Kernel density estimators are commonly used for estimating the home range of animals (see my previous post on estimating home ranges with kernels).
But, a common issue is that the kernel contour for an animal extends beyond a boundary the animal cannot cross. Can we adjust the density estimator and limit kernel contours to not cross boundaries? The code and data I use in this tutorial are available on my on my GitHub repo. One of my favourite ways to visualize wildlife tracking data is to animate paths. Using `ggmap` and `gganimate`, it has never been easier to show-off your hard-earned tracking data with animated maps you can use in presentations, meetings, and at dinner parties.
The code and data I use in this tutorial are available on my on my GitHub repo. Kernel density estimators are often used for measuring home ranges and this is useful for measuring interactions between animals and their environment. However, kernels are sensitive to the choice of a smoothing factor (h).
For reptiles, Row & Blouin-Demers (2006) recommended using an h that creates a 95% contour area equal to the 100% minimum convex polygon. I have written two functions in R to do this for any tracking data set. This post will be helpful if you:
Kernel density estimators, which map a utilization distribution, are one of the most popular methods for measuring home ranges. I show how to create kernel home range estimates in R using sample data.
The code and data used are available on my GitHub page. This post builds on my previous post estimating home ranges with minimum convex polygons. What is a home range?
"that area traversed by the animal during its normal activities of food gathering, mating and caring for young. Occasional sallies outside the area, perhaps exploratory in nature, should not be considered as in part of the home range.” -Burt 1943 The most commonly cited definition is vague and does not provide a clear method for estimating the home range. So what should someone wanting to calculate home ranges do? |
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