wildfire

Animals navigate landscapes based on perceived risks vs. rewards, as inferred from features of the landscape. In the wild, knowing how strongly animal movement is directed by landscape features is difficult to ascertain, but widespread disturbances such as wildfires can serve as natural experiments. We tested the hypothesis that wildfires homogenize the risk/reward landscape, causing movement to become less directed, given that fires reduce landscape complexity as habitat structures (e.g., tree cover, dense brush) are burned. We used satellite imagery of a research reserve in Northern California to count and categorize paths made primarily by mule deer (Odocoileus hemionus) in grasslands. Specifically, we compared pre-wildfire (August 2014) and post-wildfire (September 2018) image history layers among locations that were or were not impacted by wildfire (i.e., a Before/After Control/Impact design). Wildfire significantly altered spatial patterns of deer movement: more new paths were gai..., Animal paths were traced from satellite imagery before and after a wildfire, in areas impacted by fire and in unimpacted areas (i.e., a BACI design). Paths were then counted, categorized by size, and assessed to see whether paths were persistent or were formed or lost dynamically over time. This was a pandemic project., , # Dataset of how animal movement paths in a landscape vary due to wildfire

This project has one script that performs all analyses and generates all figures. This project has two datasets.

Dataset 1 (**fidelity data.csv**) is used for the majority of the analyses in the paper.

Site and subplot are self explanatory - type indicates whether the data was collected on a plot that was impacted by wildfire between 2014 and 2018.

The rest of the columns are counts of the number of deer paths of a certain thickness in 2014 vs in 2018. For example, THIN_to_thick are paths that were thin in 2014 and became thick in 2018. NONE_to_(thick/medium/thick) are paths that didn't exist in 2014, whereas (THICK/MEDIUM/THIN)_to_none are paths observed in 2014 that disappeared.

Plots 10 and 20 do not have associated data because originally we were planning to have 10 replicates per burn treatment but could only find 9 that met our criteria for inclusion, and did not want to introduce errors by renumbering...