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Deciphering Universal Patterns
of
Biodiversity
Dan McGlinn http://mcglinn.web.unc.edu
Weecology Lab @danmcglinn
Deciphering
STRANGE
Patterns
Dan McGlinn http://mcglinn.web.unc.edu
Weecology Lab @danmcglinn
What Determines Mate Choice
1st Law of Geography
• Everything is related to everything else…
• But near things are more related than distant
things
• As we move further way the more
different things become
“the nice Watson girl next door”
Aunt May
Things are Patchy
Ecological Communities are Patchy
Ecological Communities are Patchy
Ecological Communities are Patchy
Ecological Communities are Patchy
Distribution of Energy
Preston 1950
Temperature (i.e., Energy)
Num
ber
of
Mole
cule
s
Galactus the Devourer
Preston 1950
Distribution of Energy
Temperature (i.e., Energy)
Num
ber
of
Mole
cule
s
Preston 1950
Distribution of Energy
Temperature (i.e., Energy)
Num
ber
of
Mole
cule
s
Preston 1950
Distribution of Energy
Temperature (i.e., Energy)
Num
ber
of
Mole
cule
s
Household Income
Distribution of Wealth in the US
$50,000 $100,000 $150,000 $200,000 $250,000 $0
Num
be
r of H
ou
se
ho
lds = 500,000 Households
Most Poor
Few Wealthy
Distribution of Abundance
Among Species
Preston 1948
Most species Rare Few Species Common
Two Universal STRANGE
Patterns
Species are Patchy Species are Rare
Universal Explanation?
• Maximum Entropy Theory of Ecology (METE) Harte et al. (2008), Harte (2011)
• Predicts many distributions Abundance and Patchiness
• Prior Information Total number of species (S0)
Total number of individuals (N0)
Total area of a community (A0)
Total energy of community (E0)
• Assumes that communities are in a ‘most likely’ state given constraints
Show me the Data • 16 communities
– 15 tree
– 1 herb
• 6 habitat types – Tropical forest
– Oak-hickory
– Old field, pine forest
– Oak woodland
– Mixed-evergreen forest
– Serpentine grassland
• 1611 species
• 350,000 individuals
Example Results
Species Rank Area (m2)
Abundance
Num
be
r o
f S
pe
cie
s
100000
Total Number of Species = 124
Total Number of Individuals = 32,320
1
10
100
Observ
ed A
bundance
1000
10000
1 10 100 1000 10000
R2 = 0.85
Predicted Abundance
Crosstimbers
1
10
100
Observ
ed A
bundance
1000
10000
1 10 100 1000 10000
Predicted Abundance
R2 = 0.85
1 10 100
1
10
100
Predicted Number of Species
Observ
ed N
um
ber
of S
pecie
s
R2 = 0.99
Implications
• We can predict local scale
– patterns of abundance across species
– patterns of diversity across areas
• With only prior knowledge of
– S: total number of species in the community
– N: total number of individuals in the community
• Approach likely can be applied to other
disciplines
Why is this Important?
How many species are quite rare?
Why is this Important?
How many species are likely to go locally
extinct?
Thank you!
• The volunteer data collectors
• The data providers
• NSF Career Award to E.P. White
• Utah State Ecology Center
• Weecology Lab
Questions
