Projected Changes in Tree Species Habitat in Pennsylvania

Pennsylvania's forests will be affected by a changing climate during this century. These handouts summarize projected changes in tree species habitat for four regions in Pennsylvania, and the spreadsheets provide the complete model results for those regions. The Lake Erie and Ontairo Lake Plain and Atlantic Coastal Plain areas are too small for analysis; data for these areas are best combined with the larger Mid-Atlantic region and are available here: https://forestadaptation.org/MARspecies.  

Climate Change Tree Atlas

Two climate scenarios were used to “bracket” a range of possible futures. These future climate projections were used with the Climate ChangeTree Atlas DISTRIB model to provide information about how individual tree species' habitat may change. Results for “low” and “high” climate scenarios can be compared on each spreadsheet. These handouts provide more information.

Heat and Hardiness Zones

Some trees were not modeled by Tree Atlas. For these species, climate change effects can be assessed by examining future projections of hardiness zones and heat zones for regions of Pennsylvania (right). The climate change effect was calculated by comparing the species’ published heat zone tolerance to the map of projected heat zones under two climate scenarios. As temperatures increase, it is expected that hardiness and heat zones will shift by up to 3 hardiness zones and 5 heat zones by the end of the century. This handout provides more information

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Remember that models are just tools, and they’re not perfect. Model projections don’t account for some factors that could be modified by climate change, like droughts, wildfire, and invasive species. These factors, and others, could cause a particular species to perform better or worse than a model projects. Human choices will also continue to influence forest distribution, especially for tree species that are projected to increase. Planting programs may assist the movement of future-adapted species, but this will depend on management decisions.

Despite these limits, models provide useful information about future expectations. It’s perhaps best to think of these projections as indicators of possibility and potential change. The model results presented here provide the best information when combined with information from published reports and local management expertise.