a global test of the diversity-productivity and diversity-stability hypotheses australia hautier,...
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A Global Test of the Diversity-Productivity and
Diversity-Stability Hypotheses
Australia
Hautier, Borer, Lind, Seabloom, Anderson, Harpole, Hector, Hillebrand, Mac Dougall, Meyer, Prober, Ries,
Stevens + Anyone interested
Along the natural diversity gradient represented by 39 herbaceous-dominated plant ecosystems on five continents, plant cover at the species and ecosystem organizational levels was stabilized with increasing plant species richness, as indicated by a decrease of the temporal variability. On average, the plots with the highest diversity were about 40% more stable in time than the plots with the lowest diversity.
Fertilization significantly reduced species richness; on average 1.2 species (SEM = 0.4) were lost with fertilization relative to the controls. Along the reduced diversity gradient plant cover at all organizational levels was not related to species richness. The results support the diversity-stability hypothesis that greater diversity leads to greater ecosystem stability in natural systems and demonstrate that fertilization has negative effect on ecosystem stability.
Global Drivers of Loss of Biodiversity with Eutrophication
Hautier, Hector, Anderson, Grace, Seabloom, Borer, Lind, Stevens, Harpole + Anyone interested
Australia
Potential mechanisms explaining the loss of plant diversity with fertilization
• General increase in the strength of competition – aboveground for light and belowground for nutrients (Grime 1973)
• Increase in the strength of aboveground competition for light only (Newman 1973, Tilman 1982)
• Acidification (Silvertown et al. 2006)
• Accumulation of plant litter (Berendse 1999, Foster et al. 1998, Lamb 2008, Tilman 1993)
Using AMOS we made a Structural Equation Modeling to explain the changes in proportional species richness between the control and NPK+ plots. We found that once we controlled for the covariate “elevation”, proportional richness loss is greatest (1) where light reduction is greatest, and (2) where pretreatment evenness was low. Dead biomass had no effect on the change in species richness as well as other mechanisms such as acidification of competition for nutrients.
Elevation Eveness Proportion of total biomass change
Proportion of dead biomass change
Proportion of change in light
Proportion of change in richness
Eurasian herbaceous species are better competitors for nutrients away from home
• 17 species (8 grasses & 9 forbs); 25 sites: 3 UK, 3 EU, 1 China (native sites), 16 US, 1 CA and 1 AU
• 3 years of treatments• Ran separate analyses for introduced sites with multiple study species or just one
species• Analyses: Population level: LMEM with temporal autocorrelations-extracted
parameter estimates; Community level (only included 10 sites that shared 5 or more study species, 5 in native and 5 in introduced): PERMANOVA and tested study species associations (positive, negative and neutral) pre- and post-treatment.
Nutshell: Eurasia herbaceous species are stronger competitors in their away range and consumers likely enable their persistence in native communities.
• Responses (relative cover) to nutrient additions and consumer treatments differ home and away, and depending on life-form (grass or forb)
• Nitrogen and phosphorus increase away; no change home• Fencing: no change or increase (when nutrients added) at away sites; decrease at
home• Grass spp. Interactions at sites with 5 or more study species tended to be positive
at home but negative away. Where forbs had more negative interactions at home but positive away.
Relative importance of deterministic vs. stochastic community assembly increases with increasing productivity (experimental)
Davies, Melbourne, Chase, NCEAS working group, all data contributors and anyone who is interested.
What we see:• By year three, increasing productivity created communities that deviate further from
the null than communities (are more nichey) in which productivity was not increased. • Further, the effect varies with baseline productivity: at low productivity sites,
increasing productivity does not change community structure, while at productive sites, increasing productivity creates communities that are more deterministic.
• Related: increasing productivity reduced beta diversity in some treatments: NPKOther thoughts:• We are hoping that the results will strengthen further in year four.• We plan a second panel of graphs that include some environmental variables like
temperature and rainfall that might help further explain what is going on.• It would make sense to report the effects of nutrient addition on alpha and gamma
diversity -- an option would be to have this paper follow up the paper that reports these results.
Working title:
N-0
.4-0
.20.
00.
2
Yea
r 1
P K NP NK PK NPK-0
.4-0
.20.
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2
Yea
r 2
-0.4
-0.2
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0.2
Yea
r 3
100 300 500 100 300 500 100 300 500 100 300 500 100 300 500 100 300 500 100 300 500
Productivity (live mass in year 1)
Nul
l dev
iatio
n
Green=controls, Black=treatments, x-axis= observed productivity in the first year, pre treatment
Dominant plant species drive the ecosystem response to variation in
resource availability across a precipitation gradient
• Kimberly La Pierre, Dana Blumenthal, Cynthia Brown, Julia Klein, and Melinda Smith
• Submission in Summer 2012
Study Sites
TGP
SGS
MIX
SGS: Shortgrass Steppe (Shortgrass LTER)MIX: Mixed-grass Prairie (Saline Experimental Range)TGP: Tallgrass Prairie (Konza Prairie LTER)
Plant trait responses to chronic nutrient additions
• Kimberly La Pierre and Melinda Smith
• Data collected and analyzed
• Writing in Summer 2012
• Submission in Fall 2012
PC1 (32.77%)
-2 -1 0 1 2 3 4
PC
2 (1
9.2
9%
)
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
green leaves
biomass
SLAthickness
Natural Dominants
Altered Dominants
Control
Nitrogen
Phosphorus
Nitrogen and Phosphorus
short-term
Nutrient additions alter invertebrate community structure and feeding
strategy
• Kimberly La Pierre and Melinda Smith
• Data collected and analyzed
• Writing in Fall/Winter 2012
• Submission in Spring 2012
PN
plant biomass
invertebrate herbivores
K
invertebrate predators
invertebrate parasitoids
TGP
1
3 2 4
Χ2=5.480, df=15, p=0.987, RFI=0.874
0.522
0.311
0.502
(c) Per Capita Rate of Herbivory
TGP MIX SGS
Rat
e of
her
bivo
ry(d
amag
e /
chew
ing
herb
ivor
e)
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14ControlNitrogen
a
b
Phylogenetic, functional, and plant trait diversity: Examining potential drivers of
primary production in herbaceous systems
• Network-wide opt-in manuscript
• Data collection and analysis in 2012
• Write in Spring 2012
NutNicheA global test of niche destruction and biodiversity loss
• Lead: Stan Harpole (opt-in)
• Evidence for multiple nutrient limitation
• Addition of nutrients to remove limitation = niche destruction
• Loss of species with greater numbers of added nutrients
• Link to other MS’s:
– Hautier, Grace, et al.
– Fay et al.
1/2
NutNiche•general pattern, but site variation: not all sites show predicted response
•mostly multi/co-limitation (~63%); super-additive (~45%)
•mostly not sampling effect (~80% sites multiple additions > single)
•different nutrients important for different responses:
– max richness effect ≠ max biomass effect
•covariates, not much, so far
•Status: rough draft
•To do:
– composition response—get at species tradeoff assumption?
– using max trt year (responses over time appear consistent but increase with time)
– other?
2/2
N-Gradientfunctional response, critical loads
• Lead: Stan Harpole (opt-in)
• CBGB, CDCR, SEDG N-gradients
– 0,1,5,10 g m-2 yr-1
• General N10 patterns
• Status: need to write up soon!
• NutNet add-ons:
– N-dep collectors
– N1 treatments
1/1
Global EcologySS 20: Global Environmental Challenges Require Global
Ecological Research– MS for Frontiers
• status: some text, outline for ESA panel
• to do: synthesize panel results
– Meeting Report (like White et al. Bio Lett)
– SeSynC proposal
• status: draft
• to do: develop sociology
1/1
Organization/Network
Biosphere 2
EPA
EREN
FunDivEurope, Biodepth-Jena
LTER
NEON
NSF Dimensions of Diversity
Numerical Terradynamic Simulation GroupNutrient Network
Phenology Network
TraitNet, BioMERGE
ZEN seagrass network
GLEON
(Opt-out) Answering one of the 3 original NutNet questions:
Under what conditions do grazers or fertilization control plant diversity and productivity?
This paper’s goal is to examine vertebrate herbivory x nutrient supply on •plant diversity •relative abundance (evenness)•net primary production
within the context of site and regional drivers • climate• soils• regional productivity • regional diversity
NUTRIENTS AND HERBIVORES CONTROL PLANT DIVERSITY AND FUNCTION IN A GLOBAL GRASSLAND EXPERIMENT
Results1. Fertilization: species richness declined and live biomass increased (p=0.0001 and
p=0.001, respectively); 2. Fences: no overall effect on plot-scale richness, evenness, or biomass3. Inside fences, NPP declines through time, but this effect is counteracted with
fertilization4. Both Bray-Curtis & Jaccard metrics show that species in plots turnover in response to
both fertilization and fencing (will also test contingency on site diversity)
We will also look at:1. the association between grassland responses to fencing and fertilization among and
within sites (log-ratios)2. the relationship b/w turnover and change in biomass 3. global-scale predictors (contingencies) – best models of change in richness,
evenness, and biomass as a function of soils, climate, and site-level diversity, evenness, NPP (test of Gruner/Bolker model of additivity; Hillebrand contingencies model)
Next steps: re-run with current data; make final figures; hone message; write discussion
What are the biogeographic patterns of species invasions?
Biological Invasions (Seabloom et al.)
• Mainly focuses on observational data • Rejected from PNAS April 2012 – positive reviews but there were concerns about site
selection criteria and land use history (e.g., agriculture and grazing)• Currently preparing for submission to Ecology or Global Change Biology (Other
suggestions welcome)• Main changes will be adding in land use and grazing data from Cini and Suzanne’s
survey, adding in site selection survey data, and removing the bimodal graph.
• Nutrient addition caused a loss of 0.6 native species per year but had no effect on exotic diversity
• Nutrient addition caused exotic cover to increase 6% per year but had no effect on native cover
• Have had first round of reviews by all authors with no major hiccups from anyone
• Still a bit undecided about target journal
Are native and exotic species functionally distinct? Biological Invasions (Seabloom et al.)
What are the effects of fertilization and herbivory on spatial and temporal turnover of species
composition
Damschen , Gruner, Hillebrand, Lind, Wragg, Wright, Yang
Adler, Bakker, Cavender-Barres, Dev, Orrock, Sullivan
Three motivating questions
NF Y1
NF Y3
C Y1
C Y3
Spatial heterogeneity – mean similarity within treated plots relative to mean similarity within control plots
Spatial turnover– mean similarity between treated plots and control plots relative to mean similarity within control plots
Temporal Turnover– mean similarity between treated plots in Y1 and Y3 control plots relative to mean similarity within control plots in Y1 and Y3
t-values (>2 ~significant)
Heterogeneity within treatmentsLog Ratio Fert Fence Fert*FenceJaccard Y2 . . 2.632Bray Y2 . . .Jaccard Y3 . . .Bray Y3 . . .
Spatial Turnover between treatmentsJaccard Y2 . . .Bray Y2 3.298 . .Jaccard Y3 . . .Bray Y3 2.149 . .
Temporal turnover between treatments
Jaccard Y2 2.498 . .Bray Y2 . .Jaccard Y3 - -Bray Y3 . . 2.32
To do
• Re-run with this year’s data– Are lack of effects in Y3 due to limited sample size
• Test important question: What controls between site variability
• Predictor variables:– Site fertility (Y0 mean productivity)– Site sensitivity (Log response of productivity to trts)– Species Pool – Evenness, site α
Grassland Soil Stoichiometry at the Global Scale
• Currently working on a manuscript draft explaining the abundance and stoichiometry of soil organic matter in relation to climate and vegetation using NutNet observational data
The distribution of soil stoichiometric ratios is an order of magnitude larger than previously reported Redfield-like ratios for soil; this is largely due to large variation in phosphorous as reflected in C:P and N:P ratios
C and N are highly correlated with little relationship between C and P and N and P despite a previous meta-analysis reporting these relationships
• In addition, we see strong relationships between climate (temperature and precipitation) with SOM and very weak relationships between productivity or diversity
• These different factors may make it difficult to apply cornerstones of ecological stoichiometry like the Redfield ratio to grassland soils at the global scale
species response to treatments: competition-defense
vgrowth-defense
32
Eric LindElizabeth BorerEric SeabloomPeter AdlerJonathan D. BakkerDana BlumenthalMick CrawleyKendi DaviesJennifer FirnDan Gruner
Stan HarpoleYann HautierHelmut HillebrandJohannes KnopsBrett MelbourneBrent MortensenAnita C. RischMartin SchuetzCarly StevensPeter Wragg
33
34
Effects of primary production and producer diversity on consumer biomass
Lind, Borer, Kay, Wolkovich, Wright, Gruner, Yang, LaPierre, others….
Does primary productivity predict "secondary productivity"?
Native-Exotic Richness Relationship (NERR)
• 32 Nutnet sites: ‘native’ grasslands from four regions (Australia, Central, Intermountain, and Pacific.
• Four sections:
• Scale-dependent relationships between native and exotic richness (four scales: subplot 1m2, plot, site, and region).
• Drivers of NR and ER: independent or interactive? [Jenn Firn]
• Scale-dependent heterogeneity (Davies et al. 2005, 2007; Melbourne 2006): the impacts of CV on the NERR slope.
• Species associations: are species pairs more positively or negatively associated with each other, than expected by chance (Fridley et la. 2004, 2007)? [Joe Bennett]
Australia
Pacific
Central
Intermountain
f
Native richness (fine-scale 1 m-2)
Exoti
c ric
hnes
s (fi
ne-s
cale
1 m
-2) fr
eque
ncy
NS
Neg
ative
slo
pes
Posi
tive
slop
es
Fixed effects
F values (df as subscript), P value
INT_rich F1, 460=0.68, P< 0.50
MAP F1, 8=1.34, P< 0.30
MAT F1, 8=6.14, P< 0.04
MAP_VAR F1, 8=13.90, P< 0.006
Temp_VAR F1, 8=0.09, P< 0.80
Int_rich MAP_VAR F1, 460=3.15, P< 0.08
MAP MAT F1, 8=6.80, P< 0.04
MAP_VAR Temp_Var F1, 8=3.55, P< 1.0
Plot-level native richness [random intercepts due to site (σ
2 site), and block within site (σ 2
block). Full model AICc =2261; simplified model with StepAIC
function AICc=2247]
Fixed effects
F values (df as subscript), P value
Nat_rich F1, 456=3.21, P< 0.08MAP F1, 12=0.93, P< 0.40MAP_VAR F1, 12=5.68, P< 0.04MAT F1, 12=5.47, P< 0.04Temp_VAR F1, 12=3.48, P< 0.09Nat_rich MAP F1, 456=0.00006, P< 1.0Nat_rich MAP_VAR F1, 456=12.94, P< 0.0004
Nat_rich Temp_VAR F1, 456=0.07, P< 0.80MAP MAT F1, 12=7.31, P< 0.02Nat_rich x MAP x MAT F1, 456=13.74, P< 0.0002
Plot-level introduced richness {random intercepts due to region (σ
2 region), site within region
(σ 2 site), and block within site within region (σ
2 plot). Full model
AICc =1593; simplified model with StepAIC function AICc=1584
Fixed effects
F values (df as subscript), P value
MAP F1, 21=0.91, P< 0.40
MAT F1, 21=2.72, P< 0.20
Temp_VAR F1, 21=12.75, P< 0.002
MAP x MAT F1, 21=2.05, P< 0.20
MAP Temp_VAR F1, 21=3.98, P< 0.06
Site-level native richness[random intercepts due to region (σ
2 region), and site within block (σ 2 site). Full
model AICc =273; simplified model with StepAIC function AICc=256]
Fixed effects
F values (df as subscript), P value
NAT_rich F1, 14=1.83, P< 0.20
MAP F1, 14=0.70, P< 0.50
MAT F1, 14=2.86, P< 0.20
MAP_VAR F1, 14=8.5, P< 0.01
Temp_VAR F1, 14=0.80, P< 0.40
MAP x MAT F1, 14=4.80, P< 0.05
Nat_rich Temp_VAR F1, 14=2.47, P< 0.15
Nat_rich MAP F1, 14=0.24, P< 0.70
Nat_rich MAT F1, 14=0.05, P< 0.90
Nat_rich MAP x MAT F1, 14=0.61, P< 0.50
Nat_rich MAP x Temp_VAR F1, 14=2.98, P< 0.20
Site-level introduced richness[random intercepts due to region (σ
2 region), and site within region (σ 2
site). Full model AICc =236; simplified model with StepAIC function
AICc=227]
Prop
ortio
n of
sig
nific
ant c
orre
latio
ns
****
**
A. Site-level species associations - natives vs. exotics
B. Plot-level species associations - natives vs. exotics
** contrasts the proportion of significant asstns that are positive vs those that are negative
A global study of below-ground allocation patterns in grasslands
• Proportional root allocation should decline when growth is limited by above-ground resources (e.g. light), and increase when growth is limited by below-ground resources (e.g. water and nutrients).
• Extracted roots from 21 sites (8 more expected this summer)
• Plan to do a full analysis and write much of a paper this week (hope that the additional sites do not change the main results substantially)
Specific hypotheses• Proportional root allocation will decline as total
production increases– With increasing number of nutrients added– Inside herbivore exclosures (high litter accumulation
leading to light limitation)
• Flexibility in allocation will decline with decreasing soil moisture availability (interaction between nutrient addition and site-level mean rainfall)
Manuscript 1: Strong abiotic controls over seed removal in a continent-wide study
Status: analyses completed, ms drafted, submit after current round of comment by co-authors (Ecology is target journal)
400 600 800
0.0
0.2
0.4
0.6
0.8
1.0
Annual Evapotranspiration (mm)
400 600 800 1000 1200
0.0
0.2
0.4
0.6
0.8
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Mean Annual Precipitation (mm)
Pro
po
rtio
n o
f S
ee
ds
Re
mo
ved
Authors: Orrock, Brudvig, Firn, MacDougall, Yang, Melbourne, Baker, Bar-Massada, Borer, Crawley, Damschen, Davies, Gruner, Kay, Lind, McCulley, Seabloom.
Manuscript 2: Contingency in consumer-mediated invasion
Status: introduction drafted, analyses in progress. Pending completion of analyses, send discussion draft to co-authors by September, submit ms by November
Objective: examine how the role of consumers in affecting exotic plant abundance varies as a function of abiotic constraints (e.g. temperature, precipitation)
Authors: Orrock, Firn, Bakker, Blumenthal, Borer, Brown, Brudvig, Buckley, Chu, Cleland, Cottingham, Crawley, Damschen, Davies, Firn, Frater, Gruner, Kay, Kirkman, Klein, Knops, LaPierre, Leakey, Li, Lind, MacDougall, McCulley, Melbourne, Moore, Morgan, Nelson, Prober, Seabloom, Stevens, Wolkovich, Wright, Yang
Manuscript 3: Biofuel potential of three semi-natural grasslands
Objective: examine the energy produced by plant biomass derived from grasslands in CA, MO, and SC
Authors: Orrock, Watling, Brudvig, Damschen, Borer, Seabloom, Baker
Status: analyses need to be re-visited, ms drafted, revise discussion, send to co-authors, then submit (Ecological Applications is target journal)
Working Title: What limits productivity in grasslands worldwide?Co-Leads: Phil Fay, Suzanne Prober, John Knops (opt-out paper)
Hypotheses:1.Nitrogen is a globally significant limitation on productivity at most sites2.Nitrogen response of Productivity is independent of climate3.Phosphorus limitation prominent on old, weathered soils4.Additional nutrient (co-)limitation in some cases/places
ANPP: 40 sites
Site
frue
.ch
trel
.us
hall.
ushe
ro.u
kaz
i.cn
bogo
ng.a
ucb
gb.u
sco
wi.c
ase
reng
.tzty
so.u
sko
nz.u
ssp
in.u
sel
liot.u
ste
mpl
e.us
unc.
ushn
vr.u
sro
ok.u
ksm
ith.u
sbu
rraw
an.
sier
.us
sedg
.us
mcl
a.us
bnch
.us
salin
e.us
valm
.ch
hopl
.us
look
.us
lanc
aste
rcd
pt.u
sba
rta.
uski
ny.a
usa
ge.u
sbl
dr.u
ssa
va.u
ssh
ps.u
scd
cr.u
sm
tca.
ausg
s.us
hart
.us
sevi
.us
AN
PP
(g
m-2
s-1
y-1
)
0
200
400
600
800
1000
1200
1400
1600
1800
Mean all yearsyear 1year 2year 3
Nutrient main effects 40 sites, all avail. years
Nutrients added
C N P NP K NK PK NPK
AN
PP
(g
m-2
s-1
y-1
)
0
100
200
300
400
500
600
ab ab
c
cc
ab
d
Nutrient response to rainfall and temperatureMAT.N Chi P=0.003MAP.N Chi P<0.001MAP.P Chi P<0.001MAT.K Chi P= 0.009
Random model: site_code + site_code.year_trt + site_code.block + site_code.year_trt.block + site_code.plot + plot.syVariance structures: differing variance between sites; differing variance between pots within sites each year
• Currently: Fine-tuning hypotheses and statistical models• Investigating covariance of nutrient effects with climate/grazing intensity
variables.• Need to investigate soil property effects.
• Currently: Fine-tuning hypotheses and statistical models• Investigating covariance of nutrient effects with climate/grazing intensity
variables.• Need to investigate soil property effects.
Site
AN
PP
(g
m-2
s-1
)
0
200
400
600
800
1000
1200
1400
Control+N
22 Sites with N-main effect significant
20 - 84% increase
Site
hero
.uk
hall.
ussp
in.u
sbu
rraw
an.
unc.
usro
ok.u
khn
vr.u
sbn
ch.u
ssm
ith.u
sla
ncas
ter
sier
.us
look
.us
valm
.ch
salin
e.us
hopl
.us
sage
.us
bldr
.us
shps
.us
cdcr
.us
hart.
ussa
va.u
sm
tca.
au
AN
PP
(g
m-2
s-1
)
0
200
400
600
800
1000
1200
Control+P+K+PK
22 Sites withP or PxK effect significant
P, P x K: -28 to +184%
Nutrient response to rainfall
MAP*N*P P=0.005, adjusted for grazing coefficientRandom model: site_code + site_code.year_trt + site_code.block + site_code.year_trt.block + site_code.plot + plot.syVariance structures: differing variance between sites; differing variance between pots within sites each year
History of Grazing & Cultivation Survey• Surveys completed for 39 sites• Information from survey
– Whether there is grazing currently & when started– Whether or not & when site was cultivated– Management activities w/in plots– What herbivores present & relative abundance in
evolutionary, ecological, recent historic times– Timing of influential climatic events– What is the level of current and recent historic grazing
(nil, low, medium, high)
Evolutionary History of Vertebrate Grazing and Plant Invasions
• What is the role played by evolutionary histories of grazing on the relative success of native and introduced plant species?
• Is recovery from exotic invasion with grazing exclusion influenced by the evolutionary history of grazing?