Transcript No Slide Title

Diversity: alpha – beta – gamma
Beta diversity is a concept that helps us to cope with the fact that
not every species lives everywhere
120
Whittaker 1972
100
 =  avg
Species
80
60
BETA
40
GAMMA
Lande 1996
20
ALPHA
0
0
1
2
3
4
Area
5
6
7
 = avg + 
Beta diversity indices
Koleff et al. 2003 J anim Ecol 72:367
"Broad sense" measures
incorporate differences in species richness
as well as differences in composition
Jaccard
"Narrow sense" measures
independent of differences in species richness
Example 1
a = 10, b = 10, c = 100
Jaccard = 10/120 = 0.08
Sorensen = 20/130 = 0.15
Lennon = 1- 10/20 = 0.5
Sorensen
Lennon et al.
1-
Example 2
a = 10, b = 10, c = 1000
Jaccard = 10/1020 = 0.010
Sorensen = 20/1030 = 0.019
Lennon = 1- 10/20 = 0.5
Koleff et al. 2003 J anim Ecol 72:367
temperate
Beta diversity along e.g. latitudinal gradient:
• change in community composition measured by beta diversity
• change in beta diversity
E
F
ßEF
Latitude
ßCE
ßDF
C
D
ßCD
ßAC
ßBD
tropical
A
B
ßAB
lowland
montane
Altitude
Latitudinal gradient in alpha
diversity – owls
Koleff et al. 2003
Latitudinal gradient in A, B, C
parameters – owls
for adjacent pairs of quadrats
A
focal area
C
B
Koleff et al. 2003
Beta diversity A/(A+B+C) of owls along latitudinal gradient
Koleff et al. 2003
Beta diversity of vertebrates
Birds
Amphibians
Mammals
decrease in species overlap over 500 km
Beta diversity and optimum selection of protected areas
richness-based algorithm
1.
2.
select the most species rich plot
add the plot bringing the highest
number of new species
rarity-based algorithm
1.
2.
Reyers et al. 2000
select the plot with the rarest species
add the plot with the rarest
unrepresented species
Causes of species turnover in space
Speciation and dispersal limitation:
species migration ability vs. barriers
Habitat availability:
biotic and abiotic resources and limiting factors
Biological interactions:
competitive exclusion from suitable habitats
Apparent species turnover:
species too rare to be sampled
Speciation and dispersal limitation: the Hubbell’s (2001) neutral model
- all species ecologically identical
- species turnover generated by dispersal limitation
The probability F(r) that 2 trees r km apart are conspecific
is modelled as depending on:
speciation rate , mean dispersal distance  and population
density 
is predicted to decrease linearly with log r
Habitat availability: altitudinal gradient, the mother of all environmental gradients
Ficus copiosa in New Guinea raingorest:
2 samples of 200 caterpillars 150 km apart
% of shared species
45
30
15
0
lowland x lowland
lowland x montane
Two modes of altitudinal species turnover:
with complete nestedness and zero nestedness
Identical altitudinal trends in species richness mean
different trends in mean altitudinal range of species and
beta diversity between adjacent altitudes
1.0
Beta diversity [1-Jaccard] .
10
No. of species
8
6
4
2
0
0.8
0.6
0.4
0.2
0.0
low
high
Altitude
low
high
Altitude
Species turnover along altitudinal gradients:
Rhododendron spp. on Mt. Kinabalu
Rhododendrones: 900 spp. worldwide, 300 spp. in SE Asia, 50 spp. in
Borneo, 25 spp. on Mt. Kinabalu, incl. 5 endemic spp.
Altitudinal distribution of 454 bird species in Papua New Guinea
0 m asl.
4500 m asl.
each row is 100 m elevation belt, each column a bird species
K. Tvardikova, unpubl. data
Biological interactions: “checkerboard” distributions
Altitudinal segregation of competing parrots in New Guinea:
2500
Language distribution among tribal societies:
Altitude (m)
2000
1500
1000
500
0
Mt. Niba
Sepik
Mts.
Mt.
Karimui
Charmosyna placentalis
Karkar
Is.
Tolokiwa
C. rubronotata
New
Britain
C. rubrigularis
“Checkeboard distribution” - not predicted by island biogeography
M. nigrirostris
M. mackinlayi
Cockoo-dove Macropygia mackinlayi and M. nigrirostris
Diamond, J.M. (1975) Community Ecology
Checkerboard distribution: Zosterops birds in New Guinea
Zosterops chloris
Zosterops atriceps
Herpetofauna on British Virgin Islands:
a nested pattern of species distribution
species
Nestedness can be
used to determine
extinction probabilities
islands
(a) a maximally cold matrix,
(b) actual data, small
mammals in Rocky Mts., (c),
(d) matrices randomly filled
under successively relaxed
constraints [Patterson &
Atmar 1986].
Matrix temperature T
U = 1/(mn) i  j uij
T = U/Umax * 100