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Allen Brandt, UW Stevens Point GIS Center & College of Natural Resources
Aquaculture is one of the fastest growing food production systems in the world.The aquaculture industry in Wisconsin,
comprised of approximately 2,000 registered fish farms, contributes over $7 million to the state’s economy annually.
There are many species of game, food, and bait fish cultivated throughout the state in a variety of production systems. In
recent years, the growth of the aquaculture industry in Wisconsin has slowed and the number of registered fish farms is
beginning to decrease.The reason for the decrease in fish farms is not known, but it could be from the tough economic
times, high costs of production, limited markets, environmental restrictions, or the site location of the fish farms.The
objective of the study is to determine if the site location characteristics play a part in the success of the fish farm
operation.The utilization of Geographic Information Systems (GIS) to create an evaluative model examining the
environmental and socio-economic characteristics of current registered fish farms and those that have closed.The
characteristics considered are land cover, soil types, elevation, water quality and source, and proximity to infrastructure
and potential markets.The evaluative model will then be used to create a predictive model using a multi-criteria
evaluation procedure using a GIS.The predictive model will be able to determine suitable locations for sustainable
system-specific and species-specific aquaculture facilities.

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  • Picture needed? Maybe the WAA logo? Or a fish
  • Aquaculture is the cultivation of aquatic organisms in a controlled environment for food or natural resource enhancement. Farms need to be registered with Department of Agriculture, Trade, and Consumer Protection. Must renew annually. Recreational ponds can be registered, but not needed. Saves money and inconvenience. WI 5th state for production Rainbow trout. From 2007-2008 was $170,000 in trout production. In 2009 73 new farms but 91 2008 registered farms out. The reason for the decrease is not known but may be from tough economy, high cost of production, limited markets, environmental restrictions or site location of farms. Aquaculture allows fish to be produced without harming the wild fish populations.
  • I may possibly add to this section to make it sound better.
  • The picture is of a flow-through in Alaska. If you know/find of one in WI change picture. I may also have a good pic from WI just need to look
  • Pic is from Nelson and Pade Aquaponics in Montello WI
  • A pic or two of the species
  • Louisiana for different kinds of aquaculture development and clarify development alternatives and feasibilities before investments in unsuitable areas.Do we need to define what GIS is and does?
  • Do we have data from the all the listed places. Also I put is being collect for the county data because 2 are still over $1000 and 1 is working on getting the data and 1 I am trying to get a response.
  • May have to reclassify the files into same coordinate system and format to work with overlay operations. Soil, water quality, source (springs, wells, diverted streams), elevation, slope, roads cities. Type of system, species of fish
  • Chi squared
  • Will be editing this map to have larger symbols to match second map
  • Predict based on water quality and source
  • There needs to be a smooth flow for this page.
  • Could be a different picture. If you know of a good one add it.

    1. 1. By: Allen Brandt and Jon GalloyUniversity of Wisconsin-Stevens Point WLIA Conference 2012
    2. 2. Outline Background  Aquaculture  GIS and Aquaculture Objectives Data Collection Methods Results  Current and Anticipated Future Work
    3. 3. Background Definition of aquaculture Fastest growing form of food production (NOAA) Wisconsin 2000+ registered fish farms  3 types of registered farms  Aquaculture production systems WI aquaculture contribute $7 mil. to economy  Presently there is a slow decline  Exact reason for decline is not known
    4. 4. Production Systems Three main production systems used  Ponds  Flow-Through  Recirculating Aquaculture System (RAS) Systems usually get water supply from wells and springs but can be obtained from other sources Each system varies in the intensity that is needed for managing and maintaining the system
    5. 5. Pond Production System Most common production system used Can vary in surface area size from ¼ acre to over 5 acres Normally have a varying depth from 2.5 feet to 7-8 feet Use a large amount of land Least intensive management needed
    6. 6. Flow-Through/Raceway System Continual flow of water through the system Rectangular in shape with a length:width:depth ratio of 30:3:1 Often used in cultivation of salmonids (salmon and trout) Is more intensive than the pond system
    7. 7. Recirculating AquacultureSystem (RAS) The water is recycled (filter) and put back into the system Requires more system components than ponds and raceways Usually located indoor and in smaller spaces Used for aquaponics Most intensive system to manage
    8. 8. Fish Species Cold-water species  Salmon and trout  < 60F Cool-water species  Walleye, perch, and northern pike  60—75F Warm-water species  Tilapia, sunfish, and bass  >75F
    9. 9. GIS’s Importance GIS and Aquaculture  One study estimated surface area and locations for catfish and crawfish in Louisiana  Looked at soil and slope of sites  In Arizona, a study looked at what characteristics are found at the aquaculture sites  Site Suitability Modeling Process by National Oceanic and Atmospheric Administration (NOAA)  Used in comparing locations for mariculture based on economic and environmental characteristics.
    10. 10. Objectives Determine if site location characteristics of aquaculture operations are significant for determining success or failure of commercial operations in Wisconsin Locate areas in watershed sites in the state that have suitable characteristics for successful fish farms
    11. 11. Data Collection County GIS data is being collected from the County offices  Data obtained includes: parcels, zoning, land use, hydrology, and orthophotos Fish farm location data was obtained from the Department of Agriculture Trade and Consumer Protection(DATCP) Other needed data has been gather from the US Geological Survey, WI Dept. of Natural Resource, SSURGO, and WI Dept. of Transportation
    12. 12. Methods Create an evaluative model from fish farms site location characteristics The model will determine important characteristics  Environmental  Land cover/use, hydrology, parcel ownership…etc.  Socio-economic  Proximity of infrastructure and markets Result will identify and classify best to worst site characteristics of fish farms
    13. 13. Methods Create a predictive model for the state using the characteristics from the evaluative model ArcGIS multi-criteria evaluation to make predictive model  Using weighted overlays for data layers Predictive model will be able to indicate locations by production system or species by thermal range  Weighting data layers that are important for each category
    14. 14. Methods Compare predictive model to actual aquaculture farms  Using parametric and spatial correlation statistics  To ascertain initial validity Model accuracy used to determine predictive power
    15. 15. Example Scoring Scheme, Adams CountyKsat Permeability Score %Slope Score Soil Score pH Score Texture (Soil)0.0-.01 Very Low 5 0-1% 1 Sand 1 <=5 0 Clay Loam0.01-.1 Low 4 2-4% 2 Sandy 1 6-9 1 Clay0.1-1 Mod. Low 3 5-7% 1 Clay 1 >=10 01-10 Mod. High 2 >=8% 0 Clay 2 Loam10-100 High 1 Silty Clay 2 Loam100-705 Very High 0 Silty Clay 3 All 0 Others**Includes: Sand, Loamy Sand, Sandy Loam, Loam, Silt Loam, Silt
    16. 16. Soil Scores, Adams County, WI Ksat(permeability) Soil texture pH Clay content
    17. 17. Slope Scores, Adams County, WI Idealized slopes for siting between 2-4% Important consideration in pond construction
    18. 18. Combined Scores, Adams County, WI Ksat(permeability) Soil texture pH Clay content Slopes
    19. 19. Fish Farm Sites, Adams County, WI Scores for fish farms ranged from 1-4 based on the combined soils and slopes Reflects importance of water source
    20. 20. Predicting Watersheds from Distance Predicted watersheds suitable for fish farms based on distance markets Markets broken down into 3 population classes  Market Class A population ≥10,000 and < 50,000  Market Class B ≥ 50,000 and < 100,000  Market Class C ≥ 100,000 Separate watersheds based on fish farms status  Open = registered in 2011  Closed = not registered in 2011 Calculated distance to five closest markets in each class from the mean center of watersheds
    21. 21. Predicting Watersheds from Distance Depicts location of # 0 watersheds with open and closed # 0 fish farms and # 0 # 0 # # 0 0# 0 # 0# 0 # 0 # 0 ## 0 location of market # 0 ## 00 0 ## # 00 0 ## # # 0 #0 00 0 classes # 0 Market Class A >10,000 & < 50,000 # 0 # 0 # 0 # 0 # 0 # 0 # 0 Market Class B >50,000 & < 100,000 # 0 # ## 0 00 # ## 0 00 # 0 Market Class C #0# # # ### 0 0 0 0 ##0 # 0#0 # 0 ## 00 0## 00 >100,000 # # # 000# 0 0 0 ##0 #0 0 0# Watersheds with # 0 # 0 # # 0 0 # 0 open fish farms # 0 Watersheds with closed fish farms # 0
    22. 22. Predicting Watersheds from Distance Located watersheds without prior fish farms with a closer distance than watersheds with closed fish farms The average distance to Market Class A was 22.7 mi. for open watersheds and 44.4 mi. for closed watersheds For Markets B and C the difference between average distance was small with 94.9 mi (B) and 156.3 mi (C) for open watersheds and 100 mi (B) and 159.2 mi (C) for closed watersheds The model was able to predict 46 watersheds a suitable distance from markets
    23. 23. Predicting Watersheds from Distance Location of suitable watersheds Located in southeast portion of the state
    24. 24. Anticipated Results Predictive Model will be system-specific and species- specific  It will evaluate potential fish farm sites throughout WI based on watersheds The model will hopefully aid in success of new aquaculture facilities in the state  Predict what system/species should be sited based on several characteristics Anticipate pond and flow-through systems to have higher predictive ability than RAS
    25. 25. Future Work Complete the evaluative model Complete the predictive model using the evaluative model Conduct a random sample of farm visits to gain more information on factors of success
    26. 26. After Completion Predictive Model will be available to public  Through Wisconsin Aquaculture Association, WI DNR, WI DATCP, UWSP- NADF, Midwest Tribal Aquaculture Network, UW Extension
    27. 27. AcknowledgmentsProject Advisors Dr. Chris Hartleb Dr. Keith Rice Doug MiskowiakGIS Data WI Dept. of Agriculture, Trade & Consumer Protection, Wisconsin County LIO’s, Surveyors, and Land Records personalFunding for this project was provided by theNOAA/Sea Grant programs, project #R/SFA5.
    28. 28. Questions?