The DREAM Project – Desired Regeneration through Assisted Migration
Climate change is altering conditions across the planet. Increasing temperature and variations in amount and seasonality of precipitation throughout the year will continue to impact how species respond. The future is uncertain. Thus, natural resource managers need climate-informed decision support tools to effectively plan for and counteract these changes to sustain long-term forest health and resilience.
Projections indicate changes in climate may outpace the rate of natural plant adaptation and migration. This mismatch presents a significant challenge for resource managers as they make decisions on what tree species to select, grow, and plant during reforestation and restoration projects.
How can land managers be sure that trees planted today will meet the climatic challenges of tomorrow? One strategy that holds promise is assisted migration. Assisted migration is defined as the human-assisted relocation of species in response to climate change and may include one of the following components:
- Assisted population migration involves the movement of seed sources or populations to new locations within a historical range of variability.
- Assisted range expansion is the movement of seed sources or populations from their current range to suitable areas just beyond their current range, facilitating or mimicking natural dispersal.
- Assisted species migration is the movement of seed sources or populations to a location outside of the established range of a species, beyond locations accessible by natural dispersal.
The DREAM (Desired Regeneration through Assisted Migration) Project is comprised of three major components:
- Developing next generation climate impact assessment tools.
- Testing physiological tolerances of species.
- Planting trees across a range of silvicultural scenarios.
Climate Impact Assessment Tools
Climate Impact Assessment Tools increasingly incorporate climate analogs (locations in space and time that share similar climatic conditions) to forecast potential future climate change impacts on ecological systems. Specifically, climate analogs match projected future climates with contemporary climates on the landscape today. If an ecosystem is projected to experience a warmer and drier climate, climate analog models locate contemporary locations elsewhere on the landscape that are also similarly warm and dry – supporting ecological forecasting by analogy. The locating of climatic analogs relative to future conditions supports identification of source populations and/or novel tree species that may be potentially future adapted to climate change in assisted migration applications. Northern Research Station researchers are developing next generation climate analog models by incorporating tree species range information, thus easing the decision process in developing assisted migration action by combining these two important pieces of information.
Climate analogs can also be used to identify future time periods when projected climate change exceeds historical range of variability – after which ecological systems will occur in climates with no historical analogs at those locations. Estimating the Time of Emergence (ToE) of local climatic novelty reflects the varying state of urgency in climate change adaptation across locations and more precisely fine-tunes the timing of assisted migration applications. Identifying climate analogs and ToE of local novel climatic regimes will help land managers identify potential future-adapted seed sources and plan for restoration projects..
After identification of analog locations, our next two components begin to tease apart the influence of environmental variation on physiological tolerances.
Testing Physiological Tolerances
Every species has a set of environmental conditions within which it can best survive and reproduce. Abiotic conditions, such as temperature and soil chemistry and biotic conditions, such as browsing and competition, influence growth and population.
By testing the physiological tolerances of tree species, Northern Research Station scientists are working to identify species that have a higher ability to cope with extreme conditions (e.g. drought tolerance) as well as how changing environmental factors may impact tree growth and vigor. Testing the physiological tolerances of tree species can provide answers to land managers on what species may thrive in future conditions before costly investment and waiting decades to monitor outcomes.
Silvicultural Scenario Planting
Predicting the appropriate climate analogs and testing them for their physiological tolerances alone will not guarantee planting success. Experimental plantings are necessary to observe seedling survival, growth, and condition as they occur under a wide range of environmental conditions known to strongly affect seedling success.
Our researchers are conducting experimental planting trials. The DREAM approach differentiates itself from other assisted migration trials in that planting trials explicitly consider and manipulate three factors known to strongly affect seedling success: light levels, competing vegetation, and deer browsing (Figure 2).
In collaboration with managers, our scientists are designing harvesting schemes to influence understory light levels, mitigates competing vegetation, and manages browsing impacts. By planting future-adapted seedlings under a broad set of conditions, the DREAM approach will provide guidelines on how to maximize future-adapted nursery stock success efficiently and cost-effectively.
Given the high level of uncertainty in the timing and intensity of climate change and the resulting impact on forests, land managers need access to the best available science to support strategies that confer resilience to a broad range of climatic futures.
This research will build a foundation of identifying tree species and genetic stock that could perform well as climate continues to change as well as develop the silvicultural tools that will help managers plant the forests of tomorrow, today.
Champagne, Emilie; Bonin, Michaël; Royo, Alejandro A; Tremblay, Jean-Pierre; Raymond, Patricia. 2020. Predicting terpene content in dried conifer shoots using near infrared spectroscopy. Journal of Near Infrared Spectroscopy. 28(5-6): 308-314. https://doi.org/10.1177/0967033520950516.
Champagne, Emilie; Royo, Alejandro A.; Tremblay, Jean-Pierre; Raymond, Patricia. 2019. Phytochemicals Involved in Plant Resistance to Leporids and Cervids: a Systematic Review. Journal of Chemical Ecology. 46: 84-98. https://doi.org/10.1007/s10886-019-01130-z.
- Bryce Adams, USDA Forest Service Northern Research Station, Research Forester
- Dustin Bronson, USDA Forest Service Northern Research Station, Research Plant Physiologist
- Christel Kern, USDA Forest Service Northern Research Station Research Forester
- Patricia Raymond - Ministère des Forêts, de la Faune et de Parcs, Québec.
- Alejandro Royo, USDA Forest Service Northern Research Station Research Ecologist
- Paula Marquardt, USDA Forest Service Northern Research Station (retired)
- Carrie Pike – Area Regeneration Specialist, Northeastern Area State and Private Forestry
- Jessica Miesel, Michigan State University - College of Agriculture & Natural Resources Department of Plant, Soil and Microbial Sciences Assistant Professor
- Tyler Refsland, Michigan State University - College of Agriculture & Natural Resources Department of Plant, Soil and Microbial Sciences Post-Doctoral Fellow
- Amanda McGraw –Wisconsin Department of Natural Resources - Division of Forestry
- Carrie Sweeney, USDA Forest Service Eastern Region
- Mike Tighe, USDA Forest Service Eastern Region
- Nick Labonte, USDA Forest Service Eastern Region
- Last modified: May 14, 2021