Part 1: An introduction to β diversityPart 1: An introduction to β diversity –Scale: grain &...
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Transcript of Part 1: An introduction to β diversityPart 1: An introduction to β diversity –Scale: grain &...
• Part 1: An introduction to Part 1: An introduction to ββ diversitydiversity– Scale: grain & extentScale: grain & extent– What is What is ββ diversity? diversity?– The Two Pillars and Two Components of The Two Pillars and Two Components of ββ
diversitydiversity• Niche difference or Gradient Niche difference or Gradient ββ • Spatial & Temporal Constraint Spatial & Temporal Constraint ββ
• Part 2: Examples of Spatial & Temporal Part 2: Examples of Spatial & Temporal Constraint Constraint ββ diversity at large scales diversity at large scales – Diversity in North Temperate forestsDiversity in North Temperate forests– Narrow endemism in eastern North AmericaNarrow endemism in eastern North America
The Spatial & Temporal The Spatial & Temporal ConstraintConstraint
Component ofComponent of ββ diversity: diversity: here, there, & everywherehere, there, & everywhere
αα,,ββ,,γγ,,δδ diversity diversity
• Most famous from the papers of Most famous from the papers of Whittaker and MacArthur in the 1960sWhittaker and MacArthur in the 1960s
• As we will see, As we will see, ββ is different than the is different than the othersothers
• And these 4 Greek symbols represent And these 4 Greek symbols represent just two concepts: just two concepts: – Inventory Diversity Inventory Diversity – Differentiation diversityDifferentiation diversity
Scale: Grain & ExtentScale: Grain & Extent
Scale: Grain & ExtentScale: Grain & Extent
Grain: Grain: αα,,γγ,,δδ
Extent: Extent: ββ
Scale: Grain & ExtentScale: Grain & Extent
Grain: Grain: αα,,γγ,,δδ
Extent: Extent: ββ
For nested samples, For nested samples, Extent incr. with grain Extent incr. with grain by way of the by way of the Pythagorean TheoremPythagorean Theorem
Extent/area sampled:Extent/area sampled:
1.4/1, 4.2/9, 7.1/251.4/1, 4.2/9, 7.1/25
2/2, 3/2, 5/22/2, 3/2, 5/2
Scale: Grain & ExtentScale: Grain & Extent
Many estimates of spp-Many estimates of spp-grain (area) relation; few grain (area) relation; few of spp-extent relationof spp-extent relation
For nested samples, For nested samples, Extent incr. with grain Extent incr. with grain by way of the by way of the Pythagorean TheoremPythagorean Theorem
Extent/area sampled:Extent/area sampled:
1.4/1, 4.2/9, 7.1/251.4/1, 4.2/9, 7.1/25
2/2, 3/2, 5/22/2, 3/2, 5/2
Grain, extent, & sampling
2 Kinds of 2 Kinds of DiversityDiversity
Inventory Inventory DiversityDiversity
α, γ, δα, γ, δ
Differentiation Differentiation Diversity Diversity
ββ
2 Kinds of 2 Kinds of DiversityDiversity
Inventory Inventory DiversityDiversity
αα, γ, δ, γ, δ
ααCommunityCommunity
Differentiation Differentiation Diversity Diversity
ββ
2 Kinds of 2 Kinds of DiversityDiversity
Inventory Inventory DiversityDiversity
α, α, γγ, δ, δ
ααLandscapeLandscape
Differentiation Differentiation Diversity Diversity
ββ
2 Kinds of 2 Kinds of DiversityDiversity
Inventory Inventory DiversityDiversity
α, γ, α, γ, δδ
ααRegionRegion
Differentiation Differentiation Diversity Diversity
ββ
2 Kinds of 2 Kinds of DiversityDiversity
Inventory Inventory DiversityDiversity
α, γ, δα, γ, δ
Differentiation Differentiation Diversity Diversity
ββ
2 Kinds of 2 Kinds of DiversityDiversity
Inventory Inventory DiversityDiversity
α, γ, δα, γ, δ
Differentiation Differentiation Diversity Diversity
ββSmall ExtentSmall Extent
ββLandscapeLandscape
ββGradientGradient
2 Kinds of 2 Kinds of DiversityDiversity
Inventory Inventory DiversityDiversity
α, γ, δα, γ, δ
Differentiation Differentiation Diversity Diversity
ββLarge extentLarge extent
ββRegionRegion
β diversity measures• β = γ / α…and many others
αα γγ
β diversity measures• β = γ / α…and many others• β = the distance decay of similarity
Similarity = c / (a + b – c) and others
The first law of geography:the similarity between two observations decreases or decays with distance
Sd = S0 e-cd, d is distance, c is the rate of distance decay, S0 is the initial similarity
a a cc bb
The Two Pillars The Two Pillars of Ecological Explanationof Ecological Explanation
The Niche Difference ModelThe Niche Difference Model
The Model of Spatial & The Model of Spatial & Temporal ConstraintTemporal Constraint
The Niche Difference The Niche Difference Model:Model:Niche differences, Niche differences, Environmental Environmental gradients, gradients, & disturbances& disturbancesexplain distributionexplain distribution
The Two Pillars The Two Pillars of Ecological Explanationof Ecological Explanation
The Model of The Model of Spatial & Temporal Spatial & Temporal Constraint:Constraint:Size & isolation of Size & isolation of habitats habitats implying also time implying also time explain distributionexplain distribution
The Two Pillars The Two Pillars of Ecological Explanationof Ecological Explanation
The rate of distance decay, c, varies with Two traits of environment &Two traits of organisms:
Environment Organism traits
Adaptation Gradients Niche
Movement Resistance Vagility
The rate of distance decay, c, varies with Two traits of environment &Two traits of organisms:
Environment Organism traits
Adaptation Gradients Niche
Movement Resistance Vagility
The rate of distance decay, c, varies with Two traits of environment &Two traits of organisms:
Environment Organism traits
Adaptation Gradients Niche
Movement Resistance Vagility
Two relationships between organisms & environment:Adaptation & MovementShortly: The Two Pillars of Ecological Explanation
The rate of distance decay, c, varies with Two traits of environment &Two traits of organisms:
Environment Organism traits
Adaptation Gradients Niche
Movement Resistance Vagility
Two relationships between organisms & environment:Adaptation & Movement
The Two Pillars of Ecological Explanation
ExtentExtent correlates with similarity decay correlates with similarity decay in in two waystwo ways! ! The The two componentstwo components of beta diversity: of beta diversity:As DistanceAs Distance
Niche DifferenceNiche Difference Environmental Environmental similarity similarity
Spatial & Temporal ConstraintSpatial & Temporal Constraint
Barriers to dispersalBarriers to dispersalTime needed to Time needed to
saturatesaturateSimilarity Similarity
Spatial extent & distance decaySpatial extent & distance decay
2 Kinds of 2 Kinds of DiversityDiversity
Inventory Inventory DiversityDiversity
α, γ, δα, γ, δ
Differentiation Differentiation Diversity Diversity
ββ
ββGradientGradient
ββSpatial & Spatial & Temporal Temporal
ConstraintConstraint
Diversity patternsDiversity patternsin North temperate forestsin North temperate forests
Explanations of Explanations of distributiondistributionThe Niche Difference The Niche Difference ModelModelThe Model of Spatial & The Model of Spatial & Temporal ConstraintTemporal Constraint
Explanations of species richness Explanations of species richness patternspatterns
11stst Pillar: Energy-Diversity Theory Pillar: Energy-Diversity TheorySpecies richness is self-limiting, Species richness is self-limiting, in equilibrium with in equilibrium with environment (energy environment (energy availability), & convergent in availability), & convergent in similar environments (at similar similar environments (at similar energies).energies).
Explanations of species richness Explanations of species richness patternspatterns
11stst Pillar: Energy-Diversity Theory Pillar: Energy-Diversity TheorySpecies richness is self-limiting, Species richness is self-limiting, in equilibrium with in equilibrium with environment (energy environment (energy availability), & convergent in availability), & convergent in similar environments (at similar similar environments (at similar energies).energies).
All you need to know is current All you need to know is current environment (energy environment (energy availability)!availability)!
Energy-Diversity Theory
Currie & Paquin 1987
Nature 329, 326-327
AETAET
Tre
e S
pp
Tre
e S
ppData only for Data only for
North North American trees American trees at grain sizes at grain sizes of ca 2.5 degr of ca 2.5 degr Lat x 2.5 degr Lat x 2.5 degr LongLong
AET > LatitudeAET > Latitude
Energy-Diversity Theory
Currie & Paquin 1987
Nature 329, 326-327
AETAET
Tre
e S
pp
Tre
e S
pp
rr22=.76=.76
Residuals=Elevation, Residuals=Elevation, coastal proximity coastal proximity
not climate not climate variability or variability or glacial glacial historyhistory
Data only for Data only for North North American trees American trees at grain sizes at grain sizes of ca 2.5 degr of ca 2.5 degr Lat x 2.5 degr Lat x 2.5 degr LongLong
Energy-Diversity Theory
Currie & Paquin 1987
Nature 329, 326-327
AETAET
Tre
e S
pp
Tre
e S
pp
The equation The equation for No America for No America predicts tree predicts tree richness in richness in Europe—no Europe—no glacial glacial extinctions extinctions need be need be invoked—but invoked—but predictions predictions often 10-20% often 10-20% off.off.
Explanations of species richness Explanations of species richness patternspatterns22ndnd Pillar: Historic Biogeography Pillar: Historic Biogeography
Species richness is a Species richness is a function of the function of the constraints of time & constraints of time & space.space.
Explanations of species richness Explanations of species richness patternspatterns22ndnd Pillar: Historic Biogeography Pillar: Historic Biogeography
Species richness is a Species richness is a function of the function of the constraints of time & constraints of time & space.space.
Not predictable from Not predictable from current environment current environment (unless environment (unless environment and history are and history are themselves correlated)!themselves correlated)!
The question of The question of intercontinental intercontinental convergence in convergence in similar similar environments:environments:Temperate forests Temperate forests in East Asia in East Asia & Eastern North & Eastern North America America
JapanJapan
Tree Species Richness
0
10
20
30
40
50
60
70
1 2 3 4 5 6 7 8 9 10 11
Genera
Nu
mb
er o
f S
pec
ies
EAsia ENoAmerica
Carpinus
Alnus PopulusMalus
Prunus
Sorbus
Acer
FraxinusCarya
Quercus
Crataegus
From Ricklefs From Ricklefs & Latham 1993& Latham 1993
WalnutWalnut
Striped Striped maplemaple Sugar mapleSugar maple
Red Red maplemaple
Silver mapleSilver maple
Chestnut Chestnut oakoak
BasswooBasswoodd
ElmElm
ElmElm
White pineWhite pine PoplarPoplar
AshAsh
HawthornHawthorn
CherryCherry
BirchBirch
MulberryMulberry
MaakiaMaakia
PhelodendrPhelodendronon
Asian Asian maplesmaplesBeechBeech
BirchBirch
HollyHolly
Magnolia, LiriodendronMagnolia, Liriodendron NyssNyssaa
CaryCaryaa
PachysandPachysandrara
Buckleya, Catalpa, Buckleya, Catalpa, CladrastisCladrastis, , EpigaeaEpigaea, , GleditsiaGleditsia, , GymnocladusGymnocladus, , HalesiaHalesia, Itea, Menispermum, , Itea, Menispermum, MitchellaMitchella, , Pieris, Pyrularia, Pieris, Pyrularia, SassafrasSassafras, Wisteria, Wisteria
Adlumia, Astilbe, Adlumia, Astilbe, CaulophyllumCaulophyllum, , DiphyleiaDiphyleia, Hydrastis, , Hydrastis, JeffersoniaJeffersonia, , PanaxPanax, Phryma, , Phryma, PodophyllumPodophyllum, , ShortiaShortia, , TipulariaTipularia
Supragenera: Calycanthus, Supragenera: Calycanthus, ChimonanthusChimonanthus
Subgenera: Striped Subgenera: Striped maplesmaples
Magnolia, NyssaMagnolia, Nyssa
Fagus, Ostrya, TiliaFagus, Ostrya, Tilia
Magnolia, NyssaMagnolia, Nyssa
HamamelidaceaeHamamelidaceae
Fagus, Ostrya, TiliaFagus, Ostrya, Tilia
Magnolia, NyssaMagnolia, Nyssa
Clintonia, Torreya, Tsuga, Clintonia, Torreya, Tsuga, TrilliumTrillium
HamamelidaceaeHamamelidaceae
Fagus, Ostrya, TiliaFagus, Ostrya, Tilia
Magnolia, NyssaMagnolia, Nyssa
Acer, Cornus, Aesculus, CercisAcer, Cornus, Aesculus, Cercis
Clintonia, Torreya, Tsuga, Clintonia, Torreya, Tsuga, TrilliumTrillium
HamamelidaceaeHamamelidaceae
Fagus, Ostrya, TiliaFagus, Ostrya, Tilia
Magnolia, NyssaMagnolia, Nyssa
Acer, Cornus, Aesculus, CercisAcer, Cornus, Aesculus, Cercis
Clintonia, Torreya, Tsuga, Clintonia, Torreya, Tsuga, TrilliumTrillium
HamamelidaceaeHamamelidaceae
Fagus, Ostrya, TiliaFagus, Ostrya, Tilia
Magnolia, NyssaMagnolia, Nyssa
Acer, Cornus, Aesculus, CercisAcer, Cornus, Aesculus, Cercis
Clintonia, Torreya, Tsuga, Clintonia, Torreya, Tsuga, TrilliumTrillium
HamamelidaceaeHamamelidaceae
Fagus, Ostrya, TiliaFagus, Ostrya, Tilia
Magnolia, NyssaMagnolia, NyssaIn well-developed genera, E Asia=2x E No In well-developed genera, E Asia=2x E No AmericaAmerica
Diversity PatternsDiversity Patterns• The Challenges of The Challenges of
Demonstrating a Diversity Demonstrating a Diversity Anomaly: Anomaly: Scale Dependence & Scale Dependence & Environmental DifferencesEnvironmental Differences
• Empirical Results & Empirical Results & Interpretation: Interpretation: – Ricklefs, Qian & White 2004Ricklefs, Qian & White 2004– Qian & White, unpublished Qian & White, unpublished – Qian, Ricklefs & White 2004Qian, Ricklefs & White 2004
• CausesCauses
Similar Environments, different Similar Environments, different richness:richness:
A Diversity Anomaly!A Diversity Anomaly!
EAsia>ENAmerEAsia>ENAmer
1.3-2x as many species!1.3-2x as many species!
BUT these numbers depend on scale BUT these numbers depend on scale and range of latitudes!and range of latitudes!
Problem 1: Problem 1: Scale Scale dependence!dependence!
Diversity patterns Diversity patterns vary with grainvary with grain
Withers, Palmer, Withers, Palmer, Wade, White & Wade, White & Neal 1998Neal 1998
1,000 ha1,000 ha
1,000,000 ha1,000,000 ha
China extends China extends further S, more further S, more subtropical subtropical areaarea
Problem 2: Problem 2: Comparable Comparable environmenenvironments & ts & Latitudes!Latitudes!
But Latitude does not But Latitude does not equal climate or energy equal climate or energy availability.availability.
Problem 2: Problem 2: Comparable Comparable environmenenvironments & ts & Latitudes!Latitudes!
Both have Both have typical typical Latitudinal Latitudinal gradients in gradients in richnessrichness
Problem 2: Problem 2: Comparable Comparable environmenenvironments & ts & Latitudes!Latitudes!
Both have Both have typical typical Latitudinal Latitudinal gradients in gradients in richnessrichness
Suggestion Suggestion of of convergencconvergence Northwarde Northward
Problem 2: Problem 2: Comparable Comparable environmenenvironments & ts & Latitude!Latitude!
Latitude, Latitude, Climate Climate variables, variables, AET, PETAET, PET
Goals: Compare Goals: Compare E Asia & E No AmericaE Asia & E No America
• Total Angiosperm richness (not just Total Angiosperm richness (not just trees)trees)
• Account for environmental Account for environmental differences and Latitudinal gradientsdifferences and Latitudinal gradients– AET, PET (=Energy)AET, PET (=Energy)– Other Climate VariablesOther Climate Variables
• Account for scale dependenceAccount for scale dependence– AreaArea– Distance (N-S, E-W)Distance (N-S, E-W)
Ricklefs, Qian & White Ricklefs, Qian & White 20042004
• Excluded Japan, Taiwan, & Hainan to Excluded Japan, Taiwan, & Hainan to remove island effect on speciationremove island effect on speciation
• Area, maximum elevation, Latitude, Area, maximum elevation, Latitude, Jan temp, July temp, Summer precip, Jan temp, July temp, Summer precip, Winter precip, AET, PETWinter precip, AET, PET
• 32 floras E Asia; 82 floras E N 32 floras E Asia; 82 floras E N AmericaAmerica
• 6 fold range in richness6 fold range in richness
Ricklefs, Qian & White Ricklefs, Qian & White 20042004
• Question:Question:– After accounting for area and climate is After accounting for area and climate is
E Asia richer in Angiosperms than E No E Asia richer in Angiosperms than E No America?America?
• Results presented at 3 grain sizesResults presented at 3 grain sizes– 10-1010-1044 km km22
– 101044-10-1055 km km22 [Similar to Currie’s work] [Similar to Currie’s work]– 101055-10-1066 km km22
Ricklefs, Qian & White Ricklefs, Qian & White 20042004
After accounting for effect of Jan After accounting for effect of Jan temp, E Asia > E No America at all temp, E Asia > E No America at all scales, scales,
E Asia = 2 x E No America, rE Asia = 2 x E No America, r22=.679=.679
10-1010-1044 kmkm22
Area & Area & Jan temp Jan temp had had significansignificant effects, t effects, not AETnot AET
Ricklefs, Qian & White Ricklefs, Qian & White 20042004
Plot scalesPlot scales
0.1 ha0.1 ha
1 ha1 ha
???? ????
Ricklefs, Qian & White Ricklefs, Qian & White 20042004
Tree scaleTree scale
Plot scalesPlot scales
0.1 ha0.1 ha
1 ha1 ha
=1=1 ???? ????
Ricklefs, Qian & White Ricklefs, Qian & White 20042004
• 101044 to 10 to 1055 km km22 floras floras– Similar to grain size of Currie & colleaguesSimilar to grain size of Currie & colleagues– E Asia = 1.76 x E No America after accounting E Asia = 1.76 x E No America after accounting
for contributions of area and climate for contributions of area and climate variablesvariables
• 101055 to 10 to 1066 km km22 floras floras– E Asia = 1.32 x E No America after accounting E Asia = 1.32 x E No America after accounting
for contributions of area and climate for contributions of area and climate variablesvariables
• Continental scale (E Asia, comparable Continental scale (E Asia, comparable area in E No America)area in E No America)– E Asia = 1.4-2.5 x E No America, depending E Asia = 1.4-2.5 x E No America, depending
on latitudinal range includedon latitudinal range included
• E Asia is richer in Angiosperms E Asia is richer in Angiosperms than E No America at all observed than E No America at all observed grain sizes and after adjusting for grain sizes and after adjusting for climate variablesclimate variables
• There is indeed a richness There is indeed a richness anomaly!anomaly!
• AET not the best climate variableAET not the best climate variable
Ricklefs, Qian & White Ricklefs, Qian & White 20042004
ConclusionsConclusions
Qian & White, Qian & White, unpublishedunpublished
0
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ecie
s n
um
ber
Latit
ude
(º)
Log area in km 2
EASENA
(A) = Vascular plants, (B)=angiosperms
Qian & White, Qian & White, unpublishedunpublished
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ude
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Log area in km 2
EASENA
(A) = Vascular plants, (B)=angiosperms
Qian & White, Qian & White, unpublishedunpublished
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ude
(º)
Log area in km 2
EASENA
(A) = Vascular plants, (B)=angiosperms
Qian & White, Qian & White, unpublishedunpublished
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ecie
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um
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ude
(º)
Log area in km 2
EASENA
(A) = Vascular plants, (B)=angiosperms
Where are Where are the extra the extra species in E species in E Asia??Asia??
Within a forest?? Within a forest??
Between forests Between forests along local along local gradients??gradients??
Across larger Across larger geographic geographic areas??areas??
Where are Where are the extra the extra species in E species in E Asia??Asia??
Within a forest?? Within a forest??
Between forests Between forests along local along local gradients??gradients??
Across larger Across larger geographic geographic areas??areas??
Data lacking; Data lacking; Latham & Latham & Ricklefs forest in Ricklefs forest in JapanJapan
Where are Where are the extra the extra species in E species in E Asia??Asia??
Within a forest?? Within a forest??
Between forests Between forests along local along local gradients?? gradients??
Across larger Across larger geographic geographic areas??areas??
Data lacking; Data lacking; Latham & Latham & Ricklefs forest in Ricklefs forest in JapanJapan
Yes Yes
Yes Yes
Where are Where are the extra the extra species in E species in E Asia??Asia??
Within a forest?? Within a forest??
Between forests Between forests along local along local gradients??gradients??
Across larger Across larger geographic geographic areas?? areas??
Where are Where are the extra the extra species in E species in E Asia??Asia??
Within a forest?? Within a forest??
Between forests Between forests along local along local gradients??gradients??
Across larger Across larger geographic geographic areas??areas??
We now turn to We now turn to large scale large scale ββ diversitydiversity
Qian,Ricklefs & White Qian,Ricklefs & White 20042004• Angiosperm lists for 18 E Asian Angiosperm lists for 18 E Asian
floras & 25 E No American florasfloras & 25 E No American floras• Grain size= circle with 450 km Grain size= circle with 450 km
diameterdiameter– 411-1870 km apart in E Asia411-1870 km apart in E Asia– 342-1893 km apart in E No America342-1893 km apart in E No America– Chosen to approximate grain of Chosen to approximate grain of
Currie’s workCurrie’s work
• Computed similarity for pairs Computed similarity for pairs – Of similar latitude, for E-W Of similar latitude, for E-W ββ– Of similar longitude, for N-S Of similar longitude, for N-S ββ
Qian,Ricklefs & White Qian,Ricklefs & White 20042004
• Latitude, Jan temp, July temp, Latitude, Jan temp, July temp, diff(Jan, July temp), summer precip, diff(Jan, July temp), summer precip, winter precip, AET, PETwinter precip, AET, PET
• PCA to get 4 climatic axesPCA to get 4 climatic axes• Each flora represented by the Each flora represented by the
average of 5 data points for these average of 5 data points for these variablesvariables
• Sørensen’s Index, S = c/Sørensen’s Index, S = c/αα– Decreases exponentially toward 0 so Decreases exponentially toward 0 so
log transformed in analysislog transformed in analysis– ββ diversity = slope of ln(S) to distance diversity = slope of ln(S) to distance
Qian,Ricklefs & White Qian,Ricklefs & White 20042004
• Question: Question: – Is the higher richness of Angiosperms Is the higher richness of Angiosperms
in E Asia compared to E No America in E Asia compared to E No America the result not only of higher the result not only of higher mesoscale richness (inventory mesoscale richness (inventory diversity) but also of higher diversity) but also of higher ββ diversity (differentiation diversity)?diversity (differentiation diversity)?
Qian,Ricklefs & White Qian,Ricklefs & White 20042004
East-west
Distance (km)
0 500 1000 1500 2000
North-south
Distance (km)
0 500 1000 1500
Nat
ural
log
of S
oren
sen'
s in
dex
(lnS
)
-2.5
-2.0
-1.5
-1.0
-0.5
0.0 E No AmericaE No America
E AsiaE Asia
Qian,Ricklefs & White Qian,Ricklefs & White 20042004
East-west
Distance (km)
0 500 1000 1500 2000
North-south
Distance (km)
0 500 1000 1500
Nat
ural
log
of S
oren
sen'
s in
dex
(lnS
)
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
ββ diversity diversity N-S > E-WN-S > E-W
EAsia > E No EAsia > E No AmericaAmerica
E No AmericaE No America
E AsiaE Asia
Qian,Ricklefs & White Qian,Ricklefs & White 20042004
East-west
Distance (km)
0 500 1000 1500 2000
North-south
Distance (km)
0 500 1000 1500
Nat
ural
log
of S
oren
sen'
s in
dex
(lnS
)
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
N-S EAsia = 2.5x E No AmericaN-S EAsia = 2.5x E No America
E-W EAsia = 3x E No AmericaE-W EAsia = 3x E No America
E No AmericaE No America
E AsiaE Asia
rr22 = .888 = .888
rr22 = .876 = .876
rr22 = .803 = .803
rr22 = .653 = .653
Qian,Ricklefs & White Qian,Ricklefs & White 20042004
East-west
Distance on PC1
0 1 2 3 4 5 6 7
North-south
Distance on PC1
0 1 2 3 4 5 6
Nat
ural
loga
rithm
of
Sor
ense
n's
inde
x (lnS
)
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
Multiple regression showed distance Multiple regression showed distance & climate equally important for N-S & climate equally important for N-S but distance > climate for E-Wbut distance > climate for E-W
E No AmericaE No America
E AsiaE Asia
2 Explanations of species richness 2 Explanations of species richness patternspatterns
11stst Pillar: Energy-Diversity Theory Pillar: Energy-Diversity Theory
22ndnd Pillar: Historic Biogeography Pillar: Historic Biogeography
Species richness is a Species richness is a function of the function of the constraints of time & constraints of time & space.space.
Species richness is self-limiting, Species richness is self-limiting, in equilibrium with in equilibrium with environment (energy environment (energy availability), & convergent in availability), & convergent in similar environments (at similar similar environments (at similar energies).energies).
Energy-Diversity Theory
AETAET
Tre
e S
pp
Tre
e S
pp
Currie & Paquin 1987
Nature 329, 326-327
Energy-Diversity Theory
AETAET
Tre
e S
pp
Tre
e S
pp
Currie & Paquin 1987
Nature 329, 326-327We did find We did find
an effect of an effect of Jan Temp Jan Temp and other and other Latitudinal Latitudinal correlates correlates but AET was but AET was not the best not the best predictor.predictor.
Energy-Diversity Theory
Currie & Paquin 1987
Nature 329, 326-327
AETAET
Tre
e S
pp
Tre
e S
pp
We studied We studied a narrower a narrower range of range of AET.AET.
Energy-Diversity Theory
Currie & Paquin 1987
Nature 329, 326-327
AETAET
Tre
e S
pp
Tre
e S
pp
We found a We found a strong region strong region effect for effect for residual residual variation. variation. Geographic Geographic turnover turnover contributes to contributes to this region this region effect. effect.
The critical role of similarity & nesting
Why a Why a single grain single grain size doesn’t size doesn’t tell the full tell the full story and story and the the distance distance decay of decay of similarity is similarity is important.important.
Diversity Patterns• The Challenges of
Demonstrating a Diversity Anomaly: Scale Dependence & Environmental Differences
• Empirical Results & Interpretation: – Ricklefs, Qian & White 2004– Qian & White, unpublished – Qian, Ricklefs & White 2004
• Causes
Causes• Richness = Speciation -
Extinction• -Extinction:
Europe > E No America > E AsiaPleistocene effects
• +Speciation:E Asia > E No America
Topographic complexity (incl. Islands)Tropical connectionCenter of Origin (time)
Fossil EvidenceFossil Evidence
GinkgoGinkgo
MetasequoiaMetasequoia
MagnoliaMagnolia LiriodendronLiriodendron
NyssaNyssa TsugaTsuga
Extinction AND speciation
InferencesInferencesEnergy-Diversity theory lacks a Energy-Diversity theory lacks a
mechanism but richness does mechanism but richness does decline with Latitude…something is decline with Latitude…something is going on here but it doesn’t have going on here but it doesn’t have to be energy or its surrogates!to be energy or its surrogates!
Historical factors & spatial template Historical factors & spatial template add lots of variationadd lots of variation
Speciation seems more important Speciation seems more important than Extinction but both have than Extinction but both have added to Asian bias in richnessadded to Asian bias in richness
Recent molecular work supports Recent molecular work supports greater branch lengths in vicariant greater branch lengths in vicariant taxa in Asian of same agetaxa in Asian of same age
Narrow Endemism in the Southeast
Venus Fly Trap -- Dionaea muscipula
"The fairest bloom the mountain knows Is not an iris or a wild rose But the little flower of which I'll tell Known as the brave acony bell.” From "Acony Bell", by Gillian Welch & David Rawlings
Oconee Bell -- Shortia galacifolia
Pinkshell Azalea
Rhododendron vaseyi
Tsuga caroliniana Tsuga canadensis
Torreya taxifolia
Franklinia -- Franklinia -- Franklinia alatamahaFranklinia alatamaha
erectum
similevaseyi
catesbaei
grandiflorum
undulatum
Trillium
Trilliums of the N
--Case & Case 1997
Trilliums of the MW
Trilliums of the SE 1
Trilliums of the SE 2
Trilliums of the SE 3
Species richness – 10000 ha
Floras of North America Project
Palmer, Neal, Withers, Wade, White
Continental Diversity Gradients
AFTERAFTER WE CORRECT FOR WE CORRECT FOR AREAAREA
AND THE NORTHWARD AND THE NORTHWARD DECLINE IN TOTAL SPECIES DECLINE IN TOTAL SPECIES RICHNESS,RICHNESS,
AFTERAFTER WE CORRECT FOR WE CORRECT FOR AREAAREA
AND THE NORTHWARD AND THE NORTHWARD DECLINE IN TOTAL SPECIES DECLINE IN TOTAL SPECIES RICHNESS,RICHNESS,
IS THE SOUTH ENRICHED IN IS THE SOUTH ENRICHED IN ENDEMICS COMPARED TO THE ENDEMICS COMPARED TO THE NORTH?NORTH?
2.6
2.7
2.8
2.9
3
3.1
3.2
3.3
3.4
3.5
3.6
4.5 5 5.5 6 6.5Log(Area)
Log(
Spec
ies)
Log(area)
NS
Log
(S
pec
ies)
2.6
2.7
2.8
2.9
3
3.1
3.2
3.3
3.4
3.5
3.6
4.5 5 5.5 6 6.5Log(Area)
Log(
Spec
ies)
Log(area)
NS
Log
(S
pec
ies)
% G1G3
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
4.4 4.6 4.8 5 5.2 5.4 5.6 5.8Log(Area)
%G1
G3
SN
% G1G3 X Area
Log(Area)
% G
1G3
North American EcoregionsEastern Forests
data from WWF reports
• Latitude, Richness & Endemism:– 4 taxa in 14 Aquatic ecoregions:
•Fish, Mussels, Crayfish, Herps
– 7 taxa in 24 Terrestrial ecoregions:•Amphibians, Snails, Birds, Mammals,
Reptiles, Butterflies, Vascular Plants
30o
40o
50o
60o
70o
N Latitude
24
Terrestrial Ecoregions
70o
60o
50o
40o
30o
N Latitude
14
Aquatic Ecoregions
Birds
Mammals
Richness % Endemism
Richness % Endemism
30 40 50 60 70 80
Latitude
0
200000
400000
600000
800000
1000000
Km
2Area v. Latitude
Terrestrial Ecoregions
30 40 50 60 70
Latitude
0
400000
800000
1200000
Km
2Area v. Latitude
Freshwater Ecoregions
Data Manipulations
Rosensweig’s Correction for Areac = S/(A.18)
Rescaled to 0 to 1
Organisms have different traits in relation to time ...
And space ...
Terrestrial EcoregionsVasc Plants, Amphibians,
Reptiles, Butterflies, Landsnails
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
30 40 50 60 70 80 90
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
30 40 50 60 70 80 90
Richness %Endemism
30 N Latitude 80 30 N Latitude 80
Aquatic EcoregionsFish, Crayfish, Mussels,
Herps
0
10
20
30
40
50
60
70
80
30 40 50 60 70 80 900
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
30 40 50 60 70 80 90
Richness % Endemism
30 N Latitude 80 30 N Latitude 80
Summary of Latitudinal Patterns
• 10 of 11 groups 17-25% decrease per 10 degr. N Latitude (Reptiles steeper)
• Decline in endemism is 5-75 x steeper than richness
• Well-marked in groups with low dispersal and freshwater habitats that are naturally isolated
Glacial Boundary
% Endemism
UnglaciatedGlaciated
T-Landsnails 25.5 1.6T-Amph 9.8 0A-Crayfish 59.0 0A-Mussels 18.6 0A-Fish 14.6 1.0A-Herps 7.1 0.3
Even for birds & mammals…
% of the High Peak Region of NC-TN% of the High Peak Region of NC-TN
in Great Smoky Mts NP (5% of the in Great Smoky Mts NP (5% of the area)area)
95
70
55
18
49
32
23
0
10
20
30
40
50
60
70
80
90
100
1
Floristic Category
Pe
rce
nt
Common Native Occaisional Rare G3 G2 G1
G1G2
G3
Rare
Native
Common
27%28%
28%
16%
Rare Vascular Plants of the Southern Rare Vascular Plants of the Southern AppalachiansAppalachians
A
Why richer in endemism?
1. Decay in place model (Freshwater turtles in the SE, Stephens & Wiens 2003)
2. Legacy of past change for poor dispersers (Cain et al. 1998)
3. Isolation, selection, founder effects or hybridization in refugia
4. Selection by repeated glaciation for dispersal and wide environmental tolerance (resistance to extinction and speciation, Dynessius & Jansson 2000)
% G1G3
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
4.4 4.6 4.8 5 5.2 5.4 5.6 5.8Log(Area)
%G1
G3
SN
% G1G3 X Area
Log(Area)
% G
1G3
Distance Decay -- State Grain Size E-W
1.6
1.65
1.7
1.75
1.8
1.85
1.9
1.95
0 0.5 1 1.5 2 2.5
Distance (1000 km)
Log(
Jacc
ard'
s Si
mila
rity)
Distance (1000 km)
Similarity x DistanceSN
Summary?