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Bryce Maxell, Interim Director / Senior Zoologist (406) 444-3655 bmaxell@mt

http://mtnhp.org. Mapping Black-tailed Prairie Dog Colonies Across Montana Using the National Agriculture Imagery Program (NAIP) 2005 Imagery. March 13 th 2010, Great Falls, Montana. Bryce Maxell, Interim Director / Senior Zoologist (406) 444-3655 bmaxell@mt.gov

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Bryce Maxell, Interim Director / Senior Zoologist (406) 444-3655 bmaxell@mt

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  1. http://mtnhp.org Mapping Black-tailed Prairie Dog Colonies Across Montana Using the National Agriculture Imagery Program (NAIP) 2005 Imagery March 13th 2010, Great Falls, Montana Bryce Maxell, Interim Director / Senior Zoologist (406) 444-3655 bmaxell@mt.gov Scott Blum, Biologist / Information Specialist Karen Walker, Biological Data System Coordinator

  2. Montana’s Conservation Plan forBlack-tailed and White-tailed Prairie Dogs Objective #2 - develop statewide and regional prairie dog distribution and abundance standards - Inventory and monitor distribution and abundance - 7 km complexes of 5,000, 1,000-5,000, and <1,000 acres - 1.5 km complexes of 5,000, 1,000-5,000, and <1,000 acres (Biggins et. al. 2006) Objective #3C – identify isolated praire dog colonies in need of special consideration, assess their needs, and implement special management tasks, as appropriate

  3. Weaknesses in Current Spatial Representation Datum Shift?

  4. Weaknesses in Current Spatial Representation Missed Town

  5. Weaknesses in Current Spatial Representation • Shifted PolygonsMissed ColoniesGround Mapping Limitations (can’t see the town for the burrows)

  6. National Agriculture Imagery Program • Administered by USDA Farm Service Agency • 4 bands of information (red, green, blue and near infrared) gathered during growing season in continental U.S. to yield both natural color and color infrared imagery • Acquired at 1-meter ground sample distance or resolution (i.e. each pixel = 1 square meter) • Horizontal accuracy = 6 meters • Montana first flown in 2005 (available in 2006) • MT flown again in 2009 (available March 4, 2010) • Add 2009 NAIP to ArcMap under ArcGIS Server Connection http://gisservice.mt.gov/arcgis/services/

  7. Goals • First step toward evaluating use of NAIP imagery for digitizing prairie dog colonies • Statewide spatial representations for areas with recent evidence of prairie dog activity for environmental reviews • Summaries of colonies and complexes by various administrative units • Identification of complexes for management and potential Black-footed Ferret reintroduction using both 7 km and 1.5 km rules

  8. Methods 1 • Use existing point and polygon data to create a Maxent predictive distribution model • Stratify a network of 717 20 km x 20 km grid tiles into high, medium, and low density areas • Test mapping effort on a random selection of 92 20 km x 20 km grid tiles • For each tile, blindly evaluate 1 hectare grid cells for evidence of recent prairie dog activity (code = 1) using 2005 NAIP color and IR, MaxEnt model, slope model, and black and white DOQQ imagery at scales between 1:5,000 and 1:30,000 (1:10:000 seemed to work best) • Turn on existing point, polygon, and flight data and evaluate against grid cells turned on • Revaluate areas without recent evidence recorded and if evidence is detected (code = 2)

  9. Maxent Model for Black-tailed Prairie Dogs Black Points = current point observations and colony centroids Model is a logistic surface varying from 0 to 1. Warmer colors predict more suitable habitat

  10. Maxent Model Used to Develop Density Strata(Red = High, Green = Low, Blue = No Previous Documentation) * Grid Tiles are 20 km x 20 km

  11. Density Strata Relative to Existing Point Data(Red = High, Green = Low, Blue = No Previous Documentation) * Grid Tiles are 20 km x 20 km

  12. Pilot Mapping on Random Grid Cells(blue outline) * Grid Tiles are 20 km x 20 km

  13. Code = 1 for 1 Hectare Grid Cells on each Tile with Evidence of Recent Prairie Dog Activity

  14. Compare Grid Cell Coding Versus Points, Polygons, and Flight Lines at 20x20 km scale

  15. Compare Grid Cell Coding Versus Points, Polygons, and Flight Lines at 20x20 km scale

  16. Code = 2 for Grid Cells That Second Review shows Evidence of Recent Activity Slight Discrepancy with 2008 Flight Line Missed on Initial Pass

  17. Flight Line, but No Burrows Evident

  18. Odd Mottling Not Coded as Recent Activity

  19. Beware of Hay Bales

  20. Initially Looks Possible, but on Side of Hill

  21. Burrows?

  22. Burrows?

  23. Difficult Landscape 1

  24. Difficult Landscape 2

  25. Difficult Landscape 3

  26. Problems with IdentifyingWhite-tailed Prairie Dog Colonies What are these white features?

  27. Methods 2 • Stitch tiles together • Dissolve adjacent grid cells into colonies • Apply 750, 1,500 and 3,500 meter buffers to identify 1.5, 3, and 7 km complexes • Calculate total area of complex • Code complexes by BLM Field Office, FWP Region, Tribal Reservation, Forest, and Stewardship • Evaluate complexes relative to Goals in Montana’s Conservation Plan • NEED TO EVALUATE ACCURACY WITH GROUND TRUTHING!

  28. Example for 1.5 and 7 km Complexes

  29. Potential Colony and Complex Summary • 8,852 potential colonies (2,598 of these corroborated with previous info) - 0 ≥ 5,000 acres - 22 between 1,000-5,000 acres - 8,830 ≤ 1,000 acres - smallest = 2.5 acres, largest = 2,945 acres • 289 of the 7 km complexes - 6 ≥ 5,000 acres - 16 between 1,000-5,000 acres - 267 ≤ 1,000 acres - smallest = 2.5 acres, largest = 397,086 acres • 1,032 of the 3 km complexes - 16 ≥ 5,000 acres - 42 between 1,000-5,000 acres - 974 ≤ 1,000 acres - smallest = 2.5 acres, largest = 109,883 acres • 2,474 of the 1.5 km complexes - 10 ≥ 5,000 acres - 73 between 1,000-5,000 acres - 2391 ≤ 1,000 acres - smallest = 2.5 acres, largest = 38,766 acres Note: Acres have not been verified with ground truthing and are certainly an overestimate of on-the-ground acres due to the 1 Ha mapping unit used in this effort and likely misidentification of other features as colonies.

  30. NAIP (Black)Old Points (Purple)2008 Flight (Red)

  31. Colony Stewardship(Private = Gray, Federal = Yellow, State = Blue, Tribal = Brown)

  32. 6 x >5,000 Acre 7 km Complexes

  33. 7 km 5,000 Acre Complex Stewardship(Private = Gray, Federal = Yellow, State = Blue, Tribal = Brown)

  34. 16 x >5,000 Acre 3 km Complexes

  35. 3 km 5,000 Acre Complex Stewardship(Private = Gray, Federal = Yellow, State = Blue, Tribal = Brown)

  36. 10 x >5,000 Acre 1.5 km Complexes

  37. 1.5 km 5,000 Acre Complex Stewardship(Private = Gray, Federal = Yellow, State = Blue, Tribal = Brown)

  38. Colony Size Class Distribution

  39. 7 km Complex Size Class Distribution

  40. 3 km Complex Size Class Distribution

  41. 1.5 km Complex Size Class Distribution

  42. Summary byFWP Region *Totals are greater than total number of colonies and total acreage because some colonies are split between FWP Regions.

  43. Summary byBLM Field Office *Totals are greater than total number of colonies and total acreage because some colonies are split between BLM Office.

  44. Summary byTribal Reservation

  45. Summary byUSFS District

  46. Summary by County *Some colonies are split between counties so sum of colonies and acreages here will exceed total no. & acreage of colonies.

  47. Isolated Colony Near Grey Cliff SE of Big TimberConservation Issues? Opportunities for Research?

  48. Suggested Uses and Future Work • Do not use acreage values from this assessment • Evidence of recent activity ≠ presence • Use with previous points and polygons when possible • Use polygonal layer of colonies in environmental reviews and broad scale planning, but note the need to evaluate individual polygons on the ground • Not useful for White-tailed Prairie Dog colonies • Ground truth random selection of previously unconfirmed colonies to evaluate overall mapping accuracy (2005 and 2009) • Ground truth unconfirmed colonies outside current known range • Ground truth unconfirmed colonies on upper Missouri upstream of Craig and those that are very isolated • Ground truth and update mapping for portions of large complexes (use 2009 NAIP and GPS info)

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