Giant Kelp Canopy Cover and Biomass from High Resolution SPOT Imagery for the Santa Barbara Channel...

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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
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Transcript of Giant Kelp Canopy Cover and Biomass from High Resolution SPOT Imagery for the Santa Barbara Channel...

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 (r2 = 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 99.9th%-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

r2 = 0.98p < 1*10-7

Kelp Occupation Frequency Jan 2006- May 2007

• 8 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

NDVITransform

Validation: Biomass

r2 = 0.71p < 1*10-7

y = 14.33x - 0.13

r2 = 0.54p < 1*10-7

Regional Kelp Biomass

• Created from biomass-NDVI relationship for areas of kelp cover

Nov. 2004: 15000 tonnes

Nov. 2006: 7800 tonnes

April 2007: 22350 tonnes

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5000

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15000

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25000

Dec-05 Mar-06 Jun-06 Sep-06 Dec-06 Mar-07 Jun-07

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Biomass Along SB Coastline

Seasonal kelp biomass changes at Mohawk

Comparison of SPOT vs. Kelco Biomass Data

r2 = 0.73p < 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

Kelp Ecological Process Forcing Factor Method of Assessment Kelp cover & biomass change

- SPOT & Landsat imagery

Extinction Swell wave stress Hourly observations of swell wave height along the 10 m isobath from CDIP

Spore dispersal Currents HF radar data from PISCO & SBC-LTER. Bottom mounted ADCP observations (SBC-LTER)

Colonization Substrate suitability Sidescan mapped fields of substrate type available from CDFG – also collaboration w/ USGS

Colonization Bathymetry CDFG-high resolution gridded bathymetry (200m horizontal, 1m vertical) & Sidescan fields (2m horiz)

Productivity Background light limitation MODIS incident PAR & Kd490 imagery tuned using SBC-LTER & PnB observations

Productivity Nutrient limitation MODIS/AVHRR SST imagery & SST/Nutrient relationships from SBC-LTER & PnB observations

Productivity & colonization Sediment variability SPOT & MODIS (250 m) imagery of total suspended solids (also collaboration w/ USGS)

Kelp extinction Wind stress Winds from NDBC buoys 46053, 46054, 46069 & 46063 (ndbc.noaa.gov)