Brian P. Kinlan 1 Collaborators: Dan Reed 1, Pete Raimondi 2, Libe Washburn 1, Brian Gaylord 1,...

Brian P. Kinlan1

Collaborators: Dan Reed1, Pete Raimondi2, Libe Washburn1, Brian Gaylord1, Patrick Drake2

1University of California, Santa Barbara2University of California Santa Cruz

The Metapopulation Ecology ofThe Metapopulation Ecology ofGiant Kelp in the Northeast PacificGiant Kelp in the Northeast Pacific

Photo: K. Lafferty

I. WHAT IS A METAPOPULATION?I. WHAT IS A METAPOPULATION?

II. CASE STUDY: METAPOPULATION II. CASE STUDY: METAPOPULATION DYNAMICS IN SOUTHERN CA KELP DYNAMICS IN SOUTHERN CA KELP FORESTS?FORESTS?

III. REGIONAL VARIATIONIII. REGIONAL VARIATION

IV. CONCLUSIONSIV. CONCLUSIONS

2. CONNECTIVITY2. CONNECTIVITY

1. PATCHINESS1. PATCHINESS

3. TURNOVER3. TURNOVER

2. CONNECTIVITY2. CONNECTIVITY

1. PATCHINESS1. PATCHINESS

Modified from Hanski & Gilpin 1997

Persistence of Most Stable

Patch

Dispersal Distance (Relative to Interpatch Distance)

“Classic”(Levins)

Metapopulation

Patchy Population

Mainland-Island

Non-Equilibrium(headed for extinction)Low (Most patches

have some probability of extinction >> 0)

High (some patches, generally very large,

have virtually no probability of

extinction)Source-sink?Classic, stable

population

32.5ºN

33.6ºN

N

EW

S

Data courtesy of L. Deysher, T. Dean & Southern California Edison

Newport Beach

Pt. Loma

La Jolla

Kelp Bed Dynamics (1967-1999)Kelp Bed Dynamics (1967-1999)

Reed, Kinlan, Raimondi, Washburn, Gaylord & Drake, In press, Marine Metapopulations (P.F. Sale & J. Kritzer, eds.)

METHODS – Identifying Habitat METHODS – Identifying Habitat Long-term Kelp DistributionLong-term Kelp Distribution

METHODS – Defining PatchesMETHODS – Defining Patches

>500 m

Bed 28

Bed 27

Patch 17

Patch 18

Patch 16

Patch 19

– 1000

– 100

– 10

– 0Canopy Biomass(tons/km coast)

36.5°N

35.9°N

35.3°N

34.7°N

34.4°N

34.1°N

33.7°N

33.4°N

32.6°N

32.0°N

31.5°N

30.9°N

30.5°N

29.6°N

LatLocation

Carmel Bay

Pt.Buchon

Pt.Purisima

Coal Oil Pt.

Palos Verdes

San Onofre

Pt.Loma

Pta.San Jose

Pta.San Carlos

METHODS – Estimating TurnoverMETHODS – Estimating Turnover

Raw data provided by D. Glantz, ISP Alginates, Inc. & Santa Barbara Coastal LTER

Kelp canopy biomass, 34-year monthly time series

Historical Kelp Forest Dynamics

AUTOCORRELATION MODEL:48% noise Scale < 1 month27% stochastic patchiness Scale ~4 months9% stochastic patchiness Scale ~ 4 years9% stochastic patchiness Scale ~ 12 years3% annual periodicity Period ~ 1 year4% decadal periodicity Period ~ 20 years

b) Time

AUTOCORRELATION MODEL:28% noise Scale < 10 km39% stochastic patchiness Scale ~30 km21% stochastic patchiness Scale ~150 km6.5% mesoscale periodicity Period ~100 km5.5% regional periodicity Period ~330 km

c) Space

– 1000

– 100

– 10

– 0

Canopy Biomass(tons/km coast)

36.5°N

35.9°N

35.3°N

34.7°N

34.4°N

34.1°N

33.7°N

33.4°N

32.6°N

32.0°N

31.5°N

30.9°N

30.5°N

29.6°N

LatLocation

Carmel Bay

Pt.Buchon

Pt.Purisima

Coal Oil Pt.

Palos Verdes

San Onofre

Pt.Loma

Pta.San Jose

Pta.San Carlos

Interpolated Canopy Biomass Estimates Interpolated Canopy Biomass Estimates

METHODS - Turnover CriteriaMETHODS - Turnover Criteria

•EXTINCT if biomass = 0 for for previous 6 months or more

In any given month, all patches in an administrative unit are considered …

•OCCUPIED if biomass >0

Prob(Extinction) = P(OccupiedExtinct)

Prob(Colonization) = P(ExtinctOccupied)

1970 1975 1980 1985 1990 1995 20000

10

20

30

40

50

60

70

80

90

100

Year

Fra

ctio

n o

f pa

tche

s oc

cup

ied

(%)

Patch OccupancyPatch Occupancy

Reed et al., In press (Marine Metapopulations – P.F. Sale, ed.)

0 0.08 0.16 0.24 0.320

10

20

30

40

50

P(Extinction)

Rel

ativ

e fr

eque

ncy

(%)

0 0.08 0.16 0.24 0.320

10

20

30

40

50

P(Recolonization)

Rel

ativ

e fr

eque

ncy

(%)

Extinction and RecolonizationExtinction and RecolonizationProbabilitiesProbabilities

0 2 4 6 8 10 12 14 160

10

20

30

40

50

60

Extinction Duration (Years)

Rel

ativ

e fr

eque

ncy

(%)

0 2 4 6 8 10 12 14 160

10

20

30

40

50

60

Persistence Time (Years)R

elat

ive

freq

uenc

y (%

)

Extinction & Persistence TimesExtinction & Persistence Times

r2 = 0.05, p = 0.06 r2 = 0.15, p < 0.001

PATCH SIZE

Extinction/recolonization dynamics Extinction/recolonization dynamics weakly related to patch sizeweakly related to patch size

Metapopulation CriteriaMetapopulation Criteria

PATCHINESS

TURNOVER

CONNECTIVITY??

0 2 4 6 8 10 12 140

10

20

30

40

50

60

70

Nearest-neighbor distance (km)

Rel

ativ

e fr

eque

ncy

(%)

1 10 100 10000

10

20

30

40

50

60

70

Radius (km)

Mea

n nu

mbe

r of

pat

ches

w

ithin

rad

ius

(± 1

SD

)

Spatial arrangement of patchesSpatial arrangement of patches

Estimated Dispersal Distance (m)

1 10 100 1000

100

80

60

40

20

0

Per

cent

of T

rials

Individual Plants

1 10 100 1000

Kelp bed

100

80

60

40

20

0

Reed et al., In press; D.C. Reed & P.T. Raimondi, unpubl. data

Empirical Dispersal ProfilesEmpirical Dispersal Profiles

0 10 20 30 40 50 60

Distance from individual plant (m)

0

10

20

30

40

Spo

res

2.5

mm

-2 (

+/-

SE

)

0 50 100 1500

20

40

60

80

100

Distance from edge of kelp bed (m)

Reed et al., In press; D.C. Reed & P.T. Raimondi, unpubl. data

Empirical Settlement CurvesEmpirical Settlement Curves

15 Jan – 15 Feb 2002

0 0.2 0.40.4 0.20

40

10

20

30

Fre

quen

cy (

%)

Naples

Carpinteria

eastwest

Along-shore current speed (m ● s-1)

1 - 30 June 2002

0

10

20

30

0 0.2 0.40.4 0.2

Fre

quen

cy (

%)

eastwest

40

Reed et al., In press; D.C. Reed, P.T. Raimondi & L. Washburn, unpubl. data

Modeling Connectivity UsingModeling Connectivity Using Real Ocean Current DataReal Ocean Current Data

Table 1: Mean, minimum and maximum values for currents and significant wave height for the individual plant and kelp bed experiments. Mean currents were calculated over the duration of each experiment

Current velocity(cm / s)

Significant wave height(m)

Individual Kelp bed Individual Kelp bed

Minimum 0.001 0.04 0.323 0.273

Maximum 8.007 1.797 1.172 0.801

Mean 1.075 0.413 0.697 0.501

0.0001 0.001 0.01 0.1 1 10 1000

20

40

60

80

100

Distance (km)

Per

cent

dis

pers

ing

at le

ast

dist

ance

X

0

20

40

60

80

100

Per

cent

of

inte

rpat

ch d

ista

nces

less

tha

n X

Carpinteria - Jan/Feb

Carpinteria - June

Naples - JuneNaples - Jan/Feb

Numerical Model of Spore DispersalNumerical Model of Spore Dispersal

Gaylord et al. 2002 Ecology 83:1239-1251; Gaylord et al. 2004 J. Marine Systems 49:19-39

Currents measured in vicinity of kelp bed:

(Using Currents for Carpinteria, June)

Weak Source:

Strong Source:

Rel

ativ

e F

requ

ency

0%

0 1 2 3 4 5 6

20%

40%

60%

80%

100%x

c = 2.4 km

0%

0 1 2 3 4 5 6

20%

40%

60%

80%

100%x

c = 0.14 km

# of Connected Patches

(50th percentile)

(90th percentile)

Prediction: Connectivity Variable, But PossiblePrediction: Connectivity Variable, But Possible

Empirical Test of Connectivity: Empirical Test of Connectivity: Isolation IndexIsolation Index

IIjj = isolation of patch = isolation of patch jj

LLii = area of patch = area of patch ii

TT = month = monthDDi,ji,j = distance from patch = distance from patch jj to patch to patch ii

at closest pointat closest point

r2 = 0.57, p < 0.0001r2 = 0.39, p < 0.0001

ISOLATED CONNECTED ISOLATED CONNECTED

Extinction & Colonization RatesExtinction & Colonization RatesStrongly Influenced by ConnectivityStrongly Influenced by Connectivity

“RESCUE EFFECT”

N

EW

S

San Francisco

U.S.

Mexico

Los Angeles

Pta. Eugenia

CENTRAL

SOUTHERN

BAJA

Canopy Biomass by RegionCanopy Biomass by Region

Central

Southern

Baja

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 20020%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Date

Fra

ctio

n of

Pat

ches

Occ

upie

d (%

)

Patch Occupancy Patch Occupancy Central

Southern

Baja

ISOLATED CONNECTED

Isolation EffectIsolation Effect

Central

Southern

Baja

E

C

E

C

E

C

Modified from Hanski & Gilpin 1997

Dispersal Distance (Relative to Interpatch Distance)

“Classic”(Levins)

Metapopulation

Patchy Population

Mainland-Island

Non-Equilibrium(headed for extinction)

Source-sink?Classic single population

A: Context dependent, but A: Context dependent, but metapopulation model likely to be metapopulation model likely to be applicable more often than not.applicable more often than not.

Q: Where do Macrocystis populations fall on the spatial population dynamics spectrum?Q: Where do Macrocystis populations fall on the spatial population dynamics spectrum?

Persistence of Most Stable

Patch

NASA Kelp Forest Dynamics StudyNASA Kelp Forest Dynamics Study

Modeling FrameworkModeling Framework

Desired features:

Spatial

Dynamic

Predictive

Assimilative

Modeling FrameworkModeling Framework

Grid Patch

• Biomass dynamic– Production: BT+1 = f(∫Light, ∫Nutrients)– Loss: M=f(Waves[Substrate], Herbivory, Senescence/

Sloughing)

• Demographic– Density = f(Recruitment, Mortality)– Age/Size structure = f(?)– Fecundity = f(?)– Dispersal = f(Currents, Waves)– Recruitment = f(Light, Substrate, Nutrients(?))

Issues to Consider for first-stage (Grid-based) Model

• Decisions re: Biomass dynamic vs. Demographic aspects of model

• Linking Data/Observations to Model Elements

• Identify data gaps

• Consider scaling issues

Outputs of 6/4 Meeting?

0 2 4 6 8 10 12 14 16 18 20 22 24 26 280.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

0.8

Lag (years)

(S

emiv

aria

nc

e)ENSO scale = 2-6 yearsENSO scale = 8-24 years

What if the frequency of ENSO changes?What if the frequency of ENSO changes?

Scenario Analysis

S h o r t D i s p e r s e r L o n g D i s p e r s e r

Rel

ativ

e S

ettl

emen

t F

ract

ion

H

igh

EN

SO

Fre

qu

ency

S e t t l e m e n t u n d e r l o w E N S O f r e q u e n c y


Rel

ativ

e S

ettl

emen

t F

ract

ion

H

igh

EN

SO

Fre

qu

ency



Rel

ativ

e S

ettl

em

en

t F

rac

tio

n

Hig

h E

NS

O F

req

uen

cy



Rel

ativ

e S

ettl

em

en

t F

rac

tio

n

Hig

h E

NS

O F

req

uen

cy


Brian P. Kinlan 1 Collaborators: Dan Reed 1, Pete Raimondi 2, Libe Washburn 1, Brian Gaylord 1,...

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