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Konza LTER – Plant Community Dynamics
Melinda Smith1, David Hartnett2, Sara Baer3, Scott Collins4, Carolyn Ferguson2, Karen Garrett5, Mark
Mayfield2, Gene Towne2
1Department of Ecology & Evolutionary Biology, Yale University2Division of Biology – KSU
3Plant Biology, Southern Illinois University4Department of Biology, University of New Mexico
5Department of Plant Pathology - KSU
Overview
• Highlight major accomplishments during last five years
• Present new research activities that may be incorporated into the LTER VI proposal
Plant Community Dynamics: Metrics
• Richness, diversity (H’), dominance• Qualitative and quantitative changes in
composition over time– Community heterogeneity (dissimilarity)– Time-lag analysis – rate of change
• Turnover of species– Loss – species extinctions– Gain – patterns of invasion, invasibility
Plant community dynamics: Sampling• Permanent sampling transects are replicated at
various topographic positions (n = 4/topo position/watershed) in replicate watersheds subjected to the different fire frequency, fire season, and grazing treatments– Plant species composition (estimated cover of
individual species) is measured in spring and fall in 5 10-m2 circular plots/transect (20 plots/topo position)
• Data collected since 1984, 1993 (seasonal burns)
Since 2002, plant species composition data have been included in at least 9 cross-site comparisons or syntheses.
• Belowground Plot Experiment (1986) – burning, mowing, and nutrients
• Irrigation Transects (1991) – growing season water additions
• Cattle-Bison Comparison (1995) – assess effects of cattle vs. bison
• Dominant Species Removals (1996/2000) – assess long-term response to removal of dominant grasses
• RaMPs (1997) – timing of precipitation, warming
• Fire Reversal Experiment (2001) – fire history and changing fire regimes
• Water and N limitation Experiment (2002) – water and nitrogen limitation
• Phosphorus Plots (2003) – assess relative P and N limitation
• Savanna Convergence Project (2006) – interactions between fire and herbivory in North American and South African grasslands
• Nutrient Network (2007) – multiple resource limitation, bottom-up vstop-down control
Other resources: KSU Herbarium
• NSF-funded project to database label and annotation data for all KSC specimens (Kansas vascular plants are complete).
• Development of a digital KSU Biodiversity Information System (BiodIS)
• Continue to work to enhance the collections through ongoing and targeted collecting
Land UsePractices
ClimateChange
NutrientEnrichment
BiologicalInvasions
Tallgrass Prairie EcosystemsStructureFunction
Biotic Interactions
AlteredHydrology
Land Cover Change/Woody PlantExpansion
AlteredBiogeochemical
Cycles
• Fire• Grazing• Land use history
• Rainfall timing and amount
• Temperature
• Elevated N deposition
• Fertilization
• Exotic species introductions
Plant community dynamics are relevant to many contemporary global change issues…
Dominant species –Account for a large fraction of biomass and energy flow
Rel
ativ
e fre
quen
cy
0.0
0.2
0.4
0.6
0.8
1.0
Species rank0 5 10 15 20 25 30 35 40 45
Species rank1 2-8 9-48A
vera
ge b
iom
ass
(g m
-2)
0
100
200
300
400
Andropogon gerardii
Uncommon and rare species – account for a large fraction of richness
Smith & Knapp 2003
Fire and grazing as drivers of plant community dynamics
• Historically important, key components of land use
• Considerations:– Fire regime – frequency and timing of fires– Type of grazer – native vs. domesticated
Fire and grazing
Frequent fire
Increases dominance by C4 grasses
Reduces diversity
Decreases dominance by C4 grasses
Increases diversityGrazing
Long-term dynamics
Need to move beyond patterns of change to implications for ecosystem function
Year1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Pla
nt s
peci
es ri
chne
ss
20
30
40
50
60
70Year of fire Year of fire
Year of fire
Year ofwildfire
Year ofwildfire
010203040506070
Pre-fire Fire Post-fire
Plan
t spe
cies
richn
essAnnually burned
Long-term unburned4-yr burned
Year of fire
Rainfall ManipulationPlots Experiment
Even
t fre
quen
cy, s
ize,
inte
rval
0
10
20
30
40
50
Rainfall events (#/season)
Rainfall size (mm)
Interval between events (days)
AmbientAltered
Ambient
AmbientAltered
Altered
• Average soil water content in top 30 cm reduced by 12%. • Variability in soil moisture increased by 27%.• Soil temperature increased by 1.4 °C
Impacts on plant species diversity
ANPP (g m-2)
500 600 700 800Ambient Altered
1.0
1.2
1.4
1.6
1.8
Variability in soil water content (%wv)
4.0 6.0 8.0 10.0
Div
ersi
ty (H
')
1.5
1.6
1.7
1.8
1.9
2.0
r2 = 0.45P = 0.004
r2 = 0.40P = 0.008
P = 0.04
Knapp et al. 2002
Grass p = 0.05A
NPP
(g m
-2)
100
200
300
400
500
600
Ambienttiming
Alteredtiming
0
50
100
150
200
250
300 A. gerardii p = 0.38S. nutans p = 0.02
Differential species responses
Andropogon gerardii Sorghastrum nutans
Dominant C4 grasses
Fay et al. 2003
Treatment
Amb-C Amb-H Alt-C Alt-H
Andr
opog
on re
lativ
e co
ver (
%)
10
15
20
25
30
35
40
Treatment
Amb-C Amb-H Alt-C Alt-H
Sorg
hast
rum
rela
tive
cove
r (%
)
10
15
20
25
30
35
40Rainfall: P = 0.03Heat: NSRainfall*Heat: NS
Rainfall: NSHeat: P = 0.03Rainfall*Heat: NS
40
Amb-C Amb-H Alt-C Alt-H
Ric
hnes
s
16
18
20
22
24
26
28
30
Rainfall: P < 0.001Heat: P = 0.04Rainfall*Heat: NS
Amb-C Amb-H Alt-C Alt-H
Div
ersi
ty
1.6
1.8
2.0
2.2
2.4
2.6
Rainfall: P = 0.01Heat: P = 0.01Rainfall*Heat: NS
Effects of warming of community diversity
Differential species responses: Flowering
A. gerardii
0.0
0.2
0.4
0.6
0.8
1.0
1.2
bbsm2 bbsm2: 0.8125 bbsm2: 0.7500
S. nutans
Flow
erin
g st
ems
per m
2
0.0
1.0
2.0
3.0
4.0
5.0ControlWarmed
Ambient Altered
Andropogon more sensitive to warming
Sorghastrum more sensitive to water availability
What are the mechanisms underlying differential sensitivity?
Genotypic constraints
Geneexpression
Phenotypic effect on physiology
GeneticGenetic
Tallgrass Prairie Tallgrass Prairie Community & Ecosystem Community & Ecosystem
ResponsesResponses
EcologicalEcological
Dominant speciesDominant speciesresponsesresponses
ClimateChange
• Rainfall timing and amount
• Temperature
Linking responses across scales
Hierarchical Ecosystem Response Model
Smith, Knapp and Collins, in prep
Ecos
yste
m re
spon
se (+
/-)
Time
Press resource alteration
Invasive species
a) Physiological response
c) Immigration(new species)
b) Speciesre-ordering
Linking genetics to ecosystem responses
CarbonRelations
EnvironmentalDrivers
Water availabilityTemperature
Genes
IndividualPerformance
(growth)
Leaf-level Individual
Water Relations
CarbonRelations
Genes
IndividualPerformance
(growth)
Water Relations
PopulationPerformance Community
Diversity
EcosystemFunction(ANPP)
Community/Ecosystem
Population
Sorghastrumnutans
Andropogongerardii
PopulationPerformance
What is the genetic basis for ecosystem responses to altered climate?
Where do we go from here?
Year1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Pla
nt s
peci
es ri
chne
ss
20
30
40
50
60
70Year of fire Year of fire
Year of fire
Year ofwildfire
Year ofwildfire
010203040506070
Pre-fire Fire Post-firePl
ant s
peci
esric
hnes
sAnnually burnedLong-term unburned4-yr burned
Year of fire
Why a new approach to assessing community change should be considered…
After 8 yrs, aboveground production still remains ~30% lower than controls!
Why?
Andro Sorg Other Forbs
Abov
egro
und
prod
uctiv
ity (g
m-2
)
0
100
200
300
400
Control100% Removal
P < 0.001
P = 0.04
0% 100%
Abov
egro
und
prod
uctiv
ity (g
m-2
)
0
100
200
300
400
500
600
700P < 0.001
In 1996, 100% of A. gerardii and S. nutans were removed from 8 plots- Resampled 8 years later
Relative cover data suggested compensation
Additional recommendations
• Take advantage of existing data from long-term experiments to assess how changes in abundance of dominant species influence community change
• Targeted, more comprehensive sampling of existing manipulations– Resample long-term dominant species removal
experiments– Nutrient manipulation experiments, etc…
Integrate across scales• Broaden our definition of plant community
diversity to include other levels of diversity –e.g., genetic (of dominant species), pathogen, microbial– Assess change in genetic diversity of dominant
species in response to long-term manipulations– Consider archiving samples for measuring genetic
diversity
• Linkage of dynamics across hierarchical scales
• Explicitly include physiology-population-community linkages in ongoing research
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