Measuring and managing resistance and resilience under climate change in northern Great Lake forests (USA)

Context

Climate change will have diverse and interacting effects on forests over the next century. One of the most pronounced effects may be a decline in resistance to chronic change and resilience to acute disturbances. The capacity for forests to persist and/or adapt to climate change remains largely unknown, in part because there is not broad agreement how to measure and apply resilience concepts.

Objectives

We assessed the interactions of climate change, resistance, resilience, diversity, and alternative management of northern Great Lake forests.

Methods

We simulated two landscapes (northern Minnesota and northern lower Michigan), three climate futures (current climate, a low emissions trajectory, and a high emissions trajectory), and four management regimes [business as usual, expanded forest reserves, modified silviculture, and climate suitable planting (CSP)]. We simulated each scenario with a forest landscape simulation model. We assessed resistance as the change in species composition over time. We assessed resilience and calculated an index of resilience that incorporated both recovery of pre-fire tree species composition and aboveground biomass within simulated burned areas.

Results

Results indicate a positive relationship between diversity and resistance within low diversity areas. Simulations of the high emission climate future resulted in a decline in both resistance and resilience.

Conclusions

Of the management regimes, the CSP regime resulted in some of the greatest resilience under climate change although our results suggest that differences in forest management are largely outweighed by the effects of climate change. Our results provide a framework for assessing resistance and resilience relevant and valuable to a broad array of ecological systems.

     

A new agent-based model provides insight into deep uncertainty faced in simulated forest management

Landscape Ecology - Exploratory modeling in forestry uses a variety of approaches to simulate forest management. One important assumption that every approach makes is about the deep...     

Recovery dynamics and climate change effects to future New England forests

Context

Forests throughout eastern North America continue to recover from broad-scale intensive land use that peaked in the nineteenth century. These forests provide essential goods and services at local to global scales. It is uncertain how recovery dynamics, the processes by which forests respond to past forest land use, will continue to influence future forest conditions. Climate change compounds this uncertainty.

Objectives

We explored how continued forest recovery dynamics affect forest biomass and species composition and how climate change may alter this trajectory.

Methods

Using a spatially explicit landscape simulation model incorporating an ecophysiological model, we simulated forest processes in New England from 2010 to 2110. We compared forest biomass and composition from simulations that used a continuation of the current climate to those from four separate global circulation models forced by a high emission scenario (RCP 8.5).

Results

Simulated forest change in New England was driven by continued recovery dynamics; without the influence of climate change forests accumulated 34 % more biomass and succeed to more shade tolerant species; Climate change resulted in 82 % more biomass but just nominal shifts in community composition. Most tree species increased AGB under climate change.

Conclusions

Continued recovery dynamics will have larger impacts than climate change on forest composition in New England. The large increases in biomass simulated under all climate scenarios suggest that climate regulation provided by the eastern forest carbon sink has potential to continue for at least a century.