Cultural Resource Predictive and Sensitivity Model for the West Mojave Route Network Project

Prepared by

USDI Bureau of Land Management

Margaret Margosian, GIS Specialist, California Desert District

and

Ashley A. Blythe, Archaeologist, Ridgecrest Field Office

with contributions by

Timothy Hutzley and Fon Duke

Mojave Desert Ecosystem Project

April 2016

Introduction

The West Mojave Plan (WEMO) is a federal land use plan amendment to the California Desert Conservation Area (CDCA) Plan. It presents a comprehensive strategy on public lands to conserve and protect the desert tortoise, the Mohave ground squirrel and over 100 other sensitive plants and animals and the natural communities of which they are a part. A main component of the WEMO plan is travel management; or the way in which the BLM will manage off-highway vehicle routes of travel on 3.1 million acres of public lands in the Planning Area. In August 2006, 11 environmental organizations sued the BLM and the U.S. Fish and Wildlife Service over certain aspects of this plan, including failing to address impacts to cultural resources. In 2009, the U.S. District Court for the Northern District of California upheld most of the WEMO Plan, but found fault in the methods used to designate the over 5,000 miles of routes in the plan area. Subsequently, a Remedy Order of January 2011 remanded portions of the 2006 WEMO Plan to the BLM with direction to prepare a revised route network that included an updated catalog of the route network inventory.

The updated catalog revealed over 15,000 miles of transportation linear features throughout the WEMO area; in terms of cultural resource inventory, this represents an Area of Potential Effect that is nearly impossible to perform in any meaningful timeframe, specifically prior to a Record of Decision. A broader cultural resource analytical scope that focuses on impacts at a landscape level is more appropriate, efficient, and likely to be successful. To this end, the BLM has developed an Archaeological Sensitivity Model (Model) for the WEMO Planning Area, with assistance from the Mojave Desert Ecosystem Project (MDEP).

The BLM, in consultation with the Advisory Council on Historic Preservation and the California Office of Historic Preservation, entered into a Programmatic Agreement (Agreement) in September 2015, which directs the BLM to complete this Model. The overarching objective of the Model is to classify areas with cultural resource sensitivity in order to streamline the BLM's efforts in historic property identification and evaluation pursuant to Section 106 of the National Historic Preservation Act and its implementing regulations at 36 CFR Part 800. Ultimately, the Model will assist the BLM in identifying areas where cultural resource inventory efforts are lacking and resources should be focused, and where impacts to cultural resources from the effects of off-highway vehicle travel are most likely to occur.

Project Area

The Planning Area covers 9.3 million acres in the western portion of the Mojave Desert in southern California, and is managed by 14 federal, state, and local agencies including thousands of private landowners. It is bounded by the Owens Dry Lake, Joshua Tree National Park, the Sierra Nevada Mountain Range, Death Valley National Park, Mojave National Preserve, and the San Bernardino and San Gabriel Mountains. The Planning Area includes a mix of remote desert locales, several large military installations, and in the southwest part, the urban sprawl of the Inland Empire. It includes the majority of the management areas for the Ridgecrest and Barstow Field Offices, and small portions of the Needles and Palm Springs Field Offices. From north to south and east to west in the WEMO area, tall mountains, wide valleys, Pleistocene dry lakes, Pinyon, creosote, and Joshua tree forests, sand dunes, lava flows, granitic outcrops, and desert pavement characterize a widely variable landscape. (Figure 1)

Figure 1. The Western Mojave Planning Area in the southern California Deserts.

Creating a predictive model that teases out the possibilities of finding and protecting cultural resources in a large landscape presents issues that are not ordinarily met with models that cover smaller areas such as an individual state park. Environmental indicators that would ordinarily fit into a straightforward predictive model for a smaller area may vary more widely in importance across a landscape of this scale. Also, some environmental indicators may not be consistently as important an indicator of cultural resources across the entire landscape. To address the challenge of the large scale of the Planning Area, the BLM divided the Western Mojave area into segments that conformed to certain criteria: similarity of landscape; watershed boundaries; known geographic regions; or mountain ranges/chains. Using watersheds built from BLM contour data using the ArcGIS watershed analysis tool, as well as other resources, BL M created 32 discrete regions to focus the model more appropriately (Figure 2).

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Figure 2. The Planning Area divided into 32 discrete, relatively homogeneous regions.

The regions include (Name/Type of Region): 1. Coso-Argus (Varied Terrain) 2. Darwin (Varied Terrain) 3. Fort Irwin (Varied Terrain) 4. Owens Valley (Dry Lake Bed/Basin) 5. China Lake (Dry Lake Bed/Basin) 6. Searles (Dry Lake Bed/Basin) 7. Jawbone-Kelso (Varied Terrain) 8. Cuddeback Basin (Dry Lake Bed/Basin) 9. Superior Valley (Dry Lake Bed/Basin) 10. Black Mountain-Gravel Hills-Slocum Mountain (Mountain Range/Chain) 11. Fremont Valley (Dry Lake Bed/Basin) 12. Lava Beds (Varied Terrain) 13. Rosamond-Rodgers Lakes Basin (Dry Lake Bed/Basin) 14. Johnson Valley (Varied Terrain) 15. Emerson Lake (Dry Lake Bed/Basin) 16. Juniper Flats (Varied Terrain) 17. Deadman-Mesquite Lakes (Dry Lake Bed/Basin) 18. Coyote Lake (Dry Lake Bed/Basin) 19. Joshua Tree (Varied Terrain) 20. Dale Lake Basin (Dry Lake Bed/Basin) 21. Eastern Sierras (Mountain Range/Chain) 22. El Pasos-Summit Mountains 1 (Mountain Range/Chain) 23. El Pasos-Summit Mountains 2 (Mountain Range/Chain) 24. Afton Badlands (Varied Terrain) 25. Forest Edge 1(Mountain Range/Chain) 26. Forest Edge 2 (Mountain Range/Chain) 27. Forest Edge 3 (Mountain Range/Chain) 28. Forest Edge 4 (Mountain Range/Chain) 29. Stoddard-Ord-Newberry-Rodman 30. Rattlesnake Canyon (Varied Terrain) 31. High Desert Flats (Varied Terrain) 32. Cronese Basin (Dry Lake Bed/Basin)

Environmental Indicators Used (Data Used)

The National Elevation Dataset (NED) was used to generate three environmental indicators related to topography: aspect, slope, and elevation (Figures 3, 4, and 5).

Figure 3. Aspect Environmental Indicator.

Figure 4. Slope Environmental Indicator.

Figure 5. Elevation Environmental Indicator.

The US General Soil Map (STATSGO2) was used to generate three environmental indicator layers: the awc_l field in the attribute tables for soil moisture content, the brockdepmin attribute for depth to bedrock, and the texdesc attribute for soil texture (Figures 6, 7 and 8). These tables are then joined to the polygon feature class before further processing such as conversion to raster.

Figure 6. Soil Moisture Environmental Indicator.

Figure 7. Depth to Bedrock from Surface.

Figure 8. Soil Texture Environmental Indicator. A landform layer was extracted from the Louisiana State University and the US Army landform database (Figure 9).

Figure 9. Landforms. Historic trails were extracted and combined from sources at the BLM, and Euclidean distance from the trails calculated (Figure 10).

Figure 10. Distance from Historic Trails.

The US Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) National Hydrology Dataset supplied the locations of springs, streams, and lakes, including dry lakes. The BLM calculated Euclidean distance from these features. (Figures 11, 12, and 13).

Figure 11. Distance to Springs

Figure 12. Distance to Streams

Figure 13. Distance to Lakes

Point locations of abandoned mines in the desert were extracted from BLM source data. The BLM calculated Euclidean distance from the mines.

Figure 14. Distance to Abandoned Mines

A comprehensive ecological systems layer generated by the California Department of Fish and Game for the BLM for the Desert Renewable Energy Conservation Plan (DRECP) supplied several environmental indicators (Figure 15).

Figure 15. Ecological Systems Environmental Indicator. While in some cases it was not clear if some of these indicators would be useful, the following were also extracted from this layer to explore them further:

- Total tree cover - Shrub cover - Roadlessness - Land use - Joshua tree cover - Hydrologic modification - Herbaceous plant cover - Hardwood cover - Exotics cover - Ecological system classification - Development density - Conifer cover - Anthropogenic alteration (severity) Geology data was obtained from the US Geological Survey (USGS, Figure 16).

Figure 16. Geology environmental indicator.

MDEP compiled and processed data layers of environmental indictors using approaches from smaller scale APM’s at US Army National Training Center Fort Irwin (Ruiz 2003) and the BLM Carrizo Plains National Monument (Martinez 2015), among others. Initial processing consisted of projecting collected data to a common coordinate system; NAD 1983 Universal Transverse Mercator (Zone 11) was used. Data that did not completely cover the project area was buffered at multiple intervals to complete coverage. All layers were also converted to 30-meter resolution rasters. In cases where the processing needed to include generating additional information (for example, distance to water features or historic trails), additional processing (for example, Euclidean distance) were performed. Cultural Resource Data Used

The BLM California Cultural Resources Division maintains an internal geodatabase of cultural resource site location data. The BLM Cultural GIS was updated with records reviews from the Eastern Information Center, the San Bernardino Information Center, and the San Joaquin Valley Information Center, as well as with a major data consolidation effort of existing cultural GIS data sets from the Barstow, Ridgecrest, Needles, and Palm Springs Field Offices. The geodatabase includes over 9,000 cultural resources derived from survey work associated with renewable energy projects, transmission lines, highways, discrete surface disturbing projects, and sample surveys conducted in the 1980s.

At the time of developing the Model, some of the cultural GIS data lacked detailed attribute information to allow additional parsing out by site age and specific components, such as habitation sites, lithic locales, mining features, or can dumps. The geodatabase depicts resources in point, multipoint, line, and polygon features. The attribute table includes, at a minimum, trinomials and primary numbers as assigned by the California Information Center System and land status as derived from the BLM GIS layers. When available from the original data, the attribute table also includes the following information:

- National Register eligibility status - Time period of the site: prehistoric, historic, or both - Resource type: Site, Building, Structure, or Isolate - Site names - Agency archaeologist notes regarding digitization, - Site-specific attributes corresponding with the California Department of Parks and Recreation 523 manuals.

Site definitions are not consistent between cultural areas; therefore no standard definition of a site has been established for the BLM. Some of the locations provided in the dataset may represent isolated occurrences of cultural material. These locations have not been removed from the dataset because of the differences in site definitions and changes in survey and recordation strategies through time. The data has been used with the assumption that every piece of spatial data represents some sort of cultural phenomenon.

Areas previously surveyed for cultural resources were not available in GIS format at the time the Model was being developed.

MDEP further processed the cultural data BLM supplied by creating a 30 meter point grid from the polygon cultural data, first by converting known site polygons to a 30-meter resolution raster and then converting back to points. Point locations were likewise added. The resulting grid of points over a site, especially large sites, allows sampling (see below) across the site rather than relying on a single point, such as a centroid, to represent the site.

Model Process

Cultural predictive models typically utilize an approach that weights the importance of the environmental indicators in finding cultural sites and adds them in an overlay process to generate a map with overall likelihood of finding those sites. Because the BLM knows the location of many cultural sites, an additional step was incorporated to generate statistics about the environmental indicators at those sites.

The 30-meter grid of known site points (see above) were divided into the 32 regions and “passed through” the environmental indicator rasters individually, so that the points picked up the value of the raster at each point (Figure 17). BLM then ran statistics from the point tables to help inform how the rasters should be weighted in the additive overlay process. The statistics were graphed to show patterns in the environmental indicators, which were used to develop weights within environmental indicators on a scale of 1 to 10. These statistics also informed where certain environmental indicators were more important in a region type than others, or showed that the indicator could be weighted the same across the desert.

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Figure 17. Example of 30-meter grid site points (black dots) overlayed with two environmental indicators, elevation and ecological system.

For example, comparison of the graphs for individual regions for the Distance to Streams indicator showed that sites were uniformly situated from streams (Figure 18). However, graphs for the Aspect indicator for different regions showed different influences; sites in the Coso Range oriented most often toward the southwest, while sites in the Deadman’s Lake region most often utilized north-facing slopes (Figure 19). Table 1 shows those environmental indicators that were more relevant at the desert scale and which were more relevant at the regional scale.

Figure 18. Distance to Streams graphs for the Coso-Argus region (left) and the Deadman-Mesquite Lakes region (right) show similar patterns, suggesting that this is an environmental indicator similar across the Planning Area.

Figure 19. The aspect used for sites most often in the Coso-Argus region (left) are very different than those favored for sites in the Deadman-Mesquite region, suggesting that this environmental indicator should be evaluated at the regional rather than Planning Area scale.

Table 1. Environmental indicators listed by scale

Desert-Wide Scale Regional Scale Ecological Communities Elevation Conifer Cover Aspect Hardwood Cover Slope Herbaceous Cover Distance to Mines (focused in Mountain regions) Shrub Cover Distance to Lakes (focused in Lake Basin regions) Geology Distance to Springs (focused in Mountain regions) Landform Soil Moisture and Texture Distance to Historic Trails Distance to Streams

Each environmental indicator was reclassified (Spatial Analyst, Reclass, Reclassify) either Planning Area wide or by the discrete region (as specified in Table 1) to change the environmental indicator value to a weight based on the importance demonstrated in the graphs. For example, in the Aspect graph for Coso- Argus region above, Aspect directions between 180 and 250 degrees would have received a nine on a scale of one to ten, while directions between 50 and 150 degrees a three. The regional weighted rasters were recombined for full coverage in the project area.

It is common to combine rasters by weighting them (multiplying by a factor) by indicator and then adding to each other in a compilative process (straight sum). However, generating one version of the model with a scale of 1 to 53 does not compare well with results from another iteration that scale from 5 to 73. In this instance, the BLM wished to maintain the 1 to 10 scale when performing the sum so that succeeding iterations could be compared meaningfully. Therefore, the BLM divided the indicators into “tracks”, in which similar indicators were weighted in importance on a percentage of the value of 10 and added together before the results were re-weighted to a percentage of 10 and all tracks added. (Figures 20, and 21). Aspect-Slope-Elevation Track

Aspect by Region x .5

Slope by Region x .3 Footing Conditions x .15

Elevation by Region x .2

Vegetation Track Ecological Community x .05

Conifer Cover x .3

Hardwood Cover x .3 Vegetation Conditions x .15 Herbaceous Cover x .15

Shrub Cover x .15

Not-covered Filler x .05

Soil-Geology-Landform Track Geology x .25 Probability Model Landform x .5 Landform Conditions x .2 Soil Moisture x .125

Soil Texture x .125

Human Impact Track

Distance to Mines x .65 Proximity to Human Uses x Distance to Historic Trails x .35 .15

Current Development Erase from Probability Water Track Model Distance to Streams x .35

Distance to Springs by Region x.3 Water Availability x .35

Distance to Lakes by Region x .35

Figure 20. Example of “track” sum analysis. Different environmental factors and tracks would be re- weighted for varying iterations.

Figure 21. Final weighted sum analysis.

The final resulting raster was also graphed, and statistically split into high, medium, and low probability at the first standard deviation (low = below 1 SD, high = above 1 SD on the scale of 10, Figures 22 and 23). In future iterations, the location of the split may be adjusted in light of new data.

Figure 22. Graph of the frequency of sum totals in the map in Figure 21.

Figure 23. Map of sums divided into High, Medium, and Low probabilities (one standard deviation of graph in Figure 22).

Next Steps and Additional Data Sources

Since the initial processing of the Model, the BLM has identified subsequent data layers which may be useful in further refining the Model results. The BLM also recognizes that Tribes, Tribal Organizations, and other Consulting Parties may have specific knowledge of the Mojave Desert archaeology and history they may choose to share. This “expert-informed” component of the Model can aid the BLM in further testing the Model, as well as more appropriately direct inventory efforts to areas where eye-witnesses have already identified impacts from transportation linear features.

California Desert Conservation Area Plan Cultural Resource and Native American Values

As part of the California Desert Conservation Area Plan, the BLM undertook a large scale sample inventory of the entire California Desert Planning Area, focusing on environmental zones most likely to have cultural resources. During the spring of 1974 and winter of 1978-79, a total of 280 square miles were inventoried and seven regional cultural resource overviews were completed (USDI 1980). As a result of these field efforts, BLM archaeologists and historians created a paper-based map showing areas of known or potential cultural resource values. This map was recently digitized and minimally attributed in GIS format as part of the DRECP effort. These maps are available to the BLM as an additional layer to be incorporated into the Model, and as an additional testing parameter.

Native Americans were included in the review for all of the documents produced by the BLM Cultural Resources staff during the Desert Plan. At the time of producing the Cultural Resource Value maps, the BLM asked for input by Tribal members regarding traditional use areas, ritually associated localities, and sacred areas. The BLM took extensive steps to maintain the confidentiality of specific information provided by Native American informants. In an effort to ensure the values were not lost during subsequent planning efforts and that confidentiality of very specific locations was maintained, large polygons depicting concentrations of areas of concern were plotted on paper-based maps. These maps were likewise digitized in the DRECP mapping effort and can be incorporated into the Model as areas of sensitivity.

Survey Data

Cultural resource survey data was not available in digital format at the time of Model development. The BLM has since digitized polygons for projects associated with BLM directed inventories. Attributes for BLM survey data include the following information:

- Agency assigned number - Report title - Project specific notes - Project scope of work (Survey Class I, II, III or other) - Number of resources identified during survey - Total acreage inventoried The survey data may be used to help narrow down areas in the model where inventory has already occurred and thus “ground-truthed” for cultural resources. This is especially useful for inventories where survey strategy is known, such as the width of transects and level of ground visibility. A recent model built for the BLM in Oregon brings to light the potential for bias in the use of previous survey data in modeling efforts (Ingbar and Hall 2014). They acknowledged that variability in survey transects and strategies and the location of surveys on only one type of land-owning jurisdiction may lead to an invalid assumption that the absence of archaeological materials is just as important as the presence. To address this potential bias, the Model is currently focused on where sites have been located, regardless of how they were found. The Agreement requires the BLM to assess the quality of previous surveys before determining that additional survey is unnecessary. In the case of the Model and digital survey polygons indicating negative results, the Model will focus on inventories that were completed within the last 15 years, when survey strategies were more consistent.

Field Testing

Field testing the Model is a crucial step in the ensuring the accuracy of the results and appropriately applying the Model in the WEMO planning process. The BLM Washington Office and the BLM California State Office provided assistance to the West Mojave Cultural Resource Team to hire five archaeological technician interns through the American Conservation Experience, Emerging Professionals in Conservation Program to perform preliminary field data acquisition for the Model. The interns began a random sample of the WEMO route network in September 2014. The BLM WEMO Intern crew inventoried 5,512 acres, covering approximately 159 miles of route. Routes inventoried were a combination of previously authorized routes and unauthorized transportation linear features that were identified during the initial WEMO route cataloging effort. The routes were located in all of the landscape types identified in the Model. Additional sample surveys will take place over the next few years that focus on areas of Low, Medium, and High Sensitivity to further field test the Model. In addition, because cultural resource inventory for projects not associated with the WEMO Plan will be conducted on BLM lands in the future, the Model will be tested by independent samples.

The issue of land jurisdiction will continue to be a challenge in the testing of this Model. While the Model covers the entire Planning Area regardless of underlying landowner. the BLM will be limited to testing the results of the Model only on BLM managed lands. Recreation Use Area

A critical component to assessing the potential for impacts to cultural resources from routes of travel is the identification areas where recreation uses are concentrated. The West Mojave Plan Draft Supplemental Environmental Impact Statement (DSEIS) provides the following description of “hot spots” for recreation values in the Planning Area:

Although most recreational activities are widely dispersed, certain activities have “hot spots” that have been established over time. How or why they were established varies from case to case, but may be due to the features (topography, geology) of the area, proximity to urban areas, the availability of access into the area, and publicity. Understanding recreation patterns and hot spots is critical to the design of an effective motorized vehicle access network. Particular features or land-characteristics may make a given area highly desirable for a certain type (or types) of recreational activity. For instance, flat, expansive terrain is often desirable for recreational activities such as target shooting, driving for pleasure, and more quick-paced race events. On the other hand, mountainous terrain is often more conducive to such activities as rock climbing, hiking, rock hounding or technical four wheel rock crawling. In addition, specific attractions of an area dictate the types of use as well as the levels of use that predominate (USDI 2016:3.6-1).

The “hot spot” data, where it can be adequately mapped, along with the information provided in the DSEIS regarding the number of visitors and visitor days for specific areas, can be included as an additional layer to assess cultural resource sensitivity, especially potential for impacts. The layers can assist in setting field testing and cultural resource survey priorities. (Figure 24).

Figure 24. Recreation hotspots.

References

Ingbar, Eric and Jeremy Hall 2014 A Western Oregon Cultural Resource Forecast Model for USDI Bureau of Land Management. Prepared by Gnomon, Inc. MS on file, Oregon State Office, Bureau of Land Maneagment Martinez, Romina 2015 Predicting the Past: GIS Weighted Modeling on the Carrizo Plain National Monument. MS on file United States Department of Interior, Bureau of Land Management, Bakersfield Field Office.

Ruiz, Marilyn O. 2003 The Development and Testing of an Archeological Predictive Model for Fort Irwin, California. Prepared for United States Army Corps of Engineers.

United States Department of the Interior, Bureau of Land Management 1980 Final Environmental Impact State and Proposed Plan Appendix Volume D: Appendix VII: Cultural Values and Appendix VIII: Native American. California Desert Conservation Area