Local and regional species richness y = 0.54x - 1.2 R 2 = 0.56 0 5 10 15 20 0 10 20 30 Species of regional pool Species of local pool • 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 Bracken occurs whole over the world Species numbers of phytophages on bracken differ Is this difference an effect of competitive exlusion or do empty niches exist? John H.Lawton The common brushtail Possum Trichosurus vulpecula is at its introduced sites often free of natural parasites. There are empty niches
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Local and regional species richness y = 0.54x - 1.2 R 2 = 0.56 0 5 10 15 20 0102030 Species of regional pool Species of local pool Species richness on.
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Local and regional species richness
y = 0.54x - 1.2
R2 = 0.56
0
5
10
15
20
0 10 20 30
Species of regional pool
Spe
cies
of l
ocal
poo
l
• 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
Bracken occurs whole over the world
Species numbers of phytophages on bracken differ
Is this difference an effect of competitive exlusion or do empty niches exist?
John H.Lawton
The common brushtail Possum Trichosurus vulpecula is at its
introduced sites often free of natural parasites. There are empty niches
Cynipid gall wasps in Norh America (Cornell 1985) Lacutrine fish in North America (Gaston 2000)
Relationship between local species richness and the regional species pool size for 14 vegetation types in Estonia (Pärtel et al. 1996)
Dry grasslands Moist grasslands
y = 0.49x + 0.51
R2 = 0.73
0
5
10
15
20
25
0 10 20 30 40
Number of species regionally
Nu
mb
er
of
spe
cie
s
loca
lly
y = 0.36x + 0.41
R2 = 0.83
0
0.5
1
1.5
2
2.5
3
3.5
4
0 2 4 6 8 10
Regional number of species
Lo
cal n
um
be
r o
f sp
eci
es
y = 0.27x - 6.9
R2 = 0.93
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20
40
60
80
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120
0 100 200 300 400
Number of species regionally
Nu
mb
er
of
spe
cie
s lo
cally
y = 16Ln(x) - 49
R2 = 0.86
0
20
40
60
80
100
120
0 100 200 300 400
Number of species regionally
Nu
mb
er
of
spe
cie
s lo
cally
Local and regional species richness
Four possible relations between local and regional species numbers
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1015
202530
3540
0 10 20 30 40
Regional number of species
Loca
l num
ber
of s
peci
es
Abundance – range size relationshipsFreshwater gyrinid beetles in temporary pools (Svensson 1992) Regional distribution of 21 Bombus species in northern Spain (Obeso 1992)
Local abundance in relation to regional distribution of soil mites (Karppinen 1958)
D: Local abundance in relation to regional distribution of bumblebees in Poland (Anasiewicz 1971)
Diptera colonising dead snails in a beech forest (Ulrich 2001) Parasitic Hymenoptera of these Diptera (Ulrich 2001)
y = 0.95e2.58x
R2 = 0.83
0
2
4
6
8
0 0.2 0.4 0.6 0.8
Fraction of pools occupied
Me
an
ab
un
da
nce
y = 0.067e6.97x
R2 = 0.5472
0%
5%
10%
15%
20%
25%
30%
0 0.05 0.1 0.15 0.2
Fraction of sites occupied
Pe
rce
nta
ge
of
tota
l A
bu
nd
an
ce
y = 3.06e0.11x
R2 = 0.90
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400
600
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1000
0 10 20 30 40 50
Number of sites occupied
log
re
l. a
bu
nd
an
ce
y = 1.0e0.33x
R2 = 0.82
0
20
40
60
80
0 2 4 6 8 10
Number of sites occupied
log
re
l. a
bu
nd
an
cey = 1.35e3.674x
R2 = 0.59
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60
80
0% 20% 40% 60% 80% 100%
Percentage of site occupied
Me
an
de
nsi
ty p
er
occ
up
ied
pa
tch
y = 1.57e2.97x
R2 = 0.78
0
2
4
6
8
10
0% 20% 40% 60%
Percentage of site occupied
Me
an
de
nsi
ty p
er
occ
up
ied
pa
tch
Patch occupancy models
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12171
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• A matrix of cells refers to a metacommunity scale
• Each cell represents one local community• Cells might have different sizes • Individuals of different species of the meta-
community are now placed at random or according to certain predefined rules into the cells
• A random placement is called a passive sampling model
• The spatial distribution patterns are then compared to observed ones.
y = 6e 1.61x
R2 = 0.60
0
10
20
30
40
0.01 0.1 1
Fraction of cells occupied
Mea
n de
nsity
per
oc
cupi
ed c
ell
Individuals of 100 species were placed at random into a 100x100 matrix.
Species had different individual numbers
Matrix cells had different capacities
• The model produces an abundance - range size relationship
• This relationship follows an exponential model as observed in reality
• Abundance - range size relationships are most parsimonous explained from passive sampling in heterogeneous environments
Core and satellite species
Insects on small mangrove islands (Simberloff 1976)
Plant species in Russian Karelia (Linkola 1916)
In an assemblage of species distributed over many sites we can often differentiate a group of core species, which occur in most or even all of the
sites, and a group of satellite species, which occur only in a few or even only in one site.
0
20
40
60
80
100
1 2 3 4 5 6 7 8 9
Number of sites occupied
Num
ber
of s
peci
es
0
20
40
60
80
0 1 2 3 4 5 6 7 8 9 10 11 12
Number of sites occupied
Num
ber
of s
peci
es
Core and satellite species
05
1015202530
1 2 4 8 17
Sp
eci
es
Sites occupied
Ground beetles species on Mazuran lake island
Satellite (infrequent, tourist) species Core (frequent, permanent) species
• Random pattern of temporal or spatial occurrence
• High dispersal ability• Log-series rank abundance
distributions• Weak species interactions• Forming random assemblages
• Non-random pattern of temporal or spatial occurrence
The matrix sorted according to row and column totals (numbers of occurrences) containes two triangles. One contain species and site with very high matrix fill (numbers
of occurrences, the second contains species and site with very low matrix fill.
We call such a matrix nested.
A SitesSpecies A C F D G E B H Sum
1 1 1 1 1 1 1 1 1 8
2 1 1 1 1 1 1 1 0 7
3 1 1 1 1 1 1 0 0 6
4 1 1 1 1 0 0 0 0 4
5 1 1 1 0 0 0 0 0 3
6 1 1 1 0 0 0 0 0 3
7 1 1 1 0 0 0 0 0 3
8 1 1 0 0 0 0 0 0 2
9 1 1 0 0 0 0 0 0 2
10 1 1 0 0 0 0 0 0 2
11 1 0 0 0 0 0 0 0 1
12 1 0 0 0 0 0 0 0 1Sum 12 10 7 4 3 3 2 1 42
A perfectly nested matrix
A perfectly nested (ordered) matrix can be divided into a completely filled
and an empty part.
A SitesSpecies A C F D G E B H Sum
1 1 1 1 0 1 1 1 1 7
2 1 1 1 1 1 1 1 0 7
3 0 1 1 1 1 1 0 0 5
4 1 1 1 1 0 0 0 0 4
5 1 1 1 0 0 0 0 0 3
6 1 1 1 0 0 1 0 0 4
7 1 1 1 0 0 0 0 0 3
8 1 1 0 0 0 0 0 0 2
9 1 1 0 0 0 0 0 0 2
10 1 1 0 0 0 0 0 0 2
11 1 0 0 0 0 1 0 0 2
12 1 0 0 0 0 0 0 0 1Sum 11 10 7 3 3 5 2 1 42
Imperfectly nested matrices have holes (unexpected absences) and outliers (unexpected occurrences).
The number of holes and outlier with respect to the perfectly ordered state is a measure of the degree of nestedness.
The discrepancy metric counts the number of holes that have to be filled by outliers of the same row or column to form a perfectly nested matrix.
Species gil ful lip sos kor guc 3pog hel dab wron mil wil 2pog ter wros swi 1pogOccurren-
We have to infer how many discrepancies are expected just by chance.
0 1 1 01 0 0 1
Checkerboards
We randomize the matrix switching
checkerboards. This retains row and column
totals and therefore basic matrix properties.
0
0.05
0.1
0.15
0.2
0.25
1 3 5 7 9 11 13 15 17 19 21
Freq
uency
Discrepancy
Observed discrepancy D = 11
Nested Antinested
Lower 5% CL
Upper 5% CL
Observed
1. Use 10*sites*species checkerboard swaps per matrix to randomize.2. Calculate discrepancy.3. Repeat steps 1 and 2 1000 times to get the null distribtuion.4. Compare the observed discepancy with the expected one.
Both matrices are not significantly nested.There are not more idiosyncratic sites and
species than expected just by chance.
Low dispersal Carabidae do not colonize lake island according to
organic matter content (soil fertility).Our first eysight impression was wrong.
Always ask whether an observed pattern or process might exist just by chance.
Today’s reading
Local and regional species richness: http://www.springerlink.com/content/ugm5380764049730/
Nestedness and null models: www.uvm.edu/~ngotelli/manuscriptpdfs/UlrichConsumersGuide.pdf
Community assembly: www.msstate.edu/courses/etl5/Community%20Assembly1.ppt