This presentation at the 2015 Society of American Foresters National Convention resulted in the Journal of Forestry paper Assessing Stand-Level Climate Change Risk Using Forest Inventory Data and Species Distribution Models.

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Presentation Abstract
Climate change will increase risks for many of the dominant forest types in northern forests, presenting a challenge for natural resource professionals to reduce climate-associated risks while still achieving diverse management objectives. Projections of regional shifts in climate and vegetative response are becoming more easily available, but managers are still searching for practical and viable ways of applying this information at the site level. The Northern Institute of Applied Climate Science’s Adaptation Workbook provides a structured process to designed help managers consider potential site-level vulnerabilities and risk qualitatively, and then plan adaptive actions that help meet management objectives. We combined this approach with “key ecological attributes” (KEAs), stand-level resilience metrics developed by The Nature Conservancy in the Great Lakes, to produce “climate-informed KEAs.” Climate-informed KEAs are a practical set of metrics using standard forest inventory data that help frame key risks initially while also providing a basis for measuring the effectiveness of adaptation actions over time. By using local field data to identify and partially quantify potential site-specific vulnerabilities, managers can more easily highlight proportions of high-risk species at the stand level and set thresholds for evaluation of management actions. We determined that 6 of 9 standard KEAs provided important information regarding climate risks; to these we added an additional three metrics focused on the risk of decline of trees, saplings, and seedlings using data from vulnerability assessments and the Climate Change Atlas. These metrics have been integrated into a forest management plan in northern Wisconsin.

Climate-Informed Forest Inventory from Northern Institute of Applied Climate Science