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

Grain: Grain: αα,,γγ,,δδ

Extent: Extent: ββ

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

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

αα, γ, δ, γ, δ

ααCommunityCommunity

α, α, γγ, δ, δ

ααLandscapeLandscape

α, γ, α, γ, δδ

ααRegionRegion

ββSmall ExtentSmall Extent

ββLandscapeLandscape

ββGradientGradient

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 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 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

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

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

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

Nature 329, 326-327

AETAET

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

Nature 329, 326-327

AETAET

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

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

1 2 3 4 5 6 7 8 9 10 11

Genera

EAsia ENoAmerica

Carpinus

Alnus PopulusMalus

Prunus

Sorbus

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

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

HamamelidaceaeHamamelidaceae

Clintonia, Torreya, Tsuga, Clintonia, Torreya, Tsuga, TrilliumTrillium

Acer, Cornus, Aesculus, CercisAcer, Cornus, Aesculus, Cercis

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.

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

• 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

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

Plot scalesPlot scales

0.1 ha0.1 ha

1 ha1 ha

???? ????

Tree scaleTree scale

Plot scalesPlot scales

0.1 ha0.1 ha

1 ha1 ha

=1=1 ???? ????

• 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

ConclusionsConclusions

Qian & White, Qian & White, unpublishedunpublished

Log area in km 2

EASENA

(A) = Vascular plants, (B)=angiosperms

Log area in km 2

EASENA

Log area in km 2

EASENA

Log area in km 2

EASENA

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

Between forests Between forests along local along local gradients?? gradients??

Data lacking; Data lacking; Latham & Latham & Ricklefs forest in Ricklefs forest in JapanJapan

Yes Yes

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

• 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)?

East-west

Distance (km)

0 500 1000 1500 2000

North-south

Distance (km)

0 500 1000 1500

0.0 E No AmericaE No America

E AsiaE Asia

East-west

Distance (km)

0 500 1000 1500 2000

North-south

Distance (km)

0 500 1000 1500

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

East-west

Distance (km)

0 500 1000 1500 2000

North-south

Distance (km)

0 500 1000 1500

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 AsiaE Asia

rr22 = .888 = .888

rr22 = .876 = .876

rr22 = .803 = .803

rr22 = .653 = .653

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

x (lnS

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 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 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).

AETAET

Nature 329, 326-327

AETAET

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.

Nature 329, 326-327

AETAET

We studied We studied a narrower a narrower range of range of AET.AET.

Nature 329, 326-327

AETAET

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

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?

4.5 5 5.5 6 6.5Log(Area)

Log(area)

4.5 5 5.5 6 6.5Log(Area)

Log(area)

% G1G3

4.4 4.6 4.8 5 5.2 5.4 5.6 5.8Log(Area)

% G1G3 X Area

Log(Area)

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

N Latitude

Terrestrial Ecoregions

N Latitude

Aquatic Ecoregions

Mammals

Richness % Endemism

30 40 50 60 70 80

Latitude

200000

400000

600000

800000

1000000

2Area v. Latitude

Terrestrial Ecoregions

30 40 50 60 70

Latitude

400000

800000

1200000

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

30 40 50 60 70 80 90

Richness %Endemism

30 N Latitude 80 30 N Latitude 80

Aquatic EcoregionsFish, Crayfish, Mussels,

30 40 50 60 70 80 900

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)

Floristic Category

Common Native Occaisional Rare G3 G2 G1

Native

Common

27%28%

Rare Vascular Plants of the Southern Rare Vascular Plants of the Southern AppalachiansAppalachians

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

4.4 4.6 4.8 5 5.2 5.4 5.6 5.8Log(Area)

% G1G3 X Area

Log(Area)

Distance Decay -- State Grain Size E-W

0 0.5 1 1.5 2 2.5

Distance (1000 km)

Similarity x DistanceSN

Summary?

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