Brian P. Kinlan 1 Collaborators: Dan Reed 1, Pete Raimondi 2, Libe Washburn 1, Brian Gaylord 1, Patrick Drake 2 1 University of California, Santa Barbara 2 University of California Santa Cruz The Metapopulation Ecology of Giant Kelp in the Northeast Pacific

Photo: K. Lafferty

I. WHAT IS A METAPOPULATION? II. CASE STUDY: METAPOPULATION DYNAMICS IN SOUTHERN CA KELP FORESTS? III. REGIONAL VARIATION IV. CONCLUSIONS

2. CONNECTIVITY 1. PATCHINESS

3. TURNOVER 2. CONNECTIVITY 1. 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

I. WHAT IS A METAPOPULATION? II. CASE STUDY: METAPOPULATION DYNAMICS IN SOUTHERN CA KELP FORESTS? III. REGIONAL VARIATION IV. CONCLUSIONS

32.5ºN 33.6ºN Data courtesy of L. Deysher, T. Dean & Southern California Edison Newport Beach Pt. Loma La Jolla Kelp Bed Dynamics ( )

Reed, Kinlan, Raimondi, Washburn, Gaylord & Drake, In press, Marine Metapopulations (P.F. Sale & J. Kritzer, eds.) METHODS – Identifying Habitat Long-term Kelp Distribution

METHODS – Defining Patches >500 m Bed 28 Bed 27 Patch 17 Patch 18 Patch 16 Patch 19

– 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 Lat Location Carmel Bay Pt.Buchon Pt.Purisima Coal Oil Pt. Palos Verdes San Onofre Pt.Loma Pta.San Jose Pta.San Carlos METHODS – 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 b) Time 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 Lat Location 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

METHODS - 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(Occupied  Extinct) Prob(Colonization) = P(Extinct  Occupied)

Year Fraction of patches occupied (%) Patch Occupancy Reed et al., In press (Marine Metapopulations – P.F. Sale, ed.)

P(Extinction) Relative frequency (%) P(Recolonization) Relative frequency (%) Extinction and Recolonization Probabilities

Extinction & Persistence Times

r 2 = 0.05, p = 0.06 r 2 = 0.15, p < PATCH SIZE Extinction/recolonization dynamics weakly related to patch size

Metapopulation Criteria PATCHINESS TURNOVER CONNECTIVITY??

Nearest-neighbor distance (km) Relative frequency (%) Radius (km) Mean number of patches within radius (± 1 SD) Spatial arrangement of patches

Estimated Dispersal Distance (m) Percent of Trials Individual Plants Kelp bed Reed et al., In press; D.C. Reed & P.T. Raimondi, unpubl. data Empirical Dispersal Profiles

Distance from individual plant (m) Spores 2.5 mm -2 (+/- SE) Distance from edge of kelp bed (m) Reed et al., In press; D.C. Reed & P.T. Raimondi, unpubl. data Empirical Settlement Curves

15 Jan – 15 Feb Frequency (%) Naples Carpinteria east west Along-shore current speed (m ● s -1 ) June Frequency (%) east west 40 Reed et al., In press; D.C. Reed, P.T. Raimondi & L. Washburn, unpubl. data Modeling Connectivity Using Real Ocean Current Data Real 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) IndividualKelp bedIndividualKelp bed Minimum Maximum Mean

Distance (km) Percent dispersing at least distance X Percent of interpatch distances less than X Carpinteria - Jan/Feb Carpinteria - June Naples - June Naples - Jan/Feb Numerical Model of Spore Dispersal Gaylord et al Ecology 83: ; Gaylord et al J. Marine Systems 49:19-39 Currents measured in vicinity of kelp bed:

(Using Currents for Carpinteria, June) Weak Source: Strong Source: Relative Frequency 0% % 40% 60% 80% 100% x c = 2.4 km 0% % 40% 60% 80% 100% x c = 0.14 km # of Connected Patches (50 th percentile) (90 th percentile) Prediction: Connectivity Variable, But Possible

Empirical Test of Connectivity: Isolation Index I j = isolation of patch j L i = area of patch i T = month D i,j = distance from patch j to patch i at closest point at closest point

r 2 = 0.57, p < r 2 = 0.39, p < ISOLATEDCONNECTEDISOLATEDCONNECTED Extinction & Colonization Rates Strongly Influenced by Connectivity “RESCUE EFFECT”

I. WHAT IS A METAPOPULATION? II. CASE STUDY: METAPOPULATION DYNAMICS IN SOUTHERN CA KELP FORESTS? III. REGIONAL VARIATION IV. CONCLUSIONS

San Francisco U.S. Mexico Los Angeles Pta. Eugenia CENTRAL SOUTHERN BAJA

Canopy Biomass by Region Central Southern Baja

% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Date Fraction of Patches Occupied (%) Patch Occupancy Central Southern Baja

ISOLATEDCONNECTED Isolation Effect Central Southern Baja E C E C E C

I. WHAT IS A METAPOPULATION? II. CASE STUDY: METAPOPULATION DYNAMICS IN SOUTHERN CA KELP FORESTS? III. REGIONAL VARIATION IV. CONCLUSIONS

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 metapopulation model likely to be applicable more often than not. Q: Where do Macrocystis populations fall on the spatial population dynamics spectrum? Persistence of Most Stable Patch

NASA Kelp Forest Dynamics Study

Modeling Framework Desired features: Spatial Dynamic Predictive Assimilative

Modeling Framework Grid Patch

Biomass dynamic –Production: B T+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?

What if the frequency of ENSO changes?

Scenario Analysis