stephen gray, usgs tucson with: julio betancourt, lisa graumlich, steve jackson, mark lyford, jodi...
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Stephen Gray, USGS Tucson
With: Julio Betancourt, Lisa Graumlich, Steve Jackson,
Mark Lyford, Jodi Norris, and Greg Pederson
Nonlinear Interactions Between Climate, Landscape Structure, and
Plant Migration
Nonlinear Interactions Between Climate, Landscape Structure, and
Plant Migration
Global ChangeImpacts?
TNC Invasives Project
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 theThe Classic Example: Nonlinear Behavior in theSpread of Large FiresSpread of Large Fires
Peters et al (2004)Peters et al (2004) PNAS PNAS
Ignition- single treeIgnition- single tree
Spread within patchSpread within patch
Spread among patchesSpread among patches
Large Area: feedbacks and Large Area: feedbacks and nonlinear interactionsnonlinear interactions
Predictability?Predictability?
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
Traditional View: Climate as stochastic
variations around STATIONARY mean
0 10050
The Ecologist’s Concept of Climate
7525
North American Tree-ring Network
Spring 2005
NOAA-NCDC
Year AD1250 1350 1450 1550 1650 1750 1850 1950
An
nu
al P
reci
p. (
cm)
20
30
40
50
60
70
•High variance explained (r2 = 0.58)•Well replicated (n = 133)•Long segments (Avg. Length = 385 yr)•Conservative detrending
Test Case: Greater Yellowstone Precipitation
Gray, Graumlich and Betancourt (in review) Quat. Res.
Test Case: Greater Yellowstone Precipitation
21-yr Spline
60-yr Spline
Test Case: Greater Yellowstone Precipitation
Rocky Mountain Climate-Reconstruction Network
Gray et al. GRL (2003)
Gridded PDSI reconstructions from Cook et al. 2004, Science
D2M variability and associated wet/dry regimes can become synchronized across
large portions of the West
Non-stationary (regime-like) behavior
Sta
nd
ard
de
via
tio
ns
Example: Upper Colorado Basin Annual Precipitation
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?
D2M Variability and Internal Ocean Processes
Ocean ‘thermostat’ mechanism (Clement et al. 1996)Ocean ‘thermostat’ mechanism (Clement et al. 1996)
Uniform heatingUniform heating
Larger Larger temperaturetemperatureresponse in response in the Westthe West
Cooling by upwelling Cooling by upwelling opposes forcing in the opposes forcing in the East, reducing East, reducing temperature responsetemperature response
Coupled interactions Coupled interactions ((i.e. the Bjerknes i.e. the Bjerknes feedbackfeedback) amplify the ) amplify the East/west East/west temperature temperature difference difference
Warm, mixedSurface layer
Deep, coldocean waters
~20ºC
~20ºC
0 m0 m
10050
150
The Big Question…
• How does D2M variability and associated climatic regimes impact plant invasion and migration processes?
Tree rings:Tree rings:Climate/DemographyClimate/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
% A
rea
Occ
up
ied
no sites
all sites
Step-like change in the distribution and abundanceof pinyon pine at the watershed/landscape scale
no pinyon
pinyondominates
Medieval Dry Period
Little or nosuccessful
establishment
Migration Dynamics at the Landscape/Watershed Scale
Mo
dif
ied
dro
ug
ht
ind
ex%
Are
a O
ccu
pie
d
no sites
all sites
Migration Dynamics at the Landscape/Watershed Scale
Sm
all
Po
pu
lati
on
“Great Drought”M
od
ifie
d d
rou
gh
t in
dex
% A
rea
Occ
up
ied
no sites
all sites
Migration Dynamics at the Landscape/Watershed Scale
“Great Wet”
Step-like changein pinyon
abundance &distribution
Mo
dif
ied
dro
ug
ht
ind
ex%
Are
a O
ccu
pie
d
no sites
all sites
Switching between dry/wet regimes drives Switching between dry/wet regimes drives nonlinear invasion dynamicsnonlinear invasion dynamics
““D2M” WetD2M” WetRegimeRegime
Step-likeStep-likeChangeChange
Rapid RecruitmentLow Mortality
Switching between dry/wet regimes drives Switching between dry/wet regimes drives non-linear invasion dynamicsnon-linear invasion dynamics
““D2M” WetD2M” WetRegimeRegime
BroadscaleMortality
Abundance of Open Niches
Step-likeStep-likeChangeChange
Rapid RecruitmentLow Mortality
““D2M” DryD2M” DryRegimeRegime
Modern (shaded)Glacial (>13 kyr BP)
Rocky Mts
presentabsent
Distribution of Utah Juniper:
Holocene Migration Dynamics: Utah Juniper
- Reconstructed from 205 woodrat middens at 14 sites
-Lyford et al. (2003) Ecol. Monog. 73:567-583
cal yr B.P.0123456
Sit
es
Oc
cu
pie
d
0
2
4
6
8
10
12
Lyford et al. (2003) Ecol. Monog. 73:567-583
CLIMATIC REGIMES AND UTAH JUNIPER MIGRATION
10,000 yr BP
- Reconstructed from 205 woodrat middens at 14 sites
-Climate inferred from lake sediments and dune records
MT
WY
CurrentDist.
cal yr B.P.0123456
Sit
es
Oc
cu
pie
d
0
2
4
6
8
10
12
Mig
ratio
n S
talls
Du
ring
Co
ld P
erio
ds
Lyford et al. (2003) Ecol. Monog. 73:567-583
CLIMATIC REGIMES AND UTAH JUNIPER MIGRATION
10,000 yr BP
- Reconstructed from 205 woodrat middens at 14 sites
-Climate inferred from lake sediments and dune records
MT
WY
CurrentDist.
Lyford et al. (2003) Ecol. Monog. 73:567-583
CLIMATIC REGIMES AND UTAH JUNIPER MIGRATION
MT
WY
Oldest
Youngest
10 kyr BP
Lyford et al. (2003) Ecol. Monog. 73:567-583
CLIMATIC REGIMES AND UTAH JUNIPER MIGRATION
10 kyr BP
MT
WY 5.7 kyr BP
6.4 kyr BP
MT
WY
Youngest
Oldest
10 kyr BP
Modern Climate Cold Scenario
UTAH JUNIPER DISTRIBUTION IN RELATION TO CLIMATE AND SUBSTRATE (Lyford et al. 2003)
WY
~ 60 km
> 350 km
•Less suitable habitat in northern areas•Requires long-distance dispersal
•Abundant habitat in northern areas• Short distances between suit. hab.
Lyford et al. (2003) Ecol. Monog. 73:567-583
Higher probability of survival
Lower probability of survival
INTERACTION BETWEEN CLIMATIC REGIMES AND LANDSCAPE STRUCTURE
Favorable Climatic Regime Less-favorable Regime
++
Reduced connectivityHigh connectivity
INTERACTION BETWEEN CLIMATIC REGIMES AND LANDSCAPE STRUCTURE
Favorable Climatic Regime Less-favorable Regime
Climatic Regimes Nonlinear Dynamics
Regime-like behaviorin the climate systempromotes step-like changes that may persist for decades to millennia
Interactions betweenclimate and other factors may introduce marked spatial and temporal complexity to ecological processes
10 kyr BP
MTWY 5.7 kyr BP
6.4 kyr BP
How/why does climate drive nonlinear change?
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/Rate of Shift?
Past Present
Magnitude/Duration ofregimes?
Does the Frequency of Regime Shifts Alter the Ecological Impact of Climate?
Woo
dho
use
, G
ray
and
Mek
o (in
rev
iew
)
= sig. (p < 0.05) decadal to multidecadal power
Decadal to Multidecadal VariabilityDecadal to Multidecadal Variability
Lees FerryLees Ferry 2525 and 50 yr splines and 50 yr splines
How/why does climate drive nonlinear change?
• Climate affects large areas simultaneously
Impacts depend on:• Total area affected by regime• Magnitude and duration of
regimes• Speed/amplitude of switching
How/why does climate drive nonlinear change?
• Climate affects large areas simultaneously
Impacts depend on:• Total area affected by regime• Magnitude and duration of
regimes• Speed/amplitude of switching
• Possibility that the stressor and not the biological response behaves in a nonlinear manner?
Are current prediction methods adequate?
Statistical biogeographic models cannot account for the impacts of D2M variability,
land use/land cover, migration processes, etc.Thompson et al. 2003
Climate/Vegetation Change
Climate/Vegetation Change
What’s Next?• Dynamic Vegetation Models are a good
start (Neilson et al. 2005, Bioscience)• DVMs model changes in vegetation
based on knowledge of plant population and migration processes
• But, current DVMs capture spatial heterogeneity in the environment better than temporal variability
Thanks! Thanks!
Funding:U.S. Geological Survey-
National Research Council Associates Program
USGS Mapping DivisionNational Science Foundation
Thanks!
• Funding:– U.S. Geological Survey-National
Research Council Associates Program
– USGS Mapping Division– National Science Foundation