Dawn Phillips' Intro to WILDSPACE 1996

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Species at Risk Data and Knowledge Management
within the WILDSPACETM Decision Support System
Harrisonburg, VA May 20, 2004 ISESS 2004
Isaac Wong, Phil Fong Environment Canada
National Water Research Institute Don McNicol,
Rich Russell, Robin Bloom, Angela Darwin Canadian
Wildlife Service Ontario Region Xiao Yun
Chen University of Guelph
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WILDSPACE/SARInformation Management Research

• Introduction to WILDSPACE/SAR
• Why Decision Support Systems?
• WILDSPACE/SAR Data Model
• Next-generation of WILDSPACE DSS
• DSS Habitat Modelling
• ? Recovery Planning
• ? Risk Management

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WILDSPACETM A Geospatial Integration of Diverse
Wildlife Survey and Ecological Information in
Ontario

• For over 30 years, CWS has studied wildlife in
  Ontario and beyond, some work spanning decades
  and covering large areas.

• To maintain the integrity of this information and
  facilitate its use, Project WILDSPACETM was
  initiated in 1996.

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(No Transcript)
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Project WILDSPACETM Components
Web
Decision Support
Geo-Referencing
Biological Data
Spatial Data
Metadata
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Desktop-based Decision Support
System Maps
User Maps
(program maps from CWS-OR partners)
(via import utility)
User Interface
System Metadata
(Windows desktop)
(via import utility)
User Data
System Data
(program data from CWS-OR partners)
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Biological Environmental Data Some Examples

• Wildlife Data
• e.g., counts, presence/absence ...
• e.g., bioassay, body burdens ...
• 7.1 million records _at_ 112,000 locations

• Environmental/Habitat Data
• e.g., vegetation, air/water quality,
  weather/climate ...
• 6 million records _at_ 1.27 million sites

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Species at Risk Information Needs

• Species abundance and distribution
• Species life history and vital rates
• Habitat mapping
• Threats
• Population modelling
• Socio-economic and political considerations
• Other sources of data local knowledge, expert
  opinion

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SAR Database Design Integrated
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SAR Database Design Principles

• Formalize knowledge and make it readily
  available
• Provide a framework for research and monitoring
• Best practices for database management to
  reduce error and maintenance needs
• Facilitate data mining, integration, and
  sharing
• Security features (access levels Internet,
  Extranet and Intranet)

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SAR Database Design Entity Relationship Tables
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Input Interface of the SAR DBMS
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Species taxonomy and related Program information
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Species at Risk Site survey log
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Species at Risk Residence monitoring log
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Decision Support Processes

• Data collection/addition
• QA/QC (filtering)
• Data Storage
• Analysis modelling
• Scenario gaming
• Visualization reporting of results

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Species at Risk Modelling

• Objective To predict patterns of a species
  occupancy on the basis of habitat patch quality,
  site fidelity and local population density in the
  previous year.
• Approach
• given a known number of individuals in a
  population determine the probability of occupancy
  of each patch of available habitat.
• distribute individuals of the population randomly
  throughout the set of habitat polygons and have
  the rate of movement within the set of habitat
  patches be based on breeding evidence, site
  fidelity and neighbourhood effects

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Input data

• Population size
• Sex ratio
• Mean time lag (days)
• Length of breeding season (days)
• Number of iterations in simulation
• Habitat polygons and attributes visible area
  index (VAI), occupancy history
• Habitat centroids and attributes northing,
  easting, occupancy
• Starting points

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Habitat Selection Simulation
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Select Landscape Parameters
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Likelihood of Occupancy
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Species at Risk Decision Support
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CWS-OR (WILDSPACETM) Schematic Diagram
Collaborative Data Management in support of SARA
lt Intranet gt
lt Internet gt
Firewall
WILDSPACETM DSS On the Web
Firewall
Firewall (VPN)
lt Extranet gt
WILDSPACETM DSS Version 3 (Desktop)
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Conclusion
Data Integration WILDSPACETM open architecture
facilitates use of resident datasets external
data on the fly (shapefiles databases) Data
Visualization and Summarization mapping
modelling output Multi-scale Investigation of
populations habitat (continental to
local) Multi-species Coordination a common
analytical framework for mapping of occurrences
project areas among taxa Quantify Program
Indicators trend analyses Scenario Analysis
simulations of wildlife responses to habitat loss
alteration Data security/update
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Thank youQuestions?