Landscape Ecology

, Volume 33, Issue 2, pp 197–211 | Cite as

HexSim: a modeling environment for ecology and conservation

Research Article

Abstract

Context

Simulation models are increasingly used in both theoretical and applied studies to explore system responses to natural and anthropogenic forcing functions, develop defensible predictions of future conditions, challenge simplifying assumptions that facilitated past research, and to train students in scientific concepts and technology. Researcher’s increased use of simulation models has created a demand for new platforms that balance performance, utility, and flexibility.

Objectives

We describe HexSim, a powerful new spatially-explicit, individual-based modeling framework that will have applications spanning diverse landscape settings, species, stressors, and disciplines (e.g. ecology, conservation, genetics, epidemiology). We begin with a model overview and follow-up with a discussion of key formative studies that influenced HexSim’s development. We then describe specific model applications of relevance to readers of Landscape Ecology. Our goal is to introduce readers to this new modeling platform, and to provide examples characterizing its novelty and utility.

Conclusions

With this publication, we conclude a > 10 year development effort, and assert that our HexSim model is mature, robust, extremely well tested, and ready for adoption by the research community. The HexSim model, documentation, worked examples, and other materials can be freely obtained from the website www.hexsim.net.

Keywords

HexSim Simulation model Individual-based model Spatially-explicit model Mechanistic model Population viability analysis Forecasting 

Notes

Acknowledgements

We dedicate this paper to the memory of Dr. Brad McRae (1966–2017), our colleague and treasured friend. While insignificant in comparison to his multiple contributions to ecology and conservation science, Brad is due recognition here as a visionary force behind HexSim’s genetics toolkit. We are indebted to Jianguo Wu and two anonymous reviewers who made significant and insightful contributions that improved the paper’s structure, style, and impact. The information in this document has been funded in part by the U.S. Environmental Protection Agency. It has been subjected to review by the National Health and Environmental Effects Research Laboratory’s Western Ecology Division and approved for publication. Approval does not signify that the contents reflect the views of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use.

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Copyright information

© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2017

Authors and Affiliations

  1. 1.US Environmental Protection AgencyCorvallisUSA

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