Aquatic Gap Analysis and Biodiversity Management

1
Iowa Aquatic Gap Modeling Fish Distributions in
Iowa Rivers
Robin L. McNeely2, Anna K. Loan-Wilsey1, Patrick
D. Brown2, Kevin L. Kane2, and Clay L. Pierce3
1Department of Natural Resource Ecology and
Management, Iowa State University, Ames, Iowa
2GIS Facility, Iowa State University, Ames, Iowa
3USGS, Iowa State University, Ames, Iowa
Upper Iowa River Saukenuk Paddlers Canoe Kayak
Club
Chimney Rock, Upper Iowa River Saukenuk Paddlers
Canoe Kayak Club
Aquatic Gap Analysis and Biodiversity Management
Aquatic Gap Goals

• Provide a standardized base layer for sample
  locational accuracy
• Characterize aquatic biodiversity throughout Iowa
  at the regional, watershed, and valley segment
  scales
• Identify the extent to which current management
  efforts are conserving aquatic biodiversity in
  Iowa at the regional, watershed, and valley
  segment scales
• Help to direct management, protection,
  restoration, and educational efforts within
  Iowas river resources
• Prioritize conservation efforts
• Provide easy accessibility to all information

Developing a Data Layer of Valley Segment Types

• Purpose
• Delineate distinct stream environments
• Serve as the backbone for analyzing
  conservation status of stream segments
• Protocol
• The Nature Conservancys Aquatic Community
  Classification Framework
• Based on ecoregions and watersheds aka
  EcoDrainage Units (EDUs)

Example of a Distinct Valley Segment Type
River Size Medium Flow Perennial
Temperature Warm Gradient Moderate Soil
Texture Fine Size Discrepancy Low Link
Category Moderate Elevation Category Medium
Subregion Central Plains
Analysis Process
Step 2 Generate predicted distributions for
fish species from modeling criteria. These
results are analyzed with terrestrial GAP
stewardship data to show to what extent a species
is protected on publicly owned or managed land.
Phase 1
Step 1 Assign attribute values to reaches and
run statistical analyses to determine which
attributes describe variability. Analyses are
performed for each of the 155 species to
determine modeling criteria.
NHD
Step 3 Assess the relative conservation status
of each valley segment type using stewardship
data. Develop initial conservation priorities for
fish species, valley segments, and watersheds
(quality and quantity).
Draft
Fish Community Database

• Objectives
• Create one database that would give electronic
  access to all historic riverine fish sampling
  data in Iowa
• Geographically link each community collection to
  the National Hydrography Dataset (NHD) and to
  appropriate Hydrologic Units using GIS

Phase 2
Predictive Distribution Modeling Process
Step 4 Identify valley segments and watersheds
(HUC 8,10 and 12) which are biologically
significant and of relatively high quality.

• Database Design
• AGAP staff either directly transferred or
  manually entered data obtained into a Microsoft
  Access relational database consisting of separate
  but related tables that contain three primary
  elements
• information about the collector and collection,
  including IBI if available
• information about the location of each sample
• information about the species collected
• By using a unique numeric identifier for each
  sample, a direct relationship back to the
  original data is ensured, allowing other
  information not captured in our database to be
  retrieved by future investigators.

State Fish Species List
Turkey River Watershed
Species Point Distributions and Range Maps Plot
Species Point Locations Assign species to HUC
8 Expert Review of Ranges
Fish Community Database Data Collection Database
Creation Shapefile Generation
Expert Review

Predictive Distribution Models Use sampled reach
values for predictor variables as input to
decision tree. For each species, a statement will
be created of values for each predictor variable.

• Data Gathering Methods
• To be comprehensive in data gathering, several
  methods were used to locate riverine fish
  records. These strategies included
• visiting 15 Iowa DNR offices and field stations
  across Iowa to acquire field notes and reports
• literature searches using bibliographies, print
  and electronic database indexes and abstracts,
  and library catalogs to acquire published
  literature, dissertations and government reports
• acquiring museum collection records through
  web-accessible database searches as well as
  direct contact with curators
• directly contacting individual fisheries
  investigators to acquire unpublished field notes

Predicted Distributions ArcMap will be used to
select relevant values for each predictor
variable per fish and the selected reaches will
be the predicted distribution for that fish.
Fish Database Summary
Fish Sample Locations
The AGAP Team Kevin Kane, Co-PI AIT GIS
Facility, ISU, kkane_at_iastate.edu Clay Pierce,
Co-PIDept. Natural Resource Ecology and
Management, ISU, cpierce_at_iastate.edu Patrick
Brown, AGAP Web InterfaceAIT GIS Facility, ISU,
patrickb_at_iastate.edu Robin McNeely, AGAP
Hydrographic Base Layer AIT GIS Facility, ISU,
mobes_at_iastate.edu Anna Loan-Wilsey, Aquatic
Habitat BiologistDept. Natural Resource Ecology
and Management, ISU, awilsey_at_iastate.eduPlease
visit the following web pages for more
information about Aquatic Gap Analysis IRIS and
Aquatic GAP - maps.gis.iastate.edu/iris Iowa Gap
Analysis - www.iowagap.iastate.edu National Gap
Analysis - www.gap.uidaho.edu/gap
Final Products / CreditsThe Iowa Aquatic Gap
Analysis Program will publish a final report
explaining the biodiversity status of breeding
fish species in the state. In conjunction with
this biodiversity analysis, an atlas of fish
species will also be published. The documents
will be available on CD and on the Iowa Aquatic
GAP website in Adobe Acrobat .pdf format. The
GIS datasets used to create the stewardship and
aquatic species layers will be available for
downloading via ftp service. This same GIS data
will be available for interactive viewing and
querying over the Internet using ESRIs Internet
Map Server software. Credits Iowa State
University Iowa Dept. of Natural
Resources Missouri Resource Assessment
Partnership National Gap Analysis Program

• 10,992 sampling sites
• 155 fish species sampled
• All 99 counties sampled
• 1884-2002 sampling date range
• 169 individual sources of data
• Over 3200 unique stream reaches
• 100 8-digit HUCs sampled
• 92.1 10-digit HUCs sampled
• 73.2 12-digit HUCs sampled