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Organizing the Upper Missouri Aquatic GAP Project (UMR-GAP)

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Organizing the Upper Missouri Aquatic GAP Project (UMR-GAP) Jonathan A. Jenks, Chad J. Kopplin, Steven S. Wall, Charles R. Berry, Jr., and Vickie J. Smith. – PowerPoint PPT presentation

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Title: Organizing the Upper Missouri Aquatic GAP Project (UMR-GAP)


1
Organizing the Upper Missouri Aquatic GAP Project
(UMR-GAP)
Jonathan A. Jenks, Chad J. Kopplin, Steven S.
Wall, Charles R. Berry, Jr., and Vickie J.
Smith. Department of Wildlife and Fisheries
Sciences and South Dakota Cooperative Fish and
Wildlife Research Unit, South Dakota State
University, Brookings, South Dakota
2
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3
  • UMR-GAP Four Broad Steps
  • Coordination
  • Attributing
  • Modeling
  • GAP Analysis

4
UMR-GAP Coordination
  • What data is needed for the project?
  • 2. Who has the data that is needed?
  • 3. How can we get the data that is needed?

5
CONTACTED AGENCIES Alberta Environment
Sustainable Development, Alberta Fisheries
Management Information Systems, University of
Alberta, Alberta Fish and Wildlife Service,
Alberta Geological Survey, Natural Resources of
Canada, Geological Survey of Canada, Department
of Fisheries and Oceans (Canada), Montana Rivers
Information Systems, Montana COOP Research Unit,
Montana Gap Analysis Project, Saskatchewan Mines
and Energy, Saskatchewan Conservation Data
Center, Saskatchewan Environment and Resource
Management, University of Regina (Sask.), Wyoming
Gap Analysis Project, University of Wyoming,
Wyoming COOP Research Unit, Wyoming Geographic
Information Sciences Center, Wyoming Game and
Fish Dept., Wyoming Natural Diversity Database,
Wyoming NRCS, North Dakota Game and Fish
Department, North Dakota NRCS, North Dakota Gap
Analysis Project, University of North Dakota,
EROS Data Center, South NRCS, East Dakota Water
Development District, South Dakota Geological
Survey, Environmental Protection Agency,
6
DATA SETS OBTAINED FOR THE UPPER MISSOURI AQUATIC
GAP PROJECT
7
UMR-GAP Attributing
  • Find a method that suits the needs of the
  • project
  • Fix known errors and problems in the data sets
  • (e.g., Braided Streams)
  • Match layers across political boundaries
  • (e.g., Geology)
  • Classify the valley segments on a regional
  • level

8
Steps for Attributing Streams for the Upper
Missouri Aquatic GAP Project
  • Run TNC tools that determine d-link, link, stream
    order
  • Temperature Baileys Ecoregions
  • Stream size, size discrepancy From d-link, link
    and stream order MoRAP/TNC procedures
  • Floodplain reach slope generated from DEM
    MoRAP procedures
  • Relative gradient DEM and stream length (NHD)
    MoRAP procedure
  • Geology 1500,000 surficial geology States and
    Provinces
  • Ground water delivery DEM and surficial geology
    for glaciated landscapes Michigan Rivers
    Inventory (MRI) Darcy model.
  • Flow NHD files USGS.
  • Connectivity to lake NHD files TNC Tools
  • Elevation DEM USGS EROS Data Center

9
River Reach Attributes and Valley Segment Types
(VST)
Temperature (Cold,Warm) 1, 2 Stream Size
(Hdwater,Creek, SR,LR) 1, 2, 3,
4 Flow (Perm., Intermit.) 1,
2 Geology (Alluv,TD,COW,ESD,Till,S
Q) 1, 2, 3, 4, 5, 6 Gradient
(L,M,H) 1, 2, 3 Ground Water Potential
(L,M,H) 1, 2, 3 Size Discrepancy
(None SRLR) 1, 2, 3, 4, 5, 6 Floodplain
(Yes, No) 1, 2 Upstream Connectivity
(P,SS, SL) 0, 1, 2 Downstream Connectivity
(P,SS,SL) 0, 1, 2 Valley Segment
Code 2121131211
10
Progress of Attributing the Stream files
11
Map of the Surficial Geology for the Upper
Missouri Aquatic GAP Project
12
UMR-GAP Modeling
  • Model Known VST
  • Model VST predicted from Known VST
  • Model VST from the Habitat Affinity Database
  • Produce the model distribution by watershed
  • and by VST

13
SD Aquatic GAP Fish Species Model
14
SD Aquatic GAP Fish Model by VST
15
Example of a SD Aquatic GAP Potential Distribution
16
Example of a SD Aquatic GAP Potential
Distribution Map
17
PREDICTIVE MODELING FOR SOUTH DAKOTA AQUATIC GAP
  • Predictive valley segment models were completed
    for 98 fish species
  • Models predicted potential valley segments for
    each fish species
  • Potential watershed distribution maps were
    developed for 116 species

18
UMR GAP Analysis
  • Analyze the valley segment by management status
    and owner(from the Stewardship layer)
  • Analyze the 11 digit watersheds by status and
  • by owner
  • Analyze species richness by status and owner
  • Analyze VS richness by status and owner
  • Analyze Aquatic richness by status and owner
  • (Aquatic richness species VS)
  • Establish Conservation Priorities based on the
  • results of the above analyses
  • Accuracy assess the final models

19
South Dakota Land Status was used to Assess
Distribution of Protection of Aquatic Habitat
20
South Dakota Land Stewardship was used to
Attribute Ownership of Valley Segments
21
Gap Analysis (Protection in Status 1 and 2) of
11-digit watersheds for the SD Aquatic GAP
22
SD Aquatic GAP fish that have gt10 Protection
23
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26
Developing Conservation Priorities for South
Dakota
These 5 preserves increase protection for land
cover types and 68 mammalian species (17 of
special concern), but the 10 requirement is not
met for all classes with only 5 sites.
27
Fish sampling to assess the accuracy of our
models
28
Nowood Creek, WY with Historic Fish Locations
29
Beaver Creek, ND and Elm River, ND and SD with
Historic Fish Locations
30
  • UMR-GAP Model Improvements
  • Surrogate Model of Intermittency
  • Water Quality Conditions
  • (Temperature, Erodible soils)
  • Land use effects
  • Use EDUs to adjust the predictions to
    account for systemic effects on fish species

31
Acknowledgments
We would like to thank our funding agency, USGS,
BRD, GAP Scott Sowa, Mike Morey, and Gust Annis
from MoRAP for the procedures and
collaboration on problems encountered. Jonathan
Higgins, Mary Lammert, Tom Fitzhugh from the
Nature Conservancy for the procedures used on
this project.
32
Richness of Valley Segments per 11-digit HU
within the Bad River Ecoregional Drainage Unit
33
Ownership of Valley Segment Type 21232021103
within an 11-Digit Hydrologic Unit within the Bad
River Ecoregional Drainage Unit
34
Breakdown of Valley Segment Type by Ownership for
an 11-Digit Hydrologic Unit within the Bad River
Ecoregional Drainage Unit
lt4.3 of valley segment type in higher than
Status 4 designation. None of this valley
segment type is highly conserved (Status 1 or 2).
35
Ownership of Valley Segments within the Bad River
Hydrologic Unit
36
Valley Segment Types in Status 1 within the Bad
River Ecoregional Drainage Unit
37
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38
North Dakota Fish Distribution Points
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