In her PhD project, Karen Lone studies the ecology of forest dwelling ungulates in Norway using LiDAR to map habitat vegetation structure. This is the first published study of that work, in which she and coauthors identify several habitat characteristics that influence risk of roe deer being killed by their two main predators, human hunters and lynx. They did this by comparing the habitat at sites used by living GPS marked roe deer to confirmed kill sites of roe deer. The LiDAR variable representing the density of understory vegetation was important for risk from both predators. As hypothesized, the effect was contrasting, with lynx risk increasing and hunting risk decreasing when going from a more open understory to a denser understory. But also terrain variables derived from the accurate LiDAR terrain model were associated with different levels of risk. LiDAR variables were nearly as good as alternative field measurements of habitat characteristics. The great advantage of using LiDAR is that the data have fine resolution across large spatial scales. In this study, that meant that we could use the relationships we found to map risk predictions across the whole study area, yielding insight in the patterns on the landscape scale. In the case of roe deer facing two predators with contrasting risk pattern, it turns out that there are very few and small areas with low predation risk from both predators (see figure).

Spatial variation in risk that roe deer face from lynx and hunters, derived from GPS-marked animals, data from hunters and remotely sensed vegetation and topography from LiDAR. Below average and above average risk levels are shown by green and red colors, respectively.

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