Ken Ferschweiler

Associate Software Architect | Modeler

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Ken was a Senior Software Architect and Modeler at Conservation Biology Institute. His work focused primarily on the climate change model, MC1. Ken is now retired and an associate at CBI.

Ken Ferschweiler has 30 years of experience in computer science, and in 2010 he jumped at the opportunity to join CBI’s climate change research group and use that experience in addressing ecological modeling problems. Ken has worked in the US and in Europe in areas ranging from artificial intelligence to massively parallel computing, but has been happiest when using computers to help scientists solve scientific problems.

Simulating Effects of Climate and Vegetation Change on Distributions of Martens and Fishers in the Sierra Nevada, California, Using Maxent and MC1

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Santa Monica Mountains Woolsey Fire Recovery and Adaptation Program

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Utah DWR and BLM Colorado Plateau Step-Down Project

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Human Footprint Affects US Carbon Balance More Than Climate Change

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Data Basin integration with Northwest Knowledge Network, and a Conterminous US Climate Console

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Estimation of potential evapotranspiration from extraterrestrial radiation, air temperature and humidity to assess future climate change effects on the vegetation of the Northern Great Plains, USA

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Mapping future fire probability under climate change: Does vegetation matter?

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Climate change effects on southern California deserts

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Fire, CO2, and climate effects on modeled vegetation and carbon dynamics in western Oregon and Washington

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Projected major fire and vegetation changes in the Pacific Northwest of the conterminous United States under selected CMIP5 climate futures

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Effects of climate and vegetation on the current and future distribution of martens and fishers in the Sierra Nevada, California

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Kenogami-Ogoki Forest Conservation Planning in Ontario, Canada

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California Statewide Energy Planning

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Projected carbon stocks in the conterminous US with land use and variable fire regimes

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Soil depth affects simulated carbon and water in the MC2 dynamic global vegetation model

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