SANParks: Managing Wildlife Populations

Kruger National Park (KNP), in collaboration with the National Center for Ecological Analysis and Synthesis (NCEAS), is developing a system that uses Kepler workflows to facilitate conservation management analysis. Funded by the Andrew W Mellon Foundation, this workflow-based solution is being adopted by the twenty-two South African National Parks (SANParks) to greatly improve the adaptive management of the park system.

Adaptive management is an increasingly popular framework for managing wildlife populations. Under this framework, park management strategies are treated like scientific experiments, and scientists responsible for wildlife populations evaluate the results of the experiments to determine which works best. At any given time, dozens of loosely coordinated monitoring and experimental projects are underway at each park, and scientists face the challenge of how to most effectively collect, present, and preserve the highly variable collection of scientific data so that it can be used to inform park management decisions. In response to this challenge, scientists at Kruger National Park have developed a system of "Thresholds of Potential Concern" (TPC).

Thresholds of Potential Concern can be thought of as acceptable upper and lower limits in selected environmental indicators, such as elephant density, tree density, or buffalo population. Park scientists and managers collect data about these indicators and then test whether they are within the acceptable upper and lower limits set for them. By identifying areas of concern as well as indicators to measure them, managers can see where the park ecosystem stands in relation to its goals.

Kepler workflows are used to automatically test for TPC crossings by periodically analyzing collected data to check if a TPC has been exceeded. Results are output to a Web-based reporting system. Because the data files and numbers used by Kepler are visible on the Web, park scientists can experiment and explore possible future scenarios by changing the values of these numbers, rerunning the workflow, and comparing the new experimental output with their management goals.

For more information, please see the SANParks Data Repository.