Smorgasbord

GuSG Habitat Mapping- Habitat mapping is a critical element because habitat

loss and fragmentation is often the biggest threat to wildlife.

- Often habitat is mapped at landscape scale (i.e., 30 meter pixels), which generally isn’t accurate enough for local land managers.

- Best available GuSG mapping was not accurate enough and included some poor assumptions.

• Bird location model (empirical species occurrance model) relied upon by USFWS - 30 meter pixels

• Challenging the assumptions – bird location data is biased by time of day researchers triangulate location and use locations that are accessible.

• In this case, peer review apparently focused on methods not data suitability.

Habitat Mapping Approach - HPT

• Despite 20+ years of research the seasonal habitats of the GuSG is still debated due to lack of scientific corroboration.

• Used expert opinion approach (habitat suitability indices) to overcome scientific uncertainty.

• Committee of experts (Strategic Committee) from CPW, BLM, FS, and NRCS (USFWS participated some) reached consensus on seasonal habitats and constraints to habitat.

• Soils mapping provides more accurate mapping of vegetation (habitat) than available vegetation layers.

• Habitat and constraints were scored by experts using a novel GIS method that allows for real time review of results from applying different scores.

• GIS method maintained accuracy of vectors rather than typical approach of rasterizing, which is a process that reduces accuracy in return for simplifying the analysis process.

• HPT maps habitat potential – what it should be without outside influences (erosion, etc., something not mapped)

• 80% of CPW bird location data (8,000 points) lie within Tier1 (scores 15+). (91% of nest locations)

• HPT has been used for BLM’s planning, in-house plan reviews, and the USFWS asked that it be replicated in other sub-populations outside the Gunnison basin.

The Result

Comparison: Habitat Prioritization Tool (top) vs.Bird Model (bottom)

- HPT is far more detailed and shows what influenced the score

- HPT better informs on-site evaluations of habitat

- HPT allows better landscape analysis

• Using countywide data, USFWS calculated a total number of new homes within occupied habitat by 2050 would be 4,630.

• Using GIS/Assessor data trends since 1997 within occupied habitat, a more accurate prediction is 1,201 (¼ compared to using countywide data).

• USFWS final rule revised their analysis. Development in the Gunnison basin is less of a concern than they previously thought, but still a concern.

USFWS assumptions in proposed GuSG listing rule

Over 80% of priority habitat is protectedfrom development

Trends

• Conservation easements are conserving land faster than the amount of land being lost to development.

• It will take 31 years to conserve required land to meet Rangewide Plan goal.

• In worst case scenario, it will take 178 years for development based on current trends to “use up” the priority habitat that is available beyond the goals set forth in Rangewide Plan.

Intensity colors turn from white to purple when address points start getting closer than approximately 800’. Lone address points show as a white dot with a 700’ diameter. Also red areas show priority habitat and areas with a tanish tinge are federal or state lands.

Mapping History

- Data Sources

- Researcher/Investigator

- Storyteller

- Tools/Methods

- Future – web story maps

- Be careful what you wish for!

Data Sources- Various local and regional history books- http://www.davidrumsey.com/- Explorer Journals and Maps – Pike, Gunnison, Fremont, Beale,

Escalante/Dominguez, etc.- Hayden and Wheeler Surveys of Colorado – 1870s- Government Land Office Surveys - 1870-present

http://www.glorecords.blm.gov/default.aspx- Early aerials – BLM/FS- USGS topos – early 1900s- Old Forest Service maps- Old railroad maps- Colorado maps – Nell’s 1884, Clason 1911, etc.- Best resolution modern aerials- USGS geonames- Mines – USGS mineral resource data system- Wikipedia, Google, etc.

Stories

1st Map – Grass dominates not sagebrush - Implications for Sage-grouse management

2nd Map – Culture clash – Ute Indians and miners, reservations

3rd Map – Boom and Bust - Uncontrolled wild speculation and growth

4th Map - Economic Drivers and Growth – Recreation/Second Homes dominate

- best story may evolve or become apparent as you write

Tools/Methods

- Need fast, stable software that is:- good for georectifying old maps- helping you stay organized- manipulating databases and images

- Need a beautiful background image(s) for your maps

- Aide of a local historian is ideal.

- Cite your sources – pain but necessary

- The work often requires your best guess

Color Coding Addresses to

Roads

- Needed when it’s unclear which street applies to a street address.

- Examples: certain scales, curvy roads, lots of street address

Color Tool

Colors polygon layer so that no two adjacent polygons have same color. Theoretically only four colors are needed. Manifold adds a fifth color if it determines solving four color problem will take unreasonably long.

Web search: http://gis.stackexchange.com/questions/54029/how-to-apply-the-four-colors-theorem-in-a-polygon-map-in-arcgis-arctoolbox-autom

- QGIS has a plugin (topocolour – author warns against using with 1000s of polygons)

- Arc Python plus Arc’s Polygon Neighbor tool (7 colors)

- FME has a tool- R statistics program has code

Method

- Manifold’s tool adds an integer field to the layer’s table

- To use on line layer such as roads.1) Buffer roads 50 feet to make them polygons2) Merge roads based on road name so all roads with same

name end up with same color3) Run color tool then add a

color as needed for clarity4) Using road name transfer

color value to road lines and address points

Open Street Map Trail Data

- JuicyTrails is a private company that maps trails, stores them in Open Street Maps, and sells the data and trail mapping app. Much of his data is better than other sources, such as BLM/USFS.

- Shapefile export for Colorado is missing some attributes - http://download.geofabrik.de/north-america.html

- Use QGIS’s OSM download plugin allows zooming to an area and extracting data to shapefile with all data included.

- Unfortunately some data is stored as tags to save space. For example:

4wd_only=>yes,bicycle=>yes,motorcycle=>yes,mtb:scale:imba=>4,pathtype=>motorized singletrack,surface=>ground

- Way to extract specific tags in Arcmap - https://github.com/Esri/arcgis-osm-editor/wiki/Extracting-specific-tags

- Write queries or scripts to extract the data to a field and allow for easily updating the latest OSM data.