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Oak_Patches (FeatureServer)

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Service Description: Identification and scoring of Oregon white oak (Quercus garryana) occurrences and canopy areas (oak patches) in the greater Portland-Vancouver metropolitan region to help prioritize protection and restoration actions. Oak patches are based on Oregon white oak tree/cluster locations. Oak patches are scored based on size and context indicators. PN (Metro) added a few fields for PN and the web application. They include,OWP_patch_ID and OWP_patch_sum_Max. Though some Oak patches get split they maybe related to more than one patch, we chose the larger one and only used the highest OWP sum score. some OP, though few do not have a OWP associated with it but the OP still has a score. Additional fields ind_OP_A_results, ind_OP_B_results and ind_OP_A_results were added for quick reference to the Oak Patch indicator value with the multiplier.

Service ItemId: 01b8ae8b6d5e4e88bfc9e9094059e42a

Has Versioned Data: false

Max Record Count: 2000

Supported query Formats: JSON

Supports applyEdits with GlobalIds: False

Supports Shared Templates: False

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Executive Summary

To improve conservation outcomes for biodiverse native Oregon white (Quercus garryana) oak ecosystems, the Intertwine Oak Prairie Working Group(OPWG) has developed a series of oak data and map products for the greater Portland-Vancouver metropolitan region. The OPWG encourages the use of this information by the community, planners, conservation practitioners, landowners, and others with the goal of protecting and restoring our native oak ecosystems and their rich cultural legacy.

Oak distribution data was compiled from field and computer mapping. Oak patches were defined based on oak occurrences and canopy areas, land cover, and planimetric data. Not every oak tree is reflected in the data, but we have high confidence in the overall landscape pattern and the locations of significant oak clusters. We also have high confidence that areas depicted as absent of oak do not harbor clusters of undocumented oak.

Scoring identifies the largest and least fragmented clusters of Oregon white oak, to help prioritize land acquisitions and locate restoration actions that improve connectivity. Other oak habitat excluded from high-scoring oak patches also has value, and finer-scale analyses or those emphasizing different criteria may reveal other patterns and priorities. Future map updates will depend on available resources.

This product is best used for landscape-level planning for conservation as well as land use, development, transportation, utility, park, farm and forest planning, and project scoping. For individual site- or parcel-scale, this data should be used with caution and supplemented with field surveys, as needed.

This data has particular strengths and is built on assumptions which are important to keep in mind. For example, it is inappropriate to assume that Oregon white oak that do not receive high scores in this product are unimportant and of low conservation value. Individual oak trees can have high ecological and cultural significance and should be protected whenever possible.

Data Inputs to This Product

  1. OakQuest 2019 Point Data, Intertwine (“OakQuest_2019”)

  2. Regional Conservation Strategy 2011 Landcover, 5m resolution, Intertwine (“RCS_Landcover”)

  3. EPA EnviroAtlas 2014 Landcover, 1m, Environmental Protection Agency (“EPA_Landcover”)

  4. Buildings, Metro RLIS and Clark County, 2019 (“Buildings”)

  5. Street Centerlines, Metro RLIS and Clark County, 2019 (“Streets_CL”)

  6. Railroads, Metro RLIS and Clark County, 2019 (“Railroads”)

  7. Oregon Urban Growth Boundaries, Oregon Department of Administrative Services Geospatial Enterprise Office, 2019 (“UGB”)

  8. Washington Urban Growth Areas, Washington State Department of Ecology, 2019 (“UGA”)

Methodology

Methodology to Create Oak Patches

Landcover Base

1. “RCS_Landcover” was the beginning file for the base. This raster was at 5m resolution, and all raster operations that followed were at 5m resolution.

2. Where “EPA_Landcover” existed, it superseded “RCS_Landcover.” “EPA_Landcover” was more recent and higher resolution than “RCS_Landcover,” but covered less area and had fewer landcover categories.

3. Buildings superseded any landcover below in “RCS_Landcover” and “EPA_Landcover.”

4. Steps 1 through 3 created “Landcover_Base,” with the following six landcover categories: Water, Developed/Impervious Surfaces, Low Vegetation, Tree Cover, Agriculture, Soil/Barren/Sand Bars.

Oak Canopy

5. “OakQuest_2019” points that were <=118-feet from each other and not separated by “Streets_CL” centerlines, “Developed/Impervious Surfaces” landcover, or “Railroads” were joined into a single Oak Patch for scoring purposes. Each Oak Patch area was tabulated collectively, but additional canopy polygon was not created beyond the 30-feet radius of “Oak Canopy.”

6. For “Oak Canopy” area calculations, this 30-feet radius superseded all landcover in “Landcover_Base.” This approach gave highest priority to “OakQuest_2019” data and the standard 30-feet radius used for area calculations. This also counted canopy that overhangs streets and other impervious surfaces.

Oak Patches

7. “OakQuest_2019” points that were <=118-feet from each other and not separated by “Streets_CL” centerlines, “Developed/Impervious Surfaces” landcover, or “Railroads” were joined into a single Oak Patch for scoring purposes. Each Oak Patch area was tabulated collectively, but additional canopy polygon was not created beyond the 30-feet radius of “Oak Canopy.”

8. The 118-feet threshold was based on a 1-acre radius from each tree. A 1-acre radial plot is the maximum spacing between trees that could still contain 5 trees per acre. 5 trees per acre is the minimum density for Oak Woodland in Altman and Stephens (2012) Land Managers Guide to Bird Habitat and Populations in Oak Ecosystems of the Pacific NW.

9. “Streets_CL” centerlines, “Developed/Impervious Surfaces” landcover, and “Railroads” were used to separate the aggregation of “Oak Canopy” into Oak Patches. However, “Oak Canopy” was not erased, only separated. In this approach, “Streets_CL” centerlines that bisected tree canopy created separate patches. Tree canopy might have connected across the street, but that did not create a continuous patch. This approach recognized roads as a break in habitat continuity.

Scoring Methodology

10. Oak Patches were scored with three indicators: (1) Size of Oak Patch, (2) Percent of Oak Patch bordered by “Natural” land cover, and (3) Area of Oak Canopy within a 20 acre vicinity.

11. Scores of 1 through 10, from lowest to highest score, were used for each indicator.

12. A multiplier was applied to each Ecological Indicator score to create a Summary Score for each Oak Patch. The multiplier gave different relative weighting to each Ecological Indicator.

13. Possible Summary Scores for each Oak Patch ranged from 100 to 1000.

14. Indicators and scoring were as follows:

INDICATOR A

Multiplier: 45

Category: Patch Characteristic

Ecological Indicator: Size of Oak Patch

Scoring:

  • 1 (low)= Natural Breaks 1st

  • 2= Natural Breaks 2nd

  • 3= Natural Breaks 3rd

  • 4= Natural Breaks 4th

  • 5= Natural Breaks 5th

  • 6= Natural Breaks 6th

  • 7= Natural Breaks 7th

  • 8= Natural Breaks 8th

  • 9= Natural Breaks 9th

  • 10 (high)= Natural Breaks 10th

Indicator Notes:

  • Scoring breakpoints are based on the range and frequency of Oak Patch sizes in the full study area. A rounded Jenks Natural Breaks classification is used to create 10 groups for scoring.

INDICATOR B

Multiplier: 30

Category: Landscape Context Characteristic

Ecological Indicator: Percent of Oak Patch bordered by "Natural" landcover

Scoring:

  • 1 (low)= 0 to <10%

  • 2= 10 to <20%

  • 3= 20 to <30%

  • 4= 30 to <40%

  • 5= 40 to <50%

  • 6= 50 to <60%

  • 7= 60 to <70%

  • 8= 70 to <80%

  • 9= 80 to <90%

  • 10 (high)= 90 to 100%

Indicator Notes:

  • Landcover is measured as the percent area from the edge of Oak Canopy to a distance of 100-feet according to the following categories:

    • "Natural"= Tree Cover, Water

    • Low Vegetation= Weighted at 75% Natural (i.e. if an Oak Patch is 100% surrounded by Low Vegetation, that would be weighted to 75% Natural, and receive a score of 8. Prairie landcover data for the study area does not exist. The weighting rationale is that data for low vegetation includes lawn and prairie, thus it is not as reliably "Natural" as Tree Cover. This likely overweights lawn areas but tries to avoid underweighting prairie.)

    • Agriculture= Weighted at 50% Natural. (i.e., if an Oak Patch is 100% surrounded by Agriculture, that would be weighted to 50% Natural, and receive a score of 6.)

    • Developed/ Impervious/ Roads, Sandbars/Soil/ Barren= Not Contributing.

INDICATOR C

Multiplier: 25

Category: Landscape Context Characteristic

Ecological Indicator: Area of Oak Canopy within a 20 acre vicinity

Scoring:

  • 1 (low)= Natural Breaks 1st

  • 2= Natural Breaks 2nd

  • 3= Natural Breaks 3rd

  • 4= Natural Breaks 4th

  • 5= Natural Breaks 5th

  • 6= Natural Breaks 6th

  • 7= Natural Breaks 7th

  • 8= Natural Breaks 8th

  • 9= Natural Breaks 9th

  • 10 (high)= Natural Breaks 10th

Indicator Notes:

  • Measured from the centroid of Oak Patches to a distance of 527 feet.

  • Oak Canopy within the vicinity is counted regardless of other landcover in between, including streets or impervious surfaces.

  • A radius of 527 feet from the centroid of Oak Patches equals a 20 acre circle.

  • A 20-acre radius is based on a combination of white-breasted nuthatch, acorn woodpecker, and gray squirrel territory size.

  • A rounded Jenks Natural Breaks classification is used to create 10 groups for scoring.

Data Not Used in Scoring

  1. Rare Species Occurrences

  2. Soils

  3. Wetlands

  4. Floodplains

  5. Forest interior versus forest edge

  6. Patch edge to interior ratio

  7. Historic vegetation

  8. Historic fire regime (USDA Landfire data)

  9. TNC Priority Willamette Valley Oak and Prairie Habitat Parcels

  10. WMSWCD Oak Mapping

  11. Metro Data Resource Center 2014 Coniferous vs Deciduous Landcover, 1m (DRC_Coniferous)

Field Descriptions

Field

Description

OP_PATCH_ID

Unique ID for each Oak Patch.

A_METRIC_Acres

Calculation result for Indicator A, Scoring of Oak Patches, in acres.

B_METRIC_Edge_Percent_Natural

Calculation result for Indicator B, Scoring of Oak Patches, as a percent.

C_METRIC_Vicinity_Acres

Calculation result for Indicator C, Scoring of Oak Patches, in acres.

OP_A_SCORE

Score for Indicator A, Scoring of Oak Patches.

OP_B_SCORE

Score for Indicator B, Scoring of Oak Patches.

OP_C_SCORE

Score for Indicator C, Scoring of Oak Patches.

OP_SUM_SCORE

Summary score, with multiplier applied for each component indicator.

ind_OP_A_results

Calculation result for Indicator C, Scoring of Oak Patches, in acres.

ind_OP_B_results

Score for Indicator A, Scoring of Oak Patches.

ind_OP_C_results

Score for Indicator B, Scoring of Oak Patches.

OWP_patch_ID

associated OWP patch ID for the Oak Patch (OP)

ind_OP_B_results

associated OWP high sum score for the Oak Patch (OP)

Reference

Altman B & Stephens JL. (2012) Land Managers Guide to Bird Habitat and Populations in Oak Ecosystems of the Pacific NW. American Bird Conservancy and Klamath Bird Observatory.

Distribution Liability

The data contained herein are provided on an as-is, as-available basis without warranties of any kind, expressed or implied, including (but not limited to) warranties of merchantability, fitness for a particular purpose, and non-infringement. Intertwine Oak Prairie Working Group and Biohabitats expressly disclaim any warranty that the data are error-free or current as of the date supplied.



Copyright Text: Intertwine Oak Prairie Working Group, Biohabitats

Spatial Reference: 26910 (26910)

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