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Priority effects. What are the consequences of phenological patterns for interspecific interactions ? Harper (1961) planted two species of grass: Bromus rigidus and B . madritensis either simultaneously or with B. rigidus sown 3 weeks after B. madritensis

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Priority effects

What are the consequences of phenological patterns for interspecific interactions?

Harper (1961) planted two species of grass: Bromusrigidus and B. madritensis either simultaneously or with B. rigidus sown 3 weeks after B. madritensis

Grown together: B.rigidus accounted for 75 % of biomass

Sown later: B.rigidus accounted for 10 % of biomass

What might determine a priority effect like this??

Benke (1978) Priority effects on dragonflies

- Different dragonfly species have predictable seasons of emergence from larvae to adults

• “early species” - emerge synchronously in early spring and complete breeding by mid summer

• “late species” - emerge non-synchronously mid summer. These spp oviposit when hatchlings of the early spp are already swimming around the pond…

Set up screened pens in ponds to control when female dragonflies can oviposit.

Showed that early species significantly depress the abundance of late species relative to experimental cages where early spp excluded.

Treatment effects on abundance of ‘late’ species


- early



Number “late spp”per m2

+ early












L = abundance of early species reduced

E = abundance of late species reduced

EL = open to early and late species

NO = No dragonflies (some did get in!)

Priority effects that aren’t tied to phenology

Schulman (1983) looked at recruitment of marine reef fish from the larval stage on newly created artificial reefs composed of concrete building blocks

- Recruitment of fish was inhibited by prior occupation by two species of beaugregory (territorial damselfish) and juvenile snapper

- New territories on the reef open at random. Species that have more settling larvae available when the territory opens up will have a higher probability of filling it.

Other examples??

Remember Drosophila competing for fruits?

Very similar study of Drosophila on mushrooms (Shorrocks 1994)

Probably many similar examples of competition-colonization

trade-offs are relevant here:

Many examples in succession:

Early successional species are poor competitiors but arrive first at open habitats because of superior dispersal

Many examples of priority effects in forest succession that we will look at in coming weeks

Priority effects are an example of an ‘Assembly Rule’

Jared Diamond (1975) first explored the idea that there are rules that govern how communities are assembled.

Diamond’s work based on an accumulation of observational data on the distribution of bird species on Bismark islands around New Guinea

Interested to know if certain sets of spp that could be drawn at random from a species pool fail to coexist at some local level

Bismarck Archipelago

Islands N and E of

Papua New Guinea

Diamond’s approach to examining coexistence:

Describes incidence functions: the probability that a particular specieswill occur in a particular community given some attribute of the community

Predictive attribute of the community in this case = species richness

Diamond was clearly influenced by MacArthur and his warblers…

- species fit together in a complementary way in communities dictated by the strength of interspecific competition

Species called High-S require more specialized features of communities that support a variety of other species. ‘Tramp’ species occur islands including those with low sp richness

“Tramp sp”

“High-S sp”



Probability of occurrence

:Tramp sp”


(flower pecker)


Species richness

Diamond’s explanation for these patterns:

Species use/consume resources (eg food, nesting sites) out of the total resource pool available on the island. Resource pool determined mostly by island size?

To determine if species can coexist:

Subtract individual spp. resource use from resource pool to see what resources remain. Then determine if additional species would be able to survive on those resources

Matching resource use and production allows predictions to be made of “allowed” and “forbidden” species combinations

4 spp guild with different resource requirements. Solid line represents resource production. Dashed line resource use by each species

Small island - only sp # 3 exists

Larger island spp 2 and 4 but not 2,3,4 can coexist

Larger island, sp # 1 could invade island occupied by spp 2 and 4

Diamond codified the patterns he observed into a set of

“Assembly rules”

1. Considering all combinations that could be found for a group of related spp. only certain ones exist in nature

2. Those permissible combinations resist invaders that would transform them to forbidden combinations

5. “Checkerboard rule” - some pairs of species never coexist either by themselves or as part of a larger combination

How would you test if these assembly rules actually operate??

Various tests of Diamond’s rules using null models

• Connor and Simberloff (1979) and other papers - looked

at whether fewer species combinations occurred in nature than

expected at random. Could not reject the null model

• Gotelli and McCabe (2002) - more complete analysis of particular assembly rules - first test of the checkerboard assembly rule

-Assembled data from 96 studies of species occurrences from scales of 1-1010 m2 used Monte Carlo randomizations to examine

whether there are species co-occurrences that are less likely than expected at random

-Found general SUPPORT for assembly rules


Evaluating the null model does NOT test whether competition is responsible for patterns of species occurrence

Null models are statistical tools for recognized non-random patterns, not a ‘litmus test’ for competitive effects

What other factor might result in less-than-random patterns of species co-occurrence??

Where have we seen good evidence for interspecific competition before??

M’Closkey (1978) looked for the existence of assembly rules in communities of seed eating rodents in Sonoran Desert.
  • - Collected detailed natural history on habitat niche and feeding niche of four rodent spp. Quantified differences in habitat characteristics (shrub density) and sizes of seeds consumed by each species and combined this information into a measure of niche overlap
  • Found that observed pairs and triplets of coexisting rodent species were those that had both the smallest niche separation and the maximum resource utilization for a habitat
  • cf predictions of Diamond - but resources strongly limiting in Deserts
‘M’, ‘P’, ‘A’, and ‘B’ are rodent species. Only spp combos with

Low Niche separation found. Values in brackets=occurrences

Fox (1987) expanded on M’Closkey’s idea:

If competition determines which species can enter a developing community, then the outcome of community assembly should be predictable according to the functional groups each species belongs to.

- Don’t need to know all M’Closkey’s details about what each sp eats exactly etc… just need to know how to assign it to a group (based on taxonomy or ecology)… itself not exactly easy…

Fox’s assembly rule: “there is a much higher probability that each species entering a [local] community will be drawn from a different functional group until each group is represented before the cycle repeats”

Rule is based primarily on competition for food: if some functional group becomes disproportionately represented in a local community then competition will lower the probability that the next spp will belong to that group

Fox called a community a ‘favoured state’ whenever all pairs of functional groups have the same number of species in them, or differ by only 1 sp.

Imagine a hypothetical site and 3 functional groups.

Favoured states include (2,2,2), (2,3,2) and (1,1,0).

‘Unfavoured’ states include (2,1,4) and (1,0,2)

If Fox’s rule operates then should find more favoured states than the random expectation. Provides a null hypothesis that species enter a community independently of their functional group.

Two data sets:

Nevada Test Site - 115 rodent communities. 92 found to be in favoured states. Random-draw simulations mean expected number = 62.5. Probability of finding the observed number <0.001

Arid Southwest - 202 rodent communities. 128 in favoured states. Random expectation: 111.3 Probablity of finding observed number <0.01

Evidence therefore for deterministic processes??

Maybe not...

Simberloff et al (1999) criticised the data :-

Nevada Test Site was in fact used to detonate a series of nuclear explosions 4 yr before the study… disturbance might be important??

- Criticized the randomization procedure - e.g. doesn’t take into account the frequency of occurrence of each species or its range distribution. Reanalysis of Fox’s data with different assumptions in the null model failed to find unexpectedly high numbers of favored states (Stone et al. 1996)

- Criticized functional group assignments. Stone et al. randomized species assignment to functional group. Randomized species did not generate any more favored states than did the biologically based assignment.

Application of assembly rules to restoration/invasion ecology

1) Are the component species of a community mutually selected from a larger species pool so as to ‘fit’ one another?

2) Does the resulting community resist invasion - if so why?

3) Do invasive species alter/dissassemble communities (eg affect competitive interactions between remaining species?

4) To what extent is the final community specified by the physical environment as opposed to chance colonization?

e.g. test how species arrival sequence in successional communities influences species composition.

Seems to be little formal design and analysis of restoration projects in the context of ecological rules

-Goals for land managers (pattern, outcome, specifics) and ecologists (process, mechanism, generality) are different?

-Need to focus more on traits rather than on species: How are traits associated with environmental conditions (e.g. defensive characteristics of plants, structural characteristics, response to disturbance).

  • Assembly rules idea not broadly accepted among ecologists except in a broad sense. Reflects move away from focusing on species interactions in determining community composition
  • e.g. “dispersal assembly” vs. “niche assembly”
  • Very difficult to test for assembly rules based on spp presence-absence patterns (too many explanatory variables that need to be ruled out)
  • Even if patterns are consistent with competitive effects (Diamond’s rules), other factors may also explain the pattern (range distributions, physiological tolerances etc)