Applying GIS to Santa Cruz Island An Analysis

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Applying GIS to Santa Cruz Island: An Analysis of Intertidal Biodiversity clients. alexandria. ucsb.

Applying GIS to Santa Cruz Island: An Analysis of Intertidal Biodiversity clients. alexandria. ucsb. edu By: Carola Flores, Nic Galati, Jeff Overlock, and Heather Thakar-Hucks

Motivation • GIS offers new forms of data analysis and visualization Density estimation, kriging,

Motivation • GIS offers new forms of data analysis and visualization Density estimation, kriging, overlay, etc. • Multiple scientific disciplines can benefit from GIS applications Archeology, Biology, Ecology, Geology, Oceanography, Geography, etc. • Wealth of existing data not yet applied to GIS SWAT (UCSC), PISCO (UCSB) team, Coastal Biodiversity Survey • Spatial relationships are key to understanding marine habitats Ecologic, environmental, and oceanographic variables that influence intertidal organism diversity and abundance

Main Objective • Perform a spatial analysis of intertidal ecology patterns on Santa Cruz

Main Objective • Perform a spatial analysis of intertidal ecology patterns on Santa Cruz Island • Understand if changes in the environment impact intertidal habitats Specific objectives • Map intertidal species density within ecological sites • Look for spatial patterns of intertidal species density • Compare and contrast relationship between density and environmental, ecological, and oceanographic variables among 6 sites • Look for potential causes and effects of the intertidal density variability

Methods • Density Estimation – The objective of Density Estimation Data set is interpreted

Methods • Density Estimation – The objective of Density Estimation Data set is interpreted as a collection of discrete objects • Estimation of point density – Formation of a field from set of discrete objects

cbsurveys. ucsc. edu

cbsurveys. ucsc. edu

Methods • Map area is based on 30 m baseline with 11 transects every

Methods • Map area is based on 30 m baseline with 11 transects every 3 m – Six site areas on Santa Cruz Island will be used to determine density of species per site • Discrete objects represented as x, y, and z coordinates along transects – Points contain number of species present at that location in the intertidal zone • Map will indicate spatial distribution of species density

Data Source Coastal Biodiversity Surveys on Santa Cruz Island PISCO (UCSB), SWAT (UCSC): a

Data Source Coastal Biodiversity Surveys on Santa Cruz Island PISCO (UCSB), SWAT (UCSC): a large-scale marine research program that focuses on understanding the nearshore ecosystems of the U. S West Coast.

Data set Point Contact data • Non-mobile species • Classification table data Quadrat data

Data set Point Contact data • Non-mobile species • Classification table data Quadrat data • Mobile species • Classification table data Swath data • Sea star presence or absence

Data set • Santa Cruz Island sea surface temperature data • Average site temperature

Data set • Santa Cruz Island sea surface temperature data • Average site temperature • Digital Elevation Model of each ecological site and of Santa Cruz Island

Problems 1. Data size. 2. Large data sets from 10 years of intertidal surveying

Problems 1. Data size. 2. Large data sets from 10 years of intertidal surveying may 3. become difficult to work with considering 4. the time given to work on the project. 2. Sampling area Since data sets are from just six ecological sites of Santa Cruz Island, the number of samples might not represent the density pattern of Santa Cruz’s intertidal species. 3. Uncertainty Data to be used has fine-scale multiple measurements. Due to the complex spatial distribution of species diversity in the intertidal, to portray an accurate digital representation could be a challenge.

Anticipated results 1. Different areas of density within each ecological site. Possibly due to

Anticipated results 1. Different areas of density within each ecological site. Possibly due to the location of the species habitat in the intertidal zone (high, medium or low zone). 2. Geo-spatial gradient in density among all ecological sites. 3. On a bigger scale, this spatial distribution could be 4. due to environmental factors such as sea surface 5. temperature gradients.

clients. alexandria. ucsb. edu

clients. alexandria. ucsb. edu