Disturbance & Ecological Succession
Hurricane Katrina
Aug. 29, 2005
Image from http://earthobservatory.nasa.gov/Newsroom/NewImages/Images/katrina_goe_2005241_lrg.jpg
Disturbance & Ecological Succession
Succession – directional change in community composition at a site
(as opposed to simple fluctuations), initiated by natural or
anthropogenic disturbance, or the creation of a new site
Some biologists restrict the definition to directional
replacement of species after disturbance
Disturbance – a discrete event that damages or kills residents
on a site; either catastrophic or non-catastrophic
(Platt & Connell 2003)
Photo of W. J. Platt at Camp Whispering Pines, LA from K. Harms; photo of J. H. Connell from UCSB
Disturbance & Ecological Succession
Catastrophic disturbance – a disturbance that kills all residents of
all species on a site; i.e., creates a “blank slate” (Platt & Connell 2003)
Mt. St. Helens, Washington, U.S.A.
May 18, 1980
Photo of Mt. St. Helens from Wikipedia
Disturbance & Ecological Succession
Non-catastrophic disturbance – a disturbance that falls short of
wiping out all organisms from a site; i.e., leaves “residual organisms”
or “biological legacies” (Platt & Connell 2003)
Yellowstone Nat’l. Park, U.S.A.
just after 1988 fires
Luquillo Experimental Forest, Puerto Rico
just after 1989 Hurricane Hugo
Photo of Yellowstone in 1988 from Wikipedia;
Photo of Luquillo Forest, Puerto Rico in 1989 from http://pr.water.usgs.gov/public/webb/hurricane_hugo.html
Disturbance & Ecological Succession
Primary Succession – succession that occurs after the creation of
a “blank slate,” either through catastrophic disturbance or
de novo creation of a new site
Mt. St. Helens, Washington, U.S.A.
May 18, 1980
Anak Krakatau, Indonesia
appeared above water ~ 1930
Photo of Mt. St. Helens in 1980 from Wikipedia;
Photo of Anak Krakatau from http://amazingindonesia.net/2008/06/mount-krakatoa-the-wrath-of-earth
Disturbance & Ecological Succession
Secondary Succession – succession that occurs after
non-catastrophic disturbance (including “old fields”)
Yellowstone Nat’l. Park, U.S.A.
just after 1988 fires
Luquillo Experimental Forest, Puerto Rico
just after 1989 Hurricane Hugo
Photo of Yellowstone in 1988 from Wikipedia;
Photo of Luquillo Forest, Puero Rico in 1989 from http://pr.water.usgs.gov/public/webb/hurricane_hugo.html
Disturbance & Ecological Succession
Henry David Thoreau (1859) is often credited with coining
“succession” as applied to directional changes in plant communities
Thoreau made many remarkable observations at a time when many
still believed in such phenomena as spontaneous generation
“Though I do not believe that a plant will spring up
where no seed has been, I have great faith in a seed.
Convince me that you have a seed there,
and I am prepared to expect wonders.”
Photo of Thoreau from Wikipedia
Disturbance & Ecological Succession
Connell & Slatyer (1977) – Reacted against an emphasis on life-history
strategies & competition alone; recognized a variety of species
interactions that could impact succession
Three models of succession:
1. Facilitation – Early species enhance the establishment of later
species (if it occurs, it is perhaps most likely in primary succession)
2. Tolerance – Early species have no effect on later species
3. Inhibition – Early species actively inhibit later species
Disturbance & Ecological Succession
Primary succession along the Glacier Bay chronosequence
One of the world’s most rapid and extensive glacial retreats in modern
times (so far); eliminated ~2500 km2 of ice in ~200 yr, exposing large
expanses of nutrient-poor boulder till to biotic colonization
Photo of Glacier Bay National Park, Alaska from Wikipedia
Disturbance & Ecological Succession
Primary succession along the Glacier Bay chronosequence
Classical view of Glacier Bay succession based on 50 yr of research,
which employed the simple chronosequence assumption:
- Mosses
- Mountain Avens (Dryas); shallow-rooted herbs
- Willows (Salix); first prostrate, then shrubby species
- Alder (Alnus crispus); after 50 yr forms thickets to 10 m
- Sitka Spruce (Picea sitchensis); invade alder thickets
- Hemlock (Tsuga heterophylla); establish last
Succession is driven by N-fixation (Dryas & Alnus)
Alnus acidifies the soil, allowing Picea invasion
Accumulation of soil carbon through succession improves soil texture
and water retention, ultimately allowing invasion by Tsuga
Disturbance & Ecological Succession
Primary succession along the Glacier Bay chronosequence
Fastie (1995) – Reconstructed patterns of stand development at
several sites within the chronosequence; intensively analyzed tree-rings
Figure from Fastie (1995)
Disturbance & Ecological Succession
Primary succession along the Glacier Bay chronosequence
Fastie (1995) – Identified 3 alternative pathways of compositional
change (not a single chronosequence of events):
1. Sites deglaciated prior to 1840 were colonized early by
Picea & Tsuga
2. Sites deglaciated since 1840 were the only sites colonized
early by N-fixing Alnus
3. Sites deglaciated since 1900 were the only sites dominated
relatively early by black cottonwood (Populus trichocarpa)
Disturbance & Ecological Succession
Primary succession along the Glacier Bay chronosequence
Oldest sites:
Intermediate sites:
Youngest sites:
Dryas  Picea & Tsuga
Dryas  Alnus  Picea
Dryas  Alnus  Populus  Picea
What accounts for these among-site differences in composition?
Differences are unrelated to soil parent material
Strong effect of seed source: Refugial Picea stands are
concentrated at the mouth of the bay; distance from the
nearest seed source explains 58% of among-site
variance in early Picea recruitment
Younger sites received more of their seed rain from new
communities colonizing exposed surfaces than from refugial
populations
Disturbance & Ecological Succession
Primary succession along the Glacier Bay chronosequence
What about facilitation?
Succession of Alnus to Picea was considered a textbook example of
facilitation in the mid- to-late 20th century
The real pattern is more complex!
Alnus was absent on older sites, so Picea does not require it for
establishment
Alnus may either inhibit or facilitate seedling establishment of Picea
Chapin et al. (1994) – Found net positive effects of Alnus on
Picea on glacial moraines, but net negative effects on
floodplains
Disturbance & Ecological Succession
Facilitation along cobble beaches of New England
Bruno (2000) – Determined mechanisms by which Spartina alterniflora
is a facilitator of relatively large impact on the community (i.e., a
“foundation species” - Drayton [1972]; “keystone modifier” - Bond
[1993]; “ecosystem or keystone engineer” - Jones et al. [1994])
Observations:
Spartina occurs along the
shore; cobble-beach plants
occur behind Spartina
Cobble-beach community is
absent along breaks in the
Spartina phalanx
Photo by J. Bruno
Disturbance & Ecological Succession
Facilitation along cobble beaches of New England
Bruno (2000)
Question:
At which life stage(s) is colonization of cobble-beach plants limited to
sites behind Spartina?
Experiment:
Addition experiments to determine limiting life stages (seed supply,
seed germination, seedling emergence, seedling establishment & adult
survival) for cobble-beach plants
Results:
Only seedling emergence & establishment were adversely affected
by the absence of Spartina
Disturbance & Ecological Succession
Facilitation along cobble beaches of New England
Bruno (2000)
Question:
By what mechanism(s) does Spartina facilitate seedling emergence &
establishment of cobble-beach plants?
Experiment:
Conducted manipulations of water velocity, substrate stability, herbivory
& soil quality in sites lacking Spartina
Results:
Substrate stability increased seedling emergence & establishment,
whereas manipulations of the other factors had limited influence
Disturbance & Ecological Succession
Facilitation along cobble beaches of New England
Bruno (2000)
Conclusions:
Spartina alterniflora acts as a foundation species, keystone modifier &
ecosystem engineer by stabilizing the substrate, enabling seedlings of
cobble-beach plants to emerge & survive
Photo by J. Bruno
Disturbance & Ecological Succession
Primary succession on Krakatau & Anak Krakatau
Explosion of Krakatau (1883)
The loudest explosion ever
heard by humans
Created tsunamis that killed
30,000 people on larger
islands & mainland
Anak Krakatau
The island was effectively “sterilized”
Anak Krakatau (“Child of Krakatau”) appeared out of the ocean in
~1930 & has been growing ever since
First analyses of colonizing vegetation were by Doctors van Leeuwen
(~1930s); more recent expeditions by Robert J. Whittaker
Photo of Anak Krakatau from http://amazingindonesia.net/2008/06/mount-krakatoa-the-wrath-of-earth
Disturbance & Ecological Succession
Primary succession on Krakatau & Anak Krakatau
Whittaker (1994) – Examined dispersal characteristics of plant arrivals
Nearest mainland site is Sumatra (~ 50 km away);
Nearest island is ~ 21 km away
First arrivals (within 4 yr of eruption) were either wind or water
dispersed
Early zoochorous plants were dominated by figs; 17 of 24 fig species
on the island arrived in the first 30 yr and are now canopy dominants,
which suggests that bats have been very important dispersal vectors
or mobile links (Old World bats have gut-retention times up to 12 hr)
Disturbance & Ecological Succession
Primary succession on Krakatau & Anak Krakatau
Whittaker (1994) – There are now 124 zoochorous species on Anak
Krakatau
Doves and pigeons (> 4 hr gut retention time) have been important
dispersers subsequent to colonization of the island by figs (an indirect
mechanism of facilitation by bats operating through figs?)
Many large-seeded species are absent relative to Sumatra & the
mainland flora
Disturbance & Ecological Succession
Primary succession on the flanks of Mount St. Helens
May 18, 1980 – the north face of the
previously symmetrical mountain
collapsed in a rock-debris avalanche
that essentially wiped clean 60 km2
of forest
Fagan & Bishop (2000) – Examined
the influence of herbivores on the rate
of spread of lupines (Lupinus lepidus),
the site’s main “colonizing” species
Mt. St. Helens, Washington, U.S.A.
May 18, 1980
Photo of Mt. St. Helens from Wikipedia
Disturbance & Ecological Succession
Primary succession on the flanks of Mount St. Helens
Lupines are efficient N-fixers
& trap detritus; they are often
facilitators in ecological
succession
Lupines colonized from
remnant populations
elsewhere on the
volcano to form patches
Spread rapidly initially
and then slowed
Why?
Figure from Fagan & Bishop (2000)
Disturbance & Ecological Succession
Primary succession on the flanks of Mount St. Helens
Fagan & Bishop (2000) – Ruled out various alternative explanations
for slowed population growth rates & focused on the effect of insect
herbivores, whose colonization lagged behind the lupines by 10 yr
Experimental test:
Established plots at the center of lupine patches (core) and at the edge
of expanding patches (edge)
Sprayed half of the plots with pyrethroid insecticide
Disturbance & Ecological Succession
Primary succession on the flanks of Mount St. Helens
Much higher incidence of
damaging insects at
patch edges
Higher leaf damage at
patch edges
Figure from Fagan & Bishop (2000)
Disturbance & Ecological Succession
Primary succession on the flanks of Mount St. Helens
Lower seed production
at patch edges
Edge
Site
Core
Site
Why was there more herbivore activity at the edge?
Densities of predators (e.g., spiders) & parasitoids (e.g., a tachinid fly)
were 4x higher at the core vs. edge
Predators may be more abundant in the core where plant density &
productivity are higher
Figure from Fagan & Bishop (2000)
Disturbance & Ecological Succession
Primary succession on the flanks of Mount St. Helens
Fagan and Bishop (2000) – Diffusion model showed how reduced seed
production at the edge affects rates of lupine spread (assuming no longdistance, jump-dispersal events)
Figure from Fagan & Bishop (2000)
Disturbance & Ecological Succession
Modeling secondary succession – Horn (1975)
Developed simple Markov models of successional replacement
of temperate-zone tree species
Forest consists of cells, each occupied by a single tree
Probability of replacing an individual tree with a new individual of
a given species is calculated from a transition matrix
Example of transition matrix for four species
(GB=grey birch; BG=black gum; RM=red maple; BE=beech)
GB
BG
RM
BE
GB
0.05
0.01
0
0
BG
0.36
0.57
0.14
0.01
RM
0.50
0.25
0.55
0.03
BE
0.09
0.17
0.31
0.96
Initial composition vector: (100, 0, 0, 0)
After 1 time step:
(5, 36, 50, 9)
Iterate this process & plot the
changes in relative abundance…
Disturbance & Ecological Succession
Modeling secondary succession – Horn (1975)
GB
BE
RM
BG
Figure from Horn (1975)
Disturbance & Ecological Succession
Modeling secondary succession – Horn (1975)
One approach for estimating transition probabilities: proportional to the
fraction of each species as saplings beneath adults, e.g., if 5% of
saplings beneath GB are GB, then P(GB|GB)=0.05
If the same transition matrix is used throughout, then a stable composition
(the dominant Eigenvector) will result (here dominated by BE)
However, the Markov approach is phenomenological, so…
Why do recruitment probabilities vary, i.e., what biological traits lead to
different colonization rates & relative abundances?
Disturbance & Ecological Succession
Modeling secondary succession – Pacala et al. (1996; SORTIE)
The most recent generation of forest simulation models; precursors
include FORET (Shugart & West 1977)
Spatially explicit, mechanistic simulation model developed to predict
dynamics of succession for 9 species of northeastern U.S.A. hardwoods
Early occupation by Red Oak (Quercus rubra) & Black Cherry (Prunus
serotina) followed by late dominance by Beech (Fagus grandifolia) &
Hemlock (Tsuga canadensis), with Yellow Birch (Betula alleghaniensis)
present in gaps
Disturbance & Ecological Succession
Modeling secondary succession – Pacala et al. (1996; SORTIE)
Basics of SORTIE:
Spatially explicit model predicting the fate of every individual tree
throughout its life
Individual performance is affected by resource availability at each tree’s
location (original SORTIE only included competition for light)
Species-specific functions predict each individual’s growth, mortality,
fecundity & dispersal; estimated from data collected in the field
Four sub-models determine the fate of each individual throughout its life
Disturbance & Ecological Succession
Modeling secondary succession – Pacala et al. (1996; SORTIE)
(1) Resource (light) submodel: Calculates light available to an
individual based on its neighborhood; the process is analogous to taking
a fisheye photo above each plant
Calculates a projected cylindrical crown for each individual based on data
relating crown diameter & depth to stem diameter
Computes whole-season photosynthetically active radiation (PAR) for
each plant based on the location & identity of neighbors
Figure from Pacala et al. 1996
Disturbance & Ecological Succession
Modeling secondary succession – Pacala et al. (1996; SORTIE)
(2) Growth sub-model: Species-specific equations predict radial growth
from diameter & light availability
Figure from Pacala et al. 1996
Disturbance & Ecological Succession
Modeling secondary succession – Pacala et al. (1996; SORTIE)
(3) Mortality sub-model: Species-specific equations predict probability
of death from an individual’s growth rate over the past 5 yr
Figure from Pacala et al. 1996
Disturbance & Ecological Succession
Modeling secondary succession – Pacala et al. (1996; SORTIE)
(4) Recruitment sub-model: Species-specific equations predict the
number & spatial locations of seedlings based on the sizes of adult trees
Figure from Pacala et al. 1996
Disturbance & Ecological Succession
Modeling secondary succession – Pacala et al. (1996; SORTIE)
Community-level output: From randomly seeded initial composition
Hemlock & Beech clearly dominated after 500 yr
Figure from Pacala et al. 1996
Disturbance & Ecological Succession
Modeling secondary succession – Pacala et al. (1996; SORTIE)
The mechanistic approach taken in this model allows one to ask:
Which key traits define species performance?
How sensitive are model predictions to parameter values (and therefore
sampling errors in parameter estimation)?
How would hypothetical species with different parameter values perform
in this community? What would constitute a “superspecies” (i.e., one of
J. Silvertown’s ecological / evolutionary “demons”)?
How many species could potentially coexist,
e.g., > 50 spp. for > 10,000 yr?
How would changing abiotic / biotic conditions affect forest trajectories?
Disturbance & Ecological Succession
Modeling secondary succession – Pacala et al. (1996; SORTIE)
Baseline without
disturbance
Figures from Deutschman et al. 1997
Heavy
disturbance
Large, circular
clear-cut
Disturbance & Ecological Succession
Succession may involve changes beyond species composition…
Community and Ecosystem Properties:
Diversity – often increases throughout succession
Standing-crop biomass – often increases throughout succession
Elemental cycling & other biogeochemical processes –
e.g., the Hubbard Brook experiments in New Hampshire,
and Peter Vitousek’s work in Hawaii
Susceptibility to disturbance – may be a function of time since last
disturbance, e.g., fire and the accumulation of fuel loads
Anthropogenic Disturbance & Ecological Succession
If “all species have evolved in the presence of disturbance, and thus are
in a sense matched to the recurrence pattern of the perturbation”, why
are anthropogenic disturbances often so damaging? (Paine et al. 1998)
Anthropogenic disturbances often differ from the natural
disturbance regime in timing, frequency, or intensity
Paine et al. (1998) also argued that: “more serious ecological
consequences result from compounded perturbations within the
normative recovery time of the community in question”
Anthropogenic Disturbance & Ecological Succession
A marine example: Corals in the Caribbean
Hughes (1994, Science)
One-two punch of overfishing (“selective disturbance”) & “natural”
mass mortality of dominant urchins (Diadema) has created a
“phase-shift” from coral-dominated to macroalgae-dominated reefs
Caribbean coral reefs may never recover!
Photo of macroalgae-dominated reef from http://news.mongabay.com/2008/0108-hance_coral.html
Anthropogenic Disturbance & Ecological Succession
A terrestrial example: Dipterocarps in southeast Asia
Curran et al. (1999, Science)
One-two punch of logging & increased
frequency of El Niño events (due to
anthropogenically induced climate change?)
resulted in elimination of recruitment by
dipterocarps in forests of Borneo!
May result in a large-scale “phase-shift” away
from dipterocarp domination of the forests
[dipterocarps are the principal food of giant
squirrels, bearded pigs, several species of
parakeet & myriad specialist insects, etc.]
Photo of dipterocarp forest from http://biology.ucsd.edu/news/article_012706.html
Diversity-Productivity, Diversity-Invasibility,
& Diversity-Stability Relationships
Warmer sea-surface temperatures
(indicated by warmer colors)
= higher productivity
Image from Committee on Earth Observation Satellites (CEOS): http://www.ceos.org/
Diversity-Productivity Relationship
Many shapes for this relationship have been observed in nature
Rosenzweig & Abramsky (1993)
Diversity-Productivity Relationship
Many shapes for this relationship have been observed in nature
Rosenzweig & Abramsky (1993)
Diversity-Productivity Relationship
Many shapes for this relationship have been observed in nature
S or D
Productivity
II. b.
II. a.
S or D
Sometimes curves like
I and III may arise
from sampling opposite
ends of productivity
gradients in which
curve II is the overall
relationship
Productivity
S or D
S or D
Productivity
III.
S or D
II.
I.
Productivity
Productivity
Diversity-Productivity Relationship
Many shapes for this relationship have been observed in nature
Mittelbach et al. (2001)
Methods:
Examined the relationship between productivity & diversity for 171 studies
Observations:
Even though many researchers are enamored of hump-shaped curves,
the curves vary dramatically from site-to-site, as well as within & among
taxonomic groups
Suggestions and conclusions:
Don’t assume a particular relationship – measure it
Be wary of the independent variable used as a surrogate for “productivity”
Diversity-Productivity Relationship
Many shapes, but what are the mechanisms?
Tilman (1982, 1988), Tilman et al. (1996), etc.
Explained hump-shaped curves by the changes in heterogeneity that sometimes
accompany changes in resource availability
A
A
A
A
A A
A A
A A
B
A
A
A A
A
A
B
B
B
B
A A
A A
B
B
B
B B
B
B
B B
B B
B
B
E.g., soil fertility / productivity gradient
= poorest soil;
species A outcompetes
species B
= richest soil;
species B outcompetes
species A
B
Diversity-Productivity Relationship
Rosenzweig & Abramsky (1993)
Summarized several mechanistic hypotheses for hump-shaped curves
Suggested that separate mechanisms account for the rising vs. falling portions
Preferred mechanism for the rising portion:
“A poor environment supplies too meager a resource base for its would-be
rarest species, and they become extinct”
In other words “poor environments support lower population sizes, and
population size is inversely related to extinction probability”
No well-supported mechanism for the falling portion:
Provided several potential mechanisms, but claimed that none are
well-supported by observations or experiments; even so, Tilman’s
heterogeneity hypothesis has some empirical support
Diversity-Productivity Relationship
Stevens & Carson (2001)
Declining curves could result simply from size differences; if sites are sampled with
the same sized plots, more productive sites may have fewer species because they
have fewer individuals, especially owing to the ubiquitous clumping that occurs in
natural populations
A
A
A
B
B A
A
A B
B
A
B
A
A
A
A
E.g., cloudiness-induced productivity gradient
= lowest light availability
How might this problem be avoided?
= highest light availability
Use an index that is insensitive to sample size
Diversity-Productivity Relationship
Kyle’s conjecture…
If disturbance, predation, competitive equivalence, or dispersal limitation occur
alone or in combination such that competitive exclusion does not occur among the
recruits of species within a guild (especially plants), then sites with conditions in
which more species are capable of surviving and reproducing will contain more
species, i.e., diversity will increase up the resource (e.g., fertility) gradient
Species-poor
community at low
end of resource
gradient
Species 1
Species 2
Species 3
Species 4
Species 5
Species 6
Resource availability, e.g., soil fertility
Species-rich
community at high
end of resource
gradient
Diversity-Productivity Relationship
A hump-shaped diversity-productivity relationship could result
in the “Paradox of Enrichment” within trophic levels…
Community sampled before fertilization
Species diversity
Community sampled after moderate-level fertilization
Community sampled after high-level fertilization
Productivity
Diversity-Productivity Relationship
A hump-shaped diversity-productivity relationship could result
in the “Paradox of Enrichment” within trophic levels…
Gough et al. (2001)
Methods:
Examined long-term experiments from 7 Long-Term Ecological Research
(LTER) sites in North America
Observations:
Nearly all demonstrated a decline in diversity after fertilization
Suggestions & conclusions:
The results have utility for similar situations, but little relevance to natural
productivity gradients, since species distributions along natural gradients
are influenced by long-term ecological & evolutionary processes, e.g.,
species may preferentially colonize or originate within sites of high
productivity, giving rise to a positive relationship
Diversity-Productivity Relationship
(Productivity-Diversity)
So far we have considered productivity gradients due to gradients
in resource availability, e.g., physical gradients
What happens when we reverse the axes, and ask how diversity in a given
site, i.e., one set of physical conditions, influences productivity?
Diversity-Productivity Relationship
(Productivity-Diversity)
Examples from artificial communities…
Loreau et al. (2001)
“Biodiversity and Ecosystem Functioning…”
Methods:
Compiled data from a variety of field, Ecotron & other mesocosm
experiments in which S or D were varied experimentally
Observations:
Productivity
Sites of high intrinsic
resource availability
Sites of low intrinsic
resource availability
S or D
Diversity-Productivity Relationship
(Productivity-Diversity)
Examples from artificial communities…
Loreau et al. (2001)
“Biodiversity and Ecosystem Functioning…”
Conclusions:
A monotonic or saturating curve almost always results from experimental
settings examining the influence of diversity on productivity
At least two mechanisms can create a positive relationship between
diversity and productivity:
1. Complementarity – species use complementary niche space
2. Sampling – random sampling a large species pool is more likely to
select a key (highly productive) species than sampling a small pool
How might these two mechanisms differ in their implications for
conservation, global change, etc., especially with respect to redundancy?
Diversity-Productivity Relationship
Diversity
(Productivity-Diversity)
Latitudinal gradient
Diversity
Productivity
Biomass gradient
Diversity
Experimental diversity gradient
Productivity
Productivity
Diversity
Productivity
For plants, the relationship may change with scale
(see Mittelbach et al. 2001)
Experimental manipulations of plant diversity within habitats
generally yield positive relationships
Figure from Purvis & Hector (2000)
Diversity-Invasibility Relationship
This is especially germane in today’s world of rampant spread of
exotic species, i.e., the “homogenization of biodiversity”
Charles Elton first proposed that more diverse
communities should be less invasible
Photo of Charles Elton from http://www.wku.edu/~smithch/chronob/ELTO1900.htm
Diversity-Invasibility Relationship
This is especially germane in today’s world of rampant spread of
exotic species, i.e., the “homogenization of biodiversity”
Fargione et al. (2003)
Methods:
Experimental, grassland plots containing mixtures of plants from
four “functional guilds”: C3 (cool-season) grasses, C4 (warm-season)
grasses, legumes, non-N-fixing forbs
Experimentally introduced seeds of representatives of each guild
Results and conclusion:
C4 grasses exhibited the greatest inhibitory effect on introduced species
(i.e., they were competitive dominants); established species from each
functional guild most strongly inhibited species from its own guild
Diversity reduces invasibility, both by increasing the chances of
encountering established plants of the same guild (“close competitors
cannot invade”), as well as established plants of the dominant guild (a
“sampling” effect)
Diversity-Invasibility Relationship
This is especially germane in today’s world of rampant spread of
exotic species, i.e., the “homogenization of biodiversity”
Levine (2000)
Methods:
Removed non-Carex species from sedge tussocks along streams in
California, and subsequently added 1, 3, 5, 7, 9 native species, but kept the
total cover of plants identical
After one year, added 200 seeds of 3 exotic species to each tussock
Results and conclusion:
Fewer exotic seedlings established on more species-rich tussocks
Increased diversity provides increased “immunity” to invasion
Levine also found that diversity of native species was positively related to
diversity of exotics in unmanipulated tussocks
In light of his experimental results, how could this happen?
Diversity-Stability Relationship
Initial empirical guess…
MacArthur (1955)
a.k.a. “complexity-stability” relationship
Alternative energy pathways in complex food webs might favor more constant
population sizes with reduced fluctuations, thus promoting stability
Diversity-Stability Relationship
Early modeling results…
May (1973)
Challenged MacArthur’s intuition & verbal arguments with mathematical
models that showed no theoretical basis for the relationship to necessarily
be in any particular direction (all possibilities could be obtained)
Diversity-Stability Relationship
Back to empiricism, with potential reasons for differences of opinion…
Pimm (1984; 1991) – Three levels of organization at which to measure “stability”
Population
Community (especially community composition)
Ecosystem (especially biomass, energy flux, or the flux of matter,
e.g., C, N, etc.)
Diversity-Stability Relationship
Back to empiricism, with potential reasons for differences of opinion…
Pimm (1984; 1991) – Five definitions for “stability”
Stability (in the strict mathematical sense) – a system is stable if, and only if,
the variables all return to equilibrium conditions after displacement from them
Resilience – the rapidity with which a variable that has been displaced from
equilibrium returns to it
Persistence – the duration that a variable maintains a given value until it
changes to a new value
Resistance – the degree to which other variables change when a given variable
is permanently changed to a new value
Variability – the degree to which a variable varies over time
Diversity-Stability Relationship
Back to empiricism, with potential reasons for differences of opinion…
Pimm (1984; 1991) – At least three definitions for “complexity”
Species richness – S
Connectance – the degree to which all nodes interconnect with other
nodes in a food web
Relative abundance – D
…and this isn’t an exhaustive list!
(3 levels of ecological organization) x (5 definitions of “stability”) x
(3 definitions of “complexity”) = at least 45 different questions that could be
asked about the relationship between community complexity & stability!
Diversity-Stability Relationship
Mechanisms that could generate a positive relationship between species
diversity & ecosystem-level stability…
McCann (2000) –
Averaging effect – “Assume covariances between species are zero and
variance (si2) in abundance of individual species i in a plant community is
equal to cmiz, where c and z are constants and mi is the mean density of
species i. Given that all k species in a community are equal in abundance
and sum to m (that is, mi=m/k), then the coefficient of variation (CV) of
community abundance can be determined as:
CV = 100s/m = 100(c/k)1/z
For the case z > 1, increasing k (species number) decreases the variation in
biomass for the plant community”
Diversity-Stability Relationship
Mechanisms that could generate a positive relationship between species
diversity & ecosystem-level stability…
McCann (2000) –
Negative-covariance effect – “If covariances between species (say,
species a and b) are negative (that is, cov(a,b)<0), then the variance in the
abundance of two species:
s2(a+b) = sa2 + sb2 + 2cov(a,b)
will be less than the sum of the individual variances (that is, sa2 + sb2), and
so will decrease overall biomass variance in the plant community”
Diversity-Stability Relationship
Mechanisms that could generate a positive relationship between species
diversity & ecosystem-level stability…
McCann (2000) –
Insurance effect – “An ecosystem’s ability to buffer perturbations, loss in
species and species invasions is dependent on the redundancy of the
species having important stabilizing roles, as well as on the ability of the
species in the community to respond differently to perturbations. Increasing
diversity increases the odds that such species exist in an ecosystem. This
idea has been extended to suggest that the greater the variance of species’
responses in a community then the lower the species richness required to
buffer an ecosystem.
…increasing diversity increases the odds that at least some species will
respond differentially to variable conditions and perturbations…
greater diversity increases the odds that an ecosystem has functional
redundancy by containing species that are capable of functionally replacing
important species… taken together, these two notions have been called the
insurance hypothesis”
Diversity-Stability Relationship
Mechanisms that could generate a positive relationship between species
diversity & ecosystem-level stability…
McCann (2000) –
Weak-interaction effect – “Weak interactions serve to limit energy flow in a
potentially strong consumer-resource interaction and, therefore, to inhibit
runaway consumption that destabilizes the dynamics of food webs. In
addition, the weak interactions serve to generate negative covariances
between resources that enable a stabilizing effect at the population &
community level. The negative covariances ensure that consumers have
weak consumptive influences on a resource when the resource is at low
densities.”