Download Dispersal limitation

Theories so far….
Recruitment into communities is a lottery – which ever species has
recruits at the time that a territory becomes available will ‘win’
Storage effect (Daphnia and desert plants) – requires two
conditions: ___________ and _________________ Intermediate Disturbance Hypothesis – where diversity is
highest when disturbance-favored species (ruderals, pioneers etc)
coexist with ________. Can’t explain forest diversity because….
Recruitment limitation: species don’t compete because of two
processes – __________ and ___________
Degree of dispersal limitation can vary in communities because of
a ______ - _______ trade-off Pure dispersal assembly of communities
If propagules don’t arrive, organisms can’t compete. “Winner” of a
site or territory is the best competitor among those species that
were able to provide propagules. Hurtt and Pacala (1995) Simulation: rank species according to
competitive ability but give all species equivalent and restricted
dispersal ability.
Limited dispersal slows population and community dynamics in
species rich communities. As richness increases, individual species become rarer and more
dispersal limited. If a species becomes super-abundant then it can
escape dispersal limitation
Barro Colorado Island 50 ha plot – best dataset for evaluating
dispersal limitation in tree communities - 20+ years of data. Long-term seed trapping studies can be used to see how
frequently seeds arrive at potential recruitment sites
BCI 50 ha plot
Two hundred 1 m2 seed traps arrayed along trails over
50 ha. Traps emptied every week…for last 20 years.
Hubbell et al. (1999)
Analysis of seed trap captures over 10 years
260 plant species identified based on seed characters
1.3 million seeds collected
over 10 years!
On average, 31 species were
recorded in a single trap
over 10 YEARS
A small number of
wind-dispersed species
reach nearly all traps.
No captures
HALF of the species
had seeds dispersed to 6
traps or fewer
40 species no captures
at all
Conclude: most individual trees will disperse seeds to only a
handful of potential recruitment sites during their reproductive
lifetimes
Decomposing seed limitation
Seed limitation arises because of: insufficient seed production,
or inadequate seed distribution.
Seed limitation: Proportion of sites not receiving seeds of a
given species
Can be broken down into:
Source limitation: Proportion of sites not receiving seeds when
seeds are randomly distributed among sites
Dispersal limitation (strict definition): is defined as 1 –
(proportion of sites receiving seeds)/(proportion of sites that
would receive seeds if seeds were randomly distributed). Degree
to which aggregated dispersal further contributes to limitation
beyond source limitation.
How dispersal limited are pioneer trees in the forest?
Example of 2 pioneer species from Panama growing in the
Barro Colorado Island Forest.
Jacaranda copaia (Bignoniaceae)
Canopy tree
Wind dispersed
Seed mass 4.7 mg
Reprod. DBH =
20 cm
n=193 adult trees
in 50 hectares
Croton billbergianus (Euphorbiaceae)
Sub-canopy tree
Seeds explosively
dispersed
Seed mass 24 mg
Repro. DBH =
3 cm
n=367
reproductive
trees in 50 ha
Can we model seed dispersal at the landscape
scale?
Sort of… Traditional approach - measure seed patterns around isolated trees
and scale up to the forest.
- Need lots of isolated trees to describe the relationship between
tree size and reproductive output, as well as inter-annual variation
in seed output
- Additional problem that isolated trees may differ from the overall
population in the activity of pollinators, seed predators, or
dispersers.
Can we model seed dispersal at the landscape scale?
Start with a known pattern of seed rain (e.g. seed captures in
traps), a map of the location of the traps, and a map of trees (and
their sizes) that could have contributed seeds to those traps…
Use maximum-likelihood analysis to locate parameter values
for dispersal functions that best fit observed see rain data
Start by assuming some relationship between tree size and seed
production, and some relationship between distance from tree
and probability of dispersal and then calculate expected
captures of seeds to each of the traps... This approach is called
‘inverse-modeling’.
Jacaranda
Pearson r = 0.73
Median dispersal 7m
Croton
Pearson r = 0.87
Median dispersal 1 m
Problems with inverse-modelling approach
Assumes a distribution of dispersal probabilities as function of
distance from source Cebus mean seed dispersal distance >200 m
25 % of dispersal events were outside the 50 ha plot
Wehncke et al. (2003)
Jones et al. (2005) Genetic evaluation of dispersal of Jacaranda
Microsatellite genotypes of maternal tissue to identify seed sources
Grey bars are minimum dispersal
distances for trees with no parent
assigned to them
Experimental tests of the importance of seed limitation
Turnbull et al (2000) reviewed results of seed sowing
experiments. Seed limitation: Failure to regenerate because inadequate supply
of seeds reached favorable recruitment sites
- Found that about half of them showed evidence for seed
limitation.
- More evidence for seed limitation in early successional
habitats, and for early successional species.
Two hypothetical results of a
seed addition experiment for 3
spp at low (L), medium (M)
and high (H) sowing densities
What would you conclude
about the way spp interact if
result (a) arose?
If result (b) arose?
Interacting effects of dispersal and
competition
Outcome of competition among species may depend on
whether a competitive hierarchy is transitive or not.
transitive
a
b
c
non-transitive
a
b
c
Recognize this game??
Non-transitive
competition in
bacteria
3 bacterial types:
Colicinogenic bacteria (C) produce colicin (toxin) and
producing this toxin is costly
Resistant bacteria (R) avoid the competitive cost of carrying
‘col’ plasmid but suffer because colicin receptor is
involved in nutrient metabolism Colicin-sensitive (S) bacteria are killed by colicin
Dispersal and non-transitive
Competition
(Kerr et al. 2002)
Strains grown in three environments: (1) flask (well-mixed environment where dispersal and
interaction not local)
(2) static plate (environment in which dispersal and
interaction are primarily local; and (3) mixed plate (intermediate environment).
What would you predict the outcome will be?
S
R
=
S
wins
R
C
=
R
wins
C
S
=
C
wins
Competition
Coexistence occurs when local
structure is maintained (Fig.
2a)
With no spatial structure (in flask
or mixed plate), R strain wins
(Fig. 2b-2c)
Results show local interaction
and dispersal in this nonhierarchical competitive
interactions promoted species
coexistence (rem: tree
neighborhoods?)
Kerr et al. 2002
Equilibrium models of species coexistence
Evidence for equilibrium forces structuring communities If community composition is dictated by niche assembly then not
a lottery… And predict??
What evidence is there for community stability?
- Several examples with insect communities in which species have
annual life cycles:
e.g., Lawton and Gaston (1989) constant composition of ~20 spp of
insects living on plots of bracken fern over 7 years and at 2 sites
(woodland and open).
Several other examples of long term stability in community
composition: eg Ocean plankton, (McGowan and Walker 1979)
Odonates in lakes (Crowley and Johnson 1992), Rothamstead
Park grassland experiment (Silvertown 1987)
Fewer examples of predictable responses to disturbance…
Terborgh (1996) Substitute space for
time by examining chronosequences.
What evidence that successional
sequences culminate in mature phase
forests with similar species
composition and similar species
abundance patterns?
Terborgh looked at primary successional sequences on riverbends in the Manu river in SE Peru.
Meanders in the river generate
replicated ‘point bars’ – become
mature forest over ~300 yrs
Individual bars are largely isolated from one-another by a matrix
of upland forest
Looked at composition in plots in floodplain forest at 3 sites <1
km from each other and two sites 30 and 40 km away
Point bars along the Manu river, Peru
Rank abundance for most common spp (out of 386) present in 1000 tree samples on five mature forest floodplains
Species
PLOT 1
PLOT 2
PLOT 3
Otoba
Astrocaryum
Iriartea
Quararibea
Scheelia
Theobroma
Guarea
Lonchocarpus
Pouteria
Oxandra
Malmea
Pseudolmedia
Calatola
Ruizodendron
Poulsenia
Unonopsis
Sorocea
Sapium
Trichilia
1
2
9
3
7
4
8
14
11
6
10
12
5
18
19
17
29
23
25
4
2
6
1
3
12
20
5
8
11
48
24
20
13
16
10
9
15
25
1
2
5
3
7
6
4
23
10
37
8
11
48
21
20
200
58
24
15
FAR
PLOT 1
3
2
1
4
5
6
13
14
15
12
43
17
11
24
9
40
FAR
PLOT 2
3
2
1
4
6
5
7
119
139
56
75
11
95
13
16
62
17
22
Longer-term evidence for constancy in community composition
comes from studies of coral reefs (Pandolfi 1996)
Looked at coral composition of
reef communities at 3 sites in Papua
New Guinea over a 95,000 yr period
during which sea level fluctuated up
to 120 m and sea temp 6oC. This resulted in 9 cycles of perturbation and reef re-assembly.
For each site found no significant difference in taxonomic composition
of the reefs over time even though during any one reef-building
episode only about 25% of spp present in the available species pool
actually occupied a particular reef environment.
Found that variation in space greater than in time...
- Variation in coral reef assemblages among sites at any rebuilding
episode > that at any one site among the 9 rebuilding episodes
Evidence from these coral reefs suggests that some marine
communities exhibit consistent patterns of assembly - more so than
comparable terrestrial systems from the quaternary period
Why? Summary:
Many theories for the maintenance of diversity explore
mechanisms that can prevent species exclusion through
limiting similarity.
Classical niche differentiation may not be necessary.
Species coexistence can be mediated by repeated disturbance
(IDH), temporal fluctuations in recruitment success (Lottery
model and storage effect), competition-colonization trade-offs
or simply by steady-state dispersal limitation.
Models need not stop competitive exclusion, just slow it down
sufficiently such that species loss is balanced by species
replacement