Ecological communities
Guild
Community
Assembly
A community is a local assembly of
species that potentially interact.
Generally these species are on the same
trophic level.
A community of species with similar niches
is called an ecological guild
Counter examples
Examples of ecological communities
Insect eating birds in a forest.
Fish in a pond.
Butterflies on a meadow.
Birds in a forest form an assembly
Aphids and Ladybeetles are on different
trophic levels.
Fish in an archipelago form metacommunities.
Examples of communities
Plant visitors and pollinators
Nepenthes pitcher plants
Deep sea
bacterial
communities
Calcareous
grassland
Assemblages but not communities
Mutual effects of species interections:
Direct effects refer to the impact of the presence (or change in abundance) of species A on
species B in a two-species interaction.
Indirect effects refer to the impact of the presence (or change in abundance) of species A
on species C via an intermediary species (A --> B --> C).
Cascading effects are those which extend across three or more trophic levels, and can be
top-down (predator --> herbivore --> plant) or (plant --> herbivore --> predator).
Keystone species are those which produce strong indirect effects.
Kelp (brown
algae) forest
The starfish Pisaster
predates on Mytilus mussels
and makes space for many
other species to colonise.
The top predator Pistaster is
a keystone species.
_
_
_
+
Fisherig
Sea otter
(Enhydra)
Sea urchin
(Echinus)
_
Abiotic and
isolation filters at
different spatial
scales determine
local species
composition
Global
species pool
Isolation filter
Abiotic
filters
Abiotic
filters
Local species
pools
Community
Regional
species pools
Members of single
communities pass
these filters.
Abiotic filters
The distribution of species abundances
Rank – abundance plot
Relative abundances in a sequence of plant succession (Bazzaz 1975)
In natural comunities species abundances often differ by factors of more than 1000.
That means that the most abundant species are 1000 times more abundant than the
rare species
Three types of relative abundance distributions (SAD)
Log-series SAD
Heavy tail
𝑁 = 𝑁0 𝑖 −𝑎
Log abundance
Log abundance
Power function SAD
𝑋𝑛
𝑃(𝑁) = 𝛼
𝑛
Ronald A. Fisher
(1890-1962)
P(N) is the probabiity that
a species has exctly N
individuals
Species rank order i
Species rank order i
Robert May of Oxford
(1938-)
Log abundance
Log-normal SAD
𝑁 = 𝑒 −𝑎×𝑛𝑜𝑟𝑚(0,1)
Species rank order i
Frank W. Preston
(1896-1989)
Log abundance
Power function SAD
Parasitic Hymenoptera in a beech forest
Heavy tail
𝑁 = 𝑁0 𝑖 −𝑎
Species rank order i
Power function SADs
• have a high number of rare species (heavy
•
•
•
tail)
are input (colonization) driven
have a high degree of species turnover
often characterize species assemblages but not
true communities
have a small number of very abundant species
lack a larger number of intermediate abundant
species
Examples
• Incomplete samples
• Arthropod assemblages
• Disturbed habitats
Log abundance
Log-series SAD
Northern German Grassland spiders (Finch 2001)
𝑋𝑛
𝑃(𝑁) = 𝛼
𝑛
Species rank order i
The log series is a sample distribution. It
describes the expected abundance of
species in a sample from a large
community. It applies to assemblages.
For fully censused assemblages it occurs
most often
• at early stages of succession
• in disturbed habitats
• in heterogeneous assemblages
Examples
• Incomplete samples
• Heterogeneous assemblages
• Large arthropod samples
Beetles in a Norwegian spruce forest (Ottesen 1996)
Log abundance
Log-normal SAD
High number of species
with intermediate
abundance
𝑁 = 𝑒 −𝑎×𝑛𝑜𝑟𝑚(0,1)
Species rank order i
Breeding birds of Ohio (Hicks 1935)
𝑆 = 𝑆0 𝑒 −𝑎𝑅
veil line
2
Lognormal SADs are derived from the central limit
theorem of statistics that predict normal
distributions
Lognormal distributions occur most often in
• closed and stable communities
• undisturbed habitats
• K- species dominated communities
• Communities influenced by a large number
of divergent environmental factors.
Often the distribution is not symmetrical having
an excess of rare species.
Diversity and evennness
A measure of diversity is the number of species
Abundance
High evenness
Simpson index of
diversity
𝐻=
1
𝑆
1 𝑝𝑖
Shannon index of
diversity
𝑆
𝐻=−
𝑝𝑖 ln(𝑝𝑖 )
1
Log-series index of diversity
Species
Abundance
Lower evenness
𝑁
𝑆 = 𝐻𝑙𝑛(1 + )
𝐻
Diversity indices are measures of encounter probability
Evenness
𝐻
𝐸=
𝑙𝑛𝑆
Species
Alpha, beta and gamma diversity
Species richness
Alpha diversity refers to the local number of species
Beta diversity refers to the change in species composition among local habitats
Gamma diversity refers to the regional species pool
g
b
a
𝑦 = 𝛼𝐴𝛽
Multiplicative partitioning
of diversity
𝛾 =𝛼×𝛽
Additive partitioning of
diversity
𝛾 =𝛼+𝛽
Area
Beta diversity is a measure of regional habitat diversity
Species interactions or neutrality
Pool of
individuals
Stephen P.
Hubbell (1942-
Birth
Death
Neutral models are
individual based!
Random
migration
Ecological drift
Zero sum multinomial
Motoo Kimura
(1924-1994)
Mutations
Individuals are grouped
to evolutionary lineages
Species are ecologically
equivalent
Ji  J 0  iJ 0  bJ 0  eJ 0  dJ 0  J 0
J is the total number of
individuals
Neutral models lack any specific biological interaction like
competition, mutualism, regulation, species specific survival.
Neutral models provide ecological expectations without species interaction
Neutral models make explicit predictions about
Abundance rank order relationships
Diversity and evenness
Abundance
10000
Core species
1000
100
10
1
Leistus rufomarginatus
0
Photos by Roy Anderson
5
10
15
20
25
30
Rank order
100
Abundance
Satellite species
10
1
0.1
Ground beetles on lake islands in Lake Mamry
(Ulrich and Zalewski 2007)
0
5
10
15
20
Rank order
25
30
Neutral models make explicit predictions about
Core and satellite species
35
30
Predicted
Species
25
20
Observed
15
10
5
0
1
2
4
Sites occupied
Dyschirius globosus
Ground beetles on lake
islands in Lake Mamry
(Ulrich and Zalewski
2007)
Regional diversity patterns
Observed
Predicted
8
15
Ecological gradients and the classification of communities
Species
1pog 2pog 3pog dab
Pterostichus melanarius
0
36
13
17
Pterostichus oblongopunctatus 0
2
7
135
Pterostichus niger
0
0
3
0
Oxypselaphus obscurus
1
0
27
96
Harpalus 4-punctatus
0
41
17
9
Carabus granulatus
0
11
52
11
Patrobus atrorufus
0
6
22
81
Pterostichus antracinus
11
1
0
0
Platynusas similis
0
7
25
4
Pterostichus nigrita
30
2
2
5
Carabus hortensis
0
0
0
0
Pterostichus strennus
0
5
3
47
Distance matrix
ful
187
83
191
27
29
12
11
0
48
1
75
13
gil
345
188
167
166
77
110
348
21
39
58
52
30
guc
60
11
135
80
0
25
9
1
2
1
109
5
hel kor
lip
169 1199 704
8 1019 180
0
137
0
0
96
7
67 555 69
11 154 113
0
11
37
11
2
2
9
76 117
0
0
2
0
0
0
6
28
24
mil
394
4
0
48
0
0
0
274
0
39
0
22
sos
428
141
530
278
9
59
35
0
9
18
0
14
swi
13
1
3
0
0
1
2
0
0
0
0
4
Ground beetles
from Mazuran
lake lands
The first two eigenvectors
Species
Pterostichusoblongopunctatus(Fabricius)
Pterostichusmelanarius
Pterostichusniger(Schaller)
Oxypselaphusobscurus(Herbst)
Harpalus4-punctatusDejean
Carabusgranulatus
Patrobusatrorufus(Stroem)
Pterostichusantracinus
Platynusassimilis(Paykull)
Pterostichusnigrita(Paykull)
CarabushortensisLinnaeus
Pterostichusstrennus(Panzer)
Pterostichusmelanarius
0 787.7 1363 1393 1122 1359 1494 1515 1442 1541 1550 1518
Pterostichusoblongopunctatus(Fabricius)
787.7 0 1004 955.5 530.5 887.8 1040 1101 975.5 1062 1066 1030
Pterostichusniger(Schaller)
1363 1004 0 327.5 714.1 533.9 591.8 671 586.5 591 571.9 590.6
Oxypselaphusobscurus(Herbst)
1393 955.5 327.5 0 563.3 281.7 328.9 418.8 344.1 324.4 339 320.4
Harpalus4-punctatusDejean
1122 530.5 714.1 563.3 0 415.3 618.4 628.2 488 567.8 578 538
Carabusgranulatus
1359 887.8 533.9 281.7 415.3 0 299.4
354.5 127.5 215.1 239.6 192
Principal
Patrobusatrorufus(Stroem)
1494 1040 591.8 328.9 618.4 299.4 0 438.2 338 307.4 333.9 322.6
Pterostichusantracinus
1515 1101 671 418.8 628.2 354.5component
438.2 0 311.9 239.7 305.9 259.9
Platynusassimilis(Paykull)
1442 975.5 586.5 344.1 488 127.5 338 analysis
311.9 0 157.2 180.7 123
Pterostichusnigrita(Paykull)
1541 1062 591 324.4 567.8 215.1 307.4 239.7 157.2 0 141.3 72.41
CarabushortensisLinnaeus
1550 1066 571.9 339 578 239.6 333.9 305.9 180.7 141.3 0 139.6
Pterostichusstrennus(Panzer)
1518 1030 590.6 320.4 538 192 322.6 259.9 123 72.41 139.6 0
EV 1
0.648
0.368
-0.059
-0.179
0.036
-0.207
-0.202
-0.218
-0.240
-0.276
-0.264
-0.270
EV 2
0.496
0.361
0.298
0.240
0.262
0.218
0.262
0.267
0.228
0.237
0.244
0.232
Principal component analysis
PCA serves to identify ecological communities
Communities as ecological indicators
Ecological indicators are used to provide information about the state and the functioning of
ecological systems.
Indicators might be single species , sets of species or whole communities.
Often used indicators
Anthropogenic
disturbance
Acid rain
Eutrophication
Invasive species
Sedimentation
Logging
Heavy metals
Urbanization
Air pollution
Air quality
Indicator
Mosses
Aquatic macrophytes
Birds
Shrubs
Bark beetles
Protozoa
Birds, Carabids
Plants
Lichen