water dynamics: the experimental perspective alan k. knapp
DESCRIPTION
Water Dynamics: The Experimental Perspective Alan K. Knapp Graduate Degree Program in Ecology, Colorado State University. Overview: Experimental approach to: Climate Change - Ecosystem Function (in grasslands) Soil moisture & ANPP (4 studies) Change in precipitation pattern (long-term) - PowerPoint PPT PresentationTRANSCRIPT
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Water Dynamics: The Experimental Water Dynamics: The Experimental Perspective Perspective
Alan K. KnappAlan K. KnappGraduate Degree Program in Ecology, Colorado State Graduate Degree Program in Ecology, Colorado State
UniversityUniversity
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Overview:
Experimental approach to:
Climate Change - Ecosystem Function (in grasslands)
• Soil moisture & ANPP (4 studies)
• Change in precipitation pattern (long-term)
• Comparison among grasslands (short-term)
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Sala et al. 1988
Rainfall vs. Production across the Central US
Grasslands and similar ecosystem types cover ~ 40% of the Earth’s land surface
Most are water limited systems
Most of what we know is based on observation
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Soil moisture
Inputs Outputs
N C
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Central US grasslands provide a template for experiments at sites that span key precipitation and temperature gradients…
“Seeing the grasslands beyond the grasses”
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Mesic Grasslands of North AmericaThe Flint Hills of Kansas – The Konza Prairie
Mesic Grasslands of North AmericaThe Flint Hills of Kansas – The Konza Prairie
• Tallgrass prairie is the most mesic of US Great Plains grasslands – sufficient precipitation to support forest
• Flint Hills are located at the dry edge of the original range and on shallow soils
KPBS
C4 grass dominance
A dynamic & tractable system
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Proportion of total rainfall in the US from large (>5 cm) rainfall events
Pro
po
rtio
n (
%)
of
rain
fall
in
“ext
rem
e ev
ents
”
Abundant evidence that rainfall regimes are changing
Oklahoma
Question: (We know amount is important)
Given increased variability and frequency of extreme events, to what extent will altered precipitation patterns affect ecological processes in “mesic” grasslands?
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12 Rainfall Manipulation Plots (RaMPs) + non-sheltered controls
Collect, store, and reapply natural rainfall on intact prairie plots
Treatments include ambient and altered rainfall patterns since 1998
Elevated temperature treatment added in 2003
12 Rainfall Manipulation Plots (RaMPs) + non-sheltered controls
Collect, store, and reapply natural rainfall on intact prairie plots
Treatments include ambient and altered rainfall patterns since 1998
Elevated temperature treatment added in 2003
The Rainfall Manipulation Plot (RaMP) Experiment
Address the impact of changes in size and timing of growing season rainfall events and elevated temperature
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Target altered rainfall pattern: 50% longer inter-rainfall periods, larger individual rain events
No change in total precipitation quantity
Current
Predicted
Pre
cipi
tatio
n am
ount
Day of yearFewer events
Greater storm size
Increased dry periods
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Ambient ppt timing: • “typical” seasonal
pattern
Altered ppt timing:• repeated deficits• more extreme wetting
and drying cycles
Ambient ppt timing: • “typical” seasonal
pattern
Altered ppt timing:• repeated deficits• more extreme wetting
and drying cycles
Soil moisture dynamicsSoil moisture dynamics
Average soil water content in top 30 cm:- reduced by 12%
Variability in soil moisture:- increased by 27%
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ANPP responses to altered rainfall timing
12-22% reduction in years with significant responses
11% reduction
across years(p=0.01)
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Across all years and all rainfall treatments
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If only the entire world worked like Konza….Can we apply results from mesic grasslands to
other climates and grasslands?
If only the entire world worked like Konza….Can we apply results from mesic grasslands to
other climates and grasslands?
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Ojima and Lackett 2002
Ojima and Lackett 2002
Tallgrass
Mixed-grass
Short-grass
Precipitationgradient
A multi-system assessment of climate change responses
Heisler-White et al. 2009. Global Change Biology.Heisler-White et al. 2009. Global Change Biology.
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Annual Precipitation (mm)
358 578 833
AN
PP
(g/
m2 )
0
100
200
300
400
500
SGSshortgrass steppe, CO
HAYSmixed grass prairie, KS
KPBStallgrass prairie, KS
Semi-arid grasslandExtreme rainfall events,long dry intervals =reduced ANPP?
With the same experimental design, how will these different grasslands respond?
Mesic grasslandExtreme rainfall events,long dry intervals =reduces ANPP
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SGS
Experimental manipulation of growing season rainfall regimes
Frequent, small events vs. infrequent large events
Equal rainfall amounts within each site
A = 12 eventsB = 6 eventsC = 4 eventsTotal = 191 mm
A = 12 eventsB = 6 eventsC = 4 eventsTotal = 450 mm
KNZ
Semi-arid Mesic
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15% decrease in ANPP with fewer large events
30% increase in ANPP with fewer large events
191 mm
340 mm
450 mm
70% increase in ANPP with fewer large events
Semi-arid steppe
Mixed grass prairie
Tallgrass prairie
Heisler-White et al. 2009
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Why do arid vs. mesic grasslands respond differently?
Two key aspects of more extreme rainfall regimes:
Current
Predicted
Pre
cipi
tatio
n am
ount
Day of yearFewer events
Greater storm size
Increased dry periods
1. Larger rain events2. Longer dry periods between events
When soils are usually moist, longer dry periods negatively impact ANPP…
When soil are usually dry, larger rain events improve soil water and increase in ANPP…
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The Sevilleta LTER – the edge of the Great Plains
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Monsoon Rainfall Manipulation Experiment
During the summer monsoon July through September:3 plots receive ambient rainfall5 plots receive a 5mm rainfall event every week5 plots receive a 20 mm rainfall event every month
Scott CollinsMichell ThomeyRodrigo VargasJennifer JohnsonRenee BrownDon NatvigMike Friggens
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Seasonal average soil water content, predawn water potentials, leaf-level Anet and soil CO2 flux were highest in plots receiving a few large events
Seasonal average soil water content, predawn water potentials, leaf-level Anet and soil CO2 flux were highest in plots receiving a few large events
Thomey et al. 2011 GCB
Responses similar to shortgrass steppe, but opposite mesic grasslands
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Total ANPP and ANPP of black grama were highest in plots receiving a few large events
Thomey et al. 2011 GCB
• 25 – 40% greater ANPP of black grama with few large events compared to many small events
• Similar trends for ANPP of all species combined
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Responses to drought - is there a pattern/amount interaction?
Mixed-grass
Shortgrass
Tallgrass SGS-LTER (North)
Fort Union (South)
Sand Creek (Central)
Site ElevationMean Annual Precipitation
Mean Annual Temperature
Soil Texture
Shortgrass-Steppe LTER (SGS)
1650 m 310 - 330 mm7.2º C (45º F)
Sandy Loam
Sand Creek Massacre Nat'l
Historic Site (SAND)
1219 m 330 - 360 mm8.3º C (47º F)
Clay
Fort Union Nat'l Monument
(FOUN)2043 m 410 - 450 mm
9.4º C (49º F)
Sandy Clay Loam
Karie Cherwin
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From Huxman et al (2004)
These are observational data!
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Testing this inference of high sensitivity
• 30 plots at each site– 10 controls– 20 rainout shelters
• 10 at 50% Reduced-PPT
• 10 at 80% Reduced-PPT
• Two-year drought
• Response Variables– Net Primary Productivity– Soil Moisture
• No change in timing/pattern• Reduces event size & total amount
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Growing season mean soil moisture
Site and Year
SGS - 07 SGS - 08 SAND - 07 SAND - 08 FOUN - 07 FOUN - 08
Vol
umet
ric S
oil W
ater
Con
tent
0.00
0.05
0.10
0.15
0.20
0.25
Control-50% -80%
a
b
c
a
b
c
a
b
c
a
b
c a
b
c
a
b
c
SouthCentralNorth
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2007 & 2008 ANPP
Site and Year
SGS '07 SGS '08 SAND '07 SAND '08 FOUN '07 FOUN '08
AN
PP
(g
/m2)
0
20
40
60
80
100
120
140
160
180
200
Control- 50% -80%
North Central South
a
abb
b
bx
x
y
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Fort Union NM
Volumetric Soil Water Content (%)
0.00 0.05 0.10 0.15 0.20 0.25
AN
PP
g/m
2
20
40
60
80
100
120
140
160
180
200
220
Sand Creek
Volumetric Soil Water Content (%)
0.05 0.10 0.15 0.20 0.25
AN
PP
g/m
2
20
40
60
80
100
120
140
160
180
200
220
Se
nsiti
vity
to D
rou
ght
40° N 35° N38° NLatitude:Temperature:
Precipitation:
Elevation:
Soil Texture:
7.2° C
Coarse
8.3° C 9.4° C
310 - 330 mm 410 - 450 mm330 - 360 mm
1650 m 2043 m1219 m
Fine Intermediate(Sandy Loam) (Clay) (Sandy Clay Loam)
20072008Low
High
Shortgrass-steppe
Volumetric Soil Water Content (%)
0.00 0.05 0.10 0.15 0.20 0.25
AN
PP
g/m
2
20
40
60
80
100
120
140
160
180
200
220 Why the differential sensitivity?
Insensitive ?!?!
Within biome saturation?
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Nu
mb
er
of
even
ts (
May
- S
epte
mb
er)
0
2
4
10
20
Average years
0
2
4
10
20
Driest years
Event size (mm)
0-55-
10
10-1
5
15-2
0
20-2
5
25-3
0
30-3
5
35-4
0
40-4
5
45-5
0
50-5
5
55-6
0
60-6
5
65-7
0
70-7
575
+0
2
4
10
20
Rain daysRain periods
Mean precip = 133.3 mm (189.7 mm)
Mean precip = 273.4 mm (373.3 mm)
Mean precip = 409.4 mm (574.0 mm)
Wettest years
Mean # days with rain = 23.1 (5.9 mm)Mean # rain periods = 15.9 (8.6 mm)
Mean # days with rain =38.4 (7.2 mm)Mean # rain periods = 23.1 (11.9 mm)
Mean # days with rain = 40.2 (10.3 mm)Mean # rain periods = 23.5 (11.9 mm)Mean # days between rain = 7.2
Mean # days between rain = 9.0
Mean # days between rain = 16.9
Mean rain events across sites
Rainfall regimes – there’s more to them than amount…
In addition to more rain, wet years have more large events compared to average years.
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33.6 events 41.0 events 9.7 mm 5.3 mm
Insensitive <---------------------> Sensitive
Many, small events (dry, low ANPP)
Fewer, large events (wet, high ANPP)
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What does all this mean?!?!
There is still much we need to learn about precipitation regimes, soil moisture and ecosystem responses if we are to forecast the future… Because all three are likely to change.
•Much of what we know is from observation and correlation… We need to challenge this knowledge
•Alterations in rainfall patterns (and of course amounts) may change productivity in biome specific ways…
•Alterations in rainfall patterns may even alter sensitivity to drought…
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As Ecologists – one of our greatest challenges is to provide knowledge to help us forecast and cope with future ecosystem structure and function…
The empirical perspective - future field experiments?
We need more long-term experiments where we “push” ecosystems… in both magnitude and pattern…
We need comparative analyses of ecosystem responses to climate change within and across biomes…
Clear need for long-term, multi-site and coordinated experiments… and these should be designed with modelers…
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Divergent responses are linked to differential effects of extreme rainfall events on mean soil water content
Divergent responses are linked to differential effects of extreme rainfall events on mean soil water content
↑ SWCby 19%in arid site
↑ SWCby 19%in arid site
↓ SWCby 20%in mesicsite
↓ SWCby 20%in mesicsite
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Response Predictor variable Partial r2 Model r2
Total ANPP CV SWC 15cm 0.598 (92%) 0.651
mean SWC 15cm 0.053
Grass ANPP mean SWC 15cm 0.470 (70%) 0.676
mean SWC 30cm 0.103
CV SWC 30cm 0.103
Forb ANPP mean SWC 30cm 0.375 (82%) 0.453
CV SWC 30cm 0.078
Grasses and forbs respond to different aspects of soil water dynamics
• Grasses most responsive to mean surface SWC, while forbs respond more to deeper SWC
• Potential for long-term changes in community composition