"ClusterApp": A Shiny R application to guide cluster studies based on GPS data

Abstract

The rapid evolution of GPS devices, and therefore, collection of GPS data can be used to investigate a wide variety of topics in wildlife research. The combination of remotely collected GPS data with on-the-ground field investigations is a powerful tool for exploring behavioral ecology. "GPS cluster studies" are aimed at pinpointing and investigating identified clusters in the field. Activity clusters can be based on various parameters (e.g., distance between GPS locations and the number of locations needed to establish a cluster), which are closely related to the set research questions. Variation in methods across years within the same study may result in data collection biases. Therefore, a streamlined method to parametrize, generate interactive maps, and extract activity cluster data using a predefined approach will limit biases, and make field work and data management straightforward for field technicians. We developed the "ClusterApp" Shiny application in the R software to facilitate a step-by-step guide to execute cluster analyses and data management of cluster studies on any species using GPS data. We illustrate the use of the "ClusterApp" with two location datasets constructed by data collected on brown bears (Ursus arctos) and gray wolves (Canis lupus).

Keywords: Shiny application; animal activity; cluster analysis; fieldwork; movement data.

FIGURE 1

Flowchart showing the three main tabs when using the “ClusterApp” application to create clusters for investigations in the field.

FIGURE 2

Changes to the size of the buffer (m) or the minimum number of GPS locations influence the cluster output (red polygons) in the “ClusterApp” application. Turquoise points show the same selection of GPS locations of one collared wolf in each of the four panels.

FIGURE 3

Examples of the visualized clusters within the interactive map in the “ClusterApp” application. Cluster polygons are filled according to their “State” (in this example, all red for State = New), while the track and GPS locations of the three brown bears used in this example are visualized with different colors. The blue pin drops show the last position for each brown bear.

FIGURE 4

Completed data table (filtered for the individual W1312) and visual output of the clusters in the “ClusterApp” application, which are filled according to the “Event” column. After on‐the‐ground site visits of the identified clusters, this column, as well as the columns “State” and “Date done” could be filled in with an array of identified activities at the clusters.