DMEC Mojave Playas H

David Magney Environmental Consulting

A PRELIMINARY DRAFT REGIONAL GUIDEBOOK FOR APPLYING THE HYDROGEOMORPHIC APPROACH TO ASSESSING WETLAND FUNCTIONS OF PLAYA DEPRESSIONAL WETLANDS IN THE MOJAVE DESERT

Prepared for: U.S. ARMY CORPS OF ENGINEERS, LOS ANGELES DISTRICT

On behalf of: Richard and Laurie Lyons

Mission Statement To provide quality environmental consulting services with integrity that protect and enhance the human and natural environment

April 2015

www.magney.org DMEC

A Preliminary Draft Regional Guidebook for Applying the Hydrogeomorphic Approach to Assessing Wetland Functions of Playa Depressional Wetlands in the Mojave Desert

Prepared for: U.S. Army Corps of Engineers, Regulatory Los Angeles Regulatory Division 915 Wilshire Blvd., Suite 930 Los Angeles, California 90017-3401 Contact: Veronica Li Phone: 213/452-3292

On behalf of: Richard and Laurie Lyons P.O. Box 4 Ojai, California 93024

Prepared by: David Magney Environmental Consulting P.O. Box 1346 Ojai, CA 93024-1346 Contact: David L. Magney 805/646-6045

13 April 2015

www.magney.org This document should be cited as: David Magney Environmental Consulting. 2015. A Preliminary Draft Regional Guidebook for Applying the Hydrogeomorphic Approach to Assessing Wetland Functions of Playa Depressional Wetlands in the Mojave Desert. 13 April 2015.(PN 12-0004.) Ojai, California. Prepared for U.S. Army Corps of Engineers, Los Angeles, California. Prepared on behalf of Richard and Laurie Lyons., Ojai, California. DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC

Table of Contents

Page

SECTION I. INTRODUCTION...... 1 BACKGROUND ...... 1 OBJECTIVES ...... 2 SCOPE...... 2 REFERENCE DOMAIN ...... 2 SECTION II. OVERVIEW OF THE HYDROGEOMORPHIC APPROACH 6 HYDROGEOMORPHIC CLASSIFICATION...... 6 Depression Wetland Class ...... 8 Mineral Soil Flats Wetland Class ...... 8 REFERENCE WETLANDS...... 9 ASSESSMENT MODELS AND FUNCTIONAL INDICES...... 10 MODEL VARIABLES ...... 11 CONCEPTUAL FRAMEWORK FOR COMPUTING DIRECT AND INDIRECT FCIS: GRAPHICAL AND STATISTICAL ANALYSES ...... 13 ASSESSMENT PROTOCOLS...... 13 DEVELOPMENT PHASE ...... 13 APPLICATION PHASE...... 14 SECTION III. CHARACTERIZATION OF PLAYA LAKES...... 15 REGIONAL WETLAND SUBCLASS AND REFERENCE DOMAIN...... 15 DESCRIPTION OF THE REGIONAL WETLAND SUBCLASS...... 16 Landscape Setting...... 16 Geomorphic Setting and Geology...... 19 Climate...... 23 Cyclic Processes and Reference Standard Cycle ...... 23 Hydrology ...... 24 Water Sources ...... 24 Water Dynamics...... 31 Biogeochemical Processes...... 32 Soils ...... 33 Plant Communities...... 40 Faunal Communities...... 46 Surrounding Fauna of the Mojave Desert in General...... 47 Cultural Alterations of Playa Lakes and the Landscape...... 48 SECTION IV. WETLAND FUNCTIONS AND ASSESSMENT MODELS .... 53 OVERVIEW ...... 53

REFERENCE DATA...... 53 MODEL VARIABLES ...... 54 Vegetation Variables ...... 55 Soil Variables ...... 57 Hydrogeomorphic Variables...... 61 Land Use and Landscape Variables...... 65 PLAYA WETLAND FUNCTIONS ...... 66 Function 1: Surface Water Storage...... 67 Definition ...... 67 Rationale for Selecting the Function...... 67 Characteristics and Processes that Influence the Function ...... 67 Functional Capacity Index ...... 68 Function 2: Groundwater Recharge...... 68 Definition ...... 68 Rationale for Selecting the Function...... 69 Characteristics and Processes that Influence the Function ...... 69 Functional Capacity Index ...... 69 Function 3: Retain Particulates (Physical Processes)...... 70 Definition ...... 70 Rationale for Selecting the Function...... 70 Characteristics and Processes that Influence the Function ...... 70 Functional Capacity Index ...... 71 Function 4: Remove, Convert, Sequester Dissolved Substances (Biogeochemical Processes) 71 Definition ...... 71 Rationale for Selecting the Function...... 72 Characteristics and Processes that Influence the Function ...... 72 Functional Capacity Indices: Direct and Indirect...... 72 Function 5: Maintain Resilience of Characteristic Plant Communities and Carbon Cycling 73 Definition ...... 73 Rationale for Selecting the Function...... 73 Characteristics and Processes that Influence the Function ...... 73 Functional Capacity Indices: Direct and Indirect...... 74 Function 6: Maintain Resilience of Characteristic Faunal Habitat ...... 74 Definition ...... 74 Rationale for Selecting the Function...... 75 Characteristics and Processes that Influence the Function ...... 75 Functional Capacity Indices: Direct and Indirect...... 76 SECTION V. ASSESSMENT APPROACH ...... 77 OVERVIEW ...... 77 Statement of Purpose and Objectives ...... 77 Collate Preexisting Data ...... 78 Screen for Red Flags...... 78 Define the Wetland Assessment Area (WAA) ...... 79 Determine the Wetland Subclass...... 81

Collection and Recording of Data ...... 81 Vegetation Variables...... 82 Soil Variables...... 83 Hydrogeomorphic Variables ...... 85 Land Use and Landscape Variables ...... 87 DATA ANALYSIS AND ENTRY...... 88 Data Entry...... 88 Data Analysis...... 88 Manual Determination of FCI...... 88 Spreadsheet Determination of FCI ...... 88 Application of the Results of the Assessment ...... 88 SECTION VI. ACKNOWLEDGEMENTS...... 89 SECTION VII. CITATIONS...... 90 References Cited...... 90 Personal Communications ...... 98 APPENDICES...... 99 APPENDIX A – DISTANCE IN MILES BETWEEN REFERENCE PLAYAS...... A-1 APPENDIX B – FCI SCORE SPREADSHEETS AND PLAYA INDEX SCORES...... B-1 APPENDIX C – RANGE OF WETLAND VALUES...... C-1

LIST OF TABLES Page Table 1 – Hydrogeomorphic Wetland Classes at a Continental Geographic Scale ...... 7 Table 2 – Potential Regional Wetland Subclasses...... 9 Table 3 – Reference Wetland Terms and Definitions...... 9 Table 4 – Components of a Model Variable...... 12 Table 5 – General Characteristics of Mojave Reference Sites...... 19 Table 6 – Climate Variable Averages (1981 – 2010) for the Mojave Desert Region...... 24 Table 7 – Reference Playa Basins, Subbasins, and Watersheds ...... 31 Table 8 – Reference Playa Soil Textures ...... 37 Table 9 – Reference Playa Soil Test Locations and Depths ...... 38 Table 10 – Reference Playa Soil Test Results ...... 39 Table 11 – Vegetation Continuity Adjacent to Wetland and Variable Sub-indices ...... 56 Table 12 – Infiltration Ratings for Mojave Playa Reference Sites ...... 58 Table 13 – VSED Categorical Variable ...... 59 Table 14 – VSQI Soil Characteristics Evaluated in Determination of the Physical Soil Quality Index ...... 60 Table 15 – VSUBOUT Categorical Variable...... 62 Table 16 – VSOURCE Categorical Variable...... 63 Table 17 – VCATCHWET Categorical Variable...... 64 Table 18 – Runoff Curve Numbers for VUPUSE...... 65

LIST OF FIGURES Page

Figure 1 – Mojave Basin and Range Ecoregion – Reference Domain...... 3 Figure 2 – Mojave Basin and Range Ecoregion – Wetlands Larger than 100 Acres...... 4 Figure 3 – Mojave Basin and Range Ecoregion – Reference Wetlands ...... 5 Figure 4 – Reference Domain and Locations of Reference Playas...... 17 Figure 5 – Reference Domain and Mojave River Watershed ...... 18 Figure 6 – Reference Wetlands – Elevation Model and Watershed Boundaries ...... 20 Figure 7 – Reference Wetlands – Integrated Geology ...... 21 Figure 8 – Reference Domain – Estimated Evapotranspiration...... 25 Figure 9 – Reference Sites – Regional Hydrologic Basins ...... 27 Figure 10 – Reference Sites – Regional Subbasins and Watersheds ...... 28 Figure 11 – Reference Sites – Regional Groundwater Basins ...... 29 Figure 12 – Reference Sites – Surface Hydrology Networks...... 30 Figure 13 – Reference Sites – NRCS Soil Types...... 34 Figure 14 – Reference Sites – Natural Vegetation Communities ...... 44 Figure 15 – Reference Sites – Habitat Connectivity...... 50 Figure 16 – Reference Sites – Landscape Intactness ...... 51 Figure 17 – Reference Sites – Existing Conservation Areas ...... 52 Figure 18 – Sub-index Scores for VSQI ...... 61 Figure 19 – Single WAA within a Project Area ...... 79 Figure 20 – Spatially Separated WAA in the Same Regional Wetland Project Area...... 80 Figure 21 – Spatially Separated WAAs from Different Regional Wetland Subclasses Within a Project Area ...... 80 Figure 22 – WAA Defined Based on Differences in Site Specific Characteristics ...... 81

Note to reviewer: This is a PRELIMINARY draft guidebook. Not all questions have been answered as to the best or most appropriate methods or metrics to be used to measure functional variables or what variables should or should not be used to determine the functional index score. The playa depressional wetlands are MUCH larger than other depressional wetlands for which guidebooks have been developed; however, we believe that most of the work developed for the prairie pothole and vernal pool wetlands have applicability for the much larger playa wetlands. Clearly, hydrology is the shaping force for playa wetlands, just as it is for prairie potholes and vernal pools, even if the frequency of inundation is much less frequent. Any and all approaches or variables suggested in this guidebook are just that, suggestions, and other metrics may be better at capturing how playa wetlands function. We look forward to your comments and suggestions.

SECTION I. INTRODUCTION

BACKGROUND

The Hydrogeomorphic (HGM) Approach is a collection of concepts and methods for developing functional indices and subsequently using them to assess a wetland’s capacity to perform natural functions relative to similar wetlands in the region. The approach was initially designed to be used in the context of the Clean Water Act, Section 404 Regulatory Program permit review sequence to consider and analyze project alternatives, minimize impacts, assess unavoidable project impacts, determine mitigation requirements, and monitor the success of mitigation projects. (Smith et al. 1995.) On 16 August 1996, a National Action Plan to Implement the Hydrogeomorphic Approach (NAP) was published (National Interagency Implementation Team, Federal Register 1997). A National Interagency Implementation Team consisting of the U.S. Army Corps of Engineers (Corps), U.S. Environmental Protection Agency (EPA), National Resources Conservation Service (NRCS), Federal Highways Administration (FHWA), and the U.S. Fish and Wildlife Service (USFWS) cooperatively developed the NAP. Publication of the NAP was designed to outline a strategy and promote the development of Regional Guidebooks for assessing the functions of regional wetland subclasses using the HGM Approach; to solicit the cooperation and participation of Federal, state, and local agencies, academia, and the private sector in this effort; and to update the status of Regional Guidebook development. Development of this Regional Guidebook for “Playa Depressional Wetlands in the Mojave Desert” was developed by David Magney Environmental Consulting (DMEC) for consideration by the Corps, Los Angeles District, Regulatory Division. This Guidebook follows the format outlined in the NAP (p. 33,612) and explained in the various publications of the Corps (Brinson 1993, Clairain 2002, Smith 2001, Smith and Wakeley 2001, Smith et al. 1995, and Wakeley and Smith 2001). No Assessment Team was assembled or assigned for this preliminary draft. Reference data were collected in 2013 and 2014 at a total of 17 reference sites. These sites were selected to represent the range of subclasses and conditions of desert playa lakes in the California portion of the Mojave Desert and the Mojave Basin and Range Ecoregion. All were readily accessible from paved or good dirt roads. This Guidebook also uses and relies heavily on “A Regional Guidebook for Applying the Hydrogeomorphic Approach to Assessing Wetland Functions of Prairie Potholes” (Gilbert et al. 2006) and to a lesser extent on “A Draft Regional Guidebook for Applying the Hydrogeomorphic Approach to Assess Wetland Functions of Vernal Pool Depressional Wetlands in Southern California” (Bauder et al. 2009) since it is one of only a very few Regional Guidebooks to date that address depressional wetlands, especially for southern California. The wetland functions described and measured in the prairie potholes systems very closely mirror the functions attributable to depressional wetlands in the Mojave Desert, despite their significant geographic and ecological separation. The Gilbert et al. (2006) Guidebook is also one of very few guidebooks to progress beyond the draft stage: evidence the functions and variables described within have been thoroughly vetted and accepted.

OBJECTIVES

The objectives of this Regional Guidebook are to (a) characterize the playa wetlands in the Mojave Desert, (b) present the rationale used to select functions, (c) present the rationale used to select model variables and metrics, (d) present the rationale and analytical techniques used to develop assessment models, (e) provide data from reference wetlands and document their use in calibrating model variables and assessment models, and (f) outline the necessary protocols for applying the functional indices to the assessment of wetland functions. This Guidebook represents the first attempt to capture the functionality of desert playa wetlands using the HGM Approach.

SCOPE

This Guidebook includes seven sections, which provide:  Section 1 – background, objectives, and location;  Section 2 – overview of the HGM Approach and development and application phases;  Section 3 – characterization of desert playa depressional wetlands in the Mojave Desert, including geographic extent, climate, geomorphic setting, soils, hydrology, physical and biogeochemical processes, vegetation, characteristic fauna, and other factors that influence wetland functions;  Section 4 – descriptions of six wetland functions, model variables, and functional indices;  Section 5 – this guidebooks’ assessment approach, including assembling preexisting data, collecting and recording new data, and analytical techniques and procedures;  Section 6 – acknowledgements;  Section 7 – citations; and  Appendices. While it is possible to assess the functions of desert playa depressional wetlands in the Mojave Desert using only the information contained in Sections 4 and 5, it is strongly suggested that users familiarize themselves with the information in Sections 2 and 3 prior to conducting a functional assessment.

REFERENCE DOMAIN

The reference domain is the geographic area from which reference wetlands representing the regional wetland subclasses are selected. For this guidebook, the reference domain is the California portion of the eastern Mojave Desert within San Bernardino and Inyo Counties, as illustrated on Figure 1, Mojave Basin and Range Ecoregion – Reference Domain. The intended region to be covered by this guidebook is all of the Mojave Desert and the southwestern portion of the Mojave Basin and Range Province in California and Nevada, and small areas of southwestern Utah and northwestern Arizona. Figures 1, 2, Mojave Basin and Range Ecoregion – Wetlands Larger than 100 Acres, and Figure 3, Mojave Basin and Range Ecoregion – Wetlands Larger than 100 Acres, below provide an illustrated overview of the reference domain and associated hydrographic and regional ecosystems information as defined by the U.S. Environmental Protection Agency.

Figure 1 – Mojave Basin and Range Ecoregion – Reference Domain

Figure 2 – Mojave Basin and Range Ecoregion – Wetlands Larger than 100 Acres

Figure 3 – Mojave Basin and Range Ecoregion – Reference Wetlands

SECTION II. OVERVIEW OF THE HYDROGEOMORPHIC APPROACH

As reviewed in Section I, the HGM Approach is a collection of concepts and methods for developing functional indices and using them to assess a wetland’s capacity to perform those functions relative to similar wetlands in the region. The HGM Approach includes four components: 1) the HGM classification, 2) identification of reference wetlands, 3) assessment models/functional indices, and 4) assessment protocols. During the development phase of the HGM Approach, these four components are integrated in a Regional Guidebook for assessing the functions of a regional wetland subclass. Subsequently, during the application phase, end users assess the functional capacity of selected wetlands according to the Regional Guidebook’s assessment protocols. This section discusses each component of the HGM Approach and the development and application phases. More extensive discussions of the general approach can be found in Brinson (1993) and Smith et al. (1995). Guidelines for the development of guidebooks are contained in Clairain (2002), Smith (2001), Smith and Wakeley (2001), and Wakeley and Smith (2001). A comprehensive glossary of terms that are specific to HGM and the geology, hydrology, and biology of desert playa lakes is also provided.

HYDROGEOMORPHIC CLASSIFICATION

Long periods of inundation or saturation, hydrophytic vegetation, and hydric soils are some of the features shared by wetland ecosystems. Regardless of these shared attributes, wetlands actually occur under a wide range of geologic and physiographic settings and climatic regimes and exhibit a variety of physical, chemical, and biological characteristics and processes (Cowardin et al. 1979, Ferren et al. 1996a, Ferren et al. 1996b, Gosselink & Turner 1978, and Mitsch & Gosselink 2000). This variability of wetlands creates challenges to developing assessment methods that are both accurate and practical. For example, the methods must be able to be sensitive to significant changes in function and not take too long to conduct the assessments. Classifying wetlands into general types reduces the gross variability wetlands cumulatively possess and then focusing on a restricted set of wetlands can accomplish this (Smith et al. 1995). The HGM classification of wetlands was developed specifically to accomplish this task (Brinson 1993) and identifies groups of wetlands that function similarly using three basic criteria: geomorphic setting, water source, and hydrodynamics. Landform and wetland position in the landscape defines the geomorphic setting. The primary source of the water, such as groundwater, floodwater flows, and direct precipitation, is another key factor in the classification. Hydrodynamics refers to the energy level and direction that the water moves in the wetland. Based on these three criteria, any number of functional wetland groups can be identified and classified at different spatial or temporal scales. Brinson (1993) identified five hydrogeomorphic wetland classes at a continental scale that were later expanded to seven classes by Smith et al.

(1995), and are listed in Table 1 – Hydrogeomorphic Wetland Classes at a Continental Geographic Scale.

Table 1 – Hydrogeomorphic Wetland Classes at a Continental Geographic Scale

HGM Wetland Class General Definition

Depression Depression wetlands occur in topographic depressions that allow the accumulation of surface water. Tidal Fringe Tidal Fringe wetlands occur along coasts and estuaries and are under the influence of sea level. Lacustrine Fringe Lacustrine Fringe wetlands are adjacent to lakes where the water elevation of the lake maintains the water table in the wetland. Slope wetlands are found in association with the discharge of Slope groundwater to the land surface, or at sites with saturated overland flow with no channel formation. Mineral Soil Flats wetlands are most common on interfluves, Mineral Soil Flats extensive relic lake bottoms, or large floodplain terraces where the main source of water is precipitation. Organic Soil Flats wetlands, or extensive peatlands, differ from Organic Soil Flats Mineral Soil Flats, in part because their elevation and topography are controlled by vertical accretion of organic matter. Riverine Riverine wetlands occur in floodplains and riparian corridors in association with stream or river channels.

Generally, the level of variability encompassed by a continent-wide hydrogeomorphic class is still too great for assessment models that are both rapid to apply and sensitive to functional changes relevant to the Section 404 (of the Clean Water Act) review process or other assessment purposes. For example, at a continental scale, the depression class includes wetland ecosystems as diverse as vernal pools in California (Solomesch et al. 2007 and Witham et al. 1998) and in glaciated forests of the Northeast (Calhoun & deMaynadier 2008); prairie potholes in North and South Dakota (Hubbard 1988 and Kantrud et al. 1989); playa lakes in the high plains of Texas (Bolen et al. 1989); huecos, springs, and tinajas in Utah and west Texas (Joque et al. 2007, MacKay et al. 1990, Vinson and Dinger 2008, and Wallace et al. 2005); and cypress domes in Florida (Kurz and Wagner 1953). To reduce both interregional and intraregional variability, the three classification criteria are applied at a smaller regional geographic scale to identify regional wetlands subclasses. In many parts of the country, existing wetland classifications can serve as a starting point for identifying regional subclasses (Ferren et al. 1996a, Ferren et al. 1996b, Golet and Larson 1974, Ratliff 1982, Rheinhardt and Hollands 2008, Stewart and Kantrud 1971, and Wharton et al. 1982). Regional subclasses are distinguished on the basis of hydrodynamics, water sources, and geomorphic setting. Additionally, certain ecosystem or landscape characteristics may also help in distinguishing regional subclasses in certain regions. Depressional subclasses might be based

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 8 on water source: groundwater versus surface water, or the degree of connection between the wetland and other surface waters. Two HGM wetland classes, Depression and Mineral Soil Flats, are further defined below as they are directly related to the wetland class covered by this Guidebook. Examples of potential regional subclasses of these two classes are listed in Table 2 – Potential Regional Wetland Subclasses, after Smith et al. (1995), Rheinhardt et al. (1997), and Hauer et al. (2002), in relation to geomorphic setting, dominant water source, and hydrodynamics.

Depression Wetland Class

Depression wetlands occur in topographic depressions (i.e. closed elevation contours) that allow for the accumulation of surface waters. They may have any combination of inlets and outlets or may be closed basins that lack inlets and outlets completely. The water source may come from one or any combinations of the following: precipitation, overland flow, streams, and/or groundwater/interflow from adjacent uplands. The predominant direction of the water flow is from the higher elevations toward the center of the depression, but may come from a deep aquifer, or subsurface springs. The predominant hydrodynamics are vertical fluctuations that range from diurnal to seasonal. Depression wetlands may lose water by evapotranspiration, through intermittent or perennial outlets, or as recharge to groundwater. Prairie potholes, playa lakes, vernal pools, and cypress domes are common examples of depression wetlands.

Mineral Soil Flats Wetland Class

Mineral soil flats are most common on interfluves, extensive relic lake bottoms, or large floodplain terraces where the main source of water is precipitation. They receive virtually no groundwater discharge, which is what distinguishes them from depressions and slopes. Dominant hydrodynamics are vertical fluctuations. Mineral soil flats lose water by evapotranspiration, overland flow, and seepage to underlying groundwater. They are distinguished from flat upland areas by their poor vertical drainage due to impermeable layers (e.g. hardpans), slow lateral drainage, and low hydraulic gradients. Mineral soil flats that accumulate peat can eventually become organic soil flats and typically occur in relatively humid climates. Pine flatwoods with hydric soils are a common example of mineral soil flat wetlands. Since most if not all of the playa lakes in the Mojave Desert receive water from either, or a combination of, groundwater, precipitation, and/or interflow, as contrasted with just precipitation, the playa lakes in the Mojave Desert are herein treated as belonging to the Depression wetland class. Table 2 – Potential Regional Wetland Subclasses, summarizes some major features of the proposed potential subclasses: 1) geomorphic setting, 2) dominant water source, 3) dominant hydrodynamics, 4) comparative systems from the eastern and western United States.

Table 2 – Potential Regional Wetland Subclasses

Geomorphic Dominant Dominant Western USA Eastern USA Setting Water Source Hydrodynamics Depression Groundwater, Vertical Vernal pools, Prairie potholes, precipitation, or playa lakes marshes, interflow Carolina bays Mineral Soil Precipitation Vertical Large playas Wet pine Flats flatwoods

REFERENCE WETLANDS

Reference wetland sites are selected in the HGM development process to represent the range of variability that occurs in a regional wetland subclass as a result of natural processes and disturbances, such as succession, channel migration, fire, erosion, and sedimentation, as well as anthropomorphic alteration. The reference domain is the geographic area occupied by the reference wetlands (Smith et al. 1995). While the geographic extent of the reference domain should reflect the geographic area encompassed by the regional wetland subclass, this is not always possible because of time and resource constraints. Reference wetlands serve three basic purposes: 1) they establish a basis for defining what constitutes a characteristic and sustainable level of function across the suite of functions selected for a regional wetland subclass; 2) they establish the range and variability of conditions exhibited by model variables and provide the data necessary for calibrating the model variables and assessment models; and 3) they provide a concrete physical representation of wetland ecosystems that can be observed and measured. Following accepted HGM practice, reference standard wetlands are typically defined to be the subset of reference wetlands that perform a representative suite of functions at a level that is both sustainable and characteristic of the least-human-altered wetland sites in the least-human-altered landscapes. Table 3 – Reference Wetland Terms and Definitions, provides definitions of terms commonly used by the HGM Approach in the context of reference wetlands.

Table 3 – Reference Wetland Terms and Definitions

Term Definition Reference Domain The geographic area from which reference wetlands representing the regional wetland subclass are selected. Reference Wetland A group of wetlands that encompass the known range of variability in the regional wetland subclass resulting from natural processes and disturbance and from human alteration (anthropomorphic changes).

Term Definition Reference Standard The subset of reference wetlands that perform a representative suite of Wetland functions at a level that is both sustainable and characteristic of the least human altered wetland sites in the least human altered landscapes. By convention, the functional capacity index for all functions in a reference standard wetland is assigned a value of 1.0. Reference Standard The range of conditions exhibited by model variables in reference standard Wetland Variable wetlands. By convention, reference standard conditions receive a variable Condition subindex score of 1.0. Site Potential The highest level of function possible given local constraints of disturbance history, land use, or other factors. Site potential may be less than or equal to the levels of function in reference standard wetlands of the regional wetland subclass. Project Target The level of function identified or negotiated for a restoration or creation project. Project Standards Performance criteria and/or specifications used to guide the restoration or creation activities toward the project target. Project standards should specify reasonable contingency measures if the project target is not being achieved.

ASSESSMENT MODELS AND FUNCTIONAL INDICES

In the HGM Approach, an assessment model is a simplified representation of the functions performed by a wetland ecosystem. It defines the relationships between characteristics or processes of the wetland ecosystem, including adjacent upland habitat functions. Functional capacity is the ability of a wetland to perform a function or functions compared to the level of performance in reference standard wetlands. By definition, HGM guidebooks assign all functions in reference standard wetlands a Functional Capacity Index (FCI) of 1.0. However, this treatment of “the best wetlands in the reference domain” leads to conflicts between the principles behind the HGM Approach, calibration of specific HGM models, and unbiased application of HGM to a diversity of sites. Specifically: 1. It is usually impossible to fit a statistical FCI model with actual field data that yields the same fitted FCI as an a priori FCI (r² for the statistical model is <1.0). Thus, a priori FCI values of 1.0 that have been assigned to reference standards in any particular function can only be approximated with real data. This is true for both direct FCI estimates, and indirect FCI estimates, with greater departures generally fund with indirect FCIs. Other HGM guidebooks generally circumvent this problem by using simple FCI models with only a few variables, so that all reference standard wetlands will in fact receive a score of 1.0 for the function. However, the FCI models are not fitted to actual data in many guidebooks. When they are fitted to real data, the wetlands chosen often do not represent the full range of natural variability and anthropogenic disturbance. In this guidebook, we consider the difference between a priori FCI scores and fitted FCI scores to be error in the statistical model. We attempted to minimize these errors using standard statistical techniques, but in most cases we chose not to simplify the models to the extent necessary

to completely eliminate them. Thus, application of this guidebook is not expected to yield the maximum score of FCI = 1.0 for all undisturbed wetlands in all cases. 2. A deeper philosophical issue arises with regard to the definition of “function”. Assigning a value of 1.0 to all functions for all reference standard wetlands implies that the functional capacity is not being estimated on an absolute scale. Consider a shallow playa in a relatively small watershed (small catchment area). Even in an unaltered landscape, such a playa may only fill during the wettest years. In a typical year, it may store no surface water and very little subsurface water. What a priori value should it be assigned for the function “Surface Water Storage” and/or “Groundwater Recharge”? There are four options: a. Assign an undisturbed headwater playa an a priori FCI <1.0 for water storage because, despite its pristine nature, it stores very little water in absolute terms; however, it may be assigned a score of 1.0 for other functions. Redefine the term “reference standard” in a manner that departs from other guidebooks (Table 3), and include this playa as a reference standard. b. Do not classify it as a reference standard, based on the traditional reference standard definition. We suspect that most or all other HGM guidebooks have taken this approach, and omitted undisturbed wetlands from the reference standard class if their hydrology, biota, or other attributes are atypical or depauperate (lacking in numbers or varieties of species). If it is acceptable to assume that “function” should be estimated in relative terms, rather than absolute, option c) iii) is clearly defensible. However, accurate model fitting would require collecting data from multiple reference playas across the full spectrum of covariates. It would likely require data from many years that span the full range of precipitation events. As mentioned above, we suspect that previous HGM wetland guidebooks have focused exclusively on playas that have typical values for covariates such as hydroperiod, landscape position and depth, excluding those that have more extreme values (Gilbert et al. 2006). c. One could designate shallow headwater playas as un-scorable for the water storage function based on insufficient data for model calibration. They could still be retained as reference standards if all other functions that can be scored are given an a priori FCI of 1.0. If new data are gathered in the future, the function could be revised using one of the other options.

MODEL VARIABLES

Model variables represent the characteristics of the wetland ecosystem and surrounding landscape that influence the capacity of a wetland ecosystem to perform a function. Model variables are ecological quantities that consist of five components (Schneider 1994): 1) a name; 2) a symbol; 3) a measure of the variable and procedural statements for quantifying or qualifying the measure directly or calculating it from other measures; 4) a set of values (numbers, categories, numerical estimates [Leibowitz & Hyman 1997]) that are generated by applying the procedural statement; and 5) units on the appropriate measurement scale. Table 4 – Components of a Model Variable, provides some examples. (Bauder et al 2009.)

Table 4 – Components of a Model Variable

Name (Symbol) Measure/Procedural Statement Resulting Value Units Basin Depth The maximum depth of the playa, >0 meters (VMAXDEPTH) as estimated with surveying equipment Inlet Modification Discernible modification to the 0 = no, 1 = yes unit-less (VINLETMOD) inlet Coverage of Basin The percent cover of the basin 0 to 100 percent, written as with Cobbles surface with angular course pebbles a whole number (VCOBBLESBA) or cobbles, as defined in the 1993 USDA Soil Survey Manual Bauder et al 2009. Model variables occur in a variety of states or conditions in reference wetlands. For example, percent herbaceous groundcover could be (relatively) high or low. Based on its condition, value of the metric, model variables are usually assigned a variable subindex by rescaling them. A variable subindex of 1.0 is often assigned when the condition of a variable is within the range of conditions exhibited by the reference standard wetlands. As the condition declines from that found in the reference standard wetlands, the variable subindex is assigned based on the relationship between model variable and condition and functional capacity. In most instances, the rescaling of variables into variable sub-indices is based on pertinent literature, personal expertise, and experiences and information from references wetlands (Smith et al. 1995). Lower subindex values reflect decreasing contribution to functional capacity, relative to reference standard wetlands. In some instances, the variable subindex can drop to zero. The rationale for intermediate subindex scores is generally less well defined; however, a linear relationship is usually assumed between the original variable’s value and the subindex value. In the HGM Approach, model variables are combined into an assessment model to produce a FCI that ranges from 0.0 to 1.0. Within each function, the variables are usually combined as a simple average. However, we used a statistical model for most functions, in which the coefficient for each variable is derived from a multiple regression or general linear model. The FCI is a measure of the functional capacity of a wetland relative to reference standard wetlands in the reference domain. Wetlands with an FCI of 1.0 perform the function at a level characteristic of reference standard wetlands. As the FCI decreases, it indicates that the capacity of the wetland to perform the function is less than that of the reference standard wetlands. In some cases, the FCI may be based on model variables that directly relate to the function of the variable, and can only be assessed under specific field conditions, such as when the playa is holding water. In this guidebook, we refer to these as Direct FCIs. Alternatively, the FCI may be based on variables that can be measured at any time of the year, correlate well with the level of function, but are not causally related to the function. We refer to these as Indirect FCIs.

CONCEPTUAL FRAMEWORK FOR COMPUTING DIRECT AND INDIRECT FCIs: GRAPHICAL AND STATISTICAL ANALYSES

We employed both exploratory and formal graphical and statistical analyses to determine how single variables and groups of variables relate to the function and Biogeochemical Processes functions. Details regarding our approach are provided in Section V, Assessment Approach, in the subsection titled “Analytical Techniques and Procedures”. We included interactions among variables when they emerged from the analysis and could be explained by known processes. We searched for threshold effects and other nonlinear relationships between the variables and the level of function. Ultimately, we discarded many variables that did not have explanatory power both empirically and logically. As an initial step in developing an FCI based on direct measures of function (a Direct FCI), we developed guidelines for assigning an a priori FCI to each playa. The a priori FCI generally describes the overall level of function for a playa based on the best expert opinion. The subset of playas deemed to be reference standards, that is, the most functional representations of natural playas, received an a priori FCI of 1.0 for all functions. However, we neither expected nor enforced the assumption that non-reference standard playas should have identical FCI scores for all functions. For example, disturbances that severely alter the hydrology of a particular playa may have less impact on its fauna than its water storage capacity. To maintain objectivity, we developed verbal definitions for seven different FCI values ranging between 0.0 and 1.0. FCI guidelines similar to those in Appendix D.6 have not been made explicitly in any other HGM guidebook.

ASSESSMENT PROTOCOLS

The final component of the HGM Approach is the assessment protocol, which is a series of tasks, along with specific instructions, that allow the end user to assess the functions of a particular wetland area using the assessment variables, models, and functional indices in the Regional Guidebook. The first task is characterization, which involves describing the wetland ecosystem and the surrounding landscape, describing the proposed project and its potential impacts, and identifying the wetland areas to be assessed. The second task is collecting the data for the model variables. The final task is analysis, which involves calculation of functional indices. Section V provides detailed instructions for site characterization and data collection necessary for development of Direct and Indirect FCIs.

DEVELOPMENT PHASE

Typically, an interdisciplinary team of experts known as the “Assessment Team” or “A Team” ideally carries out the Development Phase of the HGM Approach. A team of 5-8 individuals is recommended as sufficiently large to represent critical disciplines and not too large as to be unwieldy (Smith et al. 1995). The following disciplines have been recommended for representation on the A Team: wetland ecology, geomorphology, biogeochemistry, hydrology, soil science, plant ecology, and animal ecology.

Due to time and budget constraints, we took a much more compressed approach and used a smaller team in the development of this preliminary draft guidebook, with members having expertise, training, and/or experience in each of these disciplines, with emphasis on the biological sciences. We relied heavily on the work of experts who developed other Regional Guidebooks, including Bauder et al. (2009), Gilbert et al. (2006), Lee et al. (1997, 2001, 2003).

APPLICATION PHASE

This phase involves two steps. The first is to use the assessment protocols outlined in the Regional Guidebook to carry out the following tasks: a. Define assessment objectives; b. Characterize the project site; c. Screen for red flags; d. Define the Wetland Assessment Area; e. Collect field data; and f. Analyze field data. The second step involves applying the results of the assessment (i.e. the FCIs), to the appropriate decision-making process. Although the HGM Approach was originally conceived for use in a regulatory context as part of Section 404 of the Clean Water Act, it has a variety of other potential applications. For instance, the HGM assessment models for southern Californian vernal pools were developed primarily for use in ecosystem restoration and preserve management, within an overall planning context. There are several ways in which the HGM Approach can be applied as part of an overall planning framework. For instance, in analysis of alternative plans, it can be used to measure variable impacts to existing wetlands (DMEC 2000, 2001, 2004, 2006a, 2006b, and 2009), or locate and evaluate potential restoration sites. Because the HGM Approach produces numerical values as a measure of various wetland functions, these numbers can be used to quantify and compare impacts and benefits to wetlands due to various alternative proposed plans and actions. It can similarly be used to evaluate the effectiveness of management practices and suggest corrective actions (DMEC 2006b). (Bauder et al. 2009.)

SECTION III. CHARACTERIZATION OF PLAYA LAKES

REGIONAL WETLAND SUBCLASS AND REFERENCE DOMAIN

This Draft Regional Guidebook was developed to assess the functions of temporarily and seasonally ponded depressional arid basins within the Mojave Desert region (MDR). These and other similar features are referred to by a variety of terms including dry lake, ephemeral lake, salt flat, Sabkha, and others. For the purposes of this guidebook they will be referred to as playas. Playa is the Spanish word for beach or shore, but generally refers to this landscape feature in the United States and other English speaking countries. The term playa also refers to pluvial lakes in the southern plains region of the United States; however, these are functionally different from desert playas (Brostoff et al. 2001) and will not be considered in this guidebook. Playas occur throughout the arid regions of the world. In the United States they are found throughout the western deserts. They are large flat areas that occupy the lowest portion of basins that typically have no drainage outlet and flood periodically (Neal 1975). The playas considered by this guidebook were generally formed in basins formerly occupied by large pluvial lakes during the Pleistocene epoch. They are now (Holocene epoch) dry most of the time, have been defined as being covered with water less than 25 percent of the time, and by having a negative water balance for more than half of each year (Motts 1969, Briere 2000). The sporadic and infrequent precipitation of the MDR and subsequent ephemeral nature of playa ponding events contributes to diverse floral and faunal communities. Playa surfaces are generally devoid of vegetation. However, there are vegetation communities found in mounds on the playa surface, as well as on playa margins and surrounding areas. The extent of these vegetation zones are defined by salinity and substrate, and include a variety of xerophytic, halophytic, and phreatophytic plant species (Vasek and Lund 1980, Lichvar 2006). When they are inundated playas provide an important source of water to animal species. Certain animal species are endemic to Mojave Desert playas and remain dormant as eggs and cysts, waiting for the playa to be inundated (Eng et al. 1990). These vegetation and faunal communities are undoubtedly adversely affected by alterations to playa composition and hydrology caused by anthropogenic activities such as development and agriculture, as well as by invasive species such as Tamarix. There are two main playa types that are referred to as hard and soft playas, or wet and dry playas. These two general classes of playa differ in their hydrology, surface texture, duration of inundation, and formation of mineral crusts and other surface features. Soft playas have a loose, friable structure and uneven surface, while hard playas are smooth and impermeable (Motts 1969, Brostoff et al. 2001, Laity 2008). These two playa wetland types function similarly for the most part, but they differ in certain important aspects and are thus considered as separate subclasses.

DESCRIPTION OF THE REGIONAL WETLAND SUBCLASS

Landscape Setting

The MDR occupies the majority of southeastern California, southern Nevada, northwest Arizona, as well as a small portion of southwest Utah. It is bordered by other deserts, including the Sonoran (Colorado) Desert to the south and east, and the Great Basin desert to the north and east. Several mountain ranges define its boundaries, including the Transverse Ranges to the south, the Tehachapi and Sierra Nevada ranges to the northwest and west, and the Basin and Range Province to the northeast and east. These mountain ranges generally to the west block rain storms from the Pacific Ocean and combine to form an extremely arid region. Federal agencies including the Bureau of Land Management, National Park Service, and the Department of Defense own large areas of land within the Mojave Desert, and federal land constitutes 81 percent of the region. The most significant urbanized locales in the Mojave Desert region are the Las Vegas (Nevada), Palmdale/Lancaster (California), and Barstow (California) areas (Sleeter 2014). The region is still relatively unpopulated: 1.5 percent of the land cover is developed land. The vast majority of the land is dominated by herblands (usually referred to as grasslands1) and shrublands (Vogelmann 2001). What little surface water there is has no outlet; in fact the Mojave drainage basin has likely not had surface drainage into the Pacific Ocean for over 10 million years (Sleeter 2014). Many of the reference playas used for creation of the Mojave Desert playa HGM model are located in the Mojave River drainage network and were once large pluvial lakes during the Pleistocene epoch. Others are basins in more localized drainage systems that were also likely former pluvial lakes. DMEC used ArcGIS software to ascertain the sizes and elevations of the 17 reference playas. This data is included in Table 5, General Characteristics of Mojave Reference Sites. The EPA level IV ecoregion for each reference playa is also included in this table. Figure 4, Reference Domain and Locations of Reference Playas, details the locations and names of the reference playas that were visited by DMEC in the development of this guidebook. Figure 5, Reference Domain and Mojave River Watershed, illustrates the spatial extent of the Mojave River watershed and EPA Level IV ecoregions in the reference domain.

1 Grasslands, habitats dominated by one or more species of the grass family (Poaceae) are actually quite rare in the Mojave Desert while most occurrences of herbaceous plant communities are dominated by annual or perennial herbs with only minor contributions from grass species. Therefore, the term “herblands” is used here as it more accurately portrays the basic vegetation types present.

Figure 4 – Reference Domain and Locations of Reference Playas

Figure 5 – Reference Domain and Mojave River Watershed

Table 5 – General Characteristics of Mojave Reference Sites

Name EPA Level IV Ecoregion Square Miles Acres Elevation (ft) Bristol Lake Mojave Playas 161.548 40,674.99 610 Broadwell Lake Mojave Playas 8.438 2,084.68 1,315 Dry Lake: Silurian Death Valley/Mojave Central Trough 3.797 938.22 754 Valley East Cronese Lake Eastern Mojave Basins 5.827 1,439.66 1,080 El Mirage Lake Mojave Playas 12.896 3,186.29 2,837 Green Rock Mine: Eastern Mojave Basins 0.241 59.46 1,837 Brubaker-Mann Harper Lake Mojave Playas 33.44 8,262.05 2,024 Ivanpah Dry Lake Mojave Playas 36.652 9,057.29 2,604 Lucerne Lake Mojave Playas 18.252 4,509.44 2,848 Panamint Valley Mojave Playas 20.429 5,050.02 1,015 Lake: north Panamint Valley Mojave Playas 35.677 8,818.50 1,015 Lake: south Rabbit Lake Western Mojave Basins 3.035 749.81 2,933 Searles Lake Mojave Playas 53.726 13,277.65 1,617 Silurian Lake Death Valley/Mojave Central Trough 5.346 1,321.17 670 Silver Lake Mojave Playas 26.558 6,562.38 908 Soda Lake Mojave Playas 65.221 16,114.63 935 Troy Lake Mojave Playas 8.912 2,283.67 1,778 West Cronese Lake Eastern Mojave Basins 3.444 850.90 1,072

Geomorphic Setting and Geology

The MDR exhibits a unique topography that has been heavily influenced by tectonic activity. The western Mojave Desert derives its triangular shape from the San Andreas Fault to the southwest, and the Garlock Fault to the north (Dibblee 1967). The eastern Mojave Desert contains many north-south trending mountain ranges and basins (where water converges to a single point) that are typical of the Basin and Range Province, which is formed by continental extension. Although the mountains surrounding the western Mojave reach elevations upwards of 3,000 meters, the desert floor itself is essentially an alluvial plain with generally lower elevations, with elevations as low as 85 meters below sea level in Death Valley. Figure 6, Reference Wetlands – Elevation Model and Watershed Boundaries, graphically illustrates the elevations of the Mojave Desert and the reference playas and associated watersheds. The rocks of the western Mojave and associated mountains can be described in three main classes: pre-Tertiary crystalline rocks, Tertiary volcanic and sedimentary rocks, and Quaternary localized basalt flows and sediments (Dibblee 1967). The integrated geology of the Mojave Desert is illustrated in Figure 7, Reference Wetlands – Integrated Geology.

Figure 6 – Reference Wetlands – Elevation Model and Watershed Boundaries

Figure 7 – Reference Wetlands – Integrated Geology

The Mojave River is the most significant drainage network in the Mojave Desert, and its drainage pattern has been significantly affected by the San Andreas Fault and tectonic uplift of the Transverse Ranges, which occurred during the late Cenozoic era (Cox et al. 2003). About 18,000 years ago (during the Ice Age termed the Last Glacial Maximum) it stretched from the San Bernardino Mountains in the west to Death Valley in the northeast. At that time, the Mojave River flowed through or replenished the large Pleistocene Lakes Manix and Mojave (Stoffer 2004a). Currently, the Mojave River only reaches eastward to Soda Lake and Silver Lake, and the Cronese Lakes from the San Bernardino Mountains. Lake Manix, which was situated near where Barstow is currently located and east to Afton Canyon, encompassed a large portion of the Mojave River drainage area, and occupied the Afton Lake, Coyote Lake, Cronese Lake, Harper Lake, Koehn Lake, and Troy Lake Basins from 18,000 to 450,000 years ago. Silurian Lake and Soda Lake (including Silver and Dry Lakes in between) were part of the former Lake Mojave, which was located near the present day Baker region (Stoffer 2004a). Certain landscape features were formed by dynamic changes in the Mojave River system, such as when, during the peak of the last Ice Age, Lake Manix overflowed into Lake Mojave and created a new channel that is now Afton Canyon (Stoffer 2004b). Many of the basins of ancient Lake Manix and Lake Mojave, along with many basins outside the area they encompassed and near the Mojave River, dried up around 8,000 years ago as the Pleistocene epoch ended and glaciers retreated from the Mojave Desert region (Stoffer 2004a). Many of these basins are currently playas, which are generally devoid of vegetation and usually at least 2,000 to 3,000 feet in diameter. These large landscape features are not to be confused with smaller (several hundred feet in diameter or less) barren drainage areas, which could be considered “microplayas” (Motts et al 1969). Playas are generally situated at the lowest portion of the basin and have no outlet. The playas flood and pond water after precipitation events, and slowly accumulate sediment (Lichvar and Dixon 2007). Playas and playa lakes have also formed where drainage systems were impeded by alluvial depositions, lava flows, or fault action (Stoffer 2004a). In between mountains and playas are landscape features called alluvial fans and desert flats. These alluvial slopes originate at the bases of mountains and slope towards the desert floor and the playas. Alluvial fans can be divided into pediments, which are a thin layer of alluvium (20 feet or less) on top of bedrock, and bajadas, which are formed by coalescing alluvial fans on top of thick alluvium. Desert flats have sand, fine gravel, and vegetation covering their surfaces, and extend from the base of alluvial fans to the edges of playas (Motts et al. 1969). These features can be quite large, such as the Cajon fan, a system of coalescing alluvial fans and terraces that extends from the San Gabriel and San Bernardino Mountains over ten miles to the Mojave River and Mirage Lake. Alluvial fans are often truncated by rivers and altered by tectonic action. Their sedimentation and erosional processes are affected by fluctuations in climate and precipitation (Tugel and Woodruf 1986, Harvey et al 1999). The MDR has aeolian sand deposition pathways that are dictated by the interaction of basins, mountain ranges, and prevailing wind patterns. Winds traveling through the region cause sand to accumulate in certain areas (Muhs 2013). This can lead to the creation of large dunes such as the Kelso Dunes south of the town of Baker, as well as smaller localized dunes such as those found around playa margins or on the leeward slopes of mountains, such as the falling dunes (the Cronese Cat is a textbook example on the east slope of the Cronese Mountains above the Cronese Basin and East Cronese Lake).

Climate

The MDR exists in the southwestern United States and has one of the most extreme and variable climates of the world (Bailey 1995). The MDR experiences typical desert climactic conditions such as hot dry summers and mild winters. Desert conditions prevail across the MDR largely because of local topography and the position of the region on the North American continent, and the associated global atmospheric and oceanic conditions. However, significant local climactic variation within the region exists.

Cyclic Processes and Reference Standard Cycle Topography is considered in wetland boundary determination when diagnostics exist as hydrologic confinements. Total areas of wetland habitats were calculated using delineated lines, points, and polygons using ESRI ArcView 3.3 and ArcGIS 10.2 software and onsite measurements. Delineation data points were collected using Garmin eTrex Vista GPS and GPS Map 62stc handheld units. Significant variation in temperature exists at both temporal and spatial scales across the region. The majority of the MDR sees summer maximum daily temperatures between 20°-30°C (68°- 86°F) at higher elevations that often rise above 40°C (104°F) at lower elevations, particularly in the southern portion of the region (NPS 2007). Death Valley has the United States’ highest (and the world’s second highest) recorded temperature at 57°C (134°F). Winter temperatures can range from 1°-19°C (33°-66°F) with freezing temperatures typically only seen at higher elevations and in the northern portion. The MDR is bounded on the west and southwest the Sierra Nevada and Transverse Ranges. These mountain ranges create a rain-shadow effect by intercepting moisture and altering prevailing winds from the Pacific Ocean (Hereford et al. 2006, NPS 2007). This rain shadow effect works with other regional factors to create a moisture gradient with drier conditions prevailing in the west grading to wetter conditions in the east (NPS 2007). Two general precipitation regimes prevail within the MDR and are separated approximately at the 117°W meridian (near Barstow, California, Hereford et al. 2006). The areas west of 117th meridian receive the majority of precipitation during winter season storm events, while the areas east of the 117th meridian receive precipitation from a biseasonal pattern. Winter season storm events bring moisture into the entire region, generally peaking in January. Localized summer monsoonal rains often peaking in August are derived from tropical and subtropical storms off the coast of Mexico. These rains can bring significant moisture into the eastern portion of the MDR. Winter precipitation is strongly related to elevation, ranging from approximately 100 mm/year at lower elevations to approximately 500 mm/year at higher elevations, with a regional average of 149 mm/year (Hereford et al. 2004). Precipitation in the MDR also varies on inter-annual and multi-decadal time scales, largely related to the El Nino Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) conditions, respectively. These conditions relate to fluctuations of average sea surface temperatures: ENSO/El Nino phase conditions relate to a trend of higher sea surface temperatures that result in increased moisture in the MDR. ENSO/La Nina phase conditions relate to lower sea surface temperatures that result in drier conditions in the MDR (Hereford et al 2006, NPS 2007). ENSO phase conditions typically influence climactic conditions in the MDR

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 24 for one-year periods. PDO variations can result in longer term drier or wetter conditions that persist for several decades. All these conditions have profound effects on the ecological (both biotic and abiotic) condition of the MDR (Hereford et al. 2006, NPS 2007). The percentage of precipitation that is lost to evapotranspiration in the MDR varies from 90 - 95% to more than 100% and higher, as illustrated in Figure 8, Reference Domain – Estimated Evapotranspiration. Table 6, Climate Variable Averages (1981 – 2010) for the Mojave Desert Region, contains average monthly highs and lows and precipitation amounts for 1981-2010 (U.S. Climate Data 2015). These data is from one location in the Mojave and is intended to give a general idea of temperature and precipitation values for the MDR. However, it should be noted that there is a high degree of variability in temperature and precipitation based on elevation and other factors.

Table 6 – Climate Variable Averages (1981 – 2010) for the Mojave Desert Region

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Avg. Avg. high °F 57 60 66 71 80 89 96 96 88 78 65 56 75.2 Avg. low °F 33 37 41 46 56 64 70 67 61 50 40 33 49.8 Avg. Precipitation 1.18 1.54 0.98 0.24 0.12 0.04 0.31 0.28 0.16 0.35 0.59 0.91 6.7 (in.)

Note: Data from Longitude: -118.162, Latitude: 35.0492

Hydrology

Water Sources These complex desert systems have developed in a climatic regime of wide fluctuations of precipitation, ranging from drought to flood. Yearly variations in both temperature and precipitation extremes are common. Broad seasonal fluctuations in precipitation are nested within multi-year cycles, resulting in drought and pluvial wet cycles as the norm. Variability of flow is a natural continuum in arid and semi-arid regions, and is affected by climatic and ecological conditions (Mabbutt 1977). Desert environments typically produce more runoff and erosion per unit area than in temperate regions for a given intensity of rainfall due to sparse vegetation cover and poorly developed soils with little organic matter (Thornes 1994). Rainfall patterns in arid and semi-arid regions influence when streamflow is most likely. The Great Basin and Mojave Deserts have wet winters and relatively dry summers with sporadic thunderstorms (Gochis et al. 2006). This warm-season monsoonal rainfall results from a seasonal reversal of atmospheric circulation that transports moisture from the Gulf of Mexico and/or the Gulf of California (Hereford et al. 2002). Longer duration rainfall events with embedded high-intensity thunderstorms are often the result of dissipating tropical depressions that are common in the fall and sometimes in the winter (Webb and Betancourt 1992, Gochis et al. 2006), while the lower-intensity events are typical of cool- season precipitation caused by frontal systems originating in the eastern North Pacific Ocean (Hereford et al. 2002).

Figure 8 – Reference Domain – Estimated Evapotranspiration

Desert ecosystems also rely on subsurface water flows from springs that mostly occur at the base of alluvial fans and discharge large quantities of ground water onto the playas. While hydrologists generally reject the popular concept of an “underground river”, the sediment below the river channel does convey water. For some streams, in current climatic regimes, there may not be a perennial or intermittent reach, but water may always be present below the ground and accessible to a rich assemblage of plant and animal life (Mabbutt 1977). Adjacent mountainous regions will accumulate snow fall during the winter months that will add runoff water to the region as melting occurs throughout the spring months. Desert playas are the lowest points in the watershed that typically have no associated surface outlet.All water that accumulates in the playa basin will slowly be recharged into the groundwater or evaporate (Gochis et al. 2006). The catchment basins for Mojave playas are determined by the configuration of regional basins and watersheds. Figure 9, Reference Sites – Regional Hydrologic Basins, identifies the regional basins (HUC-6) for the reference domain and Figure 10, Reference Sites – Regional Sub-basins and Watersheds, identifies the sub-basins (HUC8). The regional groundwater basins are illustrated on Figure 11, Reference Sites – Regional Groundwater Basins, and Figure 12, Reference Sites – Surface Hydrology Networks, illustrates the surface hydrology networks of the Mojave Desert and the locations of the reference playas. Table 7, Reference Playa Basins, Sub- basins, and Watersheds, identifies the basins (HUC6), subbasins (HUC8), and watersheds (HUC10) for each of the respective 17 reference sites visited by DMEC (USGS National Hydrography Dataset: NHD).

Figure 9 – Reference Sites – Regional Hydrologic Basins

Figure 10 – Reference Sites – Regional Subbasins and Watersheds

Figure 11 – Reference Sites – Regional Groundwater Basins

Figure 12 – Reference Sites – Surface Hydrology Networks

Table 7 – Reference Playa Basins, Subbasins, and Watersheds

Reference Site Name HUC10 Name HUC8 Name HUC6 Name East Cronese Lake Cronese Valley Mojave Northern Mojave Silver Lake Silver Lake Mojave Northern Mojave Sheep Creek - El El Mirage Lake Mirage Lake Mojave Northern Mojave Death Valley - Lower Dry Lake : Silurian Valley Riggs Wash - Salt Creek Amargosa Northern Mojave Troy Lake Troy Lake Mojave Northern Mojave Soda Lake Soda Lake Mojave Northern Mojave West Cronese Lake Cronese Valley Mojave Northern Mojave Broadwell Lake Broadwell Lake Mojave Northern Mojave Death Valley - Lower Silurian Lake Riggs Wash - Salt Creek Amargosa Northern Mojave Crystal Creek - Lucerne Lucerne Lake Lake Southern Mojave Southern Mojave Silver Creek - Rabbit Rabbit Lake Lake Southern Mojave Southern Mojave Bristol Lake Bristol Lake Southern Mojave Southern Mojave Ivanpah - Pahrump Central Nevada Desert Ivanpah Dry Lake Ivanpah Lake Valleys Basins Panamint Valley Lake Panamint Valley Lake: south South Panamint Valley Northern Mojave Coyote - Cuddeback Harper Lake Harper Lake Lakes Northern Mojave Panamint Valley Lake Panamint Valley Lake: north North Panamint Valley Northern Mojave Green Rock Mine : Brubaker- Baxter Wash - Mojave Mann River Mojave Northern Mojave Indian Wells - Searles Searles Lake Searles Lake Valleys Northern Mojave

Water Dynamics Mojave Desert playas exhibit fluctuations of water levels and can have multiple feet of water persisting in heavy precipitation cycles. However, winter rainstorms related to eastward-moving cyclonic systems from the Pacific Ocean and summer thunderstorms related to moist monsoonal flows moving northward from the Gulf of California and the neighboring tropical Pacific may sometimes inundate these dry lake beds. The duration of flooding depends on the magnitude and location of precipitation and ambient climatic conditions over the lakes (Lichvar et al. 2002). These playas exhibit both long- and short-term fluctuations in ponding depth. The absence or presence as well as elevation of outlets are important and may result in some functions during wet cycles, due to presence of water or lack of moisture that are more commonly associated with wetlands on open landscapes. The Mojave Desert playa landscape is characterized by large low gradient lakes that vary in depth at a single point in time, thus contributing to diverse habitats. The hydrodynamics contribute to groundwater recharge, maintenance of salt balance in the landscape, maintenance of anaerobic conditions, and fluctuations between anaerobic and aerobic conditions. The retention of surface

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 32 waters results in an aquatic-moist habitat in an otherwise semi-arid and arid landscape. These conditions directly influence biogeochemical functions. Once filled, playas hold water for varying durations that depend on evaporation and evapotranspiration rates. Early in the season, movement of water into the adjoining soils can rapidly lower playa lake levels, especially during the first few hours after storms. Later in the year or following major storms, water flowing into the playa from the adjoining soil can gradually increase water levels after a rainfall event ends. Precipitation in the Mojave Desert is variable enough that a given playa may not pond water at all in some years, while at other times it may hold water on its surface for up to three years in a row (Cooke et al. 1993). Landscape position likewise affects the likelihood of ponding and the length of ponding events. Playas may be isolated or be part of a network (rare for desert playas). The Cronese Lakes and Soda and Silver Lakes are examples. A network is an integrated set of channels and basins that drain a watershed. Basins within a network will function hydrologically in accordance with their position within the network, the size of the watershed and the antecedent and incident rainfall. Playa salinities often reach a minimum during the middle of the winter season. Early ponding events dissolve salts left on the bed and banks of the playa by the prior season’s evaporation. Salinities gradually decrease later in the season as shallow ground water enters the playas. Later in spring, salinities increase rapidly as the pools within the playa desiccate, leaving high salinity deposits behind (Bauder 2009).

Biogeochemical Processes

Playa lakes biogeochemistry is determined by a number of ecological, hydrological, and geological functions. Arid and semi-arid regions are limited in nutrient supply due to lack of biomass productivity and climatic regimes of low precipitation with limited nutrient flow into subsurface soils. Arid lands have unique adaptations to deal with nutrient cycling, nitrogen fixation, respiration, and mineralization. As described previously, precipitation is the main water source for desert playas: water falls directly on the basin, moves through the surface and subsurface soils, and enters via surface flow or spring flows. The presence of water influences biogeochemical reactions, movement of sediment, and the distribution of nutrients (Garcia-Moya and McKell 1970). Deficiencies in essential nutrients result from a combination of low decomposition rates, short- term periods of rapid growth after precipitation that exhaust nutrients faster than they can be re- placed, and intrinsically low nutrient content of the soil in some regions. The nutrient supply in arid regions is confined largely to the upper surface (0-5 cm) and lower soil layers are typically "nutrient poor" due to low decomposition and leaching rates. As a result, large quantities of nitrogen are lost to the atmosphere via erosion and volatilization, leaving only a small percentage available to roots of higher plants. Nutrient return via litter and dead plants is also strongly localized around the plants (Garcia-Moya and McKell 1970). Desert playas have a direct relationship with biological soil crusts. Biological soil crusts are a prominent component in arid and semiarid regions (West 1990), and their photosynthetic and carbon fixation capacities have been studied extensively (Zaady et al. 2000, Brostoff et al. 2001, Brostoff et al. 2005, Housman et al. 2006). Biological soil crusts control the movement of water, gases, and solutes across soil surfaces (Belnap et al. 2003), which in turn control the amount and

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 33 chemical makeup of water entering the playa. Biological crusts on rock outcrops, boulders, and smaller clasts can have a major impact on weathering through a range of chemical and physical processes. Cyanobacteria, green algae, fungi, lichens, and bacteria can secrete powerful metal chelators, such as siderochromes, which are highly effective at removing elements from rocks. Photosynthetic organisms within biological crusts also influence pH levels, often being reported to increase pH (Belnap et al. 2003). Biological crusts can also play a bioprotective role (Carter and Viles 2005), contributing to surface hardening and stabilization and preventing water from reaching the rock surface and contributing to weathering. Biological crusts also contribute to removal of carbon from arid soils, through the process of respiration with peaks noted immediately after rainfall, before photosynthesis becomes activated (Maestre and Cortina 2003). Some organisms found in biological crusts, e.g. cyanobacteria and cyanolichens, are key contributors to nitrogen fixation, whereas other important components of crusts (e.g. green algae, phycolichens, and mosses) are not able to fix nitrogen (Evans and Lange 2003). Biological soil crust microfeatures, which vary as a function of crust morphology, enhance dust capture and form complex internal voids and vesicular pores that trap surface water for uptake by crust organisms. In turn, the resulting Av [vesicular A] horizons of the bio-rich and bio-poor zones drive landscape-scale water distribution and subsurface soil processes (Turk and Graham 2011). The overall lack of plant growth on playas is certainly due to high salinity levels at the soil surface as well as extremely harsh abiotic features of playa habitats. Air content in playa soils can be very poor during periods of flooding killing trees of thirty to fifty years old. The existence of many bolsons (flat depressional surfaces) means that flood waters are held and subjected to evaporation near their place of origin, with resulting heavy accumulation of salts in playa basins. Much of the precipitation that falls on the desert soils penetrates to a short distance, dissolving the salts present, then as a result of active evaporation returns to the soil surface to be deposited again in the same area where it originated (Prose and Wilshire 2000). Closely associated with the high salt content of desert soils is the occurrence of incrustations of buried hard pan layers known as Caliche. Caliche consists of hard white sheets of calcium carbonate that cements together stones and rocks in the subsoil in a discontinuous layer. These layers in the sub soil can modify the relationship between water and plants. Caliche retards the penetration of water and interferes with the development of the root system, and its presence can hinder the best development of playa vegetation (Sheridan 1979).

Soils

Soils in the MDR are usually low in organic matter and have low rates of leaching due to low precipitation. Older, well-developed soils are generally classified as aridisols. There are also younger, less developed entisols on eroded surfaces and areas composed of alluvial depositions. There are variations within these major soil types depending factors such as organic matter levels and mineral content (North American Desert 2015). Figure 13, NRCS Soil Types – Reference Sites, illustrates the general soil types at the locations of the respective reference wetland sites.

Figure 13 – Reference Sites – NRCS Soil Types

(Legend on the following page)

NRCS General Soils - Legend

NRCS General Soils Musick-Holland-Hoda-Chaix (s844) Rock outcrop-Maymen (s921) Stonyford-Rock outcrop-Chilao (s1056) Veet-Trocken-Spanel (s1083)

Aiken (s686) Nacimiento-Los Osos-Balcom-Ayar (s897) Rock outcrop-Meiss-Andic Cryumbrepts (s1118) Stonyford-Rock outcrop-Guenoc (s832) Veritas-Tinnin-Delhi (s860)

Ayar (s918) Nanny-Lyonsville-Jiggs-Chummy (s637) Rock outcrop-Mexispring (s1077) Subaco-Oswald-Gridley (s856) Vernalis-El Solyo-Capay (s862)

Bluepoint-Arizo (s1123) Nebona-Mirage-Joshua-Cajon (s1007) Rock outcrop-Mokelumne variant-Mokelumne (s842) Suisun-Joice (s880) Vernalis-San Emigdio (s877)

Brantel-Blindspring (s1089) Neuns-Goulding-Boomer-Auburn (s634) Rock outcrop-Monache-Baldmountain (s1070) Supan variant-Supan-Rock outcrop-Iron Mountain (s847) Vina-Brentwood (s642)

Cajon-Arizo (s1143) Neuns-Kindig-Deadwood (s512) Rock outcrop-Neuns-Marpa-Hohmann-Goulding-Boomer (s518) Sur-Felton-Catelli-Ben Lomond (s958) Vint-Meloland-Indio (s996)

Cajon-Bitterwater-Bitter-Badland (s1128) Neuns-Madonna-Kindig-Josephine-Hugo-Casabonne (s724) Rock outcrop-Pacifico-Modjeska family (s1049) Sur-Sheridan-Rock outcrop-Junipero-Cieneba (s949) Vista-Cieneba-Andregg (s899)

Candlestick-Buriburi-Barnabe (s982) Neuns-Mieruf-Hartless (s1111) Rock outcrop-Peckham-Laveaga-Ararat (s796) Sweeney-Mindego (s972) Vista-Fallbrook-Cieneba (s1011)

Carbona-Calla (s864) Neuralia-Garlock-Cajon-Alko (s769) Rock outcrop-Pentz-Laniger-Hideaway (s834) Sycamore-Sailboat-Egbert (s853) Vista-Rock outcrop-Auberry-Ahwahnee (s740)

Carbona-Capay-Calla (s863) Newville (s619) Rock outcrop-Powment-Nupart-Lazan (s5676) Sycamore-Shanghai-Nueva-Columbia (s855) Vista-Rock outcrop-Cieneba (s747)

Carrizo (s1146) Nickel-Bitter-Arizo (s1142) Rock outcrop-Quinto-Millsholm (s794) Taboose-Rock outcrop (s1094) Vizcapoint-Rock outcrop-Dune land (s1046)

Chanac-Camatta (s896) Nickel-Blackmount-Arizo (s1124) Rock outcrop-Rillito-Beeline-Badland (s995) Tahoma variant-Gerle (s1074) Vizcapoint-Rock outcrop-Jehemy-Arnold (s989)

Cibo-Ayar-Altamont (s626) Nord-Grangeville-Chino (s744) Rock outcrop-Roacha-Lilten-Gaviota-Borreguero-Altamont (s798) Tallac-Hirschdale-Fraval-Booford (s5418) Volta-Pedcat-Marcuse (s787)

Ciervo-Cerini (s804) Nosrac-Ister-Hyloc-Duco-Cagle (s5712) Rosamond variant-Rosamond-Playas-Gila-Cajon variant-Cajon (s768) Tallac-Meeks (s828) Waca-Gibsonville (s524)

Clear Lake (s659) Notned-Lumberly-Ledford-Bucking (s1114) Rositas-Beeline-Badland (s1129) Tallac-Rock outcrop-Gerle (s1116) Waca-Meiss (s829)

Clear Lake (s688) Oak Glen-Gullied land-Gorman-Gaviota-Cushenbury (s1034) Rositas-Carrizo (s1137) Tamalpais-Barnabe variant (s666) Waca-Neuns-Cohasset-Boomer-Asta (s540)

Cole (s699) Oak Glen-Mottsville variant-Calpine (s1018) Rositas-Dune land-Carsitas (s1136) Tamba-Reyes (s833) Wadesprings-Millsholm-Henneke (s799)

Contra Costa-Altamont (s1105) Obispo-Fagan (s983) Rositas-Orita-Carrizo-Aco (s1041) Tamba-Reyes-Novato (s658) Waldport family-Dune land-Beaches (s716)

Corning-Anita (s643) Oceano-Dune land-Baywood (s904) Rositas-Orita-Carrizo-Aco (s994) Tangair-Narlon (s926) Wapal-Tomsherry (s536)

Danville-Botella (s690) Oceano-Greenfield-Garey (s942) Rubble land-Clanalpine family (s1085) Tecopa-Rock outcrop-Lithic Torriorthents (s1126) Wapi-Holland-Chaix-Arrastre (s528)

Danville-Chualar (s943) Oceano-Marina-Betteravia (s929) Rubble land-Rock outcrop-Lava flows (s538) Tehachapi-Steuber-Havala (s765) Wappo-Manzanita-Forbesville (s701)

Diablo-Cropley-Clear Lake (s954) Olashes (s875) Rustigate-Nuyobe-Louderback (s5663) Tehama-Hillgate-Arbuckle (s624) Wardenot-Unsel-Izo-Ardivey-Annaw (s5664)

Dierssen (s823) Oneil-Apollo (s791) Ryer-Rossmoor-Columbia (s820) Temescal-Las Posas-Cajalco (s1022) Wasco-Helendale-Bryman (s1032)

Dingman-Beaughton (s714) Ormsby-Hussman-Henningsen-Heidtman-East Fork-Dressler (s5721) Sacramento-Ryde-Egbert (s881) Temple-Merced-Grangeville (s739) Wasco-Kimberlina (s775)

Dipsea-Cronkhite-Centissima-Barnabe (s665) Orose-Mildred-Flanly (s873) Sailboat-Cosumnes-Columbia (s826) Tencee-Rumpah-Nopah-Haymont-Glencarb-Besherm (s5740) Washoe-Reno-Indian Creek (s5724)

Dosamigos-Deldota-Chateau (s788) Pablo-Bayview (s664) Salinas-Marimel-Cropley-Concepcion (s903) Tenpin-Shree-Reno-Hunewill-Fulstone (s5707) Wasioja-Hesperia-Arvin (s760)

Dune land-Cajon (s1135) Pacheco-Clear Lake (s939) Salinas-Mocho-Metz-Cropley (s940) Tierra-Pfeiffer-Elkhorn-Baywood (s955) Wasioja-Panoza (s928)

Elnido-Dospalos-Bolfar-Alros (s785) Pacheco-Clear Lake-Campbell (s967) Salt flats-Bunkerhill (s1081) Tierra-Pismo-Gaviota-Arnold (s905) Wassit-Bulake family (s5693)

Esro-Blackspar variant-Bieber-Alomax (s532) Pacheco-Hueneme-Camarillo (s910) San Andreas-Arujo-Arnold (s902) Timmons-Rohnerville-Hookton-Carlotta-Arcata (s719) Water (s8369)

Fagan (s687) Pacifico-Chirpchatter-Avawatz (s1048) San Benito-Castaic-Calleguas-Balcom-Badland (s912) Tisdale-Kilaga-Conejo (s870) Watoopah family-Ratleflat-Jenness family-Fadoll-Crunker-Breko (s5688)

Fancher-Delpiedra (s750) Pajaro family-Cole-Blucher (s657) San Emigdio-Metz-Grangeville (s1005) Toadlake-Tangle-Rock outcrop-Gozem-Etchen (s516) Watsonville-Elkhorn (s953)

Finrod-Cogna-Archerdale (s857) Palls-Ocraig-Bohna variant (s872) San Joaquin (s825) Tocaloma-Saurin-McMullin-Los Osos-Bonnydoon (s669) Waukena-Pescadero (s741)

Fontana-Diablo-Altamont (s694) Panoche-Ciervo-Cerini (s803) San Joaquin-Galt (s819) Todos-Sespe-Lodo (s919) Waukena-Temple-Pond (s743)

Freezeout-Forward (s678) Panoche-Garces (s779) San Joaquin-Madera (s858) Toem-Cagwin (s527) Webile-Retryde-Kingile (s865)

Gaviota-Cieneba-Capistrano-Caperton (s1055) Panoche-Milham-Kimberlina (s774) San Joaquin-Madera-Cometa (s746) Toem-Rock outcrop (s1066) Weitchpec-Rock outcrop-Ishi Pishi-Ipish-Grell-Beaughton (s523)

Glenview-Bottlerock-Arrowhead (s708) Parrish-Los Gatos-Hulls-Goulding (s628) San Joaquin-Rocklin-Redding-Montpellier-Cometa (s876) Toem-Rock outcrop-Cagwin (s1068) Wellington-Ulymeyer-Rovana-Bairs (s1087)

Goldridge (s680) Parrish-Maymen-Los Gatos-Etsel (s617) San Miguel-Friant-Exchequer (s1013) Toem-Rubble land-Rock outcrop-Cagwin (s827) Wellsed-Wedlar-Veet-Mickey-Fulstone (s1101)

Goleta-Elder (s916) Peltier-Egbert (s866) San Simeon-Lodo-Concepcion (s906) Toem-Temo-Rock outcrop (s1098) Weste-Redriver-Outland-Eaglelake (s613)

Goulding-Auburn (s646) Pentz-Hadselville (s816) San Ysidro-Antioch (s884) Toiyabe-Sattley-Haypress (s529) Westhaven-Lerdo-Excelsior-Cajon (s782)

Haire-Coombs (s681) Peters-Pentz (s836) San Ysidro-Pleasanton-Arbuckle (s966) Toiyabe-Temo-Rock outcrop-Cagwin (s831) Whispering-Collayomi-Aiken (s711)

Haire-Goulding-Diablo-Bosanko (s671) Petspring-Lomoine-Armoine (s5675) San Ysidro-Pleasanton-Hillgate (s968) Tokay-Greenfield (s868) Whiterock-Rock outcrop-Auburn (s818)

Hambright-Gaviota (s1020) Phipps-Bally-Arbuckle (s702) San Ysidro-Positas-Arbuckle (s895) Toll-Mottsville-Kayo (s5410) Whitewolf-Lucerne-Cuyama (s763)

Hanford-Delhi (s745) Pinnacles variant-Chamise (s946) San Ysidro-Rincon (s697) Tollhouse-Rock outcrop (s1071) Whitney-Rocklin-Montpellier (s859)

Hanford-Dinuba (s879) Playas (s1038) Santa Lucia-Bonnydoon-Aptos (s957) Tollhouse-Rock outcrop-Chawanakee (s1060) Whorled-Tahoma-Swainow-Almanor (s614)

Hartig-Glean variant-Bradshaw (s1096) Playas (s1138) Santa Lucia-Lodo-Diablo (s907) Tollhouse-Rock outcrop-La Posta (s1014) Willows-Pacheco-Clear Lake (s960)

Hesperia family-Cajon (s1090) Polvadero-Milham-Guijarral (s802) Santa Lucia-Lopez (s908) Tomales-Steinbeck-Los Osos (s667) Willows-Solano-Pescadero (s886)

Hillgate-Corning (s885) Ponto-Neuns-Neer (s654) Santa Lucia-Pomponio-Lobitos-Gazos (s973) Toomes-Hambright (s890) Willows-Waukena-Pescadero-Fresno (s869)

Hilmar-Delhi-Atwater (s754) Porterville (s755) Santa Lucia-Reliz (s948) Toomes-Supan (s622) Wilshire-Soboba-Oak Glen-Avawatz (s1047)

Holland-Chawanakee-Chaix (s1063) Porterville-Centerville (s749) Santa Ynez-Arnold (s941) Torrifluvents-Mazourka-Bobnbob (s1092) Windy-Waca (s1112)

Honova-Cashbaugh (s1088) Portola-Kyburz-Fugawee-Aldi (s1122) Santa Ynez-Placentia-Antioch (s945) Torriorthents-Elkhills (s809) Winnedumah-Numu-Manzanar-Deepwell-Cobatus (s1093)

Hoosimbim-Hollowtree-Holland-Gavel-Bollibokka (s533) Positas (s696) Scarper-Miramar (s981) Tramway-Irmulco-Empire (s715) Wisflat-Badland-Arburua (s792)

Hotaw-Crouch-Boomer (s1015) Positas-Balcom (s1107) Sebastopol-Cotati (s679) Trid-Minneha-Drit-Berit (s5709) Witherell-Squawrock-Hopland (s735)

Indio-Gilman-Coachella (s992) Quinliven-Ferncreek-Dystropepts (s731) Secca-Rock outcrop-Boomer (s837) Trid-Roloc (s1103) Wittenberg-Palomarin (s663)

Inks-Climara-Azule-Altamont (s969) Ramelli-Ormsby-Loyalton-Beckwourth (s641) Sehorn-Diablo-Balcom-Alo (s887) Trigger-Rock outcrop-Calvista (s1134) Wohly-Holohan-Casabonne (s734)

Josephine-Holland-Aiken (s525) Ramona-Hanford-Greenfield-Gorgonio (s1004) Sehorn-Millsholm-Lodo (s625) Tristan-Duco (s5415) Wolfcreek-Still-Lupoyoma-Kelsey (s700)

Kanaka-Corbett-Chaix (s632) Ramona-Placentia-Linne-Greenfield (s999) Sehorn-Rock outcrop-Lodo (s1108) Trojan-Rock outcrop-Lithic Xerorthents (s638) Woodleaf-Surnuf-Sites-Mariposa (s874)

Kesterson-Edminster-Dospalos-Bolfar (s784) Ratto family-Borealis (s5694) Sesame-Rock outcrop-Cieneba (s1010) Trojan-Sattley-Franktown (s521) Woodseye-Jayar-Goodwin-Althouse (s6361)

Kilmer-Beam-Badland (s932) Red Bluff-Newtown (s635) Sespe-Millsholm-Malibu-Lodo-Hambright (s913) Tujunga-Merritt-Grangeville-Columbia (s861) Woodseye-Rock outcrop-Crannler-Bigelow (s6359)

Kilmer-Hillbrick-Aido (s772) Red Bluff-Perkins-Pardee (s843) Shaver-Pilliken (s1062) Tujunga-Salinas-Elder (s1001) Woodseye-Smokey-Rock outcrop (s1119)

Kistirn-Hollowtree-Deadwood (s550) Redding-Corning (s821) Shedd-Gaviota (s922) Tulare (s808) Woodwest-Waca-Rock outcrop-Meiss (s1076)

Lakeside-Kimberlina-Garces (s810) Redding-Olivenhain (s997) Shedd-Nacimiento-Los Osos (s947) Tulelake-Fluvaquentic Haplaquolls (s698) Woolstalf-Rock outcrop-Jocal-Hotaw-Chaix (s1072)

Landlow-Clear Lake (s630) Redding-Pentz-Corning (s756) Sheephead-Rock outcrop-Bancas (s1016) Tunehill-Quiensabe-Orognen (s795) Xerofluvents-Oak Glen-Dotta (s937)

Las Flores-Antioch (s1019) Rescue (s849) Sheephead-Rock outcrop-Holland-Crouch (s752) Turlock-Triangle-Britto (s786) Xerofluvents-Ramona-Kilaga-Cometa (s839)

Las Flores-Diablo (s1017) Reward-Pottinger-Aramburu (s771) Sheetiron-Millich-Goulding (s616) Tuscan-Anita (s644) Xerofluvents-Salinas-Pico-Mocho-Metz-Anacapa (s909)

Lewis-Fresno-Dinuba (s742) Rillito-Gunsight (s1140) Sheetiron-Rubble land-Neuns (s706) Tuscan-Keefers-Inks (s621) Xerofluvents-Talmage-Russian-Gielow-Feliz (s712)

Linne-Calodo (s898) Rincon-Diablo-Cropley-Antioch (s962) Sheridan variant-Kehoe variant-Kehoe-Inverness (s662) Twisselman-Nahrub-Lethent (s778) Xerorthents-Saugus-San Timoteo-Badland (s1036)

Lockwood (s944) Rindge-Gazwell-Egbert (s852) Sheridan-McCoy-Cieneba (s951) Ubehebe-Rodad-Penelas-Entero (s5673) Xerorthents-Sheetiron-Marpa-Jocal (s627)

Lokern-Buttonwillow (s777) Rioblancho-Guard-Devries (s867) Sheridan-San Benito-Diablo (s964) Uhaldi-Pula-Puett-Indian Creek-Chalco (s5725) Xerorthents-Thirst-Shoba-Sanclemente-Rock outcrop-Eelpoint (s1043)

Loomer-Koontz (s5718) Riverwash-Dumps-Cortina (s648) Shimmon-Diablo-Cotati (s963) Uhaldi-Theriot-Rock outcrop (s1084) Xerorthents-Urban land (s986)

Los Banos-Damluis-Bapos (s790) Riverwash-Kerr-Bigriver (s730) Shimmon-Gaviota-Dibble (s900) Ulymeyer-Surprise-Martis-Euer-Esha (s1102) Xerorthents-Urban land (s990)

Los Gatos-Gamboa (s936) Riverwash-Loleta-Ferndale-Bayside (s726) Sierra-Caperton-Andregg (s817) Umpa-Jorge-Fugawee-Boomtown (s5419) Xerorthents-Urban land-Accelerator (s984)

Los Osos-Gaviota (s920) Riverwash-Orland-Los Robles-Cortina (s631) Sierra-Rock outcrop-Auberry-Ahwahnee (s841) Umpa-Shakespeare-Notned-Celio variant (s1065) Xerorthents-Urban land-Ballard (s660)

Lumberly-Ledford-Deadman-Cannell (s1064) Rock outcrop (s1073) Sirdrak variant-Sirdrak-Dune land-Beaches (s661) Umpa-Tahoma-Jorge-Fugawee (s1120) Xerorthents-Urban land-Botella (s987)

Mahogan-Glean (s938) Rock outcrop (s1131) Sirretta-Rock outcrop-Chaix variant (s1069) Updike-Godecke-Fettic-Dangberg (s1095) Xerorthents-Xerofluvents (s822)

Marla-Jabu variant-Jabu-Gefo-Elmira (s830) Rock outcrop (s695) Sites-Kilarc (s633) Upspring-Blacktop (s1078) Yallani-Sheld-Lava flows-Inville (s517)

Marpa-Hilt-Arrastre (s935) Rock outcrop-Beveridge (s1082) Sites-Rock outcrop-Boomer (s848) Upspring-Sparkhule-Rock outcrop (s1127) Yellowrock-Riverwash-Arizo (s1079)

Martineck-Lovejoy-Dotta-Calpine (s639) Rock outcrop-Chawanakee-Chaix (s1061) Sites-Rock outcrop-Mariposa-Diamond Springs (s846) Urban land (s670) Yermo-Gynelle (s5665)

Martis-Inville-Euer variant-Euer (s1113) Rock outcrop-Cryumbrepts (s1117) Skyhaven-Rillito-Mead-McCullough-Ireteba-Bluepoint (s1144) Urban land-Baywood variant (s689) Yermo-Ulymeyer-Tinemaha-Goodale-Cartago (s1086)

Maxwell-Leesville (s1106) Rock outcrop-Downeyville-Blacktop (s5668) Skyhigh-Millsholm-Bressa (s703) Urban land-Fagan-Accelerator (s985) Yermo-Yellowrock-Cliffdown-Bluewing family-Arizo (s1080)

Maymen-Etsel (s704) Rock outcrop-Dubakella (s850) Snopoc-Rockabin-Nire-Katyblay (s1097) Urban land-Fiddyment-Cometa (s851) Yettem-San Emigdio-Honcut (s758)

Maymen-Lompico-Felton-Ben Lomond (s959) Rock outcrop-Franktown-Aldi (s1121) Sobrante-Dibble-Bressa (s682) Urban land-Francisquito (s988) Yokayo-Xerocrepts-Pinole-Arbuckle (s713)

Maymen-Mariposa (s757) Rock outcrop-Friant-Coarsegold (s751) Sobrante-Exchequer-Cieneba (s1054) Urban land-Marina-Chesterton (s1002) Yollabolly-Rock outcrop (s707)

Mazourka-Eclipse-Cajon (s1091) Rock outcrop-Goulding (s677) Sobrante-Hambright (s709) Urban land-Monserate-Exeter-Arlington (s1003) Yolo-Pleasanton-Cole-Bale (s673)

McCarthy-Cohasset-Aiken (s620) Rock outcrop-Graylock (s1067) Sobrante-Lodo (s1057) Urban land-Redding-Olivenhain (s998) Yolo-Sycamore (s692)

McCarthy-Ledmount (s1109) Rock outcrop-Gullied land-Garlock-Bull Trail (s1023) Sobrante-Rock outcrop-Auburn (s840) Urban land-San Joaquin-Pits-Natomas-Americanos (s854) Yolo-Sycamore-Brentwood-Artois (s883)

McFarland (s780) Rock outcrop-Hambright (s685) Sodabay-Konocti-Benridge (s710) Urban land-Sirdrak (s979) Yolo-Tehama-Pleasanton-Mocho (s674)

McGarvey-Alambique (s980) Rock outcrop-Henneke-Delpiedra (s838) Soper-Chesterton (s911) Urban land-Stockpen-Antioch (s1000) Yolo-Tehama-Rincon family-Marvin (s882)

Mercey-Kettleman-Elkhills-Delgado-Cantua-Bitterwater (s773) Rock outcrop-Hi Vista-Calvista-Cajon (s1031) Soulajule-Olompali-Felton variant (s668) Urban land-Tierra (s691) Yorktree-Vanvor-Mayacama-Gudgrey family (s738)

Milham (s781) Rock outcrop-Hornitos-Amador (s835) Speaker-Sanhedrin-Kekawaka-Hopland (s705) Uripnes-Rock outcrop-Pumel-Blappert (s5671) Yorkville-Suther-Stonyford-Sobrante-Laughlin (s676)

Millerton-Las Posas-Blasingame (s748) Rock outcrop-Hurlbut-Deadwood (s1115) Spreckels-Felta (s675) Vaiva-Quilotosa-Hyder-Cipriano-Cherioni (s1141) Yorkville-Yorktree-Witherell-Squawrock-Shortyork (s736)

Millsholm-Honker-Gonzaga-Fifield (s793) Rock outcrop-Las Posas (s1012) Springdale-Rock outcrop-Etsel family (s1053) Vaiva-Rock outcrop-Quilotosa-Laposa (s1133) Youd-Remnoy-Melga-Kimberlina (s811)

Millsholm-Los Osos-Dibble-Balcom (s888) Rock outcrop-Las Posas-Cibo (s759) Springmeyer-Orr-Oest-Fleischmann (s5412) Valdez (s891) Yribarren-Twisselman-Panoche (s776)

Millsholm-Los Osos-Los Gatos-Lodo (s684) Rock outcrop-Lithic Torriorthents (s1021) Squawtip-Itca-Brier (s1099) Vallecitos-Gaviota (s971) Zacharias-Stomar-Capay (s878)

Millsholm-Maymen-Los Gatos-Dibble (s889) Rock outcrop-Lithic Torriorthents (s1130) Squawtip-Rock outcrop-Itca-Brier (s1100) Vallecitos-Honker-Gonzaga-Franciscan (s892) Zacharias-Yokohl-Honcut (s753)

Millsholm-Millerton-Lodo (s933) Rock outcrop-Lithic Xerorthents-Calleguas-Badland (s914) St. Thomas-Rock outcrop (s1125) Vallecitos-Lithic Xerorthents-Gaviota-Cibo (s965) Zamora-Rincon-Capay-Brentwood (s693)

Milpitas-Concepcion-Baywood (s917) Rock outcrop-Lithic Xerorthents-Gaviota (s952) St. Thomas-Schenco-Rock outcrop (s1132) Vallecitos-Parrish-Los Gatos-Gaviota (s970) Zamora-Urban land-Ramona (s1033)

Mocho-Capay-Camarillo (s893) Rock outcrop-Lithic Xerorthents-Hambright-Gilroy (s915) Still-Riverwash-Metz (s894) Vallecitos-Shoba-Rock outcrop-Millsholm-Lithic Xerorthents (s1045) Zamora-Willows-Marvin-Capay (s629)

Modjeska family-Coarsegold-Aramburu variant (s934) Rock outcrop-Los Osos-Lodo-Henneke (s901) Stockton-Clear Lake-Capay (s824) Vallecitos-Thirst-Shoba (s1044) Zamora-Wright-Huichica (s672)

Montara-Henneke (s683) Rock outcrop-Lumberly-Gerle (s1075) Stohlman-Palls (s871) Vandamme-Tramway-Irmulco-Hotel-Dehaven (s732) Zayante (s956)

Montara-Millsholm-Climara-Alo (s950) Rock outcrop-Mariposa-Jocal (s845) Stonyford-Maymen-Henneke (s618) Vanvor-Mayacama-Gudgrey family-Deadwood (s721) Zeibright-Pilliken-Chaix (s1110)

Zerker-Premier-Delano-Chanac (s783)

Mojave Desert playas are generally situated on top of deep alluvial deposits between mountain ranges. The upper soil strata of playas are generally stratified clay, silts, and sands. The Lacustrine clays and silts often found on playa surfaces were deposited when the playas were flooded as Pleistocene lakes, an example is the Soda Lake Basin that contains clay deposited during the Pleistocene epoch when the pluvial Lake Mojave filled the basin (Muessig et al. 1957). Playa substrates generally also contain soluble salts, and on playas where the water table is near or close to the surface, these salts will precipitate out and form temporary crusts (Stoffer 2004c). Playas often have features such as aeolian sand dunes on their surfaces and margins. The NRCS Soil Survey of San Bernardino County, California, Mojave River Area (Tugel and Woodruf 1986) notes that playa fringes and elevated areas within playas can contain Norab loamy sand, Halloran sandy loam, and Bousic clay. Soils can form on playa margins on ancient shoreline features such as beach ridges formed by Pleistocene lakes, as in the cases of the Soda and Silver Lake playas. These gravelly beach ridges have accumulated aeolian sand and formed new soils (McFadden et al. 1992). Playas have two main surface types, hard and soft, which are dictated by surface flooding regimes, groundwater, and capillary discharge. Soft playa surfaces are affected by rapid capillary discharge from groundwater and deposition of evaporate minerals. They are coarse grained and have a moist, friable, and puffy surface (Motts et al. 1969). Hard playas are not as affected by groundwater capillary discharge and do not drain readily when inundated. In fact, the soil may be dry only a few inches below a flooded hard playa surface (Brostoff et al. 2001). The hard playas are fine grained, dry, mostly smooth, and compact (Motts et al. 1969). It is possible for these surface types to change into one another as well as to intergrade; a single playa may have multiple surface types. The dynamic between hard and soft playa surfaces can provide insight into playa flooding regimes (Neal 1965). Hard playas, if undisturbed, are not greatly affected by wind erosion and produce little airborne dust. Soft playas are susceptible to wind erosion and can produce high amounts of dust depending on factors such as precipitation events, changes in water table depth, and evaporation rates (Reynolds et al. 2007). In addition to the main categories of surface types, playas often exhibit various surface patterns. The wetting and drying of playa surfaces, thermal changes such as freeze-thaw cycles, and chemical fluctuations can all contribute to surface patterns that include features such as polygons, cracks, stripes, fissures, and crusts. These features can vary quite drastically. Salt crusts and pavements form on playa surfaces, often intermixed with silt, and can be from a few centimeters to over a meter thick (Neal 1965, and Brostoff et al. 2001). Desiccation polygons (formed by decreasing groundwater depth and subsurface drying) can be nearly 300 meters long, although they are typically smaller. Fissures up to 100 meters long can be found along playa margins or in concentric rings around polygons (Brostoff et al. 2001). Playa soils differ from other wetland soils in several regards and do not have the same hydric soil indicators. Playas are generally unvegetated and lack the soil biomass and microbial activity necessary to produce the redox chemistry that is present in other hydric soils. Playa soils also generally have a high pH, which makes it difficult for iron segregation features (depletions and concentrations) to occur, due to the fact that iron reduces more consistently at lower pH levels (Brostoff et al. 2001). However, there are several characteristics that can be used to define the extent of playas. One of these is surface accumulations of organic matter, as playas often have

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 37 stratified layers of organic matter within the upper 15 centimeters. Salt crystals in the upper horizons and on the soil surface are also an indicative of playa soils (Brostoff et al. 2001). DMEC collected soil texture samples from 17 reference playas in the Mojave Desert Region. These soil samples were saturated with clean water and put in jars and allowed to settle, after which the relative amounts of clay, silt, and sand could be measured and soil texture could be determined. Very little if any sand was observed from any of the samples. These data are summarized in Table 8, Reference Playa Soil Textures.

Table 8 – Reference Playa Soil Textures

Site Clay (%) Silt (%) Sand (%) Soil Texture Biotite 18.18% 81.82% 0 Silt Loam Bristol #2 27.78% 72.22% 0 Silty Clay Loam Bristol #3 47.37% 52.63% 0 Silty Clay Broadwell #1 50.00% 50.00% 0 Silty Clay Broadwell #2 26.32% 73.68% 0 Silt Loam Broadwell #3 45.00% 55.00% 0 Silty Clay Broadwell #4 22.22% 77.78% 0 Silt Loam E. Cronese #1 21.05% 78.95% 0 Silt Loam E. Cronese #2 16.67% 83.33% 0 Silt Loam E. Cronese #3 7.69% 92.31% 0 Silt E. Cronese #4 24.00% 76.00% 0 Silt Loam E.Cronese #5 30.00% 70.00% 0 Silty Clay Loam El Mirage Lake 5.56% 94.44% 0 Silt Ivanpah #1 31.58% 68.42% 0 Silty Clay Loam Ivanpah #2 25.00% 75.00% 0 Silt Loam Lucerne #1 10.00% 90.00% 0 Silt Lucerne 29.17% 70.83% 0 Silty Clay Loam N. of Silver #1 56.25% 43.75% 0 Silty Clay N. of Silver #2 33.33% 66.67% 0 Silty Clay Loam N. of Silver #3 31.58% 68.42% 0 Silty Clay Loam N. Tip of Soda #1 5.00% 95.00% 0 Silt N. Tip of Soda #2 8.70% 91.30% 0 Silt Rabbit Springs #1 30.00% 70.00% 0 Silty Clay Loam Rabbit Springs #2 27.78% 72.22% 0 Silty Clay Loam Silurian #1 21.43% 78.57% 0 Silt Loam Silurian #2 27.78% 72.22% 0 Silty Clay Loam Silver #1 0.00% 100.00% 0 Silt Silver #2 30.00% 70.00% 0 Silty Clay Loam Soda #1 37.50% 62.50% 0 Silty Clay Loam Soda #2 27.78% 72.22% 0 Silty Clay Loam Soda #3 35.29% 64.71% 0 Silty Clay Loam Soda #4 41.18% 58.82% 0 Silty Clay

Site Clay (%) Silt (%) Sand (%) Soil Texture Troy #1 31.58% 68.42% 0 Silty Clay Loam Troy #2 26.09% 73.91% 0 Silt Loam Troy #3 26.32% 73.68% 0 Silt Loam Troy #4 15.38% 84.62% 0 Silt Loam Troy #6 20.00% 80.00% 0 Silt Loam Troy #7 27.27% 72.73% 0 Silty Clay Loam Troy #8 19.05% 80.95% 0 Silt Loam W. Cronese #1 13.04% 86.96% 0 Silt Loam W. Cronese #2 47.37% 52.63% 0 Silty Clay W. Cronese #3 37.50% 62.50% 0 Silty Clay Loam

DMEC also conducted soil tests for 13 of the reference sites, the results of which are included in Table 9, Reference Playa Soil Test Locations and Depths, and Table 10, Reference Playa Soil Test Results. Table 9 contains the location and depth of the soil test samples, while Table 10 contains the results of the soil tests. Two trials were conducted on separate dates for each variable measured (temperature, pH, and conductivity).

Table 9 – Reference Playa Soil Test Locations and Depths

Site Sample Type Depth (inches) Latitude Longitude El Mirage Surface 0-1 34.62154 -117.5481 Soda 1 Crust 0-2 35.16162 -116.10648 Soda 2 SubCrust 2-6 35.16162 -116.10648 Soda 3 Crust 0-1 35.16249 -116.10437 Soda 4 SubCrust 1-4 35.16249 -116.10437 Ivanpah 1 Crust 0-1 35.60181 -115.40433 Ivanpah 2 SubCrust 1-3 35.60181 -115.40433 Silver 1 Crust 0-2 35.36898 -116.112 Silver 2 SubCrust 2-4 35.36898 -116.112 N of Silver 1 Crust 0-0.25 35.44633 -116.16664 N of Silver 2 SubCrust 0.25-4 35.44633 -116.16664 N of Silver 3 DarkSufacePatch 0-0.5 35.44737 -116.1161 Silurian 1 Crust 0-0.5 35.52716 -116.17411 Silurian 2 SubCrust 0.5-4 35.52716 -116.17411 N tip Soda 1 Crust 0-1 35.25414 -116.07723 N tip Soda 2 SubCrust 1-4 35.25414 -116.07723 E Cronese 1 Crust 0-0.5 35.12458 -116.28704 E Cronese 2 SubCrust 0.5-4 35.12458 -116.28704 E Cronese 3 Surface 0-3 35.1182 -116.2879 Troy 1 Crust 0-2 34.8064 -116.54257 Troy 2 SubCrust 2-6 34.8064 -116.54257

Site Sample Type Depth (inches) Latitude Longitude Troy 3 Crust 0-2 34.80915 -116.55977 Troy 4 SubCrust 2-4 34.80915 -116.55977 Troy 5 Crust 0-1 35.80878 -116.55997 Troy 6 SubCrust 1-4 35.80878 -116.55997 Troy 7 Crust 0-1 34.81156 -116.57284 Troy 8 SubCrust 1-4 34.81156 -116.57284 Broadwell 1 Crust 0-2 34.82328 -116.17711 Broadwell 2 SubCrust 2-6 34.82328 -116.17711 Broadwell 3 Crust 0-4 34.86569 -116.19022 Broadwell 4 SubCrust 1-4 34.86569 -116.19022 Bristol 1 Salt_Crust 0-2 34.47017 -115.74237 Bristol 2 SubCrust 0.25-6 34.45287 -115.74123 Bristol 3 Crust 0-0.25 34.45287 -115.74123 Lucerne 1 Crust 0-2 34.49525 -116.94416 Lucerne 2 SubCrust 2-4 34.49525 -116.94416 Rabbit Springs 1 Crust 0-2 34.45184 -117.00896 Rabbit Springs 2 SubCrust 2-4 34.45184 -117.00896

Table 10 – Reference Playa Soil Test Results

Temp Temp Site C C (2) pH pH (2) Conductivity Conductivity 2 PPM PPM (2) El Mirage 19.5 22.2 7.9 7.39 3999 3999 2000 2000 Soda 1 18.8 22.2 10.06 9.49 3999 3999 2000 2000 Soda 2 18.7 22.2 9.57 9.32 3999 3999 2000 2000 Soda 3 17.9 22.5 10.26 9.57 3999 3999 2000 2000 Soda 4 19 22.1 10.24 9.69 3999 3999 2000 2000 Ivanpah 1 18.8 22.2 8.5 8.14 3999 3999 2000 2000 Ivanpah 2 18.8 22 8.66 8.45 3999 3999 2000 2000 Silver 1 17.1 21.6 10.14 8.82 900 1076 250 543 Silver 2 16.8 22.2 9.6 8.29 2657 3999 1337 2000 N of Silver 1 17 21.4 8.88 6.86 270 1595 146 797 N of Silver 2 15.5 21.7 8.72 7.06 581 710 290 371 N of Silver 3 17.2 21.7 7.5 6.69 3999 3999 2000 2000 Silurian 1 16.2 21.7 8.35 7.13 305 717 155 352 Silurian 2 16.1 22.1 7.75 7.08 3999 3999 2000 2000 N tip Soda 1 16.1 22.2 9.8 8.73 387 485 196 243 N tip Soda 2 16.8 22.2 10.1 9.18 711 821 337 411 E Cronese 1 17.5 21.7 9.2 7.68 275 552 141 275 E Cronese 2 18.7 22.3 8.3 7.8 816 1131 408 520

Temp Temp Site C C (2) pH pH (2) Conductivity Conductivity 2 PPM PPM (2) E Cronese 3 16.9 22 9.2 7.8 425 900 213 440 Troy 1 18.8 22.2 8.2 8.05 3999 3999 2000 2000 Troy 2 18.8 22.3 8.73 8.3 3999 3999 2000 2000 Troy 3 18.8 22.1 8.79 8.25 3999 3999 2000 2000 Troy 4 16.9 22.1 8.87 8.49 3999 3999 2000 2000 Troy 5 18.9 22.2 8.9 8.35 3999 3999 2000 2000 Troy 6 15.7 22 8.8 8.45 3999 3999 2000 2000 Troy 7 18 21.6 10.65 9.83 1025 941 513 463 Troy 8 18.9 22.2 10.49 9.93 3999 3999 2000 2000 Broadwell 1 17 21.6 10 8.04 3999 3999 2000 2000 Broadwell 2 18.8 22.1 8.25 7.57 3999 3999 2000 2000 Broadwell 3 17.6 21.6 9.67 8.63 2990 2824 1496 1425 Broadwell 4 15.9 21.7 9.05 8.2 3999 3999 2000 2000 Bristol 1 Bristol 2 18.8 22.1 7.8 7.44 3999 3999 2000 2000 Bristol 3 19 22.4 7.71 7.39 3999 3999 2000 2000 Lucerne 1 18.8 22.1 10.2 9.38 1100 1201 495 499 Lucerne 2 17.1 22.1 10.03 9.28 1713 1859 858 930 Rabbit 1 17.2 21.6 9.47 8.64 3999 3999 2000 2000 Rabbit 2 18.6 22.4 9.56 9.13 3999 3999 2000 2000 Notes: Trial 1 was conducted on 2/26/2014; Trial 2 was conducted on 3/7/2014. 3999 is the highest possible value for salinity/conductivity, and DMEC is unsure as to why some sites have a large discrepancy between the trials.

Plant Communities

The terrestrial landscape of the MDR is primarily intact, with the exception of developed areas that are situated just north of the Transverse Ranges, and to a lesser extent, east of the Tehachapi Mountains and southern Sierra Nevada Range, along the Colorado River (adjacent to Arizona), adjacent to the Las Vegas, Nevada area, and along some of the highways that crisscross the Mojave Desert, such as the City of Barstow. The vegetation communities of the MDR are illustrated on Figure 14, Reference Sites – Natural Vegetation Communities2. In the MDR, generally the closer to urbanized areas, the more nonnative invasive vegetation is present. Farther from urbanized areas, mostly native vegetation is present, with the exception of agricultural areas. Therefore, plant communities in the vast Mojave Desert region are for the most part in their natural state, undisturbed except for the presence of bird-carried, mammal- dispersed, or wind-distributed exotics such as invasive nonnative grasses and herbs. However, human disturbance is an imminent threat. Grazing does not play as significant a role in this region as it does in the coastal and montane ecoregions of California; however, fire, off- road vehicle use, blading and excavating by heavy equipment, military exercises, cultivation, air

2 Based on data obtained from www.drecp.org

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 41 pollution, and development can alter the seed bank and species composition, and select for invasive species (DeFalco and Esque 2014). Desert soil disturbance and vegetation disturbance by human activities can also negatively impact the carbon sequestration process, releasing excessive amounts of carbon dioxide to the atmosphere that would otherwise be fixed deep in the soil by the plant roots or incorporated into plant biomass (Allen et al. 2014). The increase in invasive annual grasses such as Bromus tectorum in the Mojave Desert has resulted in increases in the frequency and size of wildfires in the Mojave Desert (Allen et al. 2014). Further gains by nonnative grasses occur because many native Mojave shrubland species do not resprout readily after fire, while nonnative grasses and forbs do (DeFalco and Esque 2014). Major themes of plant literature for the desert playas of the arid southwest consist of zonation patterns, wetland classification, vegetation dynamics, relationships between environment and plants, and impacts of anthropogenic disturbance. All of the preceding themes are interrelated and must be viewed in concert (Lichvar et al. 2006). Specifically, factors influencing species composition and distribution along the gradient (zonation) in desert playa wetlands include hydrologic regime, salinity of water, edaphic complex, plant competition, pH, nutrient status, and the seed banks (Courtois 1984, Fort and Richards 1998, Lichvar et al. 2006, Toft and Elliott-Fisk 2002, Vasek and Lund 1980). Zonation in playa depressional systems is a function of the water depth and duration (Courtois 1984, Lichvar et al. 2006). Observations on vegetation zonation and plant–environmental relationships have formed the basis of wetland classification for the Prairie Pothole Region (Gilbert et al. 2006), but vegetation zonation for desert playas can be somewhat problematic (Lichvar and Dixon 2007). Lichvar et al. (2014) developed a classification for the Mojave Desert region and Lichvar et al. (2006) and Vasek and Lund (1980) have classified desert playa vegetation. Desert playas are sporadically inundated for varying lengths of time. However, in their more typical dry state playas still harbor many rare and specialized species (e.g. halophytic and phreatophytic plant species). The often extremely saline soil conditions reduce competition by many wide-ranging, prolific desert species, allowing salt-tolerant species to establish and dominate communities. Establishment and succession of these species is dictated by the extent of surface waters following inundation, salt and mineral tolerance, and the accumulation of aeolian sediments. The majority of desert playa vegetation is restricted to playa edges because of adverse physical playa depression conditions such as compacted soil, high salinity, and relatively unpredictable cycles of inundation and desiccation (Lichvar and Dixon 2007). There are two types of playas: those with groundwater within five (5) meters of the surface are termed “soft” playas, and those without groundwater within five (5) meters of the surface are “hard” playas (Lichvar & Dixon 2007). Soft playas are suited for succulent chenopods of the “alkaline sink scrub” described by Barbour et al. (1987) according to Lichvar and Dixon (2007). Hard playas host vegetation varying from the xerophytic taxa of saline dry habitats that appear similar to their upland counterparts of the same species, to halophytic taxa of saline wet habitats of the “alkaline sink scrub” vegetation type (Lichvar & Dixon 2007). Desert playa edges have vegetation that Thorne (1976) classified as “alkaline scrub”, generally consisting of “scattered scrub of halophytic plants mostly in the Chenopodiaceae, Asteraceae, Brassicaceae, Fabaceae, and Poaceae families” (Lichvar and Dixon 2007). Lichvar (2007) adds

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 42 that Barbour & Billings (1988) stated “20% of this vegetation type consists of monocultures of single perennial species dominance”. Playa edge flora is often situated on phreatophytic mounds 1 to 5 meters tall and 2 to 10 meters in circumference, which are accumulations of soil and vegetation. The mounds are created from wind-blown sand and silt building upward from the level of the playa surface around plant species called phreatophytes. Phreatophytes have roots in perennial groundwater or in the capillary fringe above the water table (Lichvar et al. 2006). Between the playa edge and the nearest mountain slopes, vegetation very roughly forms into zones, shifting from halophytic to xerophitic Atriplex (saltbush) taxa - with a transition area in between - then to the Larrea tridentata (Creosote Bush) dominated plant community (Lichvar and Dixon 2007). Adaptations by plants at playa edges depend on a taxon’s site requirements, and may be at once drought-tolerant and salt-tolerant. Because of this, desert playa vegetation (except for algae in biotic crust) is not necessarily a clear indicator of wetland status for delineation purposes (Lichvar and Dixon 2007). Experience in the field has demonstrated that “the reliability of the status ratings of wetland plant species as indicators along playa edges is compromised by halophytes and phreatophytes responding to saline soils and groundwater at depths greater than the surface or near-surface hydrology required to meet wetland criteria” (Lichvar et al. 2006). It can probably be safely assumed that for desert playas, artificial drainage for mining of minerals and cultivation of wetlands habitat alters species composition and selects for annual or invasive species, or both, as it does for Prairie Potholes (Gilbert et al. 2006). Drainage features inhibit natural hydro-dynamics, which in turn selects for species with opportunistic life-cycle requirements. Cultivation is a drastic type of disturbance. Agriculture in low-relief areas with fine-grained soils can result in tremendous dust emissions resulting in a loss of soil fertility where the dust originated. Cultivation was prevalent in the non-mountainous areas of the Mojave, sometimes occurring directly in or around desert playas (DMEC 2014). Once native vegetation is removed for agricultural operations, the species composition is likely to change to opportunistic non- native annuals such as Bromus spp. (brome grasses), Schismus spp.(Arabian/Mediterranean grasses), Brassica tournefortii (Saharan Mustard), Salsola tragus (Russian Thistle), and Erodium cicutarium (Redstem Filaree). These invasive plant taxa can prevent or delay the recolonization of abandoned farmland by native taxa because natives take decades to become re-established and are outcompeted, especially if nitrogen fertilizer was added to the soil or nitrogen-fixing plants like alfalfa were grown as crops (Belnap et al. 2008). The productivity of invasive grasses is also increased when nitrogen deposition from air pollution is high, diminishing the diversity of native wildflowers (Allen et al. 2014, DeFalco and Esque 2014). Cultivation of Tamarix ramosissima (Saltcedar) and other Tamarix species for erosion control and/or windbreaks has led to water depletion and increased soil salinity in desert playas and other desert wetlands (Allen et al. 2014). Hard-rock mining can leave depositions of tailings on alluvial fans, and generate dust, as can placer and gravel mining. Water and wind can carry the easily erodible spoils from mining (including substances that are potentially toxic) several miles from the source (Belnap et al. 2008). The covering of seed banks with disturbed soil inhibits native vegetation recolonization (DeFalco and Esque 2014). This is because mechanical mixing or covering of the top inch or two of the topsoil dilutes seed numbers or buries seed too deeply to sprout to the surface.

The vegetation ecology of desert ephemeral playa lake systems is poorly understood. The unpredictable flood regime of these systems creates many challenges in research and study. Further, playa ecosystems are often overlooked because of their relatively low economic value and apparent simplicity. So far, human disturbance, seed dispersion by wildlife and wind, soil content, and flooding appear to be the greatest factors in determining what grows on playas.

Figure 14 – Reference Sites – Natural Vegetation Communities

(Legend on the following page)

Natural Vegetation Communities Legend Inter-Mountain Dry Shrubland and Grassland NVCS Classification Name Inter-Mountain West mesic tall sagebrush shrubland and steppe Acacia greggii Intermontane deep or well-drained soil scrub Achnatherum hymenoides Intermontane seral shrubland Achnatherum speciosum Irrigated Row and Field Crops Adenostoma fasciculatum Isocoma acradenia Aesculus californica Juncus arcticus (var. balticus, mexicanus) Agave deserti Juniperus californica Agriculture Krascheninnikovia lanata Allenrolfea occidentalis Lacustrine Alnus rhombifolia Larrea tridentata Ambrosia dumosa Larrea tridentata - Ambrosia dumosa Ambrosia salsola Larrea tridentata - Encelia farinosa Amsinckia (menziesii, tessellata) Lasthenia californica - Plantago erecta - Vulpia microstachys Arctostaphylos glandulosa Lepidospartum squamatum Arctostaphylos glauca Lower Bajada and Fan Mojavean - Sonoran desert scrub Arid West freshwater emergent marsh Lycium cooperi Arizonan upland Sonoran desert scrub Madrean Warm Semi-Desert Wash Woodland/Scrub Artemisia tridentata Mediterranean California naturalized annual and perennial grassland Artemisia tridentata spp. Parishii Menodora spinescens Arundo donax Mojave and Great Basin upper bajada and toeslope Atriplex canescens Mojavean semi-desert wash scrub Atriplex confertifolia North American Warm Desert Alkaline Scrub and Herb Playa and Wet Flat Atriplex hymenelytra North American warm desert bedrock cliff and outcrop Atriplex lentiformis North American warm desert dunes and sand flats Atriplex parryi Not Mapped Atriplex polycarpa Open Water Atriplex spinifera Panicum urvilleanum Baccharis emoryi Parkinsonia florida - Olneya tesota Baccharis salicifolia Peucephyllum schottii Baccharis sergiloides Pinus monophylla Bebbia juncea Pinus sabiniana Brassica nigra and other mustards Platanus racemosa Brickellia incana Playa Bromus rubens - Schismus (arabicus, barbatus) Pleuraphis rigida Caesalpinia virgata Pluchea sericea California Annual and Perennial Grassland Populus fremontii California annual herb/grass Prosopis glandulosa Californian broadleaf forest and woodland Prosopis glandulosa coppice dunes Californian mesic chaparral Prunus fasciculata Californian montane conifer forest Prunus ilicifolia Californian pre-montane chaparral Psorothamnus spinosus Californian xeric chaparral Purshia tridentata Ceanothus crassifolius Quercus berberidifolia Central and South Coastal Californian coastal sage scrub Quercus berberidifolia - Adenostoma fasciculatum Cercocarpus ledifolius Quercus chrysolepis tree Cercocarpus montanus Quercus cornelius-mulleri Chilopsis linearis Quercus john-tuckeri Chorizanthe rigida - Geraea canescens Quercus lobata Coleogyne ramosissima Quercus wislizeni tree Cropland, Barren Riverine Cylindropuntia bigelovii Rural Deciduous Orchard, Vineyard Salazaria mexicana Developed Salix exigua Developed and Disturbed Areas Salix gooddingii Dicoria canescens - Abronia villosa Salix laevigata Distichlis spicata Salix lasiolepis Encelia (actoni, virginesis) Sambucus nigra Encelia farinosa Sarcobatus vermiculatus Ephedra californica Shadscale - saltbush cool semi-desert scrub Ephedra nevadensis Sonoran-Coloradan semi-desert wash woodland/scrub Ephedra viridis Southern Great Basin semi-desert grassland Ericameria cooperi Southwestern North American alkali marsh/seep vegetation Ericameria linearifolia Southwestern North American introduced riparian scrub Ericameria nauseosa Southwestern North American riparian evergreen and deciduous woodland Ericameria paniculata Southwestern North American Riparian Flooded and Swamp Forest Ericameria teretifolia Southwestern North American riparian/wash scrub Eriodictyon (crassifolium, trichocalyx) Southwestern North American salt basin and high marsh Eriogonum fasciculatum Sporobolus airoides Eriogonum wrightii Suaeda moquinii Eschscholzia (californica) Tamarix spp. Forestiera pubescens Tetracoccus hallii Fouquieria splendens Typha (angustifolia, domingensis, latifolia) Frankenia salina Urban Fremontodendron californicum Viguiera parishii Geraea canescens - Chorizanthe rigida Washingtonia filifera Grayia spinosa Western Mojave and Western Sonoran Desert borderland chaparral Great Basin cool semi-desert alkali basin Wislizenia refracta Great Basin Pinyon - Juniper Woodland Yucca brevifolia Gutierrezia sarothrae Yucca schidigera Hyptis emoryi

Faunal Communities

The unique conditions of Mojave Desert playas support diverse faunal communities. The ephemeral nature of playa inundation, as well as factors such as salinity and alkalinity, affect the life cycles of diverse playa organisms. The often barren playa surfaces at a glance appear entirely uninhabited, yet are home to a variety of endemic and rare species. The soils of playa surfaces can harbor eggs and cysts of microbial organisms, fairy shrimp species (Anostraca), and Tadpole Shrimp (Notostraca), that can lay dormant for decades. Navarro et al. (2008) documented the highest concentration of culturable planktonic heterotrophs in any natural aquatic ecosystem while examining Silver Lake playa in the Mojave Desert, California. Navarro et al. (2008) also documented a distinct succession of species directly related to salinity and chemical content of the water. The diverse microbial community drastically shifted (in both species composition and abundance) as surface waters evaporated and infiltrated into the ground. The flourishing of this microbial community provides food for larger crustaceans such as fairy shrimp species and Tadpole Shrimp, which in turn provide food for larger animals such as birds, mammals, amphibians, and reptiles. CDFW has documented over 2,000 water birds a year visiting the wastewater ponds present at Searles Lake (Hampton et al. 2002). These water birds are primarily utilizing the wastewater ponds as a resting point during migration. However, these ponds are extremely saline, so toxic they kill approximately 25% of the visiting birds, and provide little to no foraging opportunity. It can be reasonably assumed that non-toxic, highly productive, naturally inundated playas are also significantly utilized by migrant and resident birds; however, no reliable studies have been located. The ephemeral nature of inundation creates many challenges to studying the interactions within these systems. Certain animals are desert playa obligates that spend their entire life cycle nowhere else. The most visible examples are crustaceans such as Branchinecta mackini and Thamnocephalus platyuras, species of fairy shrimp in the invertebrate family Anostraca. The distribution of some of these species is entirely limited to Mojave Desert playas. These organisms persist through the desert playas’ dry phase as dormant eggs or cysts in the playa sediments (Eng et al. 1990). These cysts hatch when the playas fill with water, and the fairy shrimp mature and reproduce before the ponded water dries up. Typically, Branchinecta gigas and B. mackini thrive in water with high turbidity, high pH, and with at least moderate levels of total dissolved solids (TDS) and conductivity, and moderate to high chloride content with a wide range of temperatures, while T. platyuras prefers high water temperatures, low to moderate alkalinity, TDS, chloride, and conductivity, with pH varying on either side of neutral. Another species of Branchinecta, B. lindahli, is found in waters lower in TDS, chloride, conductivity, alkalinity, and chloride than for Californian Anostraca (Eng et al. 1990). Desert playa invertebrates such as fairy shrimp are therefore endemic to small, disjunct areas, because desert playas are usually several miles apart. Fairy shrimp feed on organisms or material lower in the food chain including algae, bacteria, smaller animals and detritus. They are in turn fed upon by amphibian larva and migratory waterfowl (Baker et al.1992 for Vernal Pools). Dispersal among playas is often carried out by vectors such as birds and mammals. Therefore, as with Prairie Potholes, “gene flow and recolonization are dependent upon maintenance of appropriate vectors” (Bauder et al. 2009).

In addition to so-called “obligates”, playas also have organisms termed “lifestyle dependent” by Bauder et al. (2009) in his characterization of vernal pool fauna. These include amphibians and insects that “spend only part of their life cycles” in ponded playa waters. Western Toad and Pacific Tree Frog both breed and their tadpoles forage for algae and fairy shrimp in the playa waters, while many insects (such as dragonflies) spend their larval stages in the ponded water. Upon adulthood, these organisms usually move to the uplands. Another specialized species of limited distribution in and around Mojave Desert playas is the Chisel-toothed Kangaroo Rat (Dipodomys microps). It is not necessarily an “obligate” of playas, but is adapted to consuming typical playa vegetation that would be too salty for other rodents of the Mojave region. This rodent has flat-edged, broad lower incisor teeth with which it scrapes off the salty epidermis of its favorite leaves when green vegetation (such as Atriplex spp.) is available on and near playas, avoiding high-salt intake. Its lower incisors are distinctly different from all other kangaroo rats’ awl-like lower incisors (Eder 2005). DMEC expects that, as with the “opportunists” described for vernal pools by Bauder et al. (2009), many more species frequent desert playas during periods of inundation. Anthony Chavez (pers. comm. 2014) with the BLM reported that East Cronese Lake playa contains fairy shrimp (Order Anostraca) which in turn, during periods of inundation, attract a wide variety of birds. Louis Courtois (1984) reported several species of fish present in East Cronese Lake following a flood event in April 1981. Courtois (1984) also reported the presence of Pelicanus occidentalis (Brown Pelican), a coastal bird, indicating that many undocumented waterfowl and shorebirds likely frequent playas during periods of inundation.

Surrounding Fauna of the Mojave Desert in General

After recording natural history and habitat data from the California Department of Fish and Game’s California Wildlife volumes (Zeiner et al. 1990) for each of 274 vertebrate species (includes 9 introduced), it was determined that for the majority of species, habitat information was related to elevation, water requirement, landform, and vegetation (Mouat 2004). Mojave Desert mammals must be nocturnal (active during the night) or crepuscular (active at dawn and dusk) to avoid high daytime temperatures (e.g. the Black-tailed Jackrabbit, Lepus californicus). Temperatures are lower and humidity is higher at these times. Therefore, nocturnal and crepuscular mammals lose less water through perspiration and breathing than diurnal mammals. In addition to being nocturnal or crepuscular, many desert mammals have adopted other water saving habits such as conservation of urine. Because desert reptiles are cold- blooded and lack a constant body temperature, they must avoid excessive heat by remaining in the shade, underneath objects, or underground during the day. Desert birds are generally most active during the parts of the day close to dawn and dusk to avoid high temperatures. Certain species, like the Greater Roadrunner, drink water where available, but it is uncertain whether water is required3. Other survival strategies/special adaptations of Mojave Desert mammals include periods of torpidity, dormancy, or even hibernation (e.g. the Mohave Ground Squirrel, Xerospermophilus mohavensis, hibernates from August to March, when food is scarce, to avoid competition for

3 Digital Desert: Mojave Desert website, accessed June 22, 2014

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 48 food with the more prevalent White-tailed Antelope Squirrel, Ammospermophilus leucurus) during the hottest, driest months, coldest months or during times of food scarcity; ability to obtain water from food sources such as cacti, other green vegetation, or large seeds rather than from surface water during dry months; storage of non-perishable seeds for future food; and spending a lot of time in burrows (Eder 2005). A review of mammal range maps in Eder (2005) revealed that a wide variety of rodents (including the Desert Woodrat, Botta’s Pocket Gopher, three species of ground squirrels, and several species of kangaroo rats and pocket mouse), two species of rabbits, and eleven species of bats frequent the Mojave Desert. Bighorn Sheep, a vegetation browser, are found at the eastern edge of the Mojave Desert. Numerous reptile species and some amphibians are also found in the Mojave region (Stebbins 2003), in addition to many invertebrate species. The highest level of natural predator found in the Mojave Desert is the Bobcat (Lynx rufus), according to its range map in Eder (2005). It consumes mostly lagomorphs and rodents, along with birds and some other vertebrates (Reid 2006). The unique assemblage of faunal communities associated with playa wetlands as well as the surrounding MDR in general rely on a variety of habitats. Many organisms rely on large areas of intact habitat in order to be successful, and there must be sufficient habitat connectivity, which is often impacted by development and other human activities. Figure 15, Reference Sites – Habitat Connectivity, illustrates the locations and condition of habitat connectivity linkages in the MDR.

Cultural Alterations of Playa Lakes and the Landscape

Due to their remote geographic placement most of the playas in the MDR have remained intact and have not been developed. However, many playas have been used throughout human history as places for settlement, and more recently for agriculture, mining, and recreation. Modern human impacts on desert playas began with small mining and ranching operations in the 1880s. Minerals mined throughout the MDR included ores of gold, silver, lead, copper, iron, molybdenum, lead, tungsten, and zinc. A substantial shift has occurred in mining-related activities as the ecoregion has shifted away from precious-metal and ore extraction to increased surface and aggregate mining for infrastructure construction uses. Most of the active mining operations observed were arranged within close proximity of existing developed areas or an interstate highway expansion project. The landscape of the Mojave Desert has been subject to grazing for more than 125 years. Commercial ranches developed extensive water systems that provided a year round water source for both native and nonnative species. Cattle grazing practices have been attributed to increasing the amount of unpalatable shrubs which provide microclimates that nurture Joshua trees (NPS). In the early 1800’s burros were used as pack animals for the mining operations in the Mojave Desert region (Thomas 1979). Following the decline in mining in the late 1800’s many burros were released or escaped and became feral (Zarn et al. 1977). Feral burro grazing is focused on grasses and small forbs and has contributed to decreased native perennial grass cover (Jordan 1979). The World War II era was probably the time of greatest human impact on the region with military activities, mining, and road building being the most important impacts. After 50 years, many of the old traces of tank tracks are gradually vanishing, particularly on active washes and

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 49 alluvial fan areas, but in some areas, such as flats that rarely flood, many of these traces are still clearly visible. The largest of these military facilities entirely within the ecoregion is Fort Irwin National Training Center (2,369 km2). Fort Irwin is used for desert warfare training, including live-fire exercises. Tracked and wheeled vehicles operate throughout the facility and can have a major impact on the health and composition of desert flora and fauna (Prose and Wilshire, 2000). Evidence of this use includes compacted and rutted soils, low shrub density, and stunted growth of Creosote Bush and other vegetation. The growing population of the west brought increasing pressure on the development of the Mojave Desert. Additional utility lines (electricity, gas, communications, and water) and their service roads were developed. Off-highway vehicle (OHV) enthusiasts discovered the Mojave Desert, and perhaps the worst period of environmental degradation of the Mojave Desert landscape began. The growth of OHV activity in the ecoregion can be largely attributed to the open-access policy of the BLM and the close proximity of these lands to major urban areas (Sheridan 1979). The growing environmental conscience starting perhaps in the late 1960s led to the establishment of the Mojave National Preserve, which was created in October 1994 when Congress passed the California Desert Protection Act. Additional human impacts in the region include the ongoing extraction of water and associated lowering of groundwater tables and drying of springs, groundwater contamination (particularly from mining wastes), the introduction of invasive species and vanishing habitats, ongoing grazing, and the influx of air pollution from the metropolitan areas. More recently, large-scale development of solar electric facilities have been, and are being, developed in the Mojave Desert, several of which are thousands of acres in size. In addition, the ongoing natural progression of climate change may produce significant impacts over the long term. Only time will determine how the whole ecosystem, or parts of it, will respond to the combined effects of climate change and human interactions. The landscape impacts associated with agriculture, grazing, development, invasive species and non-natural fire regimes in the MDR are illustrated on Figure 16, Landscape Intactness. Figure 17, Existing Conservation Areas, illustrates the locations of the reference sites in the context of existing conservation areas.

Figure 15 – Reference Sites – Habitat Connectivity

Figure 16 – Reference Sites – Landscape Intactness

Figure 17 – Reference Sites – Existing Conservation Areas

SECTION IV. WETLAND FUNCTIONS AND ASSESSMENT MODELS

OVERVIEW

The following functions of MDR playa wetlands were selected for this model: 1. Storing water; 2. Recharging groundwater; 3. Retaining particulates (physical processes); 4. Removing, converting, and sequestering dissolved substances (biogeochemical processes); 5. Plant community resilience and carbon cycling; and 6. Faunal habitat resilience

REFERENCE DATA

A total of 17 reference sites were evaluated. One preliminary dataset was collected by DMEC and used in these analyses. Data were collected in late 2013 and early 2014. The model variables and functions for assessing MDR playas were primarily adapted from “A Regional Guidebook for Applying the Hydrogeomorphic Approach to Assessing Wetland Functions of Prairie Potholes” (Gilbert et al. 2006), and also from “A Draft Regional Guidebook for Applying the Hydrogeomorphic Approach to Assess Wetland Functions of Vernal Pool Depressional Wetlands in Southern California” (Bauder et al. 2009). The reference sites encompass a range of variation, from developed and highly utilized to relatively undisturbed. Each site was described as belonging to one of the following treatment groups, which may be referred to in discussion of some variables: Ideas for treatment separations: Separating treatment groups is somewhat problematic as larger playas (in particular Soda) may have a huge variety of conditions present. a. Impacted Soft Playas (n = x) b. Impacted Hard Playas (n = x) c. Reference Soft Playas (n = x) d. Reference Hard Playas (n = x) Perhaps separating them by size is appropriate: a. <1,000 Acres (n = 4) b. 1,001 – 5,000 Acres (n = 6) c. 5,001 – 10,000 Acres (n = 3) d. >10,000 Acres (n = 4) The sampled reference domain is entirely within California, and within the Mojave Basin and Range Level III Ecoregion (EPA 2014). Reference sites are also categorized into physiographic group designations by their Basin, (NHD HUC6), Subbasin (NHD HUC8), Watershed (NHD

HUC10), and EPA level IV Ecoregions. Locations and physiographic group designations for the reference sites are provided and illustrated in Section III. The majority of sampled reference sites exist in the central and western Mojave Desert. Improvement of reference data would include sites from the entirety of the Mojave Desert, including the Northern and Eastern Mojave Desert, into the states of Nevada, Arizona, and Utah. For characterization of each reference site, transects were established circumnavigating the playa shoreline where possible. At selected sites where access was limited, transects were established along playa shorelines wherever possible. Vegetation data were collected continuously along amorphous transects (inside perimeter of the playas) to characterize major changes in dominant species and vegetation alliances, with special attention to the presence on non-native species. Soil samples were collected at randomly selected sites on the playa surface. At selected sites with clear differences in surface morphology, multiple soil samples were collected at randomly selected sites within each distinct morphological region to characterize the variability present. Due to operational constraints, the majority of reference data collection and analysis were conducted via research and GIS. Soil samples were taken from the playa surface of each reference site. Soil samples consisted of crust and sub-crust samples to a depth of 6 inches, when there was a clearly defined separation between crust and sub-crust sediments. When no clear separation was present, a single sample to a depth of 6 inches was collected. For catchment characterization, boundaries and area were determined from aerial imagery, topographic maps, and use of National Hydrography Data Set4. Catchment basins were characterized by NHD Hydrologic Unit Code 10 and checked for accuracy with aerial imagery and topographic maps. In some cases a single playa has several HUC10 watersheds draining into it. Catchment land use and land cover were documented in the field, from aerial photography, and using the National Land Cover Dataset5. A Landscape Assessment Area (LAA) was circumscribed by a 1.6-km radius from the center of the assessment wetland. The LAA area evaluated was 8.1 km2. This convention was artificially defined and is considered the surrogate for assessing the wetland complex. National Wetland Inventory6 (NWI) linear wetland data with an “x” modifier (excavated) or “d” modifier (partly drained), and all classes of roads derived from the U.S. Bureau of Census data were also summarized for the LAA. Note: the size of the LAA needs to be evaluated for suitability for desert playa wetlands as a 1.6- km radius will not extend beyond several of the playa lakes found within the Reference Domain.

MODEL VARIABLES

Model variables are physical conditions in and around playa lakes that we believe are important and necessary to capture the state of condition of the six wetland functions used for this model. A number of these variables are identical to, similar to, or modified versions of variables developed and used in other depressional HGM guidebooks (Bauder et al. 2009, Gilbert et al.

4 Obtained from http://nhd.usgs.gov/ 5 National Land Cover Dataset is available from http://www.mrlc.gov/nlcd06_data.php 6 The NWI is a program run by the U.S. Fish and Wildlife Service with the goal of classifying and mapping all wetlands in the United States according to its wetlands classification system (Cowardin et al. 1979).

2006). The following variables integrate the results of reference data collection and are used to calculate the functional capacity indices. Following is the abbreviation used and a brief summary of what that variable is intended to capture, grouped by general category. Combinations of these variables are then used in index formulas for each of the six wetland functions to determine the functional index score.

Vegetation

VBUFFCONT = continuity of natural buffer adjacent to the wetland

VBUFFWIDTH = width of natural buffer perpendicular to the wetland

VVEGCOMP = vegetation composition

Soils

VRECHARGE = estimated soil recharge potential

VSED = sediment deposition in the wetland

VSQI = soil quality index

Hydrogeomorphic

VOUT = wetland surface outlet

VSUBOUT = subsurface drainage

VSOURCE = reduction or increase in catchment area

VEDGE = modified shoreline irregularity index

VCATCHWET = ratio of catchment area to wetland area

Land Use and Landscape

VUPUSE = land use within the catchment

VWETPROX = proximity to nearest wetlands

VHABFRAG = sum of the length of roads and ditches in the landscape assessment area.

Vegetation Variables

Buffer Continuity (VBUFFCONT) This variable represents the average continuity of natural landscapes and vegetation communities around the perimeter of the wetland. Buffer continuity is measured by determining the perimeter (in meters) of the wetland boundary that is contiguous with unaltered, intact shrubland. This measure is then divided by the total perimeter of the assessment wetland and is expressed as a percentage for calculation of the variable sub-index score. Based on the range of values at reference sites, a sub-index of 0 indicates that no buffer was contiguous with the wetland edge and a sub-index of 1.0 indicates the entire wetland perimeter was surrounded by buffer. The relationship of the metric to the sub-index score is presented in Table 11, Vegetation Continuity Adjacent to Wetland and Variable Sub-indices.

Table 11 – Vegetation Continuity Adjacent to Wetland and Variable Sub-indices (under development)

Presence and abundance of exotic species VVEGCOMP sub-index score Few if any exotic plants are present. Any exotic plants 0.9 present are not significantly detrimental to ecosystem and hydrologic function. Exotic plants are present but cover less than 10% of the 0.75 buffer area cover. Few if any exotic plants are present that are significantly detrimental to ecosystem and hydrologic function. Exotic plants are present and cover over 10% of the 0.5 buffer area cover. OR Exotic plants that are significantly detrimental to ecosystem and hydrologic function are a conspicuous part of the landscape. Exotic plants are present and cover over 20% of the 0.25 buffer area cover. OR Exotic plants that are significantly detrimental to ecosystem and hydrologic function are a conspicuous part of the landscape. Exotic plants are present and cover over 30% of the 0.1 buffer area cover. OR Exotic plants that are significantly detrimental to ecosystem and hydrologic function are a dominant part of the landscape.

Buffer Width (VBUFFWIDTH) This variable represents the average width in meters of buffer adjacent to the wetland edge. Robins (2002) determined that a three hundred (300) foot buffer was sufficient for riparian areas, but larger buffers were required for several species. We selected 1,000 meters as appropriate for playas lakes. Buffer width is measured perpendicular from the wetland perimeter to a length 1,000 meters distant. The width of vegetation is measured at a minimum of 12 equidistant intervals around the perimeter and the average width determined. A score of 0 indicates that there is no vegetation surrounding the wetland. A variable sub-index score of 1.0 is assigned when the average vegetation width is at least 1,000 meters.

Vegetation Composition (VVEGCOMP) This variable represents the floristic community quality assessed through field surveys of species present within the wetland. Vegetation community composition is used as a surrogate for overall native species richness and diversity, both flora and faunal. This variable is calculated by

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 57 assessing the amount and percent cover of exotic species within the 1,000 meter buffer zone around the playa, using aerial imagery or field surveys. The presence of exotic species such as Tamarix that are significantly detrimental to ecosystem and hydrologic function also affect this variable. GIS data from the Bureau of Land Management, California Department of Fish and Wildlife, the Desert Renewable Energy Conservation Plant, and other sources can also be used where appropriate to estimate the presence and abundance of exotic species. Table 11 is used to determine a sub-index score for this variable.

Soil Variables

Soil Recharge Potential (VRECHARGE)

An initial assessment of whether or not the playa contributes to groundwater recharge should be conducted before applying this variable. If it is determined that the playa does not recharge groundwater, this variable and its associated function, groundwater recharge, will not apply. This variable is an indirect measure of potential recharge based on the areal extent of soil types in the playa area. It is determined onsite by making a site-specific soil map and obtaining the extent of different soil types. The soil types are then used to determine an infiltration value for recharge potential based on soil structure. Soil infiltration values range from 1 to 0, with 0 being nearly completely impermeable and 1 being extremely permeable. Most playas are composed of hard, soft, or a mosaic of hard and soft surfaces. Hard playas can be given a soil infiltration value of 0.1 (extremely poorly drained), and soft playas 0.9 (excessively drained). For example, if a playa area is 80 percent hard surfaced and 20 percent soft surfaced, the soil infiltration value can be determined with the following equation: Site Soil Infiltration Potential = (0.8 × 0.1) + (0.2 × 0.9) = 0.23. There may be cases where the parts of the playa or the general area being assessed have soil types other than playa surfaces. If this is the case a soil map can be found for the area, and infiltration values can be assigned based on the soil description of that soil. For example, the inlet to East Cronese Lake is on the Rositas-Carrizo soil series, which is described as being “somewhat excessively drained” (Rositas) and “excessively drained” (Carrizo). The infiltration capacity for this series can be found by consulting Table 12, Infiltration Ratings for Mojave Playa Reference Sites, and averaging the infiltration capacity value for the soils in the soil series. Rositas-Carrizo would receive a value of 0.83 (0.75 + 0.9/2=0.83). If the assessed area was 60 percent hard surfaced, 20 percent soft surfaced, and 20 percent Rositas-Carrizo, the soil infiltration potential could be calculated as follows: Site Soil Infiltration Potential = (0.6 × 0.1) + (0.2 × 0.9) + (0.2 × 0.83) = 0.41.

Table 12 – Infiltration Ratings for Mojave Playa Reference Sites

Soil/Surface Type Infiltration Capacity Value Hard playa surface Extremely poorly drained 0.1 Bunker Hill Somewhat poorly drained 0.25 Gila Well drained 0.5 Rosamond Well drained 0.5 Wasco Well drained 0.5 Rositas Somewhat excessively drained 0.75 Arizo Excessively drained 0.9 Carrizo Excessively drained 0.9 Soft playa surface Excessively drained 0.9

Note: This variable needs to be evaluated for applicability for playa wetlands. We have the following questions regarding this variable: Should we remove this variable and replace it with sediment and or soil quality index for the groundwater recharge function? (It is only used for the groundwater recharge function?). Change name to Drainage/infiltration? Infiltration is the entry into the soil of water made available at the ground surface. Recharge is the entry into the saturated zone of water made available at the water table surface. Should the soil texture data from the reference playas be included for this variable? We could have two wetland subclasses for hard and soft that have different functions/variables. I.e. for a hard playa, lack of permeability would be functioning. For a soft playa, too much compaction and lack of permeability would be non-functioning. However, this is probably picked up in the Soil Quality Index variable.

Sediment (VSED) This variable is defined as the extent of increased or decreased sedimentation within the playa from culturally accelerated sources. Playas are generally at the bottom of basins and naturally accumulate sediments over time. Manmade obstructions can impound and divert sediment so that it no longer reaches the playa surface. Surface flow is also often concentrated into culverts and other drainage structures that alter the amount and location of sediment flow into and across playas. Farms, roads, solar arrays, mines and other manmade features can also increase the rate and amount of sediment that reaches the playa. For example, utility scale solar plants often involve removal of native vegetation, road construction, compaction, and significant land grading. These activities can increase the amount of soil lost to water and wind (Hernandez et al. 2014). Mining operations can leave depositions of tailings on playa catchment areas, which can then be transported up to several miles from their source (Belnap et al. 2008). Large deposits of sediments on can affect both vegetation and faunal communities by covering soils, seedbanks, and eggs (Belnap 2008, Gleason et al. 2002). Additionally, activities such as mining and road building on the surface of playas can alter and displace naturally occurring sediments, including increasing dust emissions (Reynolds et al. 2007). This can also have detrimental effects on plants and wildlife, as well as alter playa hydrology. Finally, non-native materials such as rubble and concrete are present on some playa surfaces, and too much of this can also have negative effects on playa function.

VSED is determined by estimating the impacts of the above activities to sediment processes on the playa and assigning them qualitative and or percentage values. The appropriate index value can then be assigned based on the measurements or conditions as described in Table 13, VSED

Categorical Variable. A single playa can have impacts that both increase and decrease sedimentation and may or may not have non-native materials. However, the presence of any one of the thresholds defined in Table 13 is sufficient to assign the associated index value.

Table 13 – VSED Categorical Variable

Measurement or Condition Index7 No signs of culturally accelerated erosion and sedimentation are evident on the playa surface or nearby. 1.0 The playa surface is not disrupted by human activities. There are no manmade structures that impound, divert, or concentrate sediment so that it does not reach the playa surface, or only reaches a small part of it. There are no non-native materials such as rubble and concrete present. Large sources of sediment or sediment disruption from as farms, roads, solar arrays, mines or other 0.75 manmade features are evident on the playa surface, but they cover or disrupt less than 5% of the playa surface. OR Some manmade structures are impounding or diverting sediment from the playa surface, but natural sedimentation is still able to occur. Sediment may be concentrated by culverts or other manmade features, but this is an insignificant part of the overall sediment reaching the playa. OR Some non-native materials are present, but they are mostly inconspicuous. Large sources of sediment or sediment disruption from farms, roads, solar arrays, mines or other manmade 0.50 features are evident on the playa surface, and they cover or disrupt 5 to 15 percent of the playa surface. OR Manmade structures are impounding or diverting sediment from the playa surface in a way that significantly affects natural sedimentation. Sediment reaches the playa, but it is concentrated in outwashes from culverts or other manmade features. OR Non-native materials are present and are a conspicuous part of the playa surface, up to 5 percent is covered by them. Large sources of sediment or sediment disruption from farms, roads, solar arrays, mines or other manmade 0.25 features are evident on the playa surface, and they cover or disrupt 15 to 25 percent of the playa surface. OR Manmade structures are impounding or diverting sediment from the playa surface in a way that significantly affects natural sedimentation. Very little sediment is able to reach the playa. OR Non-native materials are present and cover 5 to 25 of the playa surface. Large sources of sediment or sediment disruption from manmade features such as farms, roads, solar 0.10 arrays, mines etc. are evident on the playa surface, and they cover or disrupt over 25 percent of the playa surface. OR Manmade structures are impounding or diverting sediment from the playa surface in a way that stops nearly all sediment from reaching the playa surface. OR Non-native materials are present and cover 25 to 50 percent of the playa surface.

Soil Quality Index (VSQI) This variable represents the physical integrity of the upper 30 cm of the soil within the outer ponded depressional soil. Higher soil quality values on similar soils under different management may indicate soils that have improved aggregation and greater macroporosity, both of which may

7 The index scores have not yet been calibrated to reference site conditions and are placeholders for this preliminary draft of the model.

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 60 be related to greater soil biological activity (Lowery et al. 1996). Water moving through the soil is important for maintaining plant growth, preventing erosion, carrying solutes into the soil biological “filter”, and maintaining wetland surface and soil water storage capability. Soil morphology has been used to estimate permeability (i.e. hydraulic conductivity) (O’Neal 1952, Bouma and Hole 1971, McKeague et al. 1982, Kooistra et al. 1985), as well as soil quality (Grossman et al. 2001). This variable is measured by assessing the soil structure, soil pores, and rupture resistance (i.e. consistence) of the upper 30 cm (Soil Survey Division Staff 1993). Numbers assigned for each characteristic are listed in Table 14, VSQI Soil Characteristics Evaluated in Determination of the Physical Soil Quality Index. It is recommended that this procedure be used by experienced soil scientists, or by specifically trained personnel. Human induced disturbance to the playa surface is also important for assessing soil quality and includes activities such as OHV use and agriculture, which can contribute to soil compaction and poor soil quality. Human induced disturbances can be qualitatively assessed by determining the amount of vehicle tracks, tillage for agriculture, or other human induced disturbances in the area being sampled for VSQI. Table 14 contains values for five different soil quality characteristics. The summation of these values from a soil description is then used to determine the physical Soil Quality Index (SQI). Data are averaged across replicates within the outer, temporary depressional zone. The possible range of values for the SQI is a minimum of 0 (a parking lot) and a maximum of 15. A variable sub-index score of 1.0 was assigned for SQI values of greater than or equal to 12. Sub-index scores as they pertain to SQI values are shown on Figure 18, Sub-index Scores for VSQI.

Table 14 – VSQI Soil Characteristics Evaluated in Determination of the Physical Soil Quality Index

Assigned Value Characteristic 0 1 1.5 2 2.5 3

Few to Common to Pores None Few Common Many Common Many

Pore continuity None Low Moderate High

Not Structure Massive Compound Compound

Extremely Firm and Consistence Friable Very Friable Firm Very firm

Human Induced Highly Moderate Light Not disturbed Disturbance disturbed disturbance disturbance Adapted from Gilbert et al. 2006.

Figure 18 – Sub-index Scores for VSQI

Hydrogeomorphic Variables

Wetland Outlet (VOUT) This variable is the ratio of the elevation of the proposed constructed outlet to the natural outlet, if present. Measuring the depth and duration of ponding would be preferable; however, in rapid assessment it is not practical. A measurement assessing the impacts of alteration on ponding is more practicable. A ratio is derived from the elevations of the wetland boundary, basin center, natural outlet, and any proposed or existing constructed outlet. For example, the natural outlet is 2 m above the basin central elevation and the proposed project lowers that outlet by 0.25 m. 1.75/2 = 0.875. Playas are generally situated at the bottom of drainages and as such often do not have a natural outlet, so this variable will almost always be assessed as 1.0 (no difference between natural and constructed outlets). However, we have observed at least one instance where a playa was drained via a constructed outlet (Calico playa8), so this variable may apply in some instances. The lowest ratio allowed is 0.05., because there will always be some water holding capacity during rainfall events. The only time the VOUT sub-index score would be equal to 0.0 is when the wetland storage capacity has been completely eliminated by fill or excavation, which is not likely to happen for playas due to their large size. Alterations or existing artificial features such as drainage ditches, deep road ditches, and excavation or fill of any significance (greater than 1%) on the playa surface and alteration of

8 Calico playa refers to an unnamed playa lake between the ghost town of Calico and I-15, east of Barstow.

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 62 natural outlets or overflows are all included in the definition of wetland outlet. Users will have to determine the percentage of alteration to the playa surface that occurs as a result of excavations or placement of fill. An estimation of the volume of the wetland impacted is entered into the calculation worksheet (e.g. an excavation is 15 percent of the volume of the original wetland, 15 is entered into the calculation sheet). The volume of an excavated pit, fill, or wetland, can be estimated by many means, including use of standard field survey techniques, GPS, or GIS technology (e.g. analysis of aerial imagery). The prismoidal formula uses surface areas and various depth measurements to estimate the volume. Users may consult the Engineering Field Handbook, Chapter 11, pages 11-44 for more detailed guidance9. Alterations occurring singly or in combinations may have significant impacts on wetland hydrology. Alterations that extend only into the fringes of a playa surface often allow the majority of ponding to occur naturally. Those that are situated or extend into the deepest portion of the wetland generally drain the entire area. Alterations of any kind can alter the location and duration of ponding.

Subsurface Outlet (VSUBOUT) This variable is defined as the presence of wells and groundwater pumping activities within the playa. Use of groundwater can be significant, as in the case of the Mojave River drainage area where groundwater is extracted for urban and agricultural uses at a rate which results in an overdraft of over 68,000 acre feet annually (Mojave Water Agency 1994). This variable is based on a categorical index of the amount of wells and the ground water pumping rate of any wells that may be present on a playa surface or the surrounding area. A value of 1.0 is an area with no wells or groundwater pumping, and a 0 indicates significant groundwater pumping to the point where it exceeds recharge annually. Intermediate values can be assigned index values based on Table 15, VSUBOUT Categorical Variable.

Table 15 – VSUBOUT Categorical Variable

10 Measurement or Condition Index No active wells or groundwater pumping for municipal or agricultural use. Groundwater is not impacted. 1.0 There are a low number of working wells on the playa surface or immediate area surrounding it, but the 0.75 number of acre feet per year is insignificant or less than half of average annual groundwater recharge. Active wells are conspicuous on the playa surface and immediate area surrounding it. A significant amount (half or more) of average annual groundwater recharge is extracted. The water table may have 0.5 been lowered. Active wells are conspicuous on the playa surface and immediate area surrounding it. Nearly all of the average annual groundwater recharge is pumped out of the drainage area. The water table has been 0.25 lowered. Subsidence, fissures, or other effects of groundwater pumping may be present. More water is being pumped than is being recharged annually, and the water table has been lowered 0.1 drastically. Subsidence, fissures, or other effects of groundwater pumping may be present.

9 This information is available at: http://directives.sc.egov.usda.gov/viewerFS.aspx?hid=21429 10 The index scores will need to be calibrated based on reference data.

Wetland Source Area (VSOURCE) This variable represents the gross percentage change in the catchment area of a wetland. It should be noted that the playa surface itself is part of the wetland catchment area. Change can be an increase, decrease, or combination of both. Various combinations of alterations frequently result in both an increase to the catchment along with a decrease. The user should calculate the gross overall change in the case of a combination of alterations. Alterations in the catchment can have a significant direct effect, positive or negative, on the amount surface water input into a wetland. Typically, the placement of roads, ditches, tile drainage, and other alterations within the catchment result in intercepted or diverted surface flows, away from wetlands. Some instances actually result in an increase in catchment size (e.g. land leveling for irrigation or consolidated drainage). Playas that are connected to larger drainage systems may experience increased input. For example the Mojave River has added man-made discharges from sources such as fish hatcheries and wastewater. The estimated discharge from two fish hatcheries is from about 5,000 to 17,000 acre feet per year since water year 1949. Wastewater added ~2,000 to 8,000 acre feet per year since the mid-1980s (Lines 1996). The original or historical catchment boundary can be delineated with relative accuracy by using aerial photos, topographic maps, the National Hydrography Dataset, and other sources. Then, additions or reductions to the catchment are determined to find the percentage change. Index values are scored categorically, based on the appropriate description of catchment condition, as indicated in Table 16, VSOURCE Categorical Variable.

Table 16 – VSOURCE Categorical Variable

Measurement or Condition Index Minimal alteration of the upland catchment source area through structural surface alterations (e.g. solar 1.0 plants, road ditches, etc.), subsurface alterations (e.g. groundwater pumping, ditches). Minimal additions to the catchment from irrigation, fish hatcheries, wastewater, or other sources. More than 90 percent of catchment area is intact. Surface alterations of the upland catchment source area that impact overland flow into the wetland have 0.75 occurred; however, there has been no drainage in the catchment that significantly removes water from the playa being assessed, and there have been no significant additions. 75 to 90 percent of catchment area is intact. Upland catchment source area is changed to alter the dominant surface or subsurface flow path, or both, of 0.50 water to the playa. However, the alterations do not change the wetland water regime class. 25 to 75 percent of catchment area is intact. Upland catchment source area is changed to alter the dominant surface or subsurface flow path, or both, of 0.10 water to the wetland and alteration changes the playa water regime class. (e.g. a playa no longer ponds, or ponds for much shorter durations). Less than 25 percent of catchment area is intact. The upland catchment source area is extremely altered such that almost all surface and sub-surface water 0.00 flow to the playa is eliminated (e.g. groundwater drainage intercepts water and diverts it from the playa, urbanization or agriculture move water to another area, etc.) Adapted from Gilbert et al. 2006.

Wetland Edge Index (VEDGE) This variable represents the degree of shoreline irregularity. Irregularity is expressed as a ratio of the perimeter of the assessment wetland to the perimeter of a circle of equal area which can be assessed using aerial photos. The closer this ratio is to 1.0, the more circular the assessment wetland. The further ratio is from 1.0, the more crenulated the wetland shoreline is. The longer

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 64 the wetland shoreline, the higher the rate of water loss; hence there is a higher potential for recharge (Millar 1971). The playa shoreline is also a location of distinct and often specialized vegetation alliances and ecological communities. The playa shoreline also represents an area of ecotonal overlap between three communities: playa surface, playa fringe, and upland communities; each ecotype displays a distinct species composition or abundance as compared to adjacent patches. Wetzel (1975) described a shoreline irregularity index, which has been modified and is calculated as follows:

VEDGE =

Catchment: Wetland Ratio (VCATCHWET) This variable is the ratio of catchment size to wetland size. The catchment area for a playa is generally an associated HUC 10 watershed. However, there are cases where multiple HUC 10 watersheds drain into a single playa, such as Panamint playa which has four HUC 10 watersheds in its catchment area. Other playas are part of larger drainage networks, such as East Cronese which at times receives flow from the Mojave River. Catchment size can be assessed on a case by case basis and may require the use of maps, aerial photography, and hydrology datasets. The USGS National Hydrology Dataset (NHD) is useful in this regard11. Wetlands that have a higher catchment-to-pond ratio are more likely to contribute water to recharge (Arndt and Richardson 1988). The number is calculated using the formula: X = (wetland area) / (area of the catchment) The catchment area includes the wetland. The variable sub-index score is then calculated by consulting Table 17, VCATCHWET Categorical Variable, below, which provides the values ascertained from the range of wetland ratios calculated from the reference playas. This range of values is provided as Appendix C, Range of Wetland Values (under development).

Table 17 – VCATCHWET Categorical Variable

VCATCHWET Sub-index score X (Catchment Ratio) 0.9 X>0.1, or the playa receives influence from a greater watershed such as the Mojave River. 0.75 0.05

11 An interactive NHD map can be found at http://viewer.nationalmap.gov/viewer/nhd.html?p=nhd

Land Use and Landscape Variables

Upland Land Use (VUPUSE) This variable represents the current land use/land cover categories within the present-day catchment of the wetland being assessed. The playa surface is included in the catchment area. As described in (Gilbert et al. 2006), the variable is calculated by determining an area based weighted average runoff curve for the catchment. Curve numbers (weights) corresponding to reference data land use categories are provided in Table 18, Runoff Curve Numbers for VUPUSE. If more detail is required, the user has the option of using the above table or consulting the Engineering Field Handbook’s curve numbers12.

Table 18 – Runoff Curve Numbers for VUPUSE

Upland Land Use Condition Curve Number

Urban, semi-pervious, or impervious surface 98 Military Base Infrastructure 85 Solar Electric Infrastructure 80 Conventional tillage small grain 75 Minimum till in a grass/legume rotation 74 Farmsteads 72 Rangeland—Native or non-native species, overgrazed, high amount of bare ground, low plant 70 vigor, and evidence of soil erosion (e.g. gullies, rills) Rangeland—Native or non-native species, often overgrazed, some bare ground, low plant vigor 68 Rangeland dominated by non-native species under some type of management – OR Rangeland— native species with fair grazing management such as season long grazing at slight 65 or moderate intensity – OR- Rangeland— idle grassland cover. (Includes idle native range and CRP) Native vegetation communities 61 Adapted from Gilbert et al. 2006

Wetlands Proximity (VWETPROX) This variable is a measure of the proximity of the assessment playa to other nearby playas. Because playas generally are not associated with other playas, this variable will not apply in most cases. There are, however, cases where playas are close to each other, and sometimes connected as a drainage network during high rainfall events. East and West Cronese Lakes are an example of this. Proximity between playas relates to the ability of species and propagules to disperse and move from one playa to another. It is also used to assess the wetland complex condition at a large scale, with emphasis at a finer scale of resolution as compared to the other landscape variables. Reference playas assessed by DMEC ranged from 2.7 miles apart to 139.8 miles apart

12 Source information for runoff curve numbers can be found at: http://directives.sc.egov.usda.gov/viewerFS.aspx?hid=21429

(Appendix A). A sub-index score for this variable can be assessed by finding the distance between two playas, or in the case of more than two playas as part of a network, the average distance between them. If this distance is over 100 miles, the sub-index score will automatically be assigned as 0.0. Otherwise the distance will be subtracted from 100 and then divided by 100. For example, if two playas are 11.6 miles apart the sub-index score would be calculated as follows: (100 - 11.6) / 100 = 0.884.

Landscape Habitat Fragmentation (VHABFRAG) This variable is used to assess habitat fragmentation between playas in cases where there are multiple connected playas as part of a network. This variable is an analysis of the extent of roads and drainage features (in kilometers) and conversion of habitat to urban and agricultural uses within the Landscape Assessment Area (LAA). It is used to account for fragmentation and alteration of natural landscapes in cases where playas are part of a large scale wetland complex. Historical wetland basins are often fragmented by intersecting by roads, ditches, and drainage features. This creates significant impacts on basins hydrodynamics, groundwater flow patterns, storage capacity, connectivity, and habitat suitability. Note: Use of this variable will require defining an appropriate LAA size and assess each playa for the total distance of roads and drainage features and come up with a range of values upon which to base assigning sub-index scores.

PLAYA WETLAND FUNCTIONS

The following functions of playa depressional wetlands in the Mojave Desert were selected for model development: 1. Surface Water Storage 2. Groundwater Recharge 3. Retain Particulates (physical processes) 4. Remove, Convert, Sequester Dissolved Substances (biogeochemical processes) 5. Maintain Resilience of Characteristic Plant Communities and Carbon Cycling 6. Maintain Resilience of Characteristic Faunal Habitat The following sequence is used in articulation of the selected functions. • Definition: Defines the function and identifies an independent quantitative measure that can be used to validate the functional index. • Rationale for selecting the function: Provides the rationale for why a function was selected and discusses onsite and offsite effects that may occur as a result of lost functional capacity. • Characteristics and processes that influence the function: Describes the characteristics and processes of the wetland and the surrounding landscape that influence the function. • Functional capacity index: Describes the assessment model from which the functional capacity index is derived and discusses how model variables interact to influence functional capacity.

Function 1: Surface Water Storage

Definition This function represents the capacity of a playa wetland to collect and retain direct precipitation, surface water runoff, and discharging groundwater as standing water above the soil surface, pore water in the saturated zone, or soil moisture in the unsaturated zone. An independent quantitative measure of this function is the amount of water stored in the playa wetland per a given time (e.g. acre-feet/year).

Rationale for Selecting the Function This function has profound effects upon the maintenance of the wetland and is often considered as the main driving mechanism for all other wetland processes. Water storage in MDR wetlands is important for three reasons. 1. Water that is retained in the playa wetland reduces the amount of runoff down slope, ensuring a decrease in erosion down gradient (when the playa is not the terminal basin). 2. It guarantees that sufficient moisture is available to allow the development and maintenance of the ephemeral aquatic habitat and associated habitats, including: invertebrate communities and subsequent egg banks, ephemeral aquatic habitat for migratory bird species, occasionally hydric soils, and associated hydrophytic plant communities. These plant communities ensure that habitat is available for a variety of wildlife species, both resident and migratory. 3. Water storage supports the biogeochemical processes that occur in wetlands, such as the removal of nutrients and particulates, resulting in improved water quality.

Characteristics and Processes that Influence the Function The characteristics and processes that influence the collection and retention of surface waters in playa wetlands are influenced by both natural and anthropogenic factors. Substantial variation exists in the natural performance of this function. Surrounding landscape topography and hydrology (i.e. catchment basin, groundwater discharge) greatly influence the quantity and rate of water input into a playa wetland. A playa at the terminus of a significant riverine system has the potential to receive substantially more runoff than a playa in a small isolated basin, yet both can be governed entirely by localized precipitation events. Characteristics of the playa wetland itself such as geometry, drainage features, soils, and vegetation also directly affect the quantity and duration of ponded surface waters. Some playas are impervious to groundwater infiltration (resulting in long standing surface waters) while others have an immense capacity for and high rate of groundwater recharge (Neal 1965). These characteristics can also change (due to natural or anthropogenic factors) within a short period of time, Blodgett and Williams (1990) reported the majority of a 1 inch rainfall to have drained into a newly formed desiccation crack in Rogers Playa within 24 hours. In other situations groundwater may be the primary input of surface waters into a playa; these playas tend to have a more stable water level than playas whose primary input is dependent upon precipitation (Brostoff et al. 2001).

Playa wetlands have considerable potential for storing runoff. The ability for desert playas to store water depends on the sediment makeup of the playa surface. Hard playas have an impervious clay layer on their surface which allows for little if any infiltration (Brostoff et al. 2001). Clay type sediments and calcium carbonate layers in subsurface layers can increase the storage duration for a particular playa. Soft playas have a loose, friable surface structure, and they readily drain water and discharge it into groundwater. Anthropogenic factors often drastically affect the location, duration, and quantity of ponding waters through alteration of the playa wetland itself or the surrounding landscape. Construction of ditches within the playa surface can change the areal extent of ponding waters, while construction of drainage features along the playa edge may drain the playa wetland entirely. These changes in hydrology, geomorphology, and nutrient cycling and sediment dynamics have had profound implications for aquatic ecosystems and biodiversity (Blann 2009). Anthropogenic alteration within the catchment basin can also drastically impact this function by reducing water input through diversion of surface water flows or groundwater extraction. Conversely, construction of impervious surfaces within the catchment basin can reduce upland rates of groundwater infiltration, resulting in increased rate and quantity of surface water runoff into a playa wetland.

Functional Capacity Index

FCI=

The assessment model for calculating the functional capacity index (FCI) is as follows: The ability for a playa wetland to store surface water is dependent on the playas geographic placement as well as the geological constituents. In the model, the variables having the greatest impact on ability of a playa wetland to store water are VOUT and VSUBOUT which determine the outflow of water directly from surface and the sub surface flow of water into fissures and openings in playa lake bed.

VSED is used to estimate the extent to which water holding capacity might be altered by changes in sedimentation. The variables VUPUSE and VSOURCE are used to measure the timing and quantity of water entering the wetland. If the source area is changed, there is more or less water coming into the wetland system, so the function lessens. If land use in the catchment is less than the reference standard, water can be irregular in amounts and can decrease the water storage ability of the specific playa wetland.

Function 2: Groundwater Recharge

Definition This function represents the capacity of a playa wetland to facilitate surface water infiltration resulting in recharge of the local or regional water table. These processes are treated as described by Freeze and Cherry (1979): Infiltration is the entry into the soil of water made available at the ground surface; Recharge is the entry into the saturated zone of water made available at the water

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 69 table surface. Because hard playa surfaces are impermeable and generally do not allow any infiltration, this function will not apply to playas that have 100% hard surfaces, or otherwise do not contribute to groundwater recharge. A potential independent, quantitative measure of this function is the volume of water lost to groundwater per unit area per unit of time (acre-feet/hour). Usually, this is measured or estimated on a net annual basis.

Rationale for Selecting the Function The capacity to provide groundwater recharge is an important function of wetlands. The Mojave River floodplain has an aquifer directly underlying it. This is the most significant and important aquifer in the region (Lines 1996). There are multiple playas that are fed by the Mojave River drainage system. Playas are also often the terminus of local drainages systems. Playas therefore contribute significantly to the recharge of groundwater in the MDR.

Characteristics and Processes that Influence the Function MDR playas vary dramatically in their ability to recharge groundwater. The natural physical characteristics of the playa surface and near surface sediments greatly influence an individual playa wetland’s capacity for groundwater recharge. Some playas have an enormous capacity for groundwater recharge, while the surface of others is virtually impervious to infiltration (Neal 1965). Hard playas have an impervious surface and are unlikely to contribute to groundwater in a significant way; most of the water probably evaporates rather than infiltrating. Soft playas, on the other hand, drain more readily, and probably contribute significantly to groundwater recharge. These physical characteristics can also be altered by anthropogenic activity. Extraction of groundwater may result in land subsidence and the formation of desiccation cracks that rapidly drain surface waters (Blodgett and Williams 1990, Doty and Rush 1985).

Functional Capacity Index

FCI =

In the model, the capacity of a playa wetland to recharge groundwater depends on several characteristics. The level of surface water is controlled by VOUT and VSUBOUT, which decreases the pressure head and overall available water for groundwater recharge. If the subsurface outlet has the ability to intercept all water below the wetland, the sub-index would be equal to 0.0.

VRECHARGE, VEDGE, and VCATCHWET are all hydrogeomorphic variables that reflect a playas natural affinity to recharge groundwater. VRECHARGE uses different soil types across wetland to assess the potential for groundwater recharge. VSQI, VSED and VUPUSE variables are related to the amount of water that will be available for ground water recharge and the amount of sediment that will control duration and quantity of ponded waters available for recharge.

Function 3: Retain Particulates (Physical Processes)

Definition This function is defined as the capacity of a playa to physically retain and remove both inorganic and organic particulates that are greater than 0.45 μm in size (Wotten 1990) from the water column. A potential independent measure of this function is the amount of particulates retained per unit area per unit time (i.e. [g/m2]/yr).

Rationale for Selecting the Function The ability of wetlands to retain sediment is often described as a water quality benefit (Boto and Patrick 1978). The removal of particulates reduces the amount of particle bound pollutants (e.g. heavy metals, pesticides) entering the ground water when a playa is pervious to infiltration. This refers to particulates of both onsite and offsite origin. However, too much sedimentation can be detrimental to wetland function. A proper balance of these factors is necessary for the overall maintenance of the nutrient budget and associated characteristic plant and animal communities of playa wetlands. This function is considered in contrast to biogeochemical processes that remove and sequester elements and compounds that are dissolved in surface water.

Characteristics and Processes that Influence the Function There are two main factors which influence a wetlands ability to perform this function. The first deals with the processes that affect how particulates are transported to and or prevented from entering the wetland. Sediment inputs into playas are derived primarily from wind and water erosion of soils in the immediate catchment and adjacent upwind landscapes. The second factor is the ability of the wetland to immobilize particulates after they are transported in. Because they are generally at the terminus of a basin, playas naturally accumulate sediment over time (Neal 1965). However, water volume in depressional wetlands can be decreased if too much sediment accumulates (Luo et al. 1997). Sediment can also bury egg and seed banks in wetlands (Gleason 2002). Sediment entering playas can contain elements and compounds that are then either buried in the playa strata, or precipitated out in mineral or salt crusts. Alterations to playa catchment areas and surfaces can affect the ability of the playa to retain these elements and compounds. Playa surfaces can contain concentrations of toxic metals, and disturbances can release these as dust borne particulates which have the potential to harm plant and animal communities (as well as humans), as in the case of Owens Lake (Reheis et al. 2003). Mining, road construction, OHV use, and other disturbances to a playa surface can alter catchment basin morphology and subsequently affect the both the sediment that reaches a playa and the ability of that playa to catch sediment. Hard-rock mining can leave depositions of tailings on alluvial fans, and generate dust, as can placer and gravel mining. These tailings, some of which are toxic, can then be transported into playa wetlands (Belnap et al. 2008). Destruction or alteration of vegetation communities is particularly important for this function. Intact vegetation stands reduce the intensity of surface water flow and increase infiltration and filtration of particulates. They also

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 71 reduce soil erosion. Vegetation cover and buffers surrounding playas are therefore very important for this function.

Functional Capacity Index

FCI =

In this model, the capacity of a playa wetland to retain particulates depends upon three characteristics: the ability of the playa to physically store sediment, the ability of sediment to reach the playa, and the slowing of surface waters long enough to allow particulates to settle. In the first part, VSED indicates whether there is any capacity in the basin to trap additional sediment. If the depressional characteristic of the wetland is eliminated, there is no place for the sediment to be stored.

In the second part of the model, VUPUSE, VBUFFWIDTH and VBUFFCONT represent the ability of the surrounding landscape to deliver or prevent particulates from reaching the wetland. These variables are partially compensatory and assumed to be independent and to contribute equally to the performance of the function. The variables are combined using an arithmetic mean that reduces the influence of lower sub-indices on the FCI (Smith and Wakeley 2001), which in this case is consistent with the assumption that these variables have less of an influence on the function. For example, the presence of a buffer will reduce the amount of sediment that actually reaches the wetland even if the VUPUSE sub-index is 0.0.

In the third part of the model, VVEGCOMP and VOUT reflect the ability of the wetland to reduce the velocity of the water moving into and through the wetland. These variables are partially compensatory and assumed to be independent and to contribute equally to the performance of the function. The variables are combined using an arithmetic mean that reduces the influence of lower sub-indices on the FCI (Smith and Wakeley 2001), which in this case is consistent with the assumption that these variables have less of an influence on the function. For example, even if the sub-index for VOUT is 0.0, the roughness contributed by plants will still retain some of the particulates.

Function 4: Remove, Convert, Sequester Dissolved Substances (Biogeochemical Processes)

Definition This function is defined as the playa wetlands ability to remove and sequester elements and compounds from solution in surface and near surface waters “Remove” or “Convert” refers to a permanent loss of elements or compounds through biogeochemical reactions. “Sequester” refers to the long-term accumulation of elements and compounds (e.g. incorporation into biomass by perennial vegetation). Elements and compounds include both nutrients and contaminants, which

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 72 can be either essential to organism growth (e.g. nitrogen) or toxic at high concentrations (e.g. heavy metals, pesticides).

Rationale for Selecting the Function The processes involved with this function contribute directly to a reduced load of nutrients and contaminants into the groundwater, mitigating the impacts of non-point source pollution. This in turn results in improvements in water quality and wetland habitats associated with desert playas. Substantial literature exists documenting the benefits of various wetland types to groundwater and surface water resources (Faulkner and Richardson 1989, Johnston 1991) and as sites for tertiary treatment of wastewater (EPA 1983, Godfrey et al. 1985, Ewel and Odum 1984).

Characteristics and Processes that Influence the Function MDR playas biochemistry characteristics are controlled by a number of ecological, hydrological, and geological functions. Arid and semi-arid regions are limited in nutrient supply due to lack of biomass productivity and climatic regimes of low precipitation with limited nutrient flow into subsurface soils. Geological composition affects the supply of particular minerals, the cation exchange capacity and pH. Vegetation above ground and in soil surfaces act as major processors of nutrients and organic matter producers. Precipitation is the main water source for desert playas as it falls directly on the basin, moves through the surface and sub-surface soils and enters via surface flow or spring flows. The presence of water controls biogeochemical reactions, movement and the distribution of nutrients (Garcia-Moya and McKell 1970). Salt crusts form from chemicals that precipitate out as water dries on playa surfaces, and the presence of salts defines the extent of halophytic vegetation communities. Biological soil crusts and associated organisms are important for the sequestration and fixation of a variety of compounds and elements including carbon and nitrogen (Zaady et al. 2000, Evans and Lange 2003). Additionally, biological soil crusts affect the movement of water, gases, and solutes across soil surfaces (Belnap et al., 2003), and this affects which chemicals enter the playa. Disturbance of playa uplands affects the distribution and amount of biological soil crusts, and a lack of these crusts is likely to negatively alter playa ecosystems, particularly the vegetation communities that rely on them.

Functional Capacity Indices: Direct and Indirect

FCI =

In this model, the capacity of a playa wetland to remove, convert, and sequester dissolved substances is made of three parts. The first focusses on the presence of an ephemeral wet, anaerobic environment on the wetland. The lesser of VOUT and VSUBOUT is used because the biochemical processes are dictated by moisture. The second portion of the model deals with the

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 73 mechanisms by which the substances are transported to the wetland and are represented by VBUFFCONT, VBUFFWIDTH, VSOURCE, VUPUSE, and VSED. These variables are also closely associated with the presence of biological soil crusts, which are important for arid land biogeochemistry as stated above. The five variables are equally independent. The third part deals with the biogeochemical processes involved in the function and is represented by the variables VSQI and VVEGCOMP. The second part of the model is averaged because the variables are considered to be independent and equally important. Therefore a characteristic level of removing, converting and sequestering will not be achieved if mechanisms and processes are reduced. A geometric mean is used for the sub-indices that are indicators of anaerobic conditions (VSUBOUT or VOUT) because without maintaining anaerobic conditions, the functional capacity of a wetland is dramatically diminished. The primary mechanism for transforming many of the elements and compounds is based upon the presence of water.

Function 5: Maintain Resilience of Characteristic Plant Communities and Carbon Cycling

Definition Plant Community Resilience and Carbon Cycling is defined as the ability of a wetland to maintain native plant community patterns and related processes characteristic of a Mojave Desert Playa. Playa ecosystem diversity, structure, and function are highly variable at different spatial and temporal scales. Ecosystem characteristics such as seed dispersal, vegetative propagule production, plant densities, and growth rates must be maintained at levels that allow the plant community to respond to the natural disturbance regime in order to ensure long-term sustainability. In assessing this function, one must consider the extant plant community as structured by recent and historic flood events in combination with other natural and anthropogenic influences at both the local and landscape scales.

Rationale for Selecting the Function The ability to maintain a characteristic plant community is important for its contribution to biodiversity. Many plants found in playa wetlands are extremely specialized and have a limited distribution. The characteristic plant community also contributes many attributes and processes to playa wetlands that influence other functions, such as retaining particulates, decreasing runoff and increasing water infiltration, and supporting faunal habitat.

Characteristics and Processes that Influence the Function MDR playa plant community characteristics fluctuate on both spatial and temporal scales. Disturbance (recurrent or catastrophic, natural or anthropogenic) is the primary mechanism driving plant community composition, distribution, and succession (Toft and Elliott-Fisk 2000). The primary source of disturbance driving plant community dynamics in playa wetlands is hydrologic variation that contributes directly to soil properties and surface/subsurface water

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 74 availability (Toft and Elliott-Fisk 2000, Vasek and Lund 1980). Plant succession facilitates soil chemical characteristic changes and soil accumulation, resulting in the formation and growth of phreatophyte mounds (Vasek and Lund 1980). Desert playas contribute significantly to long distance seed-dispersal, while the playa surface often limits successful recruitment (Fort and Richards 1998). Upland disturbances often have significant effects on vegetation communities. Improper grazing regimes can diminish native forb and grass populations, while encouraging the establishment of exotic plants that often diminish ecosystem function. Land use changes such as agriculture, urban development, and solar plant development generally completely remove native plant communities and have concomitant effects on playa function. Increased sedimentation can also affect playa vegetation communities, as it covers seedbanks with disturbed soil which inhibits native plant colonization (DeFalco & Esque 2014), and, as with overgrazing, encourages exotic plants. Exotic plants such as Cheat Grass (Bromus tectorum) can diminish faunal habitat as well as alter natural fire regimes. The capacity for plants to sequester carbon in the soil is also impacted by desert soil disturbance (Allen et al. 2014).

Functional Capacity Indices: Direct and Indirect

FCI=

In the model, the lesser of VOUT and VSUBOUT is used because the hydrodynamics is the major factor in plant community processes and responses. VUPUSE indicates the condition of the surrounding catchment and this is averaged with VBUFFCONT and VBUFFWIDTH. This provides an indication of the immediate area surrounding the playa wetland, which will potentially affect the inputs of sediment or pollutants. The decrease of VUPUSE, VBUFFCONT or VBUFFWIDTH variables is capable of decreasing this function. VSED and VSQI are used to determine the amount and quality of sediment that has accumulated within the wetland. Secondarily, accelerated sediment inputs can reduce wetland volume, bury seed banks, and alter vegetation dynamics and zonation. VVEGCOMP is the most direct indication of how similar the plant community is to the reference standard conditions. VVEGCOMP was given a higher weighting within the assessment model.

Function 6: Maintain Resilience of Characteristic Faunal Habitat

Definition This function is defined as the ability of a playa wetland to provide appropriate habitat which facilitates the support of aquatic and terrestrial vertebrate or invertebrate populations during some part of their life cycle. The presence of water is extremely important to faunal communities associated with playas. Because inundation is infrequent and not guaranteed to happen every year, playa faunal communities have a high degree of spatial and temporal variability. Very little literature discussing faunal usage of desert playas is available.

Playa wetland habitats and surrounding landscapes change drastically in response to natural and anthropogenic disturbance. Long term surveys of faunal diversity and abundance would provide the ideal quantitative assessment of habitat functionality. Such studies are impractical for HGM rapid assessment. Thus, less variable structural and compositional playa wetland properties are examined at multiple scales as surrogate metrics.

Rationale for Selecting the Function Santos and Whiteford (1981) have demonstrated that invertebrates contribute significantly to the decomposition within desert communities. Playa fringes are often densely vegetated with species contributing significant primary production resources in the form of leaf litter. Wetlands have some of the highest reported plant growth rates of any ecosystem in the world due to high nutrient and water inputs (Richardson 1995). This deposition of organic material forms the base of the aquatic food chain developing rich invertebrate and microbial communities that in turn contribute to the resources available to higher order consumers (Richardson 1995). Many specialized and often endemic invertebrates utilize the ephemeral aquatic habitat of inundated playas (Brostoff et al. 2010, MacKay et al. 1990, Eng et al. 1990). Some of these species (e.g. Thamnocephalus platyurus) are not found outside the desert playas California (Eng et al. 1990). This rich ephemeral aquatic community often attracts many resident and migrant vertebrate species, particularly birds. Faunal community diversity and abundance responds to the natural and anthropogenic disturbance regime, fluctuating with changes in hydrodynamics, vegetation, and season.

Characteristics and Processes that Influence the Function

HUMAN INDUCED INFLUENCES

Mojave Desert playa wetlands have been significantly impacted by human activities including alteration of the playa surface, alteration of the catchment basin and surrounding landscapes, introduction of exotic species, introduction of hazardous wastes (such as the wastewater evaporation ponds located on Ivanpah playa), alteration of natural grazing patterns, and accelerated sedimentation. Desert playa invertebrate egg banks are naturally influenced primarily by species specific biology and behavior in combination with environmental factors (MacKay 1990, Mura 2004). Alterations in the playa surface and surrounding landscape that affect the location, quantity, and duration of surface flows may ultimately affect the composition and distribution of the playa wetland’s flora and fauna. Invertebrate egg banks can be negatively affected by off-highway vehicle use, water contaminants (Eng 1990), and sediment deposition (Gleason et al. 2002). All six species of fairy shrimp that are endemic to California are threatened by ongoing habitat destruction and alteration (Eng 1990). Vertebrate species are also adversely affected by anthropogenic alterations to water quality. Hampton et al. (2009) documented approximately 25% mortality among the over 2,000 migratory birds annually visiting toxic wastewater ponds at Searles Lake.

Functional Capacity Indices: Direct and Indirect For playas with close proximity to other wetlands such as Soda Lake and Silver Lake or East and West Cronies Lakes where the interactions of faunal habitat play a significant role in faunal community assemblage the VWETPROX variable will be applied to the model to determine the value of the wetland.

FCI =

For single playas that do not have other playas nearby, VWETPROX is not used:

FCI =

Hydrology (VOUT, VSUBOUT) are given the greatest weight in the equation. The alteration in a wetlands hydroperiod will have the greatest impact to wetland dynamics, subsequent plant community responses and ultimately effect faunal habitat selection and utilization. The variables VUPUSE, and VSED, the land use and land cover of the catchment, affects the sedimentation rates and hydrodynamics within the wetland. The condition of the surrounding upland areas influences the movement of fauna between wetlands as well as providing cover for the wetland dependent fauna. VSED is measured in the wetland and is a response to anthropogenic disturbances of sediment dynamics on the playa. Both of these variables are averaged in the assessment model. The variables in the equation directly related to vegetation structure and composition as they influence fauna are VVEGCOMP,VBUFFCOMP,VBUFFWIDTH and VEDGE. The extent, composition and continuity of vegetation around the wetland directly influences habitat for fauna. Intact vegetation communities provide movement corridors, breeding habitat, cover and other ecosystem benefits for faunal communities. VBUFFCONT,VBUFFWIDTH and VEDGE are averaged in the assessment model. These three variables in combination provide an indication of habitat inter-connectivity at a local scale. For projects involving multiple playas over a large landscape area:

In this form, is substituted for:

In the preceding assessment model the assessment model for multiple projects would be:

FCI =

VOUT, VUPUSE, VSED, and VVEGCOMP are used in the landscape assessment option to maintain the linkage of the assessment playa to the surrounding ecosystem.

SECTION V. ASSESSMENT APPROACH

OVERVIEW

In previous sections of this Guidebook, we provide: a) background information on the HGM Approach, b) wetland variables that are indicators of the level of function, c) the assessment models (FCI’s) consisting of those indicator variables, and d) how those indicators and models are used to describe level of function. This section provides the specific protocols that should be followed to conduct a functional assessment of Mojave Desert playa depressional wetlands. These protocols are designed for, and will generally be used within the context of the Clean Water Act (CWA) Section 404 permit review process. They may also be used for other wetland management goals or objectives (e.g. restoration, monitoring, and evaluation) that require measures of function for Mojave Desert playas. The typical assessment scenario is a comparison of pre-project and post- project conditions in the playa wetland. In practical terms, this translates into a comparison of the functional capacity of the wetland assessment area (WAA) under both pre-project and post-project conditions with the subsequent determination of how functional capacity indices have changed as a result of the project. Data for the pre-project assessment are typically collected under existing conditions at the project site. Data for the post-project assessment are normally based on the conditions that are expected to exist following proposed project impacts, although there may be cases where an actual post-project will take place. A skeptical, conservative, and well-documented approach is required in defining post-project conditions. This section discusses each of the tasks required to complete an assessment of desert playa depressional wetlands, including: a. Define assessment objectives b. Characterize the project area c. Screen for red flags d. Define the Wetland Assessment Area e. Collect field data f. Data entry and analysis g. Apply the results of the assessment

Statement of Purpose and Objectives

Begin the assessment process by identifying the purpose for conducting the assessment. This can be as simple as stating, “The purpose of this assessment is to determine how the proposed project will impact wetland functions”. Other potential objectives could be: a) compare several wetlands as part of an alternatives analysis, b) identify specific actions that can be taken to minimize project impacts, c) document baseline conditions at the wetland site, d) determine mitigation requirements, e) determine mitigation success, or f) determine the effects of a wetland

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 78 management technique. Frequently, there will be multiple purposes identified for conducting the assessment. Defining the purposes will facilitate communication and understanding between the people involved in conducting the assessment and will make the purposes clear to other interested parties. In addition, it will help to establish the approach that is taken. The specific approach will vary to some degree, depending on whether the project is a Section 404 permit review, an Advanced Identification (ADID), Special Area Management Plan (SAMP), field work as part of a General Plan or HCP monitoring program, or for some other purpose.

Collate Preexisting Data

Characterizing the project area involves describing the project area in terms of climate, geomorphic setting, hydrology, vegetation, soils, land use, proposed impacts, and any other characteristics and processes that have the potential to influence how wetlands at the project area perform functions. The characterization should be written and should be accompanied by maps and figures that show project area boundaries, jurisdictional wetlands, WAA, proposed impacts, roads, ditches, buildings, streams, soil types, plant communities, threatened or endangered species habitat, and other important features. The following list identifies some information sources that will be useful in characterizing a project area. a. Aerial photographs or digital ortho-photos covering the wetland and surrounding landscape. b. Topographic and National Wetland Inventory maps (1:24,000 scale) covering the wetland and the surrounding landscape including c. USGS National Hydrography Dataset d. Soil maps (e.g. county, NRCS) e. Climatic records (NOAA, county, private) f. Surveys and reports including biological surveys, environmental documents (EIS, EIR, EA, MND, or equivalent), geotechnical or hydrological reports, mitigation project proposals and reports, research papers, prior restoration reports, and proposed projects. g. Land use history validated with historical aerial photographs and data.

Screen for Red Flags

Red flags are features within, or in the vicinity of, the project area to which special recognition or protection has been assigned on the basis of statutory criteria. Many red flag features, such as those based on national criteria or programs, are similar from region to region. Other red flag features are based on regional or local criteria. Screening for red flag features represents a pro- active attempt to determine if the wetlands or other natural resources in and around the project area require special consideration or attention that may preempt or postpone an assessment of wetland function. The assessment of wetland functions may not be necessary if the project is unlikely to occur as a result of a red flag feature. For example, if a proposed project has the potential to impact a threatened or endangered species or habitat, an assessment of wetland

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 79 functions may be unnecessary since the project may be denied or modified strictly on the impacts to threatened or endangered species or habitat. Since much of the land in the MDR is federal, the appropriate Bureau of Land Management or National Park Service office can be consulted with about any potential red flags that may exist on a playa wetland. These offices may also need to grant permits for activities related to the assessment such as digging for soil samples or collecting vegetation samples. Detailed discussion of red flag features is outside the scope of this guidebook. The purpose and scope of the assessment would determine which of the red flags would require consideration.

Define the Wetland Assessment Area (WAA)

The WAA is an area of wetland within a project area that belongs to a single regional wetland subclass and is relatively homogeneous with respect to the site-specific criteria used to assess wetland functions (i.e. hydrologic regime, vegetation structure, topography, soils, seral stage). In most project areas, there will be just one WAA representing a single regional wetland subclass as illustrated in Figure 19, A Single WAA within a Project Area. However, as the size and heterogeneity of the project area increases, it is possible that it will be necessary to define and assess multiple WAAs within a project area.

Figure 19 – Single WAA within a Project Area

At least three situations necessitate defining and assessing multiple WAAs within a project area (adapted from Gilbert et al. 2006). The first situation exists when widely separated wetland patches of the same regional subclass occur in the project area, as illustrated on Figure 20, Spatially Separated WAA in the Same Regional Wetland Project Area. The second situation exists when more than one regional wetland subclass (e.g. hard and soft playas) occurs within a

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 80 project area, as illustrated on Figure 21, Spatially Separated WAAs from Different Regional Wetland Subclasses within a Project Area.

Figure 20 – Spatially Separated WAA in the Same Regional Wetland Project Area

Figure 21 – Spatially Separated WAAs from Different Regional Wetland Subclasses Within a Project Area

The third situation exists when a physically contiguous wetland area of the same regional subclass exhibits spatial heterogeneity with respect to hydrology, vegetation, soils, disturbance history, or other factors that translate into a significantly different value for one or more of the site-specific variable measures. These differences may be a result of natural variability or cultural alteration (e.g. farming, urban development, hydrologic alterations), as illustrated on Figure 22, WAA Defined Based on Differences in Site Specific Characteristics. Designate each of these areas as a separate WAA and conduct a separate assessment on each area.

Figure 22 – WAA Defined Based on Differences in Site Specific Characteristics

Determine the Wetland Subclass

The assessment will involve determining if the playa is hard, soft, or a mixture of these two surface types. These two surface types are described in Sections III and IV of this guidebook. The surface type(s) of a playa will likely affect the variables and functions and should be noted in the assessment. In the case of a playa with both surface types, the playa may need to be split into two WAAs. (expand on this)

Collection and Recording of Data

The following equipment is necessary to collect field data:  Plant identification keys  Soil sharpshooter shovel  County Soil Survey

 Munsell color book and hydric soil indicator list (U.S. Department of Agriculture, NRCS 2002)  50-m distance measuring tape and meter sticks, stakes, and flagging Information and data about the variables used to assess the functions of Mojave Playa depressional wetlands are collected at several different spatial scales. Information about landscape scale variables, such as land use, is collected using aerial photographs, maps, and field reconnaissance of the area surrounding the WAA. Subsequently, information about the WAA in general is collected during a walking reconnaissance of the WAA. Finally, detailed site-specific information is collected using sample plots and transects at a number of representative locations throughout the WAA. The exact number and location of these data collection points are dictated by the size and heterogeneity of the WAA. If the WAA is relatively small (i.e. less than 1,000 acres) and homogeneous with respect to the characteristics and processes that influence wetland function, then three or four sample points in representative locations are probably adequate to characterize the WAA. However, as the size and heterogeneity of the WAA increases, more sample plots are required to accurately represent the site. As in defining the WAA, there is an element of subjectivity and practical limitations in determining the number of sample locations for collecting site specific data. Training and experience will reduce the required time to the lower end of this range. Data and information relating to the variables in this model should be collected according to methods and guidelines provided below. Note: Field data forms have not yet been created, but will be once this model is tested. Highlighted sections represent changes from the PPR manual variables/methods, and may need to be further refined and adapted to playas.

Vegetation Variables

BUFFER CONTINUITY (VBUFFCONT)

Measure/Units: The continuity of the playa buffer expressed as a percent of the playa perimeter. Method: This variable represents the average continuity of intact vegetation around the perimeter of the playa. Buffer continuity is measured by determining the perimeter (meters) of the playa boundary that is contiguous with intact vegetation. Divide the total distance of vegetated perimeter by the total playa perimeter to obtain the “percent of playa boundary that has a vegetated edge”. This variable can be measured in the field or from appropriate scale aerial photography.

BUFFER WIDTH (VGRASSWIDTH)

Measure/Units: Average buffer width in meters perpendicular from the playa edge. Method: Assign 12 points placed at equal intervals around the perimeter of the playa boundary. It is recommended that the first point be located on the northern edge of the playa and that the

Y:\DMEC\Jobs\Lyons\Mojave\HGM\DesertPlayasHGM\DMEC_Mojave_Playas_HGM_Guidebook-20150413.doc DMEC – Preliminary Draft HGM Depressional Model for Mojave Desert Playa Lakes Project No. 12-0004 13 April 2015 DMEC Page 83 remaining points correspond to the hours of a clock. From each point, measure, perpendicular from the edge of the playa, the width of the adjacent naturally vegetated area from the edge of the playa out to a distance of 1,000 m. Due to the size of this buffer length, this will have to be measured using aerial photos and GIS. If crops, roads, solar arrays, or other features are present at the edge of the playa, then no buffer edge is present and a score of 0 is generated for that point. The average width of the buffers from the 12 points is then calculated.

VEGETATION COMPOSITION (VVEGCOMP)

Measure/Units: A modified species richness estimate measuring the degree of conservatism of the plants within and around the playa. Methods: A. Stratify the playa by dominant vegetation zones or plant community types, or both. B. For each zone or plant community, list all plant species. Accurate species identification is critical for this variable. Users who do not feel confident in identifying plant species should seek help with plant identification. C. Assign a coefficient of conservatism (C) value ranging from 0–10, representing a spectrum from invasive species to native species with the highest fidelity to natural areas, respectfully (Taft et al. 1997). Non-native species are given a 0 by default. Native species most successful in highly disturbed sites are also given a 0. Native species that are restricted to natural and undisturbed areas are given a value of 10. D. Find the sum of species (N). E. Calculate FQI as aggregated from all zones/plant communities. FQI =

Soil Variables

ESTIMATED SOIL RECHARGE POTENTIAL (VRECHARGE)

Measure/Units: The weighted areal score of various soil types within the wetland. Consult Table 12 in Section IV to generate a soil recharge rating for the WAA. Methods: This variable is determined by the areal coverage of soil types within the WAA. Soil units are derived from custom on-site mapping, soil surveys, or inferred from NWI mapping (in this order of preference). Where onsite mapping is not available, the weighted recharge potential for the WAA is then calculated using the categorical variable.

SEDIMENT DEPOSITION IN THE WETLAND (VSED)

Measure/Units: VSED is an assessment of alterations to the sediment regime (both increased and decreased sedimentation) as well as disturbances to the sediments on the playa surface. Methods: Assess the condition of sediment on the playa, the extent to which sediment is unable to reach the playa due to manmade feature and alterations to the catchment area and the presence of nonnative materials on the playa surface. Consult Table 13 in Section IV to assign a value for

VSED. A large playa will likely need to be assessed at multiple locations, and the index values averaged. Aerial photographs can be consulted to help determine locations and degree of disturbances to sedimentation.

SOIL QUALITY INDEX (VSQI)

Measure/Units: VSQI is the quality of the soil surface layer (to 30 cm depth) as measured by a unit-less summation index based upon the description of the soils structure, rupture resistance (consistence), pores, and human induced disturbance. This variable is evaluated both on the playa surface and in surrounding vegetated margins. Methods: Dig soil holes with a sharpshooter spade to a depth of at least 18 in. (45 cm). The number of holes necessary will be dependent on the size of the WAA. The soil profile should be described in accordance with delineation protocol and the appropriate documentation of characteristics necessary for computation of the SQI. The SQI is based upon a description of the upper 30 cm (12 in.) of the soil. With the use of a spade (sharpshooter) take a vertical slice of soil to a depth of 45 cm. Examine in good sunlight. Apply a moderate thud to the back of the spade to help show the natural structure cleavage of the soil. Examine the slice and note the size, shape, and grade (distinctness) of the soil peds in the profile to 30 cm. Note if the structure parts to medium and fine granular and the size of blocks and prisms. If the sampling site is underwater, soil probe (preferably one with a 1.5-in-diameter coring tube) could be used to obtain a sample; however, coarser structure and grade of structure may not be evident, so therefore this is not recommended. The SQI is based on observations of moist soil. Water may need to be applied if the soil is dry (normal condition in the desert). Examine horizontal surfaces for tubular pores. Count the number of very fine and fine pores in a square centimeter and the number of medium and coarse pores in a square decimeter and record. Also examine the pores to determine their continuity. Record the number of pores and their continuity. Note: roots can be used as a surrogate for pores. To determine rupture resistance in the upper 30 cm of the soil, take a soil ped (about 1-in. cube) that has not been compressed or deformed in getting the slice and crush it between your forefinger and thumb, noting the strength needed to deform or rupture the ped. Note this estimation as very friable (very slight force), friable (slight force), firm (moderate force), or very firm (strong force). Then record the most resistant measurement found within the upper 45 cm. (Hint: if tilled, this will probably be in a 10-cm-thick layer found just below the tillage zone, which may extend to 30 cm below the surface.) Examine the level of human induced disturbance evident in the immediate area surrounding the soil sample location and assign it an appropriate value based on Table 13 in Section IV of this guidebook. Average the assessed values for pores, pore continuity, structure, consistence and human disturbance for each soil sample. Then average these values to come up with the sub-index score for the Soil Quality Index variable.

Hydrogeomorphic Variables

WETLAND SURFACE OUTLET (VOUT)

Measure/Units: Elevation of playa outlets, natural or constructed, in relation to edge of the wetland and hydric soils. The volume of excavations present within the hydric soil footprint of the wetland. Methods: Elevations and distances will be determined by approved surveying methods and equipment or GIS software. Survey the elevation of the invert (the invert is the controlling elevation, or the point where overflow water exits the basin) of any surface outlets. This includes tile intakes. Survey the elevation of the outer edge of the wetland. Survey the elevation of a representative deepest part of the wetland. For most playas many of the below elements will not be applicable, as playas generally have no natural outlet and therefore do not have an invert elevation. Because of this playas will generally receive a 1.0. If a playa does have an outlet or overflow, the sub-index score will be a ratio between the existing outlet and proposed outlet. For example, the natural outlet is 2 m above the basin central elevation and the proposed project lowers that outlet by 0.25 m, 1.75/2 = 0.875. Record the following: A. Historic Invert elevation (if one is present) in relation to wetland maximum depth. B. Present (or constructed) Invert elevation. C. Elevation of the edge of the historic wetland (determined by soil or plants and soils). D. Elevation of a representative deepest portion of the wetland. E. Calculate the difference between: C and A; B and D; A and D; and C and B. If evaluating excavation or fill, enter percent volume of the excavation/fill versus wetland (ex. 25% = 25), otherwise enter 0. F. Ratio of the constructed elevation to the natural outlet elevation:

The variable subindex score for VOUT is then calculated by averaging the ratios from E and F and the excavation or fill value. (Adapted from Gilbert et al. 2006) Note: This is based on the field form from the PPR manual. We can probably simplify this by just making this variable calculated as the difference between the proposed/constructed outlet and the deepest point of the playa.

SUBSURFACE DRAINAGE (VSUBOUT)

Measure/Units: Amount of wells and groundwater pumping in the playa and immediate area. Methods: Use Table 15 in Section IV of this guidebook to assign a sub-index score to the playa being assessed.

WETLAND SOURCE AREA (VSOURCE)

Measure/Units: The percent change (increase, decrease, or both) in the catchment area surrounding a wetland due to alterations such as surface drainage, diversions, roads, land leveling, etc. This variable is scored as a condition.

Method: These measurements can be taken at any time during the assessment. For efficiency they could be done in the office (using aerial photos and GIS) and checked in the field. Review aerial photography, USGS maps, soil maps, project maps for developments such as solar plants, and NWI maps. Note and document any surface or sub-surface alterations. From the USGS topographic map or NHD dataset delineate the original catchment area, or use an aerial photo in the field and sketch the catchment. Record the following:  Type and effect of surface alterations.  Percent of historic catchment area still contributing runoff to the wetland.  Additions of water to the wetland from other sources.  Change in wetland regime class—Yes or No? If the office review can determine that the catchment area has been altered, determine the amount of catchment area that has been structurally altered to prevent flow to the wetland. In most cases, the index score is determined based on percent of catchment from which water is prevented from reaching the wetland. Also, note areas added to the catchment due to, for example, road and drainage ditches, fish hatcheries (in the Mojave River watershed), wastewater, land leveling, irrigation, etc. In the field, verify all alterations noted during the offsite review and document any additional alteration found during the field investigations. Consult Table 15 in Section IV to assign a sub-index score to the wetland.

EDGE INDEX (VEDGE)

Measure/Units: The variable is a measure of the degree of shoreline irregularity expressed as ratio of the perimeter of the WAA as compared to the perimeter of a circle of area equal to the WAA. The closer this ratio is to 1, the more circular the wetland. A larger ratio means the shoreline is more crenellated. Method: This variable can be measured in the field or from appropriate scale aerial photography. Any offsite measurements should be verified in the field. Perimeter measurements are available from previous calculation of VBUFFCONT. The perimeter and WAA area are inserted in the equation below for calculation of the index. The Edge Index is calculated as:

VEDGE =

RATIO OF CATCHMENT AREA TO WETLAND AREA (VCATCHWET)

Measure/Units: The area of the catchment in relation to the size of the wetland. This is expressed as a ratio, such as 4:1. Catchment area has been previously determined for VSOURCE. Area of the assessment site is part of the basic site description. Method: Measure the size of the historic catchment, including the wetland. Measure the size of the existing wetland. This variable can be measured in the field or from appropriate scale aerial photography.

Land Use and Landscape Variables

LAND USE WITHIN THE CATCHMENT (VUPUSE)

Measure/Units: The weighted average score of various land uses as related to runoff potential within the catchment of the wetland. Land use determinations are made from the outer edge of the wetland to the catchment boundary. Runoff curve numbers from and the areas of each land use–land cover type are required. Method: A combination of offsite and onsite assessment methodology can be used for this variable. Review aerial photography and the land use history for the site. Use GIS to determine the area of the various land use categories. Then, multiply the area in each category by the curve number found on Table 16 in Section IV, and add them all together for a total, and divide by present-day catchment area. Use this weighted average score to derive the sub-index score.

WETLAND PROXIMITY IN THE LANDSCAPE ASSESSMENT AREA (VWETPROX)

Measure/Units: The mean distance of the assessment playa with the nearest playas (measured edge to edge). Method: Determine if the playa being assessed is a single playa, or if it is associated with nearby playas. Aerial photographs or field notes can be used to determine if the playa being assessed is part of a great drainage system involving other playas (i.e. the playa drains into other playas, or other playas drain into it). A sub-index score for this variable can be assessed by finding the distance between two playas, or in the case of more than two playas as part of a network, the average distance between them. If this distance is over 100 miles, the sub-index score will automatically be assigned as 0.0. Otherwise the distance will be subtracted from 100 and then divided by 100. For example, if two playas are 11.6 miles apart the sub-index score would be calculated as follows: (100- 11.6)/100= .884. The distances in miles between all of the reference playas assessed by DMEC are provided in Appendix A.

SUM OF THE LENGTH OF ROADS AND DITCHES IN THE LANDSCAPE ASSESSMENT AREA (VHABFRAG)

Measure/Units: This variable is the sum of the linear extent of roads and drainage features (km) within a playa complex. It is used to account for fragmentation within the playa complex. Method: If the playas being assessed are determined to be in close enough proximity to be part of a wetland complex, the Landscape Assessment Area (LAA) for this variable will be the catchment basin(s) associated with the playas. Measure the length of all roads and Cowardin et al. (1979) linear attributes from this area. Linear attributes included from NWI mapping are the “d” or “x” modifiers. Similar information can be derived from aerial photography and USGS digital ortho-quarter quads. It is recommended GIS technology be used for this variable.

DATA ANALYSIS AND ENTRY

Data Entry

Follow the assessment protocols given above to complete a wetland functional assessment using this Guidebook. It is critical that all data entries are recorded on the appropriate field forms. This will greatly reduce confusion about what data need to be collected and will help the user from accidentally skipping over necessary field data while visiting the WAA. Much of the initial site characterization and map data will come from preexisting databases, Internet sources (e.g. USGS, NRCS), or office source materials (e.g. NWI maps, county soil survey maps).

Data Analysis

The primary objective of the HGM Approach to the Functional Assessment of Wetlands is the determination of Functional Capacity Indices (FCI), which when combined with area produces a Functional Capacity Unit (FCU), which provides a basis for determining impacts and mitigation.

Manual Determination of FCI

Follow the above protocols to calculate a sub-index score for each variable. The variable sub- index scores are employed in the six Functional Capacity Index algorithms discussed and explained in Section IV of this Guidebook. The Guidebook user can then determine, by hand calculation, the Functional Capacity Indices (FCI) of each function.

Spreadsheet Determination of FCI

The data sheets are designed to assist the user enter the raw data collected from each site. The regression equations needed to calculate the variable sub-index for each wetland function are already entered into this spreadsheet. The presence of these equations is designated by gray blocks within the spreadsheet (spreadsheet to be developed). All other blocks indicate where the user is expected to enter their data. Instructions for each function are included in the spreadsheet and follow the format of the data sheets included in Appendix B. Each category, along with the corresponding variables, is located in one of worksheets. These worksheets are labeled by category. The FCIs are also entered in the spreadsheet and can be found in the worksheet labeled ‘FCI’. After each variable sub-index has been calculated using the raw data entered by the user, the FCIs will be automatically computed.

Application of the Results of the Assessment

Once the assessment and analysis phases are complete, the results can be used to compare the same wetland assessment area at different points in time, comparing different wetland assessment areas at the same point in time, comparing different alternatives to a project, or comparing different hydrogeomorphic classes or subclasses as per Smith et al. (1995).

SECTION VI. ACKNOWLEDGEMENTS

This report was written by David Magney, Evan Lashly, Joe Broberg, David Torfeh, and Jared Logan. Mr. Magney and Mr. Lashly conducted the field surveys in support of this model, particularly in gathering reference site information. The report was proofread and edited by Vickie Peters and Mr. Magney. Original graphics were created by Ms. Peters from DMEC field data and additional authoritative GIS datasets; other graphics were borrowed from the original sources as cited in the report. The FCI spreadsheet was developed by Mr. Magney and Mr. Logan. Mr. Magney managed the development of this model guidebook.

SECTION VII. CITATIONS

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Personal Communications

Chavez, Anthony, Resource Specialist, Bureau of Land Management, Barstow, California. Telephone conversation on 29 April 2014 with Richard Lyons, regarding conditions of East Cronese Lake and the bank site.

APPENDICES

APPENDIX A APPENDIX B APPENDIX C

APPENDIX A – DISTANCE IN MILES BETWEEN REFERENCE PLAYAS

Distance in Miles Between HGM Reference Playas

Reference Playa South El Green West East Searles Harper Rabbit Lucerne Troy Broadwell Soda Silver Dry Silurian Ivanpah Bristol Lake Panamint Mirage Rock Cronese Cronese South Panamint 0 18.2 63.3 92.4 103.7 100.7 85.4 96.3 74.1 75.3 77.9 85.3 75.8 69.9 66.9 107.3 135.1

Searles 18.2 0 46.8 74.3 86.7 83.5 71.5 85.7 63.5 65.9 68.4 77.4 70.1 65.1 63.9 106.7 123.7

Harper 63.3 46.8 0 31.9 42.9 41.5 42.9 63.7 48.4 54.7 57.2 69.2 69.8 68.7 71.8 112.5 98.7

El Mirage 92.4 74.3 31.9 0 35.9 38.7 60.9 82.3 72.7 80.5 81.9 93.8 97.1 97.7 101.5 139.8 110.9

Rabbit 103.7 86.7 42.9 35.9 0 5.5 36.8 54.8 52.9 61.7 63.1 72.5 80.2 82.7 88.5 118.9 76.8

Lucerne 100.7 83.5 41.5 38.7 5.5 0 31.7 49.7 49.9 56.4 57.8 67.4 75.2 77.8 83.2 113.9 73.1

Troy 85.4 71.5 42.9 60.9 36.8 31.7 0 21.7 18.8 25.4 26.1 35.8 43.4 46.6 53.1 82.3 56.8

Broadwell 96.3 85.7 63.7 82.3 54.8 49.7 21.7 0 21.8 22.1 20.3 22.6 34.3 40.3 47.2 66.3 39.4

Green Rock 74.1 63.5 48.4 72.7 52.9 49.9 18.8 21.8 0 7.5 9.7 21.5 25.5 27.9 33.9 66.9 60.6

West Cronese 75.3 65.9 54.7 80.5 61.7 56.4 25.4 22.1 7.5 0 2.7 14.2 18.8 21.3 27.7 59.3 59.1

East Cronese 77.9 68.4 57.2 81.9 63.1 57.8 26.1 20.3 9.7 2.7 0 11.9 17.6 21.3 28.1 57.9 57.1

Soda 85.3 77.4 69.2 93.8 72.5 67.4 35.8 22.6 21.5 14.2 11.9 0 13.3 19.2 25.7 47.1 52.9

Silver 75.8 70.1 69.8 97.1 80.2 75.2 43.4 34.3 25.5 18.8 17.6 13.3 0 6.6 12.9 44.7 65.7

Dry 69.9 65.1 68.7 97.7 82.7 77.8 46.6 40.3 27.9 21.3 21.3 19.2 6.6 0 6.9 59.4 71.2

Silurian 66.9 63.9 71.8 101.5 88.5 83.2 53.1 47.2 33.9 27.7 28.1 25.7 12.9 6.9 0 43.7 78.1

Ivanpah 107.3 106.7 112.5 139.8 118.9 113.9 82.3 66.3 66.9 59.3 57.9 47.1 44.7 59.4 43.7 0 75.9

Bristol 135.1 123.7 98.7 110.9 76.8 73.1 56.8 39.4 60.6 59.1 57.1 52.9 65.7 71.2 78.1 75.9 0

APPENDIX B – FCI SCORE SPREADSHEETS AND PLAYA INDEX SCORES

This section includes the FCI score spreadsheet and analysis for each reference playa. Explanations are given below for instances where the assessment methodology differed from that detailed above in Section IV and Section V, such as cases where thorough field surveys were not possible and aerial photography was used instead.

FCI Spreadsheet

HGM Playas Mojave Date: Project Name: ______City: Project Site: ______County: ______Assessor/Observer: ______

Functions Variable 1 2 3 4 5 6 6a

Vbuffcont Contiguous natural vegetation cover

Vbuffwidth Natural Vegetation buffer width Vegetation Vvegcomp composition

Vrecharge Soil recharge potential

Vsed Sediment deposition in wetland

Vsqi Soil quality index

Vout Wetland surface outlet

Vsubout Subsurface drainage

Vsource Reduction or increase in catchment area

Vedge Modified shoreline irregularity index

Vcatchwet Wetland catchment area

Vupuse Land use within catcment

Vwetprox Nearest wetland proximity

Index Function Index Formula

1 - (MINVoutVsubout)*(Vsed+(Vsource+Vupuse)/2)/2 2 - (MINVoutVsubout)*[(Vrecharge+Vedge+Vcatchment)/3]+[(Vsqi+Vsed+Vupuse)/3) 3 - Vsed*((Vupuse+Vbuffcont+Vbuffwidth)/3)+(Vvegcomp+(MIN (Vout,Vsubout))/2)/2 4 - (MIN Vout,Vsubout)*((Vbuffcont+Vbuffwidth)/2+(Vsource+Vupuse+Vsed)/3+Vegcomp)/3 5 - (MIN Vout,Vsubout)*((Vupuse+Vbuffcont+Vbuffwidth)/3)+((Vsqi+Vsed)/2)+Vegcomp)/3 6 - (MIN Vout,Vsubout)*((Vupuse+Vsed)/2)+(Vbuffcont+Vbuffwidth+Vedge)/3) +Vvegcomp)/3 7 - (MIN Vout,Vsubout)*((Vupuse+Vsed)/2)+(Vbuffcont+Vbuffwidth+Vedge+Vwetprox)/4) +Vvegcomp)/3

APPENDIX C – RANGE OF WETLAND VALUES

(under development)

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