Marine Mammal and Vessel Distribution in the Santa Barbara Channel Islands

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Marine Mammal and Vessel Distribution in the
Santa Barbara Channel Islands

• TEAM BOB
• Jeremy Freund
• Shanna Jowers
• Alma Sanchez
• Sara Smith

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Reserve Program Background

• Purpose of Reserves
• protecting and sustaining Channel Islands marine
  resources
• achieve sustainable fisheries
• Marine Reserves Working Group
• various public interests
• planned reserve locations and boundaries within
  existing Marine Protected Areas
• different perspectives represented
• Reserves implemented April 2003

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Research Questions

• How have marine mammal and vessel distributions
  around the Channel Islands changed over time?
• What changes have taken place within the Marine
  Reserve boundaries?
• How have mammal and vessel densities changed in
  the State Marine Reserves (SMRs)?

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Objectives

• Map and analyze distributions of mammals and
  vessels around the islands
• Perform spatial and temporal analysis of
  distributions
• Analyze trends within SMR boundaries
• Assess appropriateness of Reserve locations

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Hardware Software

• Windows based PC
• ArcGIS 8.3 spatial data mapping and analysis
• MS Excel XP tabular calculations, regression,
  statistical analysis
• Macromedia Fireworks, Flash graphic design, map
  layout
• ArcInfo Workstation projection, coverage
  manipulation, clipping

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Data Acquisition and Importing

• Data obtained from NOAA in tabular format
• Point sighting data in lat/long coordinates for
  seven years
• Each record represents one location and time
• 3 sighting fields per record, created challenge
  for mapping and analysis
• Original Data Import Process
• Converted tabular data to Dbase (.dbf) format
• Import x,y data to point shapefile
• Created windows compatible date field and
  imported as temporal data using ESRIs Tracking
  Analyst

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ArcGIS Data Model

• Point Data mammal and vessel sightings
• Originally shapefiles
• Converted to point coverages for analysis
• Reserve polygons
• shapefile
• California Political
• Coverage, for projection purposes
• Grid Data
• Analysis results
• All data converted to coverages to perform
  projection in Arc Workstation and back to
  original format

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Data Organization Approach

• Descretize time continuum
• Separate yearly layers
• Separate layers for mammals and vessels
• Result large number of layers required
• Separate data by mammals and vessels (species)
• Symbology to represent time
• Second, third sighting fields added as separate
  layers according to 1. and 2.
• Decision was made to omit as number of layers
  became unmanageable (gt 50 layers)

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Meta Data

• Geodetic Model
• Ellipsoid Name WGS_1984
• Semi-major Axis 6378137.000000
• Denominator of Flattening Ratio 298.257224
• Bounding coordinates
• In decimal degrees
• West -120.570684
• East -118.960375
• North 34.143228
• South 33.411325
• In projected or local coordinates
• Left 920033.250000
• Right 1067421.000000
• Top -30942.005859
• Bottom -112349.867188

• Projection
• Map Projection Name Albers Conical Equal Area
• Standard Parallel 29.500000
• Standard Parallel 45.500000
• Longitude of Central Meridian -119.696997
• Latitude of Projection Origin 34.419998
• False Easting 1000000.000000
• False Northing 0.000000
• Planar Coordinate Information
• Planar Distance Units meters
• Coordinate Encoding Method coordinate pair
• Coordinate Representation
• Abscissa Resolution 0.000256
• Ordinate Resolution 0.000256

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GIS Operations

• Queries
• Create specialized layers
• Conversions
• Workstation used for most conversions (ArcToolbox
  does not propagate projection during conversions)
• Toolbox used for conversion from coverage to
  shapefiles after projection problems solved

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GIS Operations (ctd.)

• Select by location
• Point in polygon procedure for SMRs
• Spatial Analyst
• RGB Density surfaces
• Tracking Analyst - temporal analysis
• Data clocks
• Temporal animations

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Other Software Operations

• Excel used for majority of analysis
• Density calculations
• Density trending analysis (including charting,
  regression)
• Data organization by SMR, year

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Density Analysis

• Neighborhood density calculated, plotted in RGB
  for first, middle and last years
• Identifies spatial distribution of points over
  time
• Discretized density maps generated for each year
• Demonstrates distribution within SMRs over time

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Trend Analysis

• Density compiled for each SMR polygon
• Linear regression performed on scatter plot of
  density vs. time (yearly)
• Slope of regression line classified
• Highly positive slope indicates trend toward
  higher densities in later years, or objects
  entering polygons
• Negative slope indicates higher densities in
  earlier years, or object leaving polygons

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Vessel Distribution Trends for Marine Protected
Areas
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Mammal Distribution Trends for Marine Protected
Areas
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Temporal Analysis

• Performed with ArcGIS tracking analyst
• Requires extra temporal field conforming to
  windows regional standards
• Created animation and data clocks describing
  temporal trends

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Tracking Analysis Clocks
Mammals more sightings in winter, More trips in
2002? Vessels more sightings during summer
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Tracking Analysis AnimationMammals
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Tracking Analysis AnimationVessels
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Results Summary

• Overall distribution of mammals appears random
  throughout time
• Vessel distribution closer to islands (constant)
• Approximately half of the reserves show decrease
  in vessel density
• Judith Rock, Skunk Point, Painted Cave show
  increase in mammal density
• Santa Barbara, Painted Cave, South Point and
  Carrington Point show negative correlation
  (push/pull) between mammals and vessels

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Problems/Solutions
Problem 1
Problem 2
and more

• Solution
• Invent time machine
• Go back 10 years
• Learn Arc Workstation

Solution youre hosed Charles Deitzel
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Random Numbers
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Future Work

• Cluster analysis to determine any possible
  species clustering (nearest neighbor)
• 3d mapping to view location (x,y) vs. species
  type
• Analysis of species behavior trends in time and
  space