Introduction
In my last post, I discussed the importance of quantifying social contacts to predict microbe transmission between individuals in our study herd of African Buffalo. This post deals with the other half of the equation: environmental transmission. My overarching hypothesis is that spatial and social behaviors are important for transmission of host-associated microbes. The goal of this pilot project is to establish a method for quantifying habitat overlap between individuals in the herd so that I can (eventually) compare habitat overlap with microbe community similarity and infection risk.
Methods/Results
Workflow:
I used the following outline to determine pairwise habitat overlap between a “test” pair of buffalo:
- Project GPS points in ArcMap
- Clip GPS points to the enclosure boundary layer
- Use GMe to generate kernel density estimates and 95% isopleths
- Back in Arc, used the identity tool to calculate area of overlap between the two individuals
- Computed percent overlap using Excel
Geospatial Modelling Environment (GME):
GME is a free geostatistical software that combines the computational power of R with the functionality of ESRI ArcGIS to drive geospatial analyses. A few of the functions that are especially useful for analyzing animal movement are: kernel density, minimum convex polygons, movement parameters (step length, turn angle, etc), converting locations to paths and paths to points, and generating simulated random walks. For this analysis, I used GME to generate kdes and estimate home ranges using 95% isopleths.
Kernel density estimates and isopleth lines
Kernel densities can be conceptualized as 3-dimensional surfaces that are based on density of points. Isopleth lines can be drawn in GME based on a raster dataset (such as a kernel density) and can be set to contain a specified volume of surface area. For this analysis, I was interested in calculating 95% isopleths based on the kernel densities of GPS points. In real life, this means the area that an animal spends the majority of its time in.
Using the identity tool to compute overlap
After generating home range estimates for two individuals, I uploaded the resulting shapefiles to ArcMap and used the Identity tool to overlap the home ranges. To use the identity tool, you input one identity feature and one or more input features. Arc then computes a geometric intersection between input features and identity features and merges their attributes in the output.
The map above shows 95% isopleths from animal 1 (yellow), animal 13, (purple), and the area of overlap computed using the intersect tool (red line). I exported the output table to excel, where I calculated percent overlap between animals.
Conclusion
Overall, this method seems like it will be great for estimating habitat overlap. A few things that I’m concerned about are:
(a) Habitat use may be so similar for all animals that overlap cannot be related to differences in microbe transmission.
(b) Habitat use may correlate very strongly with contacts, in which case it will be difficult to control for the effects of contacts on microbe transmission.
(c) Percent overlap can be different for each individual in a pair. In my example, #13 overlapped #1 by ~80%, while #1 overlapped #13 by 90%.
I just want to be aware of these potential issues and start thinking about how to deal with them as they arise. Any suggestions would be appreciated, as always!
