Giant Kelp Canopy Cover and Biomass from High Resolution SPOT Imagery for the Santa Barbara Channel Kyle C Cavanaugh, David A Siegel, Brian P Kinlan, Dan C Reed

Macrocystis pyrifera High economic and ecologic importance –“ecosystem engineer” Kelp abundance highly dynamic –Avg. frond life: 3-5 months –Ave. plant life: 2-3 years –Growth rates up to 0.5 m/day

Macrocystis growth and mortality Growth and mortality regulated by water temp, nutrients, depth, bottom type, predation, wave action Nice model system for the study of a number of interesting ecological theories Kelp biomass data from Kelco visual estimates; Fish observations from Brooks et al 2002

Previous surveys Aerial visual canopy biomass estimates by ISP Alginates (monthly from 1958; entire coast) CDFG 2m resolution aerial surveys using NIR imagery (annual from 2002-present; entire coast) LTER SCUBA transects (monthly for 3 SBC kelp beds from 2002-present) Scale issues…

Research goals 1.Expand spatial and temporal resolution of kelp canopy cover and biomass datasets using high resolution satellite imagery 2.Use this data to model kelp population dynamics in relation to patch size, connectivity, and biophysical forcing

Research Area

Remote Sensing of Macrocystis Surface canopy of giant kelp exhibits typical vegetation spectral signature (red-edge) –Low red reflectance –high near infrared (NIR) reflectance Canopy biomass well correlated to entire forest biomass (r 2 = 0.92)

SPOT Imagery Well suited to differentiate kelp –Spectral bands in the green, red, NIR, SWIR –10 m resolution

SPOT Imagery Datasets 1.Canopy Cover 2.Biomass

Methods: Canopy Cover Principal components analysis calculated for kelp habitat (0-60 m depths) PC band 1 PC band 2 False color SPOT image (8/15/2006) Positive contribution from all 3 bands Glint, sediment loads, atmosphere variations, etc. High NIR, low green and red reflectance Kelp

Methods: Canopy Cover Classification Minimum kelp threshold value selected from 99.9 th %-tile value of offshore (35-60 m) pixels

Validation: Canopy Cover Cover measurements compared with high resolution 2004 CDFG aerial kelp survey SPOT: Oct 29, 2004 CDFG: Sept-Nov 2004 r 2 = 0.98 p < 1*10 -7

Kelp Occupation Frequency Jan May image dates 39% of occupied pixels were present in at least half the scenes ~4% of pixels were present across all dates

Previous metapopulation analyses (Reed et al 2006) Kelp is highly dynamic Patch isolation positively correlated with extinction rates, negatively correlated with colonization rates

Biomass Data More useful for understanding and modeling ecosystem interactions –Turnover rates, export, NPP, etc. Difficult to measure directly –Time and effort intensive

SBC-LTER SCUBA Measurements of Frond Density and Biomass Monthly SCUBA measurements of frond density and biomass made at Arroyo Quemado (AQUE), Arroyo Burro (ABUR), and Mohawk (MOHK) kelp beds. Limited spatial scale

Seasonal kelp biomass changes along 3 LTER transects Maximums in late 2002 Wave driven seasonality apparent

Role of Biomass in NPP Reed et al (in press): initial biomass explains 63% of inter-annual variation in net primary production (NPP) Surprisingly, growth rate was insignificant in explaining variation in NPP Remote measures of biomass would be valuable for making regional estimates of NPP

Methods: Biomass Normalized Difference Vegetation Index (NDVI) (NIR-RED) (NIR+RED) Calculated for areas of kelp cover NDVI Transform

Validation: Biomass r 2 = 0.71 p < 1*10 -7 y = 14.33x r 2 = 0.54 p < 1*10 -7

Regional Kelp Biomass Created from biomass-NDVI relationship for areas of kelp cover Nov. 2004: tonnes Nov. 2006: 7800 tonnes April 2007: tonnes

Seasonal kelp biomass changes at Mohawk

Comparison of SPOT vs. Kelco Biomass Data r 2 = 0.73 p < 1*10 -7

Population Dynamics Modeling Persistence, extinction, and biomass changes of kelp patches as a function of size, connectivity, and biophysical factors –High spatial resolution kelp maps will allow us to include effects of sea temperature, nutrients, wave energy, substrate, light attenuation, spore production and dispersal

Assessing the role of forcing processes