Managing for Resistance and Resilience of Northern Great Lakes Forests to the Effects of Climate Change

Climate change is expected to drastically change the environmental conditions which forests depend. Lags in tree species movements will likely be outpaced by a more rapidly changing climate. This may result in species extirpation, a change in forest structure, and a decline in resistance and resilience (i.e., the ability to persist and recover from external perturbations, respectively). In the northern Great Lakes region of North America, an ecotone exists along the boreal-temperate transition zone where large changes in species composition exist across a climate gradient. Increasing temperatures are observed in the more southern landscapes. As climate change is expected to substantially affect mid-continental landscapes, this region is especially vulnerable to climate change. My research assessed the effects of climate change under business as usual (BAU) management as well as alternative management strategies. To do so, I simulated forest change in two landscapes (northeastern Minnesota and northern lower Michigan) under three climate change scenarios (current climate, low emissions, and high emissions), and four management scenarios (BAU, modified silviculture, expanded reserves, and climate suitable planting) with a spatially-explicit forest simulation model from year 2000 to year 2150. Specifically, I explored how climate change would affect relationships between tree species diversity and productivity; how expanded reserves and modified silviculture may affect aboveground biomass (AGB) and species diversity; how climate suitable planting may affect functional diversity, and AGB; and how alternative management may affect the resistance and resilience of forests to multiple disturbances interacting with climate change. Under the BAU management scenario, I found that current and low emissions climate scenarios did not affect the relationship between species diversity and productivity; however, under a high emissions climate scenario, a decline in simulated productivity was coupled with a stronger positive relationship between diversity and productivity. Under the high emissions climate scenario, overall productivity declined in both landscapes with specific species declines projected for boreal species such as balsam fir (Abies balsamea) and black spruce (Picea mariana). Under alternative management scenarios, I simulated a limited ability to increase tree species and functional diversity, AGB, and net primary productivity under climate change. The limits of management were especially apparent under the high emissions climate scenario. In a novel approach to measuring resilience, I plotted the recovery of both initial species composition and AGB to stochastic fire events for each simulation. This approach assessed both a general response (i.e. AGB) with a more specific response (i.e. species composition). My results suggest that climate change will reduce the resilience of northern Great Lake forest AGB and species composition and that management effects will be largely outweighed by the declines expected due to climate change. My results highlight the necessity to consider even more innovative and creative solutions under climate change (e.g., planting species from even further south than I simulated)

Climate-Suitable Planting as a Strategy for Maintaining Forest Productivity and Functional Diversity

Within the time frame of the longevity of tree species, climate change will change faster than the ability of natural tree migration. Migration lags may result in reduced productivity and reduced diversity in forests under current management and climate change. We evaluated the efficacy of planting climate-suitable tree species (CSP), those tree species with current or historic distributions immediately south of a focal landscape, to maintain or increase aboveground biomass, productivity, and species and functional diversity. We modeled forest change with the LANDIS-II forest simulation model for 100 years (2000–2100) at a 2-ha cell resolution and five-year time steps within two landscapes in the Great Lakes region (northeastern Minnesota and northern lower Michigan, USA). We compared current climate to low- and high-emission futures. We simulated a low-emission climate future with the Intergovernmental Panel on Climate Change (IPCC) 2007 B1 emission scenario and the Parallel Climate Model Global Circulation Model (GCM). We simulated a high-emission climate future with the IPCC A1FI emission scenario and the Geophysical Fluid Dynamics Laboratory (GFDL) GCM. We compared current forest management practices (business-asusual) to CSP management. In the CSP scenario, we simulated a target planting of 5.28% and 4.97% of forested area per five-year time step in the Minnesota and Michigan landscapes, respectively. We found that simulated CSP species successfully established in both landscapes under all climate scenarios. The presence of CSP species generally increased simulated aboveground biomass. Species diversity increased due to CSP; however, the effect on functional diversity was variable. Because the planted species were functionally similar to many native species, CSP did not result in a consistent increase nor decrease in functional diversity. These results provide an assessment of the potential efficacy and limitations of CSP management. These results have management implications for sites where diversity and productivity are expected to decline. Future efforts to restore a specific species or forest type may not be possible, but CSP may sustain a more general ecosystem service (e.g., aboveground biomass)

Beyond ecosystem modeling: a roadmap to community cyberinfrastructure for ecological data‐model integration

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data‐model integration requires investment in accessible, scalable, transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundationsof community cyberinfrastructure; data ingest; calibration of models to data; model‐data benchmarking; and data assimilation and ecological forecasting. This community‐driven approach is key to meeting the pressing needs of science and society in the 21st century

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ReadMe file is a general metadata file for all the data associated with the article

Data from: Climate suitable planting as a strategy for maintaining forest productivity and functional diversity

Within the time frame of the longevity of tree species, climate change will change faster than the ability of natural tree migration. Migration lags may result in reduced productivity and reduced diversity in forests under current management and climate change. We evaluated the efficacy of planting climate-suitable tree species (CSP), those tree species with current or historic distributions immediately south of a focal landscape, to maintain or increase aboveground biomass, productivity, and species and functional diversity. We modeled forest change with the LANDIS-II forest simulation model for 100 years (2000–2100) at a 2-ha cell resolution and five-year time steps within two landscapes in the Great Lakes region (northeastern Minnesota and northern lower Michigan, USA). We compared current climate to low- and high-emission futures. We simulated a low-emission climate future with the Intergovernmental Panel on Climate Change (IPCC) 2007 B1 emission scenario and the Parallel Climate Model Global Circulation Model (GCM). We simulated a high-emission climate future with the IPCC A1FI emission scenario and the Geophysical Fluid Dynamics Laboratory (GFDL) GCM. We compared current forest management practices (business-as-usual) to CSP management. In the CSP scenario, we simulated a target planting of 5.28% and 4.97% of forested area per five-year time step in the Minnesota and Michigan landscapes, respectively. We found that simulated CSP species successfully established in both landscapes under all climate scenarios. The presence of CSP species generally increased simulated aboveground biomass. Species diversity increased due to CSP; however, the effect on functional diversity was variable. Because the planted species were functionally similar to many native species, CSP did not result in a consistent increase nor decrease in functional diversity. These results provide an assessment of the potential efficacy and limitations of CSP management. These results have management implications for sites where diversity and productivity are expected to decline. Future efforts to restore a specific species or forest type may not be possible, but CSP may sustain a more general ecosystem service (e.g., aboveground biomass)

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

MN Biomass Succession files

Minnesota Biomass Succession input files for LANDIS-II including all three associated climate scenarios used

MN_DYNAMIC_INPUTS_COMBINED_CLIMATES

Minnesota Dynamic Input Files (All three climate scenarios

MI_DYNAMIC_INPUTS_COMBINED_CLIMATES

Michigan Dynamic Input Files (All three climate scenarios

MI_harvest_COMBINED

Michigan Harvest File