Livestock space use on REC pastures

Overview

• All data from GPS dataloggers from the first part of summer grazing at HREC and CGREC are in. HREC data extend from last week of May - all of June, CGREC data from all of June.
• The dataloggers record positions at 5-second intervals for 5 minutes, followed by a 50-min sleep period. Across all loggers and both locations, we’re talking about 2,124,112 rows of data (individual positions)!
• Data were made more manageable by calculating the mean longitude and latitude for each 5-minute bout. I made cells by rounding longitude and latitude to the nearest 25 m and then counted up the total number of bouts per cell.
• At Hettinger, animals appeared attracted to burned patches at the beginning of the grazing season (last week of May) but this pattern seemed to dissipate in June.
• At Central Grasslands, cattle were pretty consistently attracted to burned patches in the PBG units.
• Future analyses can consider data related to behavior and energetics, such as daily distance traveled, average speed of logging bouts, activity at different times of day, and accelerometer data.

Spatial patterns

Voronoi polygons connect gaps in raw spatial data (see below) to interpolate densities. Large polygons fill areas with fewer logged positions, while smaller polygons correspond to greater position density. Thick black lines denote spring 2018 burns. Broken black lines for CGREC divide pasture reps within units. Wagon Wheel data are pretty jacked up because the algorithm tries to interpolate for paddocks in which cattle hadn’t been moved into yet, and the whole WW SE pasture apparently didn’t get good collar data so it has been excluded.

Raw data

Raw spatial data on which the above Voronoi polygons are based (CGREC only). No positions were logged in the white areas. 25 sq m cells are simply UTM coordinates rounded to nearest 25 m and color corresponds to the proportion of logged positions within a pasture that occurred in that cell (proportion used to standardize differences in sampling effort due to different number of loggers and logger run time among pastures)