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Nonlinear Interactions Between Climate, Landscape Structure, and Plant Migration. Stephen Gray, USGS Tucson With: Julio Betancourt, Lisa Graumlich, Steve Jackson, Mark Lyford, Jodi Norris, and Greg Pederson. Global Change Impacts?. TNC Invasives Project. Plant Migration and Invasion.
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Nonlinear Interactions Between Climate, Landscape Structure, and Plant Migration Stephen Gray, USGS Tucson With: Julio Betancourt, Lisa Graumlich, Steve Jackson, Mark Lyford, Jodi Norris, and Greg Pederson
Global Change Impacts?
Plant Migration and Invasion • Expect significant shifts in the distribution of plant species • Will contribute to major vegetation/ ecosystem change across the West • Driven by: • Changing climate • Land use • Exotic introductions • Human vectors, etc.
Forecasting Environmental Change • Sustainable land management requires realistic predictions for future vegetation change • Provide viable scenarios for planning and policy • Tool for policy makers and stakeholders to explore potential ecological outcomes and the costs/consequences of management and mitigation efforts
Nonlinear Behavior and Environmental Forecasting • Nonlinearity is a major obstacle to environmental forecasting • Examples of nonlinear behavior- • Threshold responses • Feedbacks • Cascading responses • Cross-scale interactions
The Classic Example: Nonlinear Behavior in the Spread of Large Fires Large Area: feedbacks and nonlinear interactions Predictability? Ignition- single tree Spread within patch Spread among patches Peters et al (2004) PNAS
Nonlinearity in Western Ecosystems • Focus on inherent complexity in biological processes or cross-scale interactions
Nonlinearity in Western Ecosystems • Focus on inherent complexity in biological processes or cross-scale interactions • But, non-stationary (i.e. regime-like) behavior in the climate system may also produce nonlinear dynamics in natural systems
Nonlinearity in Western Ecosystems • Focus on inherent nonlinearity in biological processes or cross-scale interactions • But, non-stationary (i.e. regime-like) behavior in the climate system may also produce nonlinear dynamics in natural systems • Examples: Woody plant migration and invasion in western North America
The Ecologist’s Concept of Climate 0 50 100 25 75 Traditional View: Climate as stochastic variations around STATIONARY mean
North American Tree-ring Network NOAA-NCDC Spring 2005
Test Case: Greater Yellowstone Precipitation • High variance explained (r2 =0.58) • Well replicated (n = 133) • Long segments (Avg. Length = 385 yr) • Conservative detrending Gray, Graumlich and Betancourt(in review) Quat. Res.
21-yr Spline 60-yr Spline Test Case: Greater Yellowstone Precipitation
Rocky Mountain Climate-Reconstruction Network Gray et al. GRL (2003)
D2M variability and associated wet/dry regimes can become synchronized across large portions of the West Gridded PDSI reconstructions from Cook et al. 2004, Science
Example: Upper Colorado Basin Annual Precipitation Standard deviations Non-stationary (regime-like) behavior Year AD • The mean, SD, probability of • extreme single year events, etc. • changes over D2M timescales Hidalgo 2004; Gray et al. 2003, 2004
Is this D2M Variability Real? • Not an artifact of tree-ring methodology • Signals are coherent at regional to sub-continental scales • Feature of winter and growing season temp/precip • Recent modeling studies reproduce D2M variability • Schubert et al. (2004) Science • Seager et al. (2005) J. Climate • Sutton and Hodson (2005) Science • But, will D2M variability continue in the future?
Coupled interactions (i.e. the Bjerknes feedback) amplify the East/west temperature difference Uniform heating Larger temperature response in the West 0 m Cooling by upwelling opposes forcing in the East, reducing temperature response Warm, mixed Surface layer 50 ~20ºC 100 Deep, cold ocean waters ~20ºC 150 Ocean ‘thermostat’ mechanism (Clement et al. 1996)
The Big Question… • How does D2M variability and associated climatic regimes impact plant invasion and migration processes?
Tree rings: Climate/Demography
Climatic Regimes Pace Migration/Invasion Events Dutch John Mtn., Utah -Northernmost P. edulis -Study encompasses 25 km2 watershed -Reconstructed pinyon dynamics from woodrat middens and dated wood Jackson et al. (2005), J. Biogeography 32:1085-1106. Gray et al. (in press), Ecology
Migration Dynamics at the Landscape/Watershed Scale all sites no pinyon % Area Occupied pinyon dominates no sites Step-like change in the distribution and abundance of pinyon pine at the watershed/landscape scale
Migration Dynamics at the Landscape/Watershed Scale Medieval Dry Period Modified drought index all sites Little or no successful establishment % Area Occupied no sites
Migration Dynamics at the Landscape/Watershed Scale Modified drought index “Great Drought” all sites Small Population % Area Occupied no sites
Migration Dynamics at the Landscape/Watershed Scale “Great Wet” Modified drought index all sites Step-like change in pinyon abundance & distribution % Area Occupied no sites
Switching between dry/wet regimes drives nonlinear invasion dynamics Step-like Change “D2M” Wet Regime Rapid Recruitment Low Mortality
Switching between dry/wet regimes drives non-linear invasion dynamics Broadscale Mortality Abundance of Open Niches “D2M” Dry Regime Step-like Change “D2M” Wet Regime Rapid Recruitment Low Mortality
absent present Holocene Migration Dynamics: Utah Juniper • - Reconstructed from 205 • woodrat middens at 14 sites • Lyford et al. (2003) Ecol. • Monog. 73:567-583 Rocky Mts Distribution of Utah Juniper: Modern (shaded) Glacial (>13 kyr BP)
10,000 yr BP CLIMATIC REGIMES AND UTAH JUNIPER MIGRATION 12 MT Current Dist. 10 WY 8 6 Sites Occupied 4 2 0 6 5 4 3 2 1 0 cal yr B.P. - Reconstructed from 205 woodrat middens at 14 sites • Climate inferred from lake • sediments and dune records Lyford et al. (2003) Ecol. Monog. 73:567-583
10,000 yr BP CLIMATIC REGIMES AND UTAH JUNIPER MIGRATION 12 MT Current Dist. 10 WY Migration Stalls During Cold Periods 8 6 Sites Occupied 4 2 0 6 5 4 3 2 1 0 cal yr B.P. - Reconstructed from 205 woodrat middens at 14 sites • Climate inferred from lake • sediments and dune records Lyford et al. (2003) Ecol. Monog. 73:567-583
CLIMATIC REGIMES AND UTAH JUNIPER MIGRATION MT Youngest WY Oldest 10 kyr BP Lyford et al. (2003) Ecol. Monog. 73:567-583
CLIMATIC REGIMES AND UTAH JUNIPER MIGRATION MT MT Youngest 5.7 kyr BP WY WY 6.4 kyr BP Oldest 10 kyr BP 10 kyr BP Lyford et al. (2003) Ecol. Monog. 73:567-583
UTAH JUNIPER DISTRIBUTION IN RELATION TO CLIMATE AND SUBSTRATE (Lyford et al. 2003) Modern Climate Cold Scenario WY > 350 km ~ 60 km • Abundant habitat • in northern areas • Short distances • between suit. hab. • Less suitable habitat • in northern areas • Requires long-distance • dispersal Lyford et al. (2003) Ecol. Monog. 73:567-583
INTERACTION BETWEEN CLIMATIC REGIMES AND LANDSCAPE STRUCTURE Favorable Climatic Regime Less-favorable Regime + + Lower probability of survival Higher probability of survival
INTERACTION BETWEEN CLIMATIC REGIMES AND LANDSCAPE STRUCTURE Favorable Climatic Regime Less-favorable Regime High connectivity Reduced connectivity
Climatic Regimes Nonlinear Dynamics Regime-like behavior in the climate system promotes step-like changes that may persist for decades to millennia MT Interactions between climate and other factors may introduce marked spatial and temporal complexity to ecological processes 5.7 kyr BP WY 6.4 kyr BP 10 kyr BP
How/why does climate drive nonlinear change? • Climate affects large areas simultaneously
CLIMATIC REGIMES MAY BECOME SYNCHRONIZED OVER WIDE AREAS After Fye et al. 2003
What Governs the Impact of Climatic Regimes? Magnitude/ Duration of regimes? Magnitude/ Rate of Shift? Past Present
Does the Frequency of Regime Shifts Alter the Ecological Impact of Climate? Woodhouse, Gray and Meko (in review) = sig. (p < 0.05) decadal to multidecadal power