Download Other measures of communities and ecosystems?

Plant functional trait variation
and ecological strategies
Peter Vesk
School of Botany
The University of Melbourne
Diverse solutions to challenges
• 250,000 to 400,000 species of seed
plants
– Dominated by Angiosperms
– 700 - 900 extant Gymnosperms
• Honed by natural selection
Ecological study
• Autecology -- how a particular
species makes its way in the
world
• Communities -- how species
interact with one another and
with the abiotic environment
• Is every species a special
case?
• Organizing principles
Theophrastus (d. 287 BC)
• Successor of
Aristotle, director
of Lyceum.
• Father of Botany
• De historia
plantarum
• De causis
plantarum
Historical origins
• Early origins of ecology
• Plant geographers
• Descriptive, broad scale
–
–
–
–
–
–
–
von Humboldt (1807),
de Candolle (1874),
Warming (1895),
Schimper (1903),
Merriam (1890),
Du Rietz (1931),
Raunkiaer (1934)
Raunkiaer life-form categories
A) phanerophyte: tree or shrub with perennating buds held >25cm
above ground
B) and C) chamaephyte: semishrub, buds <25cm
D) hemicryptophyte: perennial herb with bud at ground level
E) geophyte: herb with bulb or other perennating organ below ground
F) therophyte: annual plant surviving only as seed (G)
Raunkiaer leaf-size
classes
• Leptophylls - < 25 mm2 (<5x5mm)
• Nanophylls – 25 – 225 mm2
(<15x15mm)
• Microphylls – 225 – 2025 mm2
(<45x45mm)
• Mesophylls – 2025 – 18225
mm2 (<135x135mm)
• Macrophylls – 18225 – 164025
mm2 (<405x405mm)
Ecological strategy schemes
• A strategy is how a species sustains a
population. Or what they do and how they live.
– Not conscious choice, but pattern of life history and
allocation that has been moulded by natural
selection
• schemes that arrange species in categories or
along spectra according to their ecological
attributes.
Periodic table or
personality
• Unlikely to be flexible enough as an analogy
for plant ecology
3 PFT1 + 2 PFT2 = ?? Veg type2
• Perhaps personality type testing schemes
more useful
• Response to question or situation,
• Several core types identified from many
correlated descriptors combined into few
principal components of variation or factors
(Factor analysis)
Theophrastus’
character types:
surliness
• The surly man when he is asked, 'Do you know where so-andso is?' will say, 'Don't worry me ' or if addressed, will refuse to
answer. If he wishes to sell something he never names to the
intending purchaser the price he will take, but always asks him
what he is to get. Those who send him presents for the festival
as a mark of esteem are informed that he is sure it is not a
present. He has no pardon for anyone who has accidentally
bespattered him with mud or jostled him or trodden on his
foot……..
Classification schemes
• Human psychology is very suited to
classification: like and not like.
• Grouping of similar species, typologies:
plant functional types
• An important question is whether to
work with ‘types’ or with ‘spectrum’
– Introvert to extrovert
– Leaf size; small to large
Strategy schemes
•
Realised niche: distribution (or response) along
environmental gradients:
–
–
•
Ellenberg’s soil moisture and N;
Noble and Slatyer’s (1980) vital attributes (fire), grazing response
(Dyksterhuis, 1949).
Physiognomic:
–
•
Raunkiaer (1934) bud position and leaf size,
Conceptual: relating to ecological opportunity (and/or
evolutionary pressures):
–
–
–
–
–
r-K and adversity selection (MacArthur & Wilson, 1967; Southwood,
1977; Greenslade, 1983),
early and late successional spp. (Bazzaz, 1979),
exploitative and competitive spp (Bormann and Likens, 1979) gap and
non-gap species in forests, density dependence, etc
Grime’s (1974, 1977) CSR scheme
types of time, Westoby (1980) theory for arid zone vegetation.
• Species selected under
“r” vs “K” conditions
• suggested correlates
– mortality densityindependent vs densitydependent
– multiplicationdominated vs
competition-dominated
– opportunistic vs
equilibrium
– climate unpredictable vs
predictable
– early vs late succession
r-K spectrum
K
r
Species traits supposedly favoured by
r-selection relative to K-selection
•
•
•
•
•
•
High maximal rate of increase rmax
many small offspring
Rapid development
early reproduction
small body size
short lifespan
Traditional r-K spectrum mixes together
two different allocation “decisions”
• 1. Reproductive effort vs growth and survival
– partitioning of reproductive value
• 2. Within reproductive effort, many small vs few large
offspring
• Limitations of r-K particularly obvious in plants (and
other sessile ecologies)
– plant populations rarely grow exponentially through a series
of generations
– growth to large body size and survival to long lifespan
doesn’t necessarily go along with few large offspring
Introduction of a second
dimension of variation, from
favourable to "stress" or
"adversity"
Frequency or
intensity of
disturbance
Low
High
Intensity of stress
Low
High
Competitors
Ruderals
Stress-tolerators
No viable strategy
Grime’s CSR triangle
Competitor
• Competitor, Stresstolerator, Ruderal
• Ruderal (weed, pioneer)
C-R
corner reflects response
to recent disturbance
• S-->C axis expresses
R
potential for rapid growth
Ruderal
given favourable
conditions
C
C-S
C-S-R
S
S-R
Stresstolerator
Features of CSR triangle
• High-stress-high-disturbance corner
claimed not viable
• Not actually the habitat that is being
classified, but the way the species deals
with the habitat
– in particular, in highly productive
environments one sees also S species
– environment is resource-poor for them
because of the presence of C species
• Conceptual strategy dimensions
(competitiveness, shade tolerance)
difficult to compare across habitats
• Hence, measurable traits emphasized
recently.
Recent approach: major measurable
dimensions of ecological variation
• Seed mass - seed output (SM-SO)
• Specific Leaf Area - leaf lifespan (SLA-LL)
– area/dry mass of leaf
• Height
– of canopy of the species when full-grown
• wood density, twig size and leaf size
– Proportional relationship
• degree of consensus emerging about first 3,
at least
Merit of using readilymeasurable dimensions
• Species from different continents or veg’n types can
be “positioned” relative to each other without requiring
info on species distributions relative to each other or to
environmental factors
– brings worldwide meta-analyses within reach
• Axis-traits need to express something important about
ecology
– SLA, seed mass, height represent basic tradeoffs
– species spread widely along each axis
Emergence of “Macroecology”
• “The division of food and space among species
on continents"
• Statistical patterns in datasets covering 100's to
1000’s of species
• Simple traits
• Environ. data
Specific Leaf Area SLA
• Plants invest dry mass in leaves, acquire further dry mass, reinvest in more leaves
• SLA (mm2 mg-1 dry mass) is light-capture area deployed per
mass invested
– analogous to a potential rate of return
Low SLA = heavy fabric of leaf
• Thick lamina or high tissue
density
– Can feel with fingertips
– banksia to basil
– grasstree to lettuce
• SLA varies widely (~tenfold)
between coexisting spp
– why are low-SLA species not
competitively inferior?
Low-SLA species are competitive because
their leaves have longer lifespans: revenuestream over longer duration
• LL varies 400-fold
between species,
up to 50-fold
within a habitat
• SLA varies 100fold between
species, up to 40fold within a
habitat
Leaf longevity (months) [log scale]
Leaf lifespan (mo)
1000
Colorado
North Carolina
New Mexico
South Carolina
Venezuela
Wisconsin
100
10
1
10
100
1000
2
-1
Specific Leaf Area (cm g ) [log scale]
SLA
Global variation in Leaf economics
The worldwide leaf economics spectrum Ian J. Wright, et al
Nature 428, 821-827(22 April 2004) doi:10.1038/nature02403
Longer leaf lifespan in wetter areas, but leaf
construction more important
*
mass
seed
- seed
output spectrum
*mass
of an individual seed
Eg dust-like seed of orchids, through to coconuts
Benefit of low seed mass: high seed output
Henery & Westoby in prep;
2
105
r =0.72
slope not sig diff from -1
104
2
• within a m2 of canopy
outline, seed output =
(reprod effort)/(seed
mass + accessory
costs)
• seed mass varies >
100X as widely as
reprod effort, hence is
the dominant influence
on seed output
• slope = -1.0
Seed output per m canopy outline
[log scale]
Seed output47/ m2
canopy
woody
spp from sclerophyll veg'n
103
102
101
10-2
10-1
100
101
102
103
Seed mass (mg) [log scale]
Henery & Westoby (2001), 47 woody spp from
sclerophyll veg’n.
counts of published expts
with >5 spp, >10-fold range
of seed mass
Benefits of large seed
during seedling
establishment: survival
of hazards
Hazard
Large-seed spp
performed better
Compet ition from established
vegetation or other seedlings
9
Large-seed spp
did not perform
better
2
Deep shade
5
3
Defoliation
2
0
Mineral nutrient shortage
2
0
Wide spread of seed mass within habitat
• Why not a single
best compromise
between costs and
benefits?
Westoby M, Falster DS, Moles AT, et al. (2002).
Annu. Rev. Ecol. Syst. 33:125-59.
Growth form
104
western NSW
central Aust
Sydney
Indiana Dunes
Sheffield
103
r
mb
e
cli
y
od
br
sc
rte
an
ve
he
ad
wi
sis
as
un
wo
10-1
id
10-1
ino
100
r2main = 0.20
r2interaction = 0.02
am
100
ate
att
er
ho
ar
d
101
t
101
siv
e
102
nd
102
gr
103
ted
mean log seed mass (mg)
2
r main = 0.29
r2interaction = 0.03
for
b
Dispersal morphology
104
• Seed mass correlated with dispersal morphology
• 70% of var’n within dispersal mode
• Very different vegetation types and continents
• Correlation pattern reasonably consistent
Smaller
seeds
towards
the poles
Global Ecology and Biogeography Vol. 16, 1 Pages: 109-116
Copyright © 2006 The Authors Journal compilation © 2006 Blackwell Publishing Ltd
• What else could explain seed mass
Yucca plant
Ground ivy (Glechoma hederacea)
reproduces clonally
Plant height: Medicago to Mountain Ash
Moles et al 2009 Jecol 97:923-932
Copyright Journal compilation © 2009 British Ecological Society
Plant
height
QuickTime™ and a
decompressor
are needed to see this picture.
Much variation at a
site, primary
productivity explains
between sites
Moles et al 2009
Jecol 97:923-932
Stem economics spectrum?
• Stem density:
balsa to teak
Cahve et al Ecology Letters Vol. 12: 351-366 Copyright Journal compilation © 2009 Blackwell
Publishing Ltd/CNRS
Geography of
wood density
• The geographical distribution of
wood density in N and S
America. the mean wood density
value of all unique species
occurrences in that cell. (b)
Predicted mean wood density
value on the basis of climatic
variables. MAT, MAP
Plants with denser stems
grow more slowly but with
lower mortality risk
Figure 5 Relationship between wood density and
relative growth rate (log-transformed, a), and
mortality rate (log-transformed, b), for two
tropical forest sites (Barro Colorado Island,
Panama, white circles, and Pasoh, Malaysia,
black circles).
Chave, J., Coomes, D., Jansen, S., Lewis, S. L., Swenson, N. G. &
Zanne, A. E. (2009) Towards a worldwide wood economics spectrum.
Ecology Letters, 12, 351-366.
Plant ecological strategy
schemes and functional traits
• Framework for organization of species and studies
• Generalization of specific cases
• Nomenclature/identity can’t help us with prediction
about unknown species
• Understanding what are the major ways in which
plants differ
• Leaf construction, plant height, stem construction,
seed size and number
• Fundamental understanding of the role of
environment and gradients on structure and function
• Meta-analysis of ecological and physiological
experiments