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Distributions in space
Biogeography
Evolutionary Ecology
Tries to understand large scale distributions
of living thinks
Tries to understand patterns of species
diversity through evolutionary history
Macroecology
Tries to link both disciplines and to explain larges scale
ecological patterns and processes in space and time
Biotic interactions
Species
assemblage
rules
Niche
Biogeography
History
It tries to explain community
structure from a top down (instead
of bottom up) perspective.
Community
structure
Life
histrory
traits
Phenology
Macroecology integrates
biogeographic and evolutionary
research in an interdisciplinary way.
Chance processes
Character evolution
Phylogenetic
constraints
Basic tools are spatially explicit
models and meta-analysis.
z
10000000
Landscape
processes in
evolutionary time
Continental
processes in
evolutionary time
Processes
in ecological
time
Landscape
processes
Continental
processes in
ecological time
Annual
ecosystem
processes
Annual regional
species turnover
1000000
Temporal scale [days]
Ecological processes
Evolutionary processes
Macroecology
100000
10000
1000
100
10
1
10
100
1000
10000
100000
1000000 10000000
2
Spatial scale [m ]
Evolutionary processes
Ecological processes
Predation
Disturbance
Competition
Dispersal
Metapopulations
Spatial processes
Dispersal
Metapopulations
Metacommunities
Fluctuations
Local species turnover
patches
1
Speciation
Extinction
Climatic processes
Speciation
Extinction
Geological processes
Theory of Island biogeography
The
Galapagos
Islands
Robert MacArthur
(1930-1972)
Edward O. Wilson
(1929-)
One islands
Immigration
Two islands
Immigration
Extinction
Extinction
Equilibrium
species richness
Rate
Rate
near
small
Equilibrium
species richness
far
large
Species richness
Species richness
The theory of island biogeography tries to understand species diversity on all sorts of
isolated islands from stochastic colonization of islands and random extinction on islands.
Colonization rates depend on island area and isolation. Extinction rates depend on island
area only.
The model is species based
S = S0e-kI
Species richness
Species richness
Theory of Island biogeography
S = S0Az
Isolation
Area
The species – area relationship
Avifauna of New Guinea
Land plant of Britain from Watson (1859)
Number of species
The species – isolation relationship
10000
y = 433.2x 0.10
R 2 = 0.98
1000
100
1
100
10000
Area [miles 2 ]
Diamond 1972, PNAS 69: 3199-3203
The increase of species richness with sample size
Parasitoid
Hymenoptera on a dry
meadow on
limestone, Ulrich 2005
Butterfly catches by
Preston 1948
Species
richness on
deep sea
mounts,
Forges 2000
Increase of land plant
families in
evolutionary time,
Knoll 1986
Increase of
herbivores
on bracken, Lawton 1986
The power function species – sample size relationship
𝑆 = 𝑆0 𝑁 𝑧
The species – area relationship
𝑙𝑛𝑆 = 𝑙𝑛𝑆0 + 𝑧𝑙𝑛𝑁
The species – area - time
relationship
𝑆 = 𝑆0 𝐴𝑧 𝑡 𝜏
𝑆 = 𝑆0 𝐴𝑧
The species – time relationship
𝑆 = 𝑆0 𝑡 𝜏
1. The number of species counts increases with area and time.
Collembolan species richness
2. This relationship often follows a power function
across Europe
3. The slope z of this function measures how fast species
richness increases with increasing area. It is therefore a
measure of spatial species turnrover or beta diversity
4. The intercept S0 is a measure of the expected number of
species per unit of area. It is therefore a measure of alpha
diversity
𝑆 = 1.36𝐴0.43
5. Changes in slope through time point to disturbances like
habitat fragmentation or destruction
6. The slope of the species – time relationship is a measure of
local species extinction rate.
The species – time relationship
Local species area and species time relationships in a temperate Hymenoptera
community studied over a period of eight years.
S = S0tt
S = S0Az
S = S0Aztt
Coeloides pissodis600
B
(Braconidae)
500
500
400
300
200
100
0
400
Turnover
700
A
600
Number of species
Number of species
The accumulation of species richness in space and time follws a
power function model
300
200
100
0
0
50
Area
100
150
0
S = (73.0±1.7)A(0.41±0.01) t(0.094±0.01)
50
Area
100
150
1.4
C
1.3
1.2
1.1
1
0.9
0.8
0.7
0
5
t
10
The mean extinction rate per year is
about 9%
Species - area relationship of the world birds at different scales
Number of species
10000
Preston 1960, Ecology
41: 611-67
between biotas: z = 0.53
1000
100
within a regional pool: z = 0.09
10
1
1.0E-01
small areas: z = 0.43
1.0E+01 1.0E+03 1.0E+05 1.0E+07 1.0E+09 1.0E+11 1.0E+13
Area [Acres]
Regional SARs have slopes between 0.1 and 0.3.
Local and continental SARs have slopes > 0.25.
The species – area relationship of plants follows a three step pattern as in birds
Number of species
1000000
100000
Shmida, Wilson 1985,
J. Biogeogr. 12: 1-20
Intercontinental scale: z = 0.5
10000
1000
100
10
1
1.E-04
Regional scale: z = 0.14
Local scale: z = 0.25
1.E-02
1.E+00 1.E+02 1.E+04 1.E+06 1.E+08 1.E+10 1.E+12
2
Area [km ]
Latitudinal gradients in species richness
1000
Pacific
shelve
mollusks
800
Species
New
worlds
birds
600
400
200
0
-80 -60 -40 -20
0
20 40 60 80
Latitude
Western Atlantic
gastropods
600
400
200
0
z
800
1000
Species richness
z
1000
Species richness
The peak in species richness is not exactly at the equator
800
Eastern Pacific
gastropods
600
400
200
0
0
10
20
Mean temperature
30
0
10
20
Mean temperature
30
Ecological hotspots
34 regions worldwide where 75% of the planet’s most threatened mammals, birds, and
amphibians survive within habitat covering just 2.3% of the Earth’s surface.
The latitudinal distribution of temperatures
Biodiversity is
most sensitive
to minimum
temperatures
and the
temperature
range
The general pattern
Hillebrand (2004, Am. Nat. 163: 192-211 ) conducted a meta-analysis for about 581
published latitudinal gradients
Scale
Global richness
Regional
Body size
High
High
•
Species richness
•
Local
Low
Tropic level
Longitude
New
world
High
Low
Low
Old
world
Latitude
Realm
Terrestrial,
marine
Freshwater
•
Nearly all taxa show a
latitudinal gradient
Body size and realm are
major predictors of the
strange of the latitudinal
gradient
The ubiquity of the
pattern makes a simple
mechanistic explanation
more probable than
taxon or life history type
specific
Counterexamples
The sawfly Arge coccinea, Photo by Tom Murray
Soybean aphid, Photo by David Voegtlin
The ichneumonid Arotes sp.,
Photo by Tom Murray
The aquatic macrophyte Hydrilla
verticilliata, Photo by FAO
These taxa are most species rich in the northern Hemisphere
The geographical distribution of body size
Trichoplax adhaerens
Balaenoptera musculus
Loxodonta africana
Neotrombicula autumnalis
Tinkerbella nana
Goliathus regius
Biogeographic distributions of invertebrate body sizes (Makarieva et al. 2005)
Makarieva, Gorshkov, Li 2005,
Oikos 111: 425-436.
World distribution of largest land vertebrates
Largest species in
Mammals:
Phytophages in tropical
regions
Predators at higher
latitudes
Birds:
In tropical regions
Reptiles and Amphibians:
In tropical regions
Kleiber’s rule
The speed of organismal
metabolism is related to
species body size by a power
function.
Simple geometry tells that
𝑀 ∝ 𝑊 2/3
Hemmingson classic plot of metabolic rate
against body size.
Each regression line has a slope of 3/4
𝑀 ∝ 𝑊 3/4
Observations z
35
Peters 1983
30
25
20
15
10
5
0
The rule of Max Kleiber
0
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Slope
1
1.1 1.2
The basic equation of metabolic theory
The Arrhenius equation
of kinetic theory
𝑣∝𝑒
𝐸
−𝑘𝑇
E = Activation energy
Boltzmann factor: 8.314 Jmol-1K-1 = 0.0000862eVK-1
T = absolute temperature
W = body mass
Adding the concentration of an
assumed limiting resource Rmin gives
𝑀∝
𝐸
3/4 −𝑘𝑇
𝑅𝑚𝑖𝑛 𝑊 𝑒
Brown et al. 2004, Ecology 85:
1771-1789
𝑀∝𝑣
𝑀∝
𝑀 ∝ 𝑊 3/4
𝐸
−𝑘𝑇
3/4
𝑊 𝑒
Population size
DNA substitution rate a should be proportional to M/W
a  M / W  a  W 1/ 4e  E / kT
𝛼 ∝ 𝑆 ∝ 𝑒 −7500/𝑇
Speciation rate
Now assume that most mutations are neutral and occur
randomly. That is we assume that the neutral theory of
population genetics (Kimura 1983)
Population size
Extinction rate
Body size specific metabolic rate M/W should
scale to the quarter power to body weight
and exponentially to temperature.
Extinction rate
MW e
M

 W 1/ 4 e E / kT
W
Speciation rate
3/ 4  E / kT
Body size
The rate of DNA evolution predicted from metabolic theory
Body size
•
Body weight corrected DNA substitution rates (evolution rates) should be a linear function
of 1/T with slope –E/k = -7541.
•
Higher environmental temperatures should lead to higher substitution rates (faster
evolution).
•
Body weight corrected DNA substitution rates (evolution rates) should decrease with body
weight.
•
Large bodied species should have lower substitution rates (slower evolution).
200
200
z=-10005
150
S
S
North
American
trees
z=-8540
150
100
50
50
S=e
0
0
0.0032 0.0034 0.0036 0.0038 0.004
0.003 0.003 0.003 0.004 0.004 0.004
1/T
1/T
80
100
z=-10250
Ecuadorian
amphibians
60
40
20
20
0
0
0.0032 0.0034 0.0036 0.0038 0.004
0.0033 0.0034 0.0035 0.0036 0.0037
1/T
1/T
Fish species richness
800
z=-9160
600
Prosobranchia species richness Ectoparasites of marine teleosts
1200
25
z=-7170
1000
S
400
600
15
10
400
200
z=-8510
20
800
S
S
S
40
z=-10810
80
60
S
North
American
amphibians
100
Costa Rican
trees along
an
elevational
gradient
200
5
0
0
0
0.0032 0.0034 0.0036 0.0038 0.004
0.0032 0.0033 0.0034 0.0035 0.0036 0.0037
0.0033 0.0034 0.0035 0.0036 0.0037
1/T
1/T
1/T
The energy equivalence rule
Soil animals of Kampinowski National Park
𝑀 ∝ 𝑊 3/4
𝐷 ∝ 𝑊 −𝑧
𝐵 = 𝑀𝐷 ∝ 𝑊 3/4−𝑧
If z = ¾
Energy equivalence rule
Damuth’s rule
𝐵 = 𝑀𝐷 = 𝑐𝑜𝑛𝑠𝑡
Hoste Thesis 2013
Local and regional species richness
Bracken occurs whole over the world
Species numbers of phytophages on
bracken differ
Pteridium aquilinum
•
•
•
John H.Lawton
Is this difference an effect of competitive
exclusion or do empty niches exist?
Species richness on bracken is higher at richer
sites
At species poorer sites there seem to be many
empty niches
Local habitats are not saturated with species
The common brush tail Possum
Trichosurus vulpecula is at its
introduced sites often free of natural
parasites. There are empty niches
Local and regional species richness
20
15
10
5
0
0
10
20
30
Number of species regionally
40
Local number of species
25
4
3.5
3
2.5
2
1.5
1
0.5
0
0
2
4
6
8
10
Regional number of species
Relationship between local species richness and the regional species pool size
for 14 vegetation types in Estonia (Pärtel et al. 1996)
Moist grasslands
120
100
80
60
40
20
0
0
100
200
300
400
Number of species regionally
Number of species locally
Dry grasslands
Number of species locally
Number of species
locally
Cynipid gall wasps in Norh America (Cornell 1985) Lacutstrine fish in North America (Gaston 2000)
120
100
80
60
40
20
0
0
100 200 300 400
Number of species regionally
Numbers of species incidences among sites
The spatial distribution of abundance
Numbers of species incidences in time
The temporal distribution of abundance
Karelian plant species (Linkola 1916)
British Channel fish species (Magurran,
Henderson 2003)
Satellite
species
Intermediate
species
Core
species
Abundance
rank order
Abundance
rank order
Importance of ecological
interactions
Core (resident, permanent) species are often
• of regionally higher abundance
• good competitors
• Pronounced species interactions
• have stable species interactions
• have low abundance fluctuations
• are K-selected species
Satellite (transient, tourist) species are often
• of regionally lower abundance
• worse competitors
• Weak species interactions
• have unstable species interactions
• have higher abundance fluctuations
• are r-selected species
Local abundance and regional distribution in pond macroinvertebrates
Verberk et al. 2010, J. Anim. Ecol. 79: 589
Habitat
specialists
Habitat specialists have often
locally higher abundances
than habitat generalists.
Local abundance is often
positively correlated to
Habitat
generalists regional distribution
Habitat generalists
High
colonisation
ability
Larger local
populations
Wide regional
distribution
Low
extinction
Habitat specialists
Feedback loop
between local
abundance and
regional
occupancy
(distribution)
Low
colonisation
ability
Smaller local
populations
Narrow regional
distribution
Higher
extinction