Ecological succession

Henry A. Gleason 1882-1975

Frederic E. Clements 1874-

1945

Patterns in time

Plant succession is the directional

development of the vegetation of a given

homogeneous area over a period of time

towards a single climax structure (Clements 1916)

Plant succession is the historically influenced random process leading to different stable states despite identical environmental conditions (Gleason 1927)

The Human impact on the biosphere

Primary Successional stagesBare soil of rocks

Soils crusts, Cyanobacteria, Lichen, Mosses

Annual and biannual plants

Shrubs, treesPioneer species

Climax community

Succession is not a deterministic process.The successional sequence might end in

different final stable states

In many temperature successioal series forests form the climax community

Succesion of freshwater bodies

Soil crusts

Soil mosses and lichenCrusts are well adapted to severe growing

conditions, drought and water loss.

Cyanobacteria

Crusts generally cover all soil spaces not occupied by vascular plants, and may be

70% or more of the living cover

Soil crusts stabilize soils and increase water retention.

Cyanobacteria, mosses, lichen

Secondary succession

Secondary succession is the change in faunal or floral composition after severe disturbance

Major disturbances areFireStormFloodingLava flows

Secondary succession starts mainly from seed banks.

Colonization is often of minor importance.

Seeds remain healthy for some months to more than 1000 years.

In cyclic succession (frequent fires) seed banks allow for fast recover.

Generation time

Reproductive effort

Flight ability

Morphological diversity

Niche breadth

Diversity

Plants, herbivorous insects

Plants, aphids

Plants, birds, some insects

Herbivorous insects

Bees, wasps

Plants, insects

Adaptive strategies

Young field Midfield Woodlands

Successional stage

Modified from Brown, Southwood 1987

Different successional stages filter for different life history strategies (habitat filtering)

K Permanent habitats A

r Temporary or ephemeral habitats

Habitat favourableness

Stress, Adversity

Sta

bilit

y of

hab

itat

Dis

turb

ance

Pop

ulat

ion

fluct

uatio

ns

Mag

nitu

de o

f r

Life

span

Impact of biotic interactions

Impact of density

dependence

The r – K – A triangle

Habitat templates (Southwood and Greenslade)

Time

Abun

danc

eAnnuals and biannuals

ShrubsTrees

Time

Spec

ies r

ichn

ess

Annuals and biannuals

ShrubsTrees

Time

Biom

ass

Community patterns during succession

Species richness, total abundance, and total biomass generally peak at intermediate stages of succession.

Brown, Southwood 1987

Succession of beta diversity

Intermediate disturbance

Number of niches

Extinction

Immigration

Competitiion

New Zealand stream invertebrates (Townsend 1997)

SpeciesP.

melanarius

P. ob-longo-punc-tatus

P. niger O. ob-scurus

H. 4-punc-tatus

C. granu-latus

D0 D1 D2 EV1

Pterostichus melanarius 0.049 0.336 0.280 0.315 0.166 0.098 12.00 4.63 4.98 0.940Pterostichus oblongopunctatus 0.093 0.068 0.052 0.016 0.268 0.280 5.00 2.23 3.74 0.700Pterostichus niger 0.105 0.186 0.158 0.001 0.207 0.072 3.00 2.95 2.92 0.597Oxypselaphus obscurus 0.272 0.107 0.186 0.261 0.034 0.087 4.00 5.53 4.12 0.751Harpalus 4-punctatus 0.288 0.277 0.031 0.091 0.232 0.238 1.00 5.77 5.05 1.000Carabus granulatus 0.192 0.026 0.292 0.316 0.092 0.226 1.00 4.89 5.19 0.908

Sum 1.000 1.000 1.000 1.000 1.000 1.000

The Markov chain approach to succession

Henry S. Horn 1941-

𝑁𝑡+ 1=𝑃 𝑁𝑡

Abundances

Stable state (eigen)vector

Column stochastic transition probability matrix

Positive interactions

Habitat amelioration

Joint defences

Increasing physical stress

Increasing consumer pressure

Freq

uenc

y of

pos

itive

in

tera

ction

Freq

uenc

y of

co

mpe

titive

inte

racti

ons

Bertness, Leonhard, Ecology 78: 1976-1989

The stress gradient hypothesis predicts increased proportions of positive (mutualistic) interactions in plant communities at intermediate levels of stress and herbivore pressure.

Linked patterns in time

-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Oulu-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Vaasa

-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Häme-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Turku-Pori

-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Central Finland

-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Uusimaa

-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Lapland-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Kuopio-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

North Karelia

-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Mikkeli

-3

-2

-1

0

1

2

3

1964 1968 1972 1976 1980

Kymi

Population dynamics (1964 to 1983) of the red squirrel in 11 provinces of Finland (Ranta et al. 1997)

Patrick A.P. Moran (1917-1988)

The Moran effect

Regional sychronization of local abundances due

to correlated environmental effects

0100000200000300000400000500000600000700000

Acre

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olia

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Maine

3000000

020000400006000080000

100000120000140000

Acre

s Def

olia

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Vermont

2500000

0

500000

1000000

1500000

2000000

Acre

s Def

olia

ted

New Hampshire

0

500000

1000000

1500000

2000000

2500000

Acre

s Def

olia

ted

Massachusetts

Year20 30 40 50 60 70 80 90

Defoliation by gypsy moths in New England states

Lymantria dispar

Data from Williams and Liebhold (1995)

Gradation:The massive

increase in density

GenerationSpecies1.00 0.71 1.25 1.27 6.36 12.50 14.52 50.84 49.072.00 0.93 1.10 3.43 0.55 14.30 15.06 31.47 27.853.00 0.09 0.83 2.08 2.45 12.34 15.45 26.01 61.754.00 0.97 0.06 0.35 3.51 13.08 27.56 5.57 44.995.00 0.14 0.60 0.56 4.33 13.47 9.86 28.64 30.706.00 0.33 1.44 3.22 4.89 15.39 27.84 34.93 39.657.00 0.63 0.41 0.94 0.87 14.89 2.87 49.46 61.228.00 0.96 0.06 2.31 6.81 12.76 28.50 48.08 60.169.00 0.20 1.48 0.90 3.43 8.08 25.14 60.29 51.97

10.00 0.30 1.49 2.80 4.60 15.75 1.52 46.60 24.2611.00 0.96 0.36 2.49 1.40 7.67 25.94 51.83 48.5712.00 0.38 0.19 3.52 5.56 1.64 28.19 24.89 4.7813.00 0.09 1.52 2.39 7.02 9.82 5.54 18.72 12.0614.00 0.88 1.10 0.43 1.23 6.92 24.29 55.69 34.6615.00 0.16 1.30 3.69 1.43 4.06 1.99 1.03 10.1516.00 0.45 1.76 2.24 4.43 8.46 17.37 7.02 36.2517.00 0.20 1.27 0.11 6.41 9.32 6.64 12.77 1.6318.00 0.83 1.60 0.12 0.04 9.55 17.38 19.19 22.0819.00 0.97 0.99 0.59 4.49 14.33 6.77 46.32 47.9120.00 0.36 0.59 1.29 0.32 0.40 4.29 46.40 7.69

Mean 0.53 0.97 1.74 3.51 10.24 15.34 33.29 33.87Variance 0.12 0.30 1.48 5.40 20.10 98.09 334.99 380.96

Taylor’s power law

Assume an assemblage of species, which have different mean abundances and fluctuate at random but proportional to their abundance.

The relationship between variance and mean follows a power function of the form

2 2a

Going Excel

Taylor’s power law; proportional rescaling

0.00

1.00

2.00

3.00

4.00

0.00 5.00 10.00 15.00 20.00Generation

Abu

ndan

ce

z

y = 0.34x2.0

R2 = 0.99

0

500

1000

1500

0 20 40 60 80Mean

Var

ianc

e z

0.00

1.00

2.00

3.00

4.00

0.00 5.00 10.00 15.00 20.00Generation

Abu

ndan

ce

z

0.001.002.003.004.005.006.00

0.00 5.00 10.00 15.00 20.00Generation

Abu

ndan

ce

z

0.001.002.003.004.005.006.007.00

0.00 5.00 10.00 15.00 20.00Generation

Abu

ndan

ce

z

2 1a

2 2a

2 0a

Ecological implications

2 za

Temporal variability is a random walk in time

Abundances are not regulated

Extinctions are frequent

Temporal species turnover is high

Temporal variability is intermediate

Abundances are or are not regulated

Extinctions are less frequent

Temporal species turnover is low

Temporal variability is low

Abundances are often regulated

Extinctions are rare

Temporal species turnover is very low

Niche conservatism refers to the tendency of closely related species to have similar niche requirements. The requirements translate into similar ecological, morphological or

behavioural traits mediated by genomic similarities.

Evolutionary time scales

Spiders Birds

100%

0%

50%

Moisture toleranceShading tolerance

Moisture preference

Shading preference

Female body length

Male body length

European range sizeHabitat toleranceGerman range size

Abundance

Migratory behaviourColours

Dietary range

Sex dimorphismBody size

Entling et al. 2007, Gl. Ecol. Biogeogr. 16: 440-448

How much variance in important niche dimensions of European plants is

explained by taxonomc relatedness?

Prinzing et al. 2001. Proc. R. Soc. B 268: 1.

Taxon species richness and local abundances

The case of Hymenoptera

0

1

2

3

4

5

1 10 100 1000 10000Number of species

Mea

n de

nsity

per

spec

ies

Continental taxon species richness of Hymenoptera is correlated to mean local

abundances

0

0.2

0.4

0.6

0.8

1

1 10 100 1000 10000

Number of species

Frac

tion

of

singl

eton

s0

0.2

0.4

0.6

0.8

1

1 10 100 1000 10000

Number of species

Frac

tion

of

abun

dant

spec

ies

Species rich hymenopteran taxa contain more locally rare and fewer locally

abundant species

Numbers of families and species scale allometrically to floral species richness

y = 1.78x0.77R2 = 0.94

010

2030

40

5060

0 20 40 60 80Number of species in a flora

Num

ber o

f gen

era

y = 1.9x0.61R2 = 0.70

05

101520253035

0 20 40 60 80Number of species in a flora

Num

ber o

f fam

ilies

• Species richer sites contain relatively less higher taxa.

• Species richer sites have higher species per genus (S/G) ratios

• Species richer sites contain higher proportions of ecologically similar species(environmental filtering)

Enquist et al. 2002. Nature 419: 610-613

Darwin’s competition hypothesis:Closely related species should be ecologically more similar and under higher selection pressure than more distantly related species

Zaplata et al. 2013

Local colonizers

Regional pool of species

Environmental filters

Random colonizationRegional pool of potential colonizers

Regional pool of species

No phylogenetic structure

No phylogenetic structure

Phylogenetic clumping

Early succession

Facilitation

Phylogenetic segregation

Local community structure

Competition

No phylogenetic structure

Phylogenetic clumping

Later succession

Positive interactions

Phylogenetic segregation

Neutral interactions