Exploring Future Flora, Environments, and Climates Through Simulations (EFFECTS)
“Studying the effects of past climate change is key to understanding potential future climate change impacts.”
Future climate change will alter the distribution of vegetation in North America and affect related ecosystem processes. This research uses state-of-the-art climate model simulations and vegetation models to simulate vegetation changes from 127 ka (127,000 years ago) to 2100 CE. We investigate the magnitude, rate, and drivers of vegetation responses to climate change across paleo to future time periods, with a focus on forest-to-grassland or shrubland and boreal forest-to-tundra transitions in North America. Results of this research will help conservation and natural resource managers develop adaptive management responses to climate change.
Large Vegetation Changes May Affect Climate
Climate model simulations help us understand the potential impacts of future climate change. We use projected future climate data with vegetation models to simulate potential future vegetation changes, but we have no data from the future to help us evaluate the accuracy of these model simulations.
To better understand the potential impacts of future climate change, climate models are run for past time periods when the Earth’s climate was different from the present climate. We use these paleoclimate simulations with vegetation models to simulate past vegetation changes and compare the results with paleoclimate- and paleovegetation-related data from ice sheets, lake and ocean sediments, tree rings, and a range of other sources.
The term “paleo” comes from the Greek word “palaios”, which means ancient.
Our research collaborations with partners at the National Center for Atmospheric Research (NCAR), the University of Oregon, and elsewhere have shown that vegetation changes over large areas during the Last Interglacial period (~127,000 years ago; animated image, right) may have affected Greenland Ice Sheet melting and subsequent sea level rise (Sommers et al. 2021, Shafer et al. 2021).
Regions of Interest
Changes in the distributions of forest versus non-forest (i.e., grassland, shrubland, tundra) vegetation are particularly important. Our research focuses on changes at forest-to-non-forest transitions, including high latitude boreal-forest-to-tundra (purple ovals) and mid-latitude forest-to-grassland (orange ovals) regions.
Vegetation Effects on Climate
One of the ways in which vegetation change may affect climate is by altering land cover. Forest vegetation may be darker (i.e., have a lower albedo) than grassland, shrubland, or tundra vegetation, such as shown in this image of tundra and forest. The lower albedo of forest vegetation may lead to warmer air temperatures near the surface at certain times of the year (Bartlein et al. 2015).
Complex Changes in Mountain Regions
In mountain regions, such as the western United States, there may be both low elevation and high elevation boundaries between forest and grassland, shrubland, or tundra vegetation. At lower elevations in drier regions, grasslands and shrublands may be present. These vegetation types may be replaced by forest at higher elevations where more moisture is available to support tree growth. At even higher elevations, forest may transition to alpine tundra.
Conservation and Natural Resource Management
Conservation and natural resource managers are interested in understanding potential future changes in the distribution of forest, grassland, shrubland, and tundra vegetation, and the ways in which these changes may impact species and habitats of management concern.
Our research develops analyses and variables that can be used for conservation and natural resource management planning efforts.
Photo: Controlled burn in the southern Willamette Valley (Oregon, USA).
Methods
This research uses vegetation models, including the equilibrium vegetation model BIOME4 (Kaplan et al. 2003) and the ecosystem model LPJ-GUESS (Smith et al. 2014), to simulate vegetation responses to climate change. BIOME4 and LPJ-GUESS are numerical models that simulate the ecological, physiological, and environmental processes governing plant distribution and growth. Vegetation is simulated in terms of plant functional types (e.g., needleleaf evergreen trees, C3 grasses) and biomes (e.g., temperate evergreen needleleaf forest, temperate grassland).
The climate data we use as input for the vegetation models come from recent state-of-the-art climate simulations, such as those from the Coupled Model Intercomparison Project phase 6 (CMIP6) and the Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4). We typically bias correct and downscale the climate data onto global and regional grids. Data for paleo time periods are month-length adjusted as needed (Bartlein and Shafer, 2019). Additional input data include soil variables and atmospheric carbon dioxide concentration.
Acknowledgements
References
Bartlein, P.J., Edwards, M.E., Hostetler, S.W., Shafer, S.L., Anderson, P.M., Brubaker, L.B., and Lozhkin, A.V., 2015, Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes: Climate of the Past 11:1197-1222, https://doi.org/10.5194/cp-11-1197-2015.
Bartlein, P.J., and Shafer, S.L., 2019, Paleo calendar-effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): impact and strategies for data analysis. Paleoclimate Modelling Intercomparison Project (PMIP4) Special Issue: Geoscientific Model Development 12:3889-3913, https://doi.org/10.5194/gmd-12-3889-2019.
Kaplan, J.O., Bigelow, N.H., Prentice, I.C., Harrison, S.P., Bartlein, P.J., Christensen, T.R., Cramer, W., Matveyeva, N.V., McGuire, A.D., Murray, D.F., Razzhivin, V.Y., Smith, B., Walker, D.A., Anderson, P.M., Andreev, A.A., Brubaker, L.B., Edwards, M.E., and Lozhkin, A.V., 2003, Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections: Journal of Geophysical Research 108(D19), 8171, https://doi.org/10.1029/2002JD002559.
Sayre, R., 2022, World Terrestrial Ecosystems (WTE) 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9DO61LP.
Shafer, S.L., Bartlein, P.J., Sommers, A.N., Otto-Bliesner, B.L., Lipscomb, W.H., Lofverstrom, M., Brady, E.C., Kluzek, E., Leguy, G., Thayer-Calder, K., and Tomas, R.A., 2021, Global biomes for the Last Interglacial period (127-119 ka) simulated by BIOME4 using CESM2-CISM2 coupled climate–ice sheet model data: U.S. Geological Survey data release, https://doi.org/10.5066/P9RPB5KD.
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S., 2014, Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model: Biogeosciences 11:2027–2054, https://doi.org/10.5194/bg-11-2027-2014.
Sommers, A.N., Otto-Bliesner, B.L., Lipscomb, W.H., Lofverstrom, M., Shafer, S.L., Bartlein, P.J., Brady, E.C., Kluzek, E., Leguy, G., Thayer-Calder, K., Tomas, R.A., 2021, Retreat and regrowth of the Greenland Ice Sheet during the Last Interglacial as simulated by the CESM2-CISM2 coupled climate–ice sheet model. Community Earth System Model version 2 (CESM2) Special Collection: Paleoceanography and Paleoclimatology 36:e2021PA004272, https://doi.org/10.1029/2021PA004272.
Future climate change will alter the distribution of vegetation in North America and affect related ecosystem processes. This research uses state-of-the-art climate model simulations and vegetation models to simulate vegetation changes from 127 ka (127,000 years ago) to 2100 CE. We investigate the magnitude, rate, and drivers of vegetation responses to climate change across paleo to future time periods, with a focus on forest-to-grassland or shrubland and boreal forest-to-tundra transitions in North America. Results of this research will help conservation and natural resource managers develop adaptive management responses to climate change.
Large Vegetation Changes May Affect Climate
Climate model simulations help us understand the potential impacts of future climate change. We use projected future climate data with vegetation models to simulate potential future vegetation changes, but we have no data from the future to help us evaluate the accuracy of these model simulations.
To better understand the potential impacts of future climate change, climate models are run for past time periods when the Earth’s climate was different from the present climate. We use these paleoclimate simulations with vegetation models to simulate past vegetation changes and compare the results with paleoclimate- and paleovegetation-related data from ice sheets, lake and ocean sediments, tree rings, and a range of other sources.
The term “paleo” comes from the Greek word “palaios”, which means ancient.
Our research collaborations with partners at the National Center for Atmospheric Research (NCAR), the University of Oregon, and elsewhere have shown that vegetation changes over large areas during the Last Interglacial period (~127,000 years ago; animated image, right) may have affected Greenland Ice Sheet melting and subsequent sea level rise (Sommers et al. 2021, Shafer et al. 2021).
Regions of Interest
Changes in the distributions of forest versus non-forest (i.e., grassland, shrubland, tundra) vegetation are particularly important. Our research focuses on changes at forest-to-non-forest transitions, including high latitude boreal-forest-to-tundra (purple ovals) and mid-latitude forest-to-grassland (orange ovals) regions.
Vegetation Effects on Climate
One of the ways in which vegetation change may affect climate is by altering land cover. Forest vegetation may be darker (i.e., have a lower albedo) than grassland, shrubland, or tundra vegetation, such as shown in this image of tundra and forest. The lower albedo of forest vegetation may lead to warmer air temperatures near the surface at certain times of the year (Bartlein et al. 2015).
Complex Changes in Mountain Regions
In mountain regions, such as the western United States, there may be both low elevation and high elevation boundaries between forest and grassland, shrubland, or tundra vegetation. At lower elevations in drier regions, grasslands and shrublands may be present. These vegetation types may be replaced by forest at higher elevations where more moisture is available to support tree growth. At even higher elevations, forest may transition to alpine tundra.
Conservation and Natural Resource Management
Conservation and natural resource managers are interested in understanding potential future changes in the distribution of forest, grassland, shrubland, and tundra vegetation, and the ways in which these changes may impact species and habitats of management concern.
Our research develops analyses and variables that can be used for conservation and natural resource management planning efforts.
Photo: Controlled burn in the southern Willamette Valley (Oregon, USA).
Methods
This research uses vegetation models, including the equilibrium vegetation model BIOME4 (Kaplan et al. 2003) and the ecosystem model LPJ-GUESS (Smith et al. 2014), to simulate vegetation responses to climate change. BIOME4 and LPJ-GUESS are numerical models that simulate the ecological, physiological, and environmental processes governing plant distribution and growth. Vegetation is simulated in terms of plant functional types (e.g., needleleaf evergreen trees, C3 grasses) and biomes (e.g., temperate evergreen needleleaf forest, temperate grassland).
The climate data we use as input for the vegetation models come from recent state-of-the-art climate simulations, such as those from the Coupled Model Intercomparison Project phase 6 (CMIP6) and the Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4). We typically bias correct and downscale the climate data onto global and regional grids. Data for paleo time periods are month-length adjusted as needed (Bartlein and Shafer, 2019). Additional input data include soil variables and atmospheric carbon dioxide concentration.
Acknowledgements
References
Bartlein, P.J., Edwards, M.E., Hostetler, S.W., Shafer, S.L., Anderson, P.M., Brubaker, L.B., and Lozhkin, A.V., 2015, Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes: Climate of the Past 11:1197-1222, https://doi.org/10.5194/cp-11-1197-2015.
Bartlein, P.J., and Shafer, S.L., 2019, Paleo calendar-effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): impact and strategies for data analysis. Paleoclimate Modelling Intercomparison Project (PMIP4) Special Issue: Geoscientific Model Development 12:3889-3913, https://doi.org/10.5194/gmd-12-3889-2019.
Kaplan, J.O., Bigelow, N.H., Prentice, I.C., Harrison, S.P., Bartlein, P.J., Christensen, T.R., Cramer, W., Matveyeva, N.V., McGuire, A.D., Murray, D.F., Razzhivin, V.Y., Smith, B., Walker, D.A., Anderson, P.M., Andreev, A.A., Brubaker, L.B., Edwards, M.E., and Lozhkin, A.V., 2003, Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections: Journal of Geophysical Research 108(D19), 8171, https://doi.org/10.1029/2002JD002559.
Sayre, R., 2022, World Terrestrial Ecosystems (WTE) 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9DO61LP.
Shafer, S.L., Bartlein, P.J., Sommers, A.N., Otto-Bliesner, B.L., Lipscomb, W.H., Lofverstrom, M., Brady, E.C., Kluzek, E., Leguy, G., Thayer-Calder, K., and Tomas, R.A., 2021, Global biomes for the Last Interglacial period (127-119 ka) simulated by BIOME4 using CESM2-CISM2 coupled climate–ice sheet model data: U.S. Geological Survey data release, https://doi.org/10.5066/P9RPB5KD.
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S., 2014, Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model: Biogeosciences 11:2027–2054, https://doi.org/10.5194/bg-11-2027-2014.
Sommers, A.N., Otto-Bliesner, B.L., Lipscomb, W.H., Lofverstrom, M., Shafer, S.L., Bartlein, P.J., Brady, E.C., Kluzek, E., Leguy, G., Thayer-Calder, K., Tomas, R.A., 2021, Retreat and regrowth of the Greenland Ice Sheet during the Last Interglacial as simulated by the CESM2-CISM2 coupled climate–ice sheet model. Community Earth System Model version 2 (CESM2) Special Collection: Paleoceanography and Paleoclimatology 36:e2021PA004272, https://doi.org/10.1029/2021PA004272.