Models of political-ecological systems can inform policies for managing ecosystems that
contain endangered species. One way to increase the credibility of these models is to
subject them to a rigorous suite of data-based statistical assessments. Doing so involves
statistically estimating the model's parameters, computing confidence intervals for these
parameters, determining the model's prediction error rate, and assessing its sensitivity to
parameter misspecification.
Results/Conclusions
Here, these statistical algorithms along with a method for constructing politically feasible
policies from a statistically fitted model, are coded as JavaSpacesTM programs that
run as compute jobs on either supercomputers or a collection of in-house workstations.
Several new algorithms for implementing such jobs in distributed computing environments
are described.
This downloadable code is used to compute each job's output for the management
challenge of conserving the East African cheetah (Acinonyx jubatus). This case study shows
that the proposed suite of statistical tools can be run on a supercomputer to establish the
credibility of a managerially-relevant model of a political-ecological system that contains
one or more endangered species. This demonstration means that the new standard of
credibility that any political-ecological model needs to meet before being used to inform
ecosystem management decisions, is the one given herein.