Trophic networks
Food web
Food chain
Parasites
Large
herbivores
Hyperparasitoids
Parasitoids
Large
carnivores
Large
omnivores
Larger
carnivores
Small
carnivores
Small
herbivores
Plant
producers
Parasites
Larger
decomposer
Medium
omnivores
Bacteriophages
Large
predators
Small
predators
Smaller
decomposer
Bacterial
producers
Typical terrestrial food with six trophic levels and 15 functional groups.
Each functional group (guild) may contain many species.
Herbivores
Plant
producers
Web size
The total number of elements S (species) in the web
Connectance
The proportion of realized links L in the web
Linkage density
𝐿
𝐿
≅ 2
𝑆(𝑆 − 1)/2 𝑆
𝐿
The proportion of realized connections per species 𝐷 = ≅ 𝐶𝑆
𝑆
𝐶=
Food chain length The average length of single food chains
Proportions of top, intermediate, and basal species.
The proportion of omnivores.
Omnivores are species that feed on more than one basic source of food (more than one
trophic level)
Loop,
Web size: 5
intraspecific
Links: 4
Predator
Predator
feeding
Connectance: 4/(5*4/2) = 0.4
Linkage density: 4/5 = 0.8
Food chain length: 2
Omnivores: 0
Herbivore
Herbivore
Basal species: 1
Intermdeiate species: 2
Top species: 2
Plant
Loops do not count
Pitcher plant food (Nepenthes albomarginata) web
Photo
Nepenthes
1
2
4
5
6
12
Loop,
Cannibalism
3
7
8
13
14
15
17
18
19
S = 19
Lmax = 19x18/2=171
L = 35
C = 35 / 171 = 0.2
Ch = 100
Li = 40
ChL = 100 / 40 = 2.5
L / S = 35 / 19 = 1.8
9
10
11
16
Trophical cascades
Energy
Abundance
Biomass
Large predators
2
2
Small predators
80
15
1
Herbivores
100
100
10
20
120
100
Plants
0.1
Trophical cascades vary from habitat to habitat.
They are habitat specific
In terrestrial habitats about 10% of energy is passed from each level to the next higher
level (rule of Lawton).
In marine food webs the biomass and abundance pyramids are sometime inverted.
The paradox of the plankton
Why is the world green?
With predators of herbivores
Venezuela
Terborgh et al.
2006, J. Ecol.
Without predators of herbivores
Comparing the defoliation by herbivores on small
(without predators), intermediate (some
arthopod predators ) and large islands/mainlands
(all types of predators) Terborgh et al. (2006)
corroborated the hypothesis of Hairston, Smith,
and Slobodkin (HSS) that herbivore predators
control defoliation and keep the world green.
Plant defense did not play a major role
Mortality
Recruitment
Predaceous birds and snakes
Parasitoid spider wasps
Songbirds
Predaceous
insects
Scorpions
Lizards
Spiders
Rodensts
Herbivorous
insects
Scavenging
insects
Detritovorous
insects
Seabird
ectoparasites
Fish and bird carcasses
Seabirds
Marince planctonic food web
Land plands, seed detritus
Seabird guano
Algal detritus
Polis 1998,
Nature395:
744-745
Marine macroalgae
An example how complex food webs might be. Each trophic level may contain several up to
several hundreds of species. Islands in the Gulf of California.
Terrestrial arthropod dominated food chains are often shorter than marine food chains
Schoenly et al. 1991,
Am. Nat 137: 597-638
Terrestrial food chains have
rarely more than five levels.
Torymus auratus
Platygaster spec.
Food chain involing insect
parasitoids have often more
than five levels.
galls
Mikiola fagi
Do terrestrial and marine food webs differ in structure ?
Schoenly et al. 1991,
Am. Nat 137: 597-638
Haven, 1997,
Oikos 78: 75-80
Terrestrial webs
Marine webs
Predator numbers increase linearly
with the number of asvailable prey
species
The total richness of predators is
often higher than the number of prey
species
Schoenly et al. 1991,
Am. Nat 137: 597-638
Numbers of food chain in a web increase
to the power of species richness.
The upper boundary marks the limit of
stability.
Parasitoid – aphid relationship on oaks
Lysiphlebus thelaxis
Thelaxes
dryophila
Quercus robur
Trioxys betulae
Callaphidius
elegans
Mamamelistes
betulinus
Betulaphis
brevipilosa
Protaphidius
wissmannii
Trioxys pallidus
Aphelinus chaonia
Symydobius
oblongus
Stomaphis
quercus
Myzocallis
castanicola
Tuberculoides
annulatus
Praon
flavinode
Trioxys
compressicornis
Betula pendula
Aphidius aquilus
Trioxys
tenuicaudus
Aphidencyrtus
aphidivorus
Euceraphis
betulae
Calaphis
betulicola
Trioxys
curvicaudus
Aphidencyrtus
quercicola
Betulaphis
quadrituberculata
Rajmanek and Stary
1979, Nature 280:
311-313
Food web connection and stability
The May equation predicts low linkage
density at higher connection rate
𝐷 𝑆𝐶 < 1
Rajmanek and
Stary 1979,
Nature 280:
311-313
D: Linkage density
S: species number
C: connectivity
The May equation predicts an upper limit
of connectance for a stable food web.
Schoenly et al. 1991,
Am. Nat 137: 597-638
Food web complexity is limited by species richness
𝐷 𝑆𝐶 < 1
Schoenly et al. 1991,
Am. Nat 137: 597-638
SC: measure of food web complexity
Aquatic food webs
Mechanisms that stabilize food webs:
The May eqaution is based on
simplified random food webs
with density dependent
regulation.
•
•
•
•
Weak and variable links
Low connectance
Dietary switches
Omnivory
The temporal stability of food webs
Temporal variability
among species
Omnivory stabilizes food webs
High proportion of specialist species
Intermediate proportion of specialist species
High proportion of omnivorous species
Undisturbed
Disturbed
Fagan 1997, Am. Nat. 150: 554-567
Mount Saint Helens
blowdown zone
Mount St. Helen’s recovery is a natural experiment on succession and community ecology.
Food chain length and habitat properties
Fresh water food chain length of North
American lakes increase with lake size but
not with productivity
Post et al.
2000,
Nature 405:
1047-1049
Compilation of well
resolved food chains
Hall and
Raffaelli 1991,
J. Anim. Ecol.
60: 823-841.
Average food chain length asymptotically
reaches a plateau independent of species
richness.
Food web complexity
and ecosystem
variability in ponds
Linkage density of fresh
water insect dominated
small pond food webs
increased with
• Species richness
• Habitat duration
and decreases with
• Pond environmental
variability
Schneider 1997,
Oecologia 110: 567-575
Connectance was
lowest at average
species richness,
variability, and pond
duration.
Empirical interaction matrices
Pollination networks
Plants
Kratochwil et al.
2009, Apidologia 40:
634-650
Bees
Plant
Asclepias AsclepiasAspidonepsis
Miraglossum
Miraglossum
PachycarpusSisyranthusXysmalobium
Xysmalobium
Pollinators
cucullata
woodii diploglossa verticillare pilosum natalensistrichostomus gerrardii involucratum
Hemipepsis
0
0
0
18
9
20
2
41
1
Pompilidae sp. 2
0
0
0
0
0
0
0
1
0
Tiphia
0
1
0
0
0
0
0
0
0
Arge
0
0
0
0
0
0
1
0
0
Apis
0
0
1
0
0
0
1
3
0
Halictidae sp. 1
0
0
2
0
0
0
0
0
0
Halictidae sp. 2
1
0
0
0
0
0
0
0
0
Other wasps
0
1
1
0
0
0
0
1
3
Other bees
0
0
0
0
0
0
0
1
1
Other solitary bees
0
1
2
0
0
9
0
0
0
Atrichelaphinis
0
15
0
1
0
0
35
15
6
Cyrtothyrea
0
8
0
1
0
0
42
6
0
Lycidae sp.
0
0
0
0
0
0
0
2
0
Cantharidae sp.
0
0
0
0
0
0
0
2
0
Elateridae sp.
0
0
0
0
0
0
0
0
4
Chrysomelidae sp. 1
0
0
0
0
0
1
0
0
1
Chrysomelidae sp. 2
0
0
0
0
0
0
1
1
1
Scarabaeinae sp. 1
0
0
0
0
0
0
0
3
0
Scarabaeinae sp. 2
0
0
0
0
0
0
0
3
1
Scarabaeinae sp. 3
0
0
0
0
0
0
0
1
0
Curculionidae sp. 1
0
0
0
0
0
0
10
4
1
Curculionidae sp. 2
0
2
0
0
0
0
0
0
0
Coleoptera sp. 3
0
0
0
0
0
0
0
2
0
Coleoptera sp. 8
0
0
0
0
0
0
1
0
0
Other Coleoptera
0
0
0
0
0
0
0
4
4
Aspilocoryphus
1
0
0
1
0
4
1
139
1
Lygaeidae sp. 2
0
0
0
1
0
1
0
8
2
Coreidae sp.
0
0
0
0
0
0
0
1
0
Spilostethus
0
0
0
0
0
1
0
0
0
Homoecerus
0
0
0
0
0
1
0
0
0
Pentatomoidea sp.
0
0
0
0
0
0
0
1
0
Other Heteroptera
0
0
0
0
0
0
0
1
0
Calliphoridae genus 1
0
0
0
0
0
0
0
1
0
Calliphoridae genus 2
0
0
0
0
0
0
2
6
0
Calliphoridae genus 3
0
0
0
0
0
0
0
1
0
Sarcophaga sp.
0
1
0
6
0
11
0
53
1
Musca
0
0
2
0
0
0
0
3
0
Muscidae genus 2
0
0
1
0
0
0
0
0
0
Empididae sp. 1
2
0
0
0
0
1
0
0
0
Empididae sp. 2
0
0
0
0
0
0
0
1
0
Chloropidae
0
0
1
0
0
0
0
1
0
Microphthalma
0
0
0
0
0
1
0
0
0
Microphthalma
0
0
0
0
0
0
0
1
0
Tachinidae subfamily Goniinae
0
0
0
0
0
0
0
1
0
Tachinidae genus 2
0
0
0
0
0
0
0
1
0
Actea
0
0
0
0
0
0
0
1
0
Sepsidae sp. 1
0
0
0
0
0
0
0
3
1
Sepsidae sp. 2
0
0
0
0
0
0
0
0
1
Sepsidae sp. 3
0
0
0
1
0
0
0
0
0
Dacus
0
0
0
0
0
1
0
0
0
Bibionidae
0
0
0
0
0
0
0
1
0
Diptera sp. 3
0
0
0
0
0
0
1
0
0
Diptera sp. 22
0
0
0
0
0
1
0
0
0
Other Diptera
0
1
0
1
0
1
0
15
0
Unidentified butterfly
0
0
0
0
0
0
1
0
0
Unidentified micromoth
2
0
0
0
0
0
0
0
0
From Ollerton et al.
2003, Ann. Botany
92: 807-834
The matrix approach to mutualistic and food webs
What are mutualistic webs:
Plant – pollinator webs
Plant seed disperser webs
Plant herbivore webs
Predator prey webs
Host parasite webs
Competition webs
Generalists
Plants
•
•
•
•
•
•
Pollinators
• Generalist pollinator visit
most plant species
• Specialist pollinator visit the
most popular plant species
• Mutualistic networks contain
forbidden links
Nestedness is defined as the ordered
loss of links in a mutualistic matrix
where rows and coloumns are sorted
according to species richness.
Specialists
Generalists
Specialists
Unexpected
link
Linkages: number of filled cells in the matrix
Linkage density: L/S1
Connectance: Matrix fill, L/(S1S2)
The architecture of
mutualistic
networks
Seed
disperser
Pollination
networks
Foods
webs
Jordi Bascompte
1967-
Bascompte 2003, PNAS
100: 9383-9387
Weak Anthropic Principle (Carter 1973):
We must be prepared to take account of
the fact that our location in the universe
is necessarily privileged to the extent of
being compatible with our existence as
observers.
In ecology this means:
Ecological systems do not have a random
strucure.
They have that non-random structure
that enabled them to survive during
evolution.
Bastolla et al. 2009,
Nature 458: 1018-1021
• Mutualistc networks are often nested.
• The nested architecture promotes diversity
and stability
Nestedness as an emergent property of ecological systems
Food webs are often compartmented
A
B
C
D
E
F
G
1
1
1
1
1
0
0
0
2
1
1
1
1
0
0
0
3
1
1
1
1
0
0
0
4
1
1
1
1
0
0
0
5
0
0
0
0
1
1
1
6
0
0
0
0
1
1
1
7
0
0
0
0
1
1
1
8
0
0
0
0
1
1
1
S
4
4
4
4
4
4
4
4
4
4
4
3
3
3
3
28
Foods webs have a modular structure.
Modularity tends to stabilize food webs.
Modules itself have a nested structure.
Nestedness tends to stabilize
mutualistic networks.
Mutualistic webs (comparirson of two
trophic levels) are most often nested.
A
B
C
D
E
F
G
1
1
1
1
1
1
1
1
2
1
0
1
1
1
0
0
3
1
1
1
1
0
0
0
4
1
1
1
1
0
0
0
5
1
1
1
0
0
0
0
6
1
1
0
0
1
0
0
7
1
0
0
0
0
0
0
8
1
0
0
0
0
0
0
S
8
5
5
4
3
1
1
S
7
4
4
4
3
3
1
1
27
Stability, resilience and tipping points
Instable
equilibrium Local stable
Global stable
state
state
Tipping point
Low stability
Local stability
Global instanility
Low resistence
Ecologial systems (particularly networks) can
be in various states:
• Instable equilibria are at tipping points
and can move towards different
directions.
• Local stable equilibria can easily be
forced to achieve other stable states.
• Global equilibria need much energy to
leave their state.
• Inequilibria can easily move between
different states.
• Resilience refers to the speed of a
systen to return to a stable state.
• Resistence is the ability of a system to
avoid displacement.
• Robustness is the ability of a system to
exist witin a wide range of conditions.
• Stability refers to the amplitude of
variability
• Sustainability i the capacity to endure
Multiple states
Probability
Instable
equilibrium Local stable
Global stable
state
state
A state reaches its tipping point
Food webs and tipping points
State
Tipping points define states where a
system irreversably changes the
probability distribution of states.
Indicators of critical tipping points:
• Resilience slows down
• Dominant eigenvectors of the food web
matrices shorten
• Increased variance
• Variance / mean relationships increased
• Multimodality of states
• Increasing connectivity and decreasing
diversity
Robustness
The importance of wild bees for pollination stability
Meta-analysis of empirical food ebs
Dunne 2002, Ecol.
Lett 5: 558
Garibaldi et al. 2013.
Science 339: 1608
In empirical foods webs robustness
increases with connectance.
In random foods webs robustness
decreases with connectance.
Therefore, empirical food webs have a
special non-random structure that
promotes stability.
Wild insects increase fruit production more
effectively than honey bees alone.
Species richness increases ecological functioning