Open AccessDeveloping political-ecological theory: The need for many-task computing
Author(s) -
Timothy C. Haas
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0226861
Subject(s) - credibility , computer science , workstation , acinonyx jubatus , task (project management) , cloud computing , data science , statistical model , code (set theory) , ecology , machine learning , set (abstract data type) , biology , engineering , political science , systems engineering , law , programming language , operating system
Models of political-ecological systems can inform policies for managing ecosystems that contain endangered species. To increase the credibility of these models, massive computation is needed to statistically estimate the model’s parameters, compute confidence intervals for these parameters, determine the model’s prediction error rate, and assess its sensitivity to parameter misspecification. To meet this statistical and computational challenge, this article delivers statistical algorithms and a method for constructing ecosystem management plans that are coded as distributed computing applications. These applications can run on cluster computers, the cloud, or a collection of in-house workstations. This downloadable code is used to address the challenge of conserving the East African cheetah ( Acinonyx jubatus ). This demonstration means that the new standard of credibility that any political-ecological model needs to meet is the one given herein.