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Groundwater Inventory, Monitoring and Assessment Technical Guide - DRAFT

Contents

3.0 Groundwater and Groundwater-Dependent Ecosystems Inventory.............................................1

3.1 Introduction to Groundwater Resource Inventory.........................................................................1

3.2 Groundwater Inventory Methods..................................................................................................1

3.2.1 Types of Groundwater Resource Inventories.........................................................................2

3.3 Groundwater-Dependent Ecosystems Inventory...........................................................................2

3.3.1 Groundwater-Dependent Ecosystems....................................................................................3

3.3.2 Determining Wetland Groundwater Dependency..................................................................4

3.3.3 Selecting the Appropriate GDE Inventory Field Guide for Data Collection.............................6

3.3.4 Planning and Design.............................................................................................................11

3.3.5 Data Management and Reporting........................................................................................17

References.........................................................................................................................................23

Appendix 3-A – Groundwater-Dependent Ecosystem Types, Definitions and Classification Methods. .24

Appendix 3-B – Inventory Sampling Design Examples.........................................................................38

3-B.1 Stratified Random Sampling of Known Springs........................................................................38

3-B.2 Grid-Based Stratified Random Sampling Design of Potential Peatlands...................................48

3-B.3 Complete Project Area Sampling Approach.............................................................................54

APPENDIX 3-C – SAMPLE COST ESTIMATION WORKSHEETS................................................................57

3-C.1: Sample Level I Cost Estimation Worksheet.................................................................................57

3-C.2: Sample Level II Cost Estimation Worksheet................................................................................58

APPENDIX 3-D – SAMPLE REPORTS.....................................................................................................59

3-D.1: Level I Site Report Example – Wallowa-Whitman National Forest..............................................60

3-D.2: Level II Site Report Example – Spring Mountains NRA................................................................62

3-D.3: Level II Area-wide Report Example – Spring Mountains NRA......................................................64

3-D.4: Case Study – Montanore Mine GDE Inventory & Monitoring Report.........................................75

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Section 3 – Groundwater and Groundwater-Dependent Ecosystem Inventory (v4.4) 12/21/13 DRAFT


3.0 Groundwater and Groundwater-Dependent Ecosystems Inventory

Groundwater inventory is the identification and characterization of groundwater resources. This section provides guidance on methods used to understand and quantify the location, distribution, and nature of groundwater resources. This section includes the following subsections:

Section 3.1 – Introduction to Groundwater Resource Inventory, describes the general concepts involved in groundwater resource inventories on National Forest System (NFS) lands.

Section 3.2 – Groundwater Inventory Methods, describes approaches for conducting groundwater inventories.

Section 3.3 – Groundwater-Dependent Ecosystems Inventory Methods, focuses on how to conduct Groundwater-Dependent Ecosystems (GDEs) inventories (i.e., ecosystems dependent upon groundwater), data management and analysis, and report development.

Appendices to this section address GDE definitions and classification methods; provide sampling design and cost estimation examples; and display different examples of reports ranging from individual sites to larger areas of interest.

3.1 Introduction to Groundwater Resource Inventory

Groundwater resources include (a) aquifers and associated groundwater flow systems as well as (b) the biological resources supported by groundwater. For aquifers and their associated groundwater flow systems, most of what is considered inventory is actually,

Geologic mapping (distribution of sediments and lithologies, characterization of secondary features – primarily fractures, dissolution features, alteration features, and chemical precipitation/cementation),

Basic hydrologic characterization (rates and distribution of precipitation and evapotranspiration, stream rating curves, and temporal responsiveness of hydrologic system), and

Evaluation of existing well and borehole information.

These information sets can be augmented by remotely sensed data to help identify features and constrain processes (see section 2.5).

Inventory of groundwater-dependent ecosystems requires additional information on biologic resources that is collected using the methods described in the Forest Service GDE Inventory Field Guides. Use of these Field Guides is discussed in greater detail in this section.

3.2 Groundwater Inventory Methods

Land management agencies use groundwater inventory data and their interpretation to identify the location and extent of groundwater flow systems, characterize the quantity of water contained and the quality of the water in an aquifer, and to identify recharge and discharge areas (both natural and artificial). The need for groundwater inventories of various kinds is found in many Federal, State, and local water-management programs (e.g., pesticide management plans; locating sustainable sources of

Section 3 – Groundwater and Groundwater-Dependent Ecosystem Inventory (v4.4) 12/21/13 DRAFT 1


drinking water or sites for underground injection of waste; and mitigating impacts to groundwater from mining operations, oil and gas development, and confined animal feeding operations.).

3.2.1 Types of Groundwater Resource Inventories

Potential inventories of groundwater-related information relevant to land management include: GDEs Existing wells and spring diversions Orphaned wells and boreholes Groundwater withdrawal quantities, their timing, and the source aquifer Location and extent of groundwater flow systems Recharge and discharge areas Exisiting hydrologic monitoring sites (wells, springs, stream gages, rain gages, etc.)

3.3 Groundwater-Dependent Ecosystems Inventory

Groundwater-Dependent Ecosystems include those ecosystems supported and sustained by groundwater. GDE inventory protocols focus on a subset of GDEs, specifically springs and groundwater- dependent wetlands (such as peatlands or fens) as highlighted in figure 3-1. Although this protocol is not intended specifically for other types of GDEs (lakes and, ponds, streams and hyporheic zones, riparian areas, phreatophytic systems, or marine systems), parts of this protocol could be used to inventory or monitor these systems.

Detailed inventory protocols for groundwater-dependent ecosystems have been developed for two “Levels” which correspond to different sets of agency business needs. They are designed to meet common business needs across the National Forest System (NFS) and describe a nationally consistent approach to meeting those needs. Field guides are published separately from this technical guide to provide documents suitable for use in conducting field inventory work. Both can be found online at:

Groundwater Dependent Ecosystems Level I Inventory Field Guide at: http://www.fs.fed.us/geology/GDE_Level_I_FG_final_March2012_rev1_s.pdf and a booklet-sized version at: http://www.fs.fed.us/geology/GDE_Level_I_FG_final_March2012_rev1_printing.pdf

Groundwater Dependent Ecosystems Level II Inventory Field Guide at: http://www.fs.fed.us/geology/GDE_Level_II_FG_final_March2012.pdf.

The Forest Service Technical Note on Measurement of Discharge at Springs and Wetlands is included as an appendix to both of these field guides.

Activities addressed in specific subsections include:

How to determine whether the protocols described are appropriate for use for inventory of different sites and selecting the appropriate level of inventory

Development of an inventory plan, including framing purpose and management needs, sampling design, skills needed, cost estimation, and reporting

Considerations specific to different inventory levels and options for meeting local business needs


http://www.fs.fed.us/geology/GDE_Level_II_FG_final_March2012.pdf

http://www.fs.fed.us/geology/GDE_Level_I_FG_final_March2012_rev1_printing.pdf

http://www.fs.fed.us/geology/GDE_Level_I_FG_final_March2012_rev1_s.pdf


Data management, analysis, and reporting tools

This section does not discuss development of more intensive inventory procedures (Level III), which may be required in managing and administering specific projects or activities, or how to develop a monitoring program plan, which is addressed in Section 5. Procedures described in the Level II Inventory Field Guide may provide a suitable foundation for data collection for these purposes.

3.3.1 Groundwater-Dependent Ecosystems

Where groundwater reaches the surface there is generally an assemblage of plants and animals that are supported by groundwater, hence the term groundwater-dependent ecosystems. In some cases groundwater emerges at a point, usually called a spring. Springs are always GDEs. In the case of wetlands supported by groundwater there is generally not a single point where the groundwater flows or emerges at the surface. In some wetlands there are springs that emerge within the wetland or there is a complex of wetlands and springs. In many cases groundwater-dependent wetlands, such as fens, are simply springs covered by unconsolidated material (glacial deposits, pumice, colluvium) that becomes saturated to the surface. Because there is an indistinct boundary between springs and wetlands dependent on groundwater, a single protocol was developed for these systems. Groundwater emerging at the ground surface is the common thread that links these features and their associated ecosystems.

Figure 3-1–Groundwater-dependent ecosystem types applicable to GDE Inventory Field Guides.



A detailed discussion of groundwater-dependent ecosystem types, definitions, and classification systems is provided in Appendix 3-A.

3.3.2 Determining Wetland Groundwater Dependency

Some wetlands are not supported by groundwater but are formed from water that originates exclusively from precipitation. Such wetlands are called “ombrogenous” hydrological systems (National Wetlands Working Group 1997). The meaning of the term ombrogenous is “rain fed” according to Mitsch and Gosselink (2007). Ombrogenous wetlands are not the focus of this protocol, although most components of the protocol can be used to evaluate them.

The type of wetlands this protocol is intended for are those supported by groundwater which has come in contact with mineral soils and bedrock. Such wetlands are called “minerogenous” hydrological systems (National Wetlands Working Group 1997). These wetland systems are normally positioned lower in the landscape than adjacent terrain, so water and mineral elements are introduced by groundwater.

Minerogenous hydrological systems have a strong linkage with the regional groundwater system and the physical and chemical characteristics of the geological environment. They are less restricted by local climatic conditions because the groundwater source is generally sufficient to maintain soil saturation and therefore wetland processes during the growing season. By contrast, ombrogenous hydrological systems are not dependent on groundwater, and climatic conditions have a greater control on their distribution. In arid and semi-arid regions most wetlands are supported by groundwater. In humid and colder regions groundwater dependence becomes more difficult to determine. Nevertheless, many wetlands in humid regions are highly groundwater dependent.

It is not always easy to verify a wetland’s dependence on groundwater. One tool to help determine groundwater dependence is a publication by The Nature Conservancy (Brown et al. 2007) featuring decision trees for determining groundwater dependence, such as the one for wetlands in table 3-1.

Table 3-1–Decision tree for identifying groundwater-dependent wetlands.

1. Is the wetland seasonal? Yes – Low likelihood of groundwater dependenceNo – Go to next question

2. Does the wetland occur in one of these landscape settings: (a) slope break; (b) intersection of a confined aquifer with a slope; (c) stratigraphic change; or (d) along a fault?

Yes – High likelihood of groundwater dependenceNo – Go to next question

3. Is the wetland associated with a spring or seep?


4. Does the wetland have signs of surface inflow?

No – High likelihood of groundwater dependenceYes – Go to next question

5. Are the wetland soils organic, muck or peat?


6. Is the wetland saturated even after surface inputs become dry and extended periods with no precipitation?

Yes – Are the wetland soils clay, hardpan, or impermeable?No – High likelihood of groundwater dependenceYes – Low likelihood of groundwater dependence.

No – Low likelihood of groundwater dependence



GDE Types to Be Inventoried Using the GDE Inventory Field Guides

As mentioned above, the GDE Inventory Field Guides were designed to address a specific subset of GDEs - springs and groundwater-dependent wetlands. Table 3-2 is based on the information included in Appendix 3-A, and describes characteristics of GDEs covered by the GDE Level I and Level II Inventory Field Guides. The primary basis for determining which systems to include in the GDE protocol is hydrogeology, specifically water source.

Table 3-2–GDE types addressed by the Inventory Field Guides and their characteristics.

Characteristics Springs Peatlands Including Fens(groundwater dependent)

Other wetlands(groundwater dependent)

Hydrology Completely groundwater dependent

Minerotrophic; always groundwater dependent

Minerotrophic; depend on groundwater, precipitation and sometimes stream inflow

Water Table Position

At ground surface or, for artesian, a piezometric surface above the ground surface

At or slightly below surface, or piezometric surface above the ground

Above or below surface; can fluctuate dramatically; can have periodic standing water

Soils and Peat Depths

Mostly mineral soils; sometimes a small accumulation of peat

Accumulation of peat up to several meters; little or no mineral soil within plant-rooting zone for fens

Relatively little or no peat or muck accumulation; sometimes wood-rich peat

Redox Conditions1

Oxic to anoxic depending on geochemistry and residence time of water in aquifer

Anoxic slightly below the surface, leading to the accumulation of peat or muck

Temporary soil anoxia during times of high water table or standing water

Water movement within GDE

Standing or flowing water Slow to imperceptible flow on surface

Periodic standing or flowing water

Water Chemistry Highly variable; from acidic to basic, temperatures vary, can be thermal, can be saline

Minerotrophic, acidic (poor fens) to basic (rich fens), can be iron rich or calcareous

Highly variable, from acidic to basic

Vegetation Graminoids, forbs, shrubs, bryophytes, and trees; variable amount of wetland vegetation

Bryophytes, graminoids , and low shrubs; lichens, sometimes trees; always wetland vegetation

Tall woody plants and forbs (swamps) or emergent graminoids and floating aquatic macrophytes (marshes); mostly wetland vegetation

1 Redox (short for REDuction-OXidation) conditions describe a key chemical characteristic in hydrologic systems that controls the availability of many elements and the propensity of the system to support the accumulation of organic matter, such as peat and muck. At the ground surface, redox conditions are often controlled by the availability of oxygen.

GDE types that would be difficult to survey using the GDE Inventory Field Guides include geysers, gushets, and hanging gardens although there are alternative systems for conducting these inventories (see Springer et al. 2008).



GDE Types Not Intended for These Inventory Field Guides

The GDE Inventory Field Guides were not designed for underground sampling (e.g., caves), although it would be appropriate to use for sampling the surface outflow from caves. Springs that include large open water areas (large exposure springs and large limnocrenes) could involve substantial safety concerns, and would be difficult to sample comprehensively with this protocol; they would require the use of limnological sampling techniques.

Settings where these field guides have not been tested include tropical, subtropical, arctic, subarctic, tundra, and permafrost areas, which were beyond the scope of the GDE Inventory Field Guide development effort, although the authors do not know why these field guides would not work in these regions.

These GDE Inventory Field Guides are not intended for evaluating:

Groundwater-dependent lakes Base-flow streams and associated riparian areas

Some wetland systems that are similar to some GDEs, but are not dependent on groundwater may be inventoried using the methods described in the GDE Inventory Field Guides although they were not designed for these features. These features include:

Bogs Insurgences and sinkholes in karst areas Pocosins, a type of bog in the southeastern United States (described in Richardson 2003)

3.3.3 Selecting the Appropriate GDE Inventory Field Guide for Data Collection

Selecting which GDE (Level I or II) Inventory Field Guide to use for data collection is determined by the requirements and management questions associated with a particular effort or project. The following subsection provides a description of the agency business requirements addressed by the Inventory Level I and II Field Guides and a description of their purposes and uses.

To provide flexibility and ensure appropriate use of the resulting protocols, the relationship between business requirements (why data are collected) and inventory and monitoring protocols (how data are collected) must be clearly understood. The relationship between business requirements and GDE inventory and monitoring protocol (intensity) levels is illustrated in figure 3-2.



Figure 3-2–General relationships between GDE business requirements and inventory level.

The number of management questions considered and the level of detail needed to address these questions increases with each inventory intensity level. Each of the boxes in figure 3-2 represents a grouping of management requirements. The level of detail and resolution for data elements needed to support business requirements increases from Level I to Level III. For example, the types of information collected in Level I for vegetation would be more general than those collected for Level III. The management requirements and questions associated with each inventory intensity level are described in detail in the Business Requirements Analysis for Groundwater-Dependent Ecosystems Inventory and Monitoring Protocols (USDA Forest Service 2010).

Relationships Between Business Requirements and Inventory Levels

The relationship between the purposes for conducting an inventory (business requirements) and data collected defines the level of inventory intensity and corresponding level of agency decision making. The amount of effort or intensity of inventory and monitoring is categorized into three levels that correspond to different groups of business needs that are linked to these decision levels. Table 3-3 describes the level of effort and focus of different intensity levels.



Table 3-3–Descriptions of GDE inventory and monitoring intensity levels.

Intensity Level Description

Level I Conducted to qualitatively characterize GDEs within an administrative unit. GDE location and extent are spatially referenced. Serves as the basis for estimating which GDEs, what types of GDEs, or how many GDEs may be affected by proposed actions or activities.

Level II Serves as the foundation for identification of project design measures, analysis of project or activity effects, and determination of mitigation measures. Describes major attributes including hydrogeologic setting, habitats, aquatic and wetland flora and fauna, and disturbances affecting GDEs. Can be used to determine ecological significance of the GDE and associated resources. May be used as a foundation for monitoring design.

Level III Usually conducted in relation to a major activity or set of activities affecting specific GDEs and their characteristics. Compiles highly quantitative information that describes spatial and temporal variation in physiochemical characteristics of GDEs. Often used in the administration of projects or activities and, therefore, is highly site specific.

Because of the variety of situations encountered on NFS lands, it is essential to develop a field guide package consisting of integrated components that can be matched to a local unit’s business requirements and needs. The use of different inventory and monitoring “intensity levels,” described above, supports this functionality.

Purpose and Use of GDE Inventory Field Guides

The GDE Level I Inventory Field Guide describes methods suitable for identifying, locating, and sampling GDEs, and describes where and how the spatial and tabular data collected for each location should be stored. All data attributes included in the Level I protocol are included in Level II. The Level I protocol is intended to document the location, size and basic characteristics of a site, during a relatively short site visit of about 2 hours.

Level I information provides managers with a basic understanding of how GDEs are distributed on the landscape, what types of GDE sites are present, their basic condition, and potential conservation and restoration needs. In general this information is used in land and resource management planning, watershed condition assessments, identification of GDEs that may be affected by proposed actions, or in designing an overall GDE management and restoration program. Specific uses of the GDE Level I Inventory Field Guide include:

Characterizing and locating GDE sites within an area of interest. Cataloging the types of GDEs in an area. Documenting the general condition of GDEs in a planning or analysis area.

The GDE Level II Inventory Field Guide describes protocols for collecting data typically used in project planning and analysis. Data collected can be used as a basis for establishing appropriate mitigation or restoration of GDE sites.



A Level II inventory includes all of the components of Level I, some with greater detail, as well as a broader array of data attributes. Procedures described in the Level II Field Guide result in more comprehensive characterization of the vegetation, biology, hydrology, geology, and soils of the GDE sites. Level II inventories will typically require 4–8 hours at the field site.

Level II inventory data will allow users to describe a site and its general condition, make comparisons among sites of a certain type within a planning or analysis area, and can provide, with the appropriate sampling design, the ability to monitor major changes over time. These data may provide useful information about the presence or distribution of plant and animal species, including invasive species and rare biota abundant enough to be detected by these protocols. Species distribution information is a secondary benefit of this protocol. If inventory or monitoring of specific species or communities is the goal then more detailed and/or targeted methods should be used, for example Threatened, Endangered, and Sensitive Species (TES) Survey or Cover Frequency protocols from another NRM application.

In some instances, the procedures described in the GDE Level II Inventory Field Guide may be used as a foundation for monitoring design. If the objective is to monitor specific conditions of a GDE then users will need to develop a site-specific (Level III) monitoring protocol that targets specific attributes and methods for monitoring.

Specific uses of the GDE Level II Inventory Field Guide include:

Characterizing an individual GDE or, after utilizing an appropriate site selection or screening process, characterizing GDEs within an area of interest.

Collecting baseline information about a specific GDE or a defined group of GDE sites. Evaluating and selecting GDE sites for restoration or rehabilitation. Evaluating and selecting GDE sites for water supply development. When used as a framework for monitoring design or observing the general conditions of an

individual site or group of sites within an area of interest over time.

Business Requirements Addressed

A detailed review of agency business requirements used to frame the development of the GDE Level I and Level II Inventory Field Guides is documented in the Business Requirements Analysis for Groundwater-Dependent Ecosystems Inventory and Monitoring Protocols (USDA Forest Service 2010; http://www.fs.fed.us/geology/groundwater.html).

Management requirements include laws, regulations, and policy. Those applicable to GDE inventory and monitoring can be summarized into the following general policy statements:

Support an affirmative agency obligation to protect, conserve, and restore waters, watersheds, listed wildlife and plant species and their habitats, and to conserve biological diversity.

Assess and disclose environmental effects associated with ongoing and proposed actions and activities, including use of monitoring data to identify needed adjustments to management practices.

Use the best available information and science to support agency decision making. Collect and maintain resource data with known data standards and data quality for use in agency decision making processes. Provide for information security.


http://www.fs.fed.us/geology/groundwater.html


Data needed to address these management requirements vary by the type of agency decision being made. Management questions addressed by the Level I and Level II Inventory Field Guides generally include land management planning (mid-scale or hydrogeologic setting) or assessment of project or activity effects (landscape - local scale or aquifer – aquifer site scales). Data addressing these business requirements are used to (a) characterize and assess the function of a GDE feature and (b) assess and evaluate a feature’s relationship to and support of ecological systems within an analysis or planning area.

Four broad groups of management questions stratified by inventory level were identified in the Business Requirements Analysis for Groundwater-Dependent Ecosystems Inventory and Monitoring Protocols USDA Forest Service 2010):

Location and Description –Management questions about location of and basic information about a GDE feature are included in both inventory levels.

Ecological Context – The ecological context of a GDE site influences water quality and quantity as well as species diversity associated with the feature. Numerous management requirements establish the need to protect, conserve and, when appropriate, restore ecological conditions necessary to sustain biological diversity, threatened and endangered species habitat, and water quality and flows. Management questions vary significantly between inventory levels with respect to the resolution and accuracy of data needed.

Hydrogeologic Setting – Understanding the hydrogeologic setting and relationship of individual GDE sites to the groundwater system required for managers to protect and conserve biological diversity and threatened and endangered species, to provide clean water, and to sustain ecological systems and services provided by GDEs and associated groundwater. The level of data resolution and accuracy varies between inventory levels because of the types of decisions being addressed. The hydrogeologic setting is defined by factors that control the flows of surface and groundwater from watersheds to wetlands. These factors include: (a) topography and slope in the watershed, (b) composition and stratigraphy of geological materials in the watershed and underlying the wetland, (c) depth of hydric soils in the wetland, and (d) position of the wetland in the landscape with respect to surface- and groundwater flow systems (Winter 1988, Komor 1994). Together these factors determine the relative importance of different water inputs and outputs in a wetland’s water budget (Brinson 1993, Carter 1996, Godwin et al. 2002). As a consequence, they play the major role in controlling the extent and seasonal patterns in water table fluctuations, direction and velocity of surface water flows, and groundwater fluxes (Winter et al. 1998). They also exert a strong influence on wetland water chemistry including pH, redox, and sources of nutrients and other solutes. These in turn drive organic matter production and decomposition, which control plant and microbial community composition and, thus, locations, abundance, and diversity of other ecosystem components.

Natural and Anthropogenic Disturbances – Natural and anthropogenic disturbances affect a GDE’s ability to support ecological functions and individual species. The Forest Service has an obligation to protect, conserve, and restore resources, including GDEs, which provide for and sustain ecological systems and habitat for obligate species. The disturbance and management indicator questions embedded in the Level I and II protocols are the same, but the additional data collected in Level II can add more detail and support when assessing these factors influencing GDEs.



3.3.4 Planning and Design

GDE Level I and II Inventory Field Guides describe specific procedures for field data collection; however, there are a number of important activities that precede and follow data collection. In fact, only about half the expected total cost for any particular inventory effort will come from field data collection. The remainder comes from setting goals, establishing an appropriate inventory design, data mining, training, quality assurance and quality control (QA/QC), administration, data entry, and, most importantly, analysis and evaluation of data collected. In particular, “data mining” prior to field activities can result in significant cost savings associated with data collection and assist in the logistics for surveys including equipment needs, access routes and methods, and skills needed.

The recommended approach for implementation of the Field Guides includes the following sequence of activities, which are discussed in detail in the following subsections:

1) Inventory Design and Planninga. Setting inventory objectives and identifying management questionsb. Determining the planning or analysis areac. Evaluating the use of existing data and coordinating with other inventory programsd. Developing a sampling design and inventory procedures, including scheduling and

selection of sites and Quality Assurance and Quality Control procedurese. Determining staffing needs and cost estimation

2) Logisticsa. Planning logistics and site access, including travel and access restrictionsb. Establishing a safety planc. Procuring and maintaining equipment, including personal protective equipmentd. Providing or verifying training/licensing

3) Data Collectiona. Selecting the appropriate Inventory Field Guide procedures for data collectionb. Applying QA/QC proceduresc. Following safety procedures

4) Data Management, Analysis, and Reportinga. Gathering field records, including field sheets, electronic data records, and imagesb. Entering and validating data into the GDE Databasec. Performing laboratory analysis or identification of samples and specimensd. Implement data management and quality control procedurese. Completing data analysis, evaluation, summaries and reports (including permit reports)f. Archiving data and/or specimens

Preparation and planning activities, processes, and considerations are similar between Level I and Level II. The following sections describe processes common to each inventory level and specify different considerations for each inventory level when appropriate.

Inventory Design and Planning

Development of an inventory design is not a trivial task, and is often under estimated in its complexity and time commitment. Establishing objectives and identifying the management questions to be



addressed provide a foundation for determining the analysis or planning area, selecting the appropriate protocols to apply, coordination with other agencies, and determination of skill requirements and cost.

Each of the following subsections provides guidance and items to consider in addressing each of the components of inventory design.

Setting Objectives and Identifying Management Questions

Project or planning objectives and management questions determine the data attributes and data resolution that need to be collected during inventory. Objectives and management questions to be addressed in planning and analysis are determined by the responsible official or the administrative unit line officer (see FSH 1909.15).

The GDE Level I and II Inventory Field Guides are designed to meet specific inventory objectives and address many management questions common across the NFS. The Business Requirements Analysis for Groundwater-Dependent Ecosystems Inventory and Monitoring Protocols (USDA Forest Service 2010) describes these relationships in detail and will aid in determining which GDE Inventory Field Guide best meets project or planning objectives.

Specific management questions (planning or environmental issues) addressed by each inventory level are also described in the Business Requirements Analysis for Groundwater-Dependent Ecosystems Inventory and Monitoring Protocols. If there are management questions not addressed by the GDE Inventory Field Guides, data attributes and the level of data resolution required need to be determined and appropriate protocols for collecting the data identified and documented. Published methods are preferred over unpublished or locally defined methods.

The following considerations may assist in determining which GDE Inventory Field Guide to use for a particular inventory:

Use the GDE Level I Inventory Field Guide when objectives associated with an inventory include determining the location and general characteristics of GDE sites within a planning or analysis area:

o To determine how to protect and conserve these sites within an area of interest. o To identify the general environmental consequences associated with different planning

options.

o To identify a subset of GDEs that require more intensive Level II inventory because of their vulnerability to projects or activities or to determine their ecological significance.

Use the GDE Level II inventory Field Guide when objectives associated with an inventory focuses on the characterization of GDE sites or features within a planning or analysis area:

o To design GDE restoration or rehabilitation proposals.o To provide a basis for evaluating environmental consequences of proposed actions

activities.o To gather information regarding the ecological significance of specific sites.

Determining the Planning or Analysis Area



The analysis or planning area (sometimes referred to as an area of interest in sampling design) is a function of the inventory objectives and follows the same basic process regardless of the inventory level selected.

When inventories are conducted to support land and resource management planning (i.e., Level I), the planning area is determined based on the scope of the planning effort consistent with requirements of Title 36 of the Code of Federal Regulations (CFR) Part 219 (Planning Rule) and Forest Service Manual (FSM) 1920. GDE inventory sampling design within the planning area is determined based upon the specific planning issues to be addressed and will determine the location and number of GDE features to be field sampled.

When inventories are conducted to support project design or environmental analysis (i.e., Level II), the analysis area is determined based on a combination of the geographic extent of the project and the activities’ direct, indirect, and cumulative effects. Guidance for determining the analysis area for a project or activity is described in detail in the National Environmental Policy Act (NEPA) Handbook (Forest Service Handbook [FSH] 1909.15).

Determining how to inventory or sample GDEs within a planning or analysis area depends on the objectives. Sampling design and intensity will be tailored to the specific information needs of the inventory, as described below.

Using Existing Data and Coordinating with Other Inventory Programs

Because of the high costs associated with collecting new data, using applicable existing data, or combining data collection efforts with other programs is most cost efficient. An example could be combining a water rights inventory with a springs inventory within the same area of interest. The needs of both programs can be satisfied by one field inventory effort instead of conducting two separate inventories with different field crews. When existing data are used, the data sources and metadata are important to document.

Coordinating or partnering with other agencies is sometimes necessary to make the inventory effort a success. Partners may include other State and federal agencies, Tribes, and non-governmental organizations or volunteers. Activities may include data sharing, permission to sample on cooperating agency lands, and cost sharing.

Supplementing the GDE Field Inventory Guide Data Collection

In cases where management questions are not addressed by the national inventory protocols, local data elements can be added to the inventory procedure. This can occur in two ways:

a) Adding information elements and methods to the Level I Inventory protocols to address management needs, or

b) Removing data collection items from the Level II Inventory protocols to address only those items needed for the project.

In most situations, the second approach is recommended because the data definitions, collection protocols, and database for storing data collected are defined and can be used.

Sampling Design



Once an appropriate GDE Field Inventory Guide has been selected and the planning or analysis area defined, the next step is to determine the sampling design. Sampling design is the procedure or plan drawn up before any data are collected to obtain a sample from a given population. The locations of sites to be inventoried and appropriate timing of those inventories, must be consistent with the inventory objectives and data needed to address specific management questions.

Appendix 3-B provides examples of sampling design methods including:

Designing a stratified random sampling scheme using a “list frame with random start” for a planning or analysis area is included in Appendix 3-B.1. This example illustrates how to stratify an area by major watershed and select springs to be inventoried from a known or suspected population.

Designing stratified random sampling scheme using a “grid based” sample selection for a planning or analysis area is provided in Appendix 3-B.2. This example illustrates how to select suspected groundwater-dependent features for inventory from a potential population identified by aerial photo interpretation using grid intersections as the selection process.

Conducting a total sample of GDE features within a planning or analysis area is displayed in Appendix 3-B.3. This example illustrates how to conduct field identification of GDE features and Level I data collection protocols.

Staffing Needs and Cost Estimation

The skills and staff needed depend on the level of GDE inventory and on inventory objectives and management needs. Table 3-4 provides an example developed for use on the Spring Mountains National Recreation Area to support a cooperative agreement for inventories conducted by a third-party. These estimates assume members of the design team have mid-level skills in managing spatial information and the use of geographic information systems (GIS) to aid in survey design and implementation.

Skills associated with spatial data collection and analyses using geographic information systems are important components of the inventory process. If individuals conducting design, data collection and analysis do not have this expertise, obtaining these skills will need to be included in cost estimates.

Cost estimation worksheets Level I and Level II inventories are provided in Appendix 3-C.

Reporting Requirements

Reporting requirements and report content should be a part of the design process to ensure documentation meets the management needs defined for the inventory. Ensure the data attributes, summaries, and characterization necessary to address management issues will be provided by the data collected.


http://www.answers.com/topic/sample-design


Table 3-4–Staffing and cost considerations.

Inventory Level Staffing and Cost Estimation Considerations

Level I Skills – Biologic and Hydrologic/Hydrogeologic, Geologic, or Soil Science Technicians at the GS 5/7/9 level

Training – 2 days training on the Level I protocols, data entry and sketch map requirements

Estimated Time per Site or Feature – 1–2 hours per site, not including travel time. On average 3 sites per day can be accomplished if they are in close proximity and minimal travel time is required between sites.

Inventory Coordination – Logistics and schedule for site visits will need to include travel times, travel restrictions, and an evaluation of most efficient groups of sites to visit.

QA/QC – In addition to training, include field audits of 5 percent of sites while crews are present and a minimum of one visit to monitor crew data collection and entry during the first portion of the inventory program.

PPE and other Equipment – Develop a Job Hazard Analysis and identify PPE required. Identify field equipment needs for each crew, including Portable Data Recorders.

Level II Skills – Botanist, Soil Scientist, Hydrologist/Hydrogeologist, Aquatic Biologist at the GS 9/11 level or higher

Training – 2 days training on the Level II protocols, data entry and sketch map requirements

Estimated Time per Site or Feature –4–8 hours per site, not including travel time. In most instances, only one site per day can be inventoried, pending the size of the site and travel time to the site.

Inventory Coordination – Logistics and schedule for site visits will need to include travel times, travel restrictions, and an evaluation of most efficient groups of sites to visit.

QA/QC – In addition to training, include field audits of 5 percent of sites while crews are present and a minimum of one visit to monitor crew data collection and entry during the first portion of the inventory program.

PPE and other Equipment – Develop a Job Hazard Analysis and identify PPE required. Identify field equipment needs for each crew, including Portable Data Recorders.

Logistics

Taking adequate time to plan and coordinate site visit schedules will result in significant cost savings and will maintain the crew’s focus on quality data collection.

Logistics and Site Access

Developing and describing efficient access routes to minimize travel times and risks to employees is a significant challenge and cost element. A particular challenge is when site locations have not previously been verified. This may require a time allowance for crews to determine where sites are physically located.



Travel restrictions on routes leading to a site can be determined by consulting the Motor Vehicle Use Map available on all Forest Service administrative units. Limitations on administrative use are described in the accompanying Forest Supervisor’s Special Order accompanying the Motor Vehicle Use Map. Wilderness and some other management designations such as Research Natural Areas establish additional limitations that must be considered during the planning phase.

Primary base series maps (U.S. Geological Survey Quadrangles and digital line graphs [DLG]), resource photography, and geospatial tools (e.g., Google Earth) are useful in setting up inventory routes and developing crew schedules. Crew training and work schedules are also factored into logistics and planning.

Safety

Access to some GDEs and physical conditions on GDE sites will require crew leaders and members to be attentive to risks and make determinations about whether the site can be accessed and inventoried safely. Discretion for making these decisions should always be left to the crew leader and crew members. The requirements of Forest Service Health and Safety Code Handbook (FSH 6709.11) apply to the conduct of all operations.

A Job Hazard Analysis for GDE Inventory Field Work is available in the field guides. This JHA should be reviewed for the specific conditions expected for the inventory project and will be used to identify training and personal protective equipment (PPE) needs.

Data Collection

Data collection procedures are outlined in the GDE Inventory Field Guides. Two aspects of data collection that cannot be over emphasized are training and quality assurance and quality control. The use of the standard protocols described in the GDE Inventory Field Guides assures that the best available science and technology for data collection is used. The application of those procedures, however, must be consistently applied and requires adequate training and QA/QC to ensure data collected are of known consistent quality and accuracy.

GDE Inventory Procedures Training

Training on the use of the GDE Inventory Field Guides is available through the National Minerals and Geology Training program. This training includes a web-based session that provides an overview of the methods and procedures associated with each level of inventory. Field training sessions are also available and can be scheduled through the National Minerals and Geology Training program.

Quality Assurance and Quality Control

Quality assurance and quality control includes procedures for consistent implementation of the study design, standards for maintaining scientific credibility of data and results, and methods for quantifying measurement error associated with the sampling design.



QA/QC is most important during the field data collection phase. A combination of crew training and field audits or “hot checks” are critical and should be performed by a person proficient in the use of the Level I or II Field Guides. Key areas to focus on, in data collection sequence, include:

Accuracy of GPS site locations and delineation (Level I and II) Representativeness of site delineation and transect layout (Level II) Representativeness of vegetation sampling along transects (Level II) Identification and detection of plant species (Level II) Estimation of plant cover (Level II) Characterization of soil profiles and attributes (Level II) Accuracy of flow measurements (Level I and II) Adherence to water quality measurement protocols (Level II) Accuracy of and placement of water table measurements (Level II) Detection of different faunal species (Level II) Recognition of natural and anthropogenic disturbances (Level I and II) Quality and consistency of Management Indicator evaluations (Level I and II)

Quality assurance and quality control in the office phases focus on data management. Key areas for QA/QC are the same for both inventory levels and include:

Minimizing for errors in data transfer Proper documentation and storage of data Technical review of data analysis reports

3.3.5 Data Management and Reporting

This subsection describes the way the GDE data are recorded, stored, and reported. Organization of this subsection follows the order in which the data are managed, from field data collection to report generation.

Field Records

The process of recording data in the field can be done either on paper (field sheets) or using an electronic data collection application that has been developed for the GDE Inventory Field Guides. Both field sheets and the electronic application are designed to facilitate data collection in a logical progression; the GDE Inventory Database (see subsection “Field Sheets” below for a description of the database) structure mirrors the field data collection process. Where possible, electronic data collection (using portable data recorders) is recommended over use of paper field sheets.

These data collection options are described below.

Field Sheets

Data collection on paper field sheets involves recording the survey data at the site, using standard forms available at: [A hyperlink for access to field data sheets will be added here].

Paper field sheets provide the ability to easily see, edit, and review data that have been recorded, although error checks and training associated with electronic data collection provide the same ability at the time data are recorded.



If the data are collected on paper field sheets then they will have to be manually entered in the GDE Inventory Database. The GDE Inventory Database was developed to facilitate efficient and accurate data entry. This is achieved through a user-friendly interface that can be used by someone with limited database experience. The GDE Inventory Database layout matches the format of the field sheets, facilitating data entry. Consistency of data is achieved by using drop-down boxes that refer to related look-up tables, thereby minimizing data entry errors. Flexibility is achieved by providing simple mechanisms for adding new items to look-up tables. Notes can also be entered to explain anomalous situations. Data entry from paper takes a significant amount of time and can be difficult especially when the person entering the data is not the person that recorded the data (which is often the case).

Disadvantages of the field sheets include the subsequent need to enter the data into the GDE Inventory Database, which takes considerable time and can be made difficult by illegible handwriting and incomplete responses. It can also lead to transcription errors, particularly if someone other than the field technicians who collected is doing the data entry. Field sheets can also be lost or damaged before the data are entered into the GDE Inventory Database.

The sooner the data are entered into the database the more likely it is that the field technicians will be available to answer questions about the data and notes they recorded. Ideally one of the field technicians who collected the data will enter them. If someone else enters the data it is important that field technicians review the data after it has been entered into the GDE Inventory Database for quality checks.

After the data have been entered into the database, the field sheets should be scanned and attached to the site’s record in the GDE Inventory Database.

Electronic Data Records

A portable data recorder (PDR) can be used to collect data electronically for entry into the GDE Inventory Database. The application is in ArcPad 6 format. This application is available by contacting the national groundwater program manager.

The advantages of electronic data collection are that it eliminates transcription errors and avoids problems with illegible handwriting. The restricted data entry options and drop-down menus facilitate appropriate data being recorded and decrease the likelihood of incomplete responses or errors. If data were collected electronically, then the GDE Inventory database has an import function that will quickly transfer the data from the PDR to the Database, which is a major advantage of electronic data collection

Disadvantages of electronic data collection can include equipment costs; slower recording of data in the field, especially if there are multiple people collecting data (some data could be recorded on paper and then entered into the PDR); the difficulty of quickly reviewing the data; and the possibility of mechanical failure, although backup systems are in place.

Images

In the field, images are generated by taking photos, drawing site sketch maps, and adding notes to maps (paper or electronic) that were used to describe the route and the site location.

Photos are taken with a digital (recommended) or film camera. Photos must have a log entry to document and describe each photo location. Digital photos should be stored in an electronic folder



clearly named based on the site ID. One photo can be stored in the GDE Inventory Database, but it is not practical to store all photos in the database.

Site sketch maps will often be on paper although they could be digital. A paper copy should be scanned into digital format, and the digital version stored in the database.

Topographic maps (paper or digital) used to describe the route to the site, the site boundaries, or features of the site should also be maintained in digital format, either in the database or in an electronic folder clearly named based on the site ID.

All images and maps should be stored at a resolution necessary to support current and future project needs at a minimum of 150 dots per inch (dpi) in .eps or .jpg formats in specified file locations on agency data servers. ArcGIS files associated with the project should be stored in the same file location.

GDE Inventory Database

The GDE Inventory Database provides a framework to compile and manage all data elements described in both the Level I and Level II Inventory Field Guides. This includes information on georeferencing, vegetation, soils, hydrology, geology, and disturbance. The GDE Inventory Database also provides for multiple visits to a site over time. The GDE Inventory Database and embedded User’s Guide are available from national groundwater program staff or Forest Service users may access the database at: O:\NFS\WOMineralsGeologyMgmt\Program\2880GeologicResourcesServices\Groundwater\GDE_Protocols\GDE_Database [Note: This is an internal FS file location not accessible to the public].

Data collected using the Level I and Level II inventory protocols must be managed and stored electronically to be accessible for current and future use. The GDE Inventory Database is designed to meet these purposes and to serve as a method for capturing data to be entered into the Forest Service Natural Resource Manager (NRM) corporate database. It is crucial that the GDE Inventory Database be maintained in its original format to ensure the integrity of the data and the ability to move it seamlessly into the NRM corporate database. Stand-alone auxiliary databases should be maintained for any additional data collected at these sites that cannot be entered in the NRM corporate database, for example, soil chemistry.

The GDE Inventory Database also facilitates public access to the data via the Enterprise Data Warehouse. GDE inventory data are extracted from the database and periodically loaded into the agency’s Enterprise Data Warehouse for public access.

Data Validation and Verification

In the field, data validation and verification can be done immediately by having someone else review the data that have been entered. Post-field validation and verification are facilitated by the GDE Inventory Database that has a number of mechanisms to ensure entry of appropriate values. The reviewer should look for:

Missing data Extreme values that may not be valid entries Incorrect or incompatible units Duplicate values, one of which may need to be deleted Plant species names are not accepted in the USDA PLANTS database (http://plants.usda.gov) Animal names that are not accepted taxa or are incorrectly spelled or use common names


http://plants.usda.gov/


Incorrect geographic data, for example, UTM coordinates

Post-field data validation is especially important for responses to the Management Indicator Tool, which includes entries based on both observed conditions and data collected in the field (summarized in GDE Inventory Database) as well as other sources (existing records and databases).

Laboratory Analysis

After the data have been entered into the GDE Inventory Database it is important to update the data with any additional data from laboratory analyses, such as:

Plant and animal species identifications recorded in the field as unknown or with a partial identification, for example, aster family, unknown forb, or unknown snail

Water quality Soil chemistry or physical properties

GDE Database Summaries and Reports

Significant amounts of data are generated during GDE field surveys. Table 3-5 lists the data attributes that can be summarized for a site or for a planning or analysis area, according to the field survey level. It is important that these data be accessible and usable after they have been entered. This is achieved through data summary tools that have been included in the GDE Inventory Database.

Table 3-5–Attributes that can be described for each site or using the GDE inventory levels.

Category Attributes Summarized Level I Level IIVegetation Presence of important or invasive species

Percent cover of each plant speciesPrevalence Index (based on wetland indicator status)Density of tree speciesBasal area of tree speciesBryophyte cover (%)Ground cover (%)

X XXXXXXX

Soil Presence of organic layersDepths and thicknesses of organic and mineral layersList of redoximorphic features observedTexture and color

X XXXX

Hydrology Hydrogeologic settingHydrologic characteristicsFlowWater table depth averageWater quality (pH, conductivity, ORP, dissolved oxygen, temperature)

XXX

XXXXX

Fauna Presence of important or invasive speciesSpecies list of animals (vertebrates and invertebrates)

X XX

Disturbance List of disturbances observed X X

Management Indicator Tool

Indicators of management activities affecting siteLow High



Comprehensive site reports, with all attributes (georeferencing, geology, vegetation, soils, hydrology, and disturbance), can be exported as .pdf files, which can serve as stand-alone reports. Table 3-6 presents a list of the reports that can be generated in the GDE Inventory Database. Inventory questions and objectives will help identify what type of analysis is needed. Mapped locations can be generated from the tabular location data and displayed with other datasets within NRM provided information regarding site location coordinates or spatial extent (polygon) are also recorded and linked to the GDE database.

Table 3-6–List of reports that can be generated in the GDE Database.*

GDE DB Report Title Description

General Survey Data General data by survey-- air temp, aspect, area of site, etc.HUC Crosstab Count of surveys by HUC.Georeferenced Survey Data Georeferencing data by survey -- coordinates, elevation, polygons, etc.Survey Vegetation Totals Vegetation summary by survey (not species lists).Quadrat Species % Crosstab Plant species and cover in herbaceous layer by survey.Tree Species % Crosstab Woody plant species and cover by survey.Vegetation List Plant list for species encountered in all surveys.Geology Survey Data Geology data by survey.Spring Type Crosstab Spring types and count by HUC.Survey Soils Data Soils data by survey.Water Quality All Water quality measurements, with parameters not in GDE field guide.Water Quality Required Water quality measurements, for parameters in GDE field guide.Water Quality Crosstab Water quality averages by survey, with parameters not in GDE field guide.Water Quality Required Water quality averages by survey, for parameters in GDE field guide.Crosstab Invertebrate List Invertebrates by survey.Invertebrate Crosstab Crosstab of invertebrates by survey.Vertebrate List Vertebrates by survey.Vertebrate Crosstab Crosstab of vertebrates by survey.Disturbance Disturbances by survey.Management Indicators Management indicator tool responses by survey.Project Survey Reports - All Multi-survey report with all attributes (exportable to PDF).Survey Report Single survey report with all attributes (exportable to PDF).Level 1 Survey Reports - All Level 1 multi-survey report with all attributes (exportable to PDF).

*Note: All reports are for Level II data unless otherwise noted.



Inventory and Monitoring Reports

Report content should address the areas described in Table 3-7. Data summaries, analysis results, and laboratory data sheets are typically included as appendices to the inventory report.

Table 3-7–Inventory report content organization.

Section Content

Introduction Describe the objectives the report is intended to address, any pertinent background, and the management questions addressed by the inventory.

Methodology Describe the inventory design and when additional attributes beyond those described in the Level I and II Inventory Field Guides are collected, describe the rationale for collecting them and the field methods used.

Analysis and Evaluation

Describe and summarize the results of data collection and organize this section to address inventory objectives and management questions. Interpret the data collected and link them to inventory objectives and management questions.

Conclusions and Recommendations

Describe conclusions related to the inventory objectives and management questions and associated recommendations, including recommended design measures, mitigation practices, and monitoring.

Examples of data reports or information summaries that can be generated using the GDE Inventory Database reports and project reports are provided in the following case studies in Appendix 3-D.

Level I Site Report – Wallowa-Whitman National Forest (GDE Database Report) (3-D.1) Level II Site Report – Spring Mountains National Recreation Area (GDE Database Report) (3-D.2) Level II Area-wide Report - Spring Mountains National Recreation Area (3-D.3) Project Area Monitoring Baseline Report – Montanore Mine, Kootenai National Forest (3-D.4)

Note: To the extent possible, the original formatting of these reports has been retained. Text has been extracted verbatim and not edited before inclusion in this document.



References

Brinson, M.M. 1993. A hydrogeomorphic classification for wetlands. U.S. Army Corps of Engineers, Technical Rep. WRP-DE-4. Washington, DC. Wetlands Research Program.

Brown, J.; Wyers, A.; Aldous, A.; Bach, L. [et al.]. 2007. Groundwater and biodiversity conservation: a methods guide for integrating groundwater needs of ecosystems and species into conservation plans in the Pacific Northwest. Portland, OR: The Nature Conservancy. 184 p.

Carter, V. 1996. Wetland hydrology, water quality and related functions. In: Fretwell, J.; Williams, J.; Redman, P., eds. National water summary on wetland resources. Water Supply Paper 2425. Reston, VA: U.S. Department of Interior, U.S. Geologic Survey. pp. 35–48.

Godwin, K.S.; Shallenberger, J.P.; Leopold, D.J.; Bedford, B.L. 2002. Linking landscape properties to local hydrogeologic gradients and plant species occurrence in New York fens: a hydrogeologic setting (HGS) framework. Wetlands. 22 (4): 722–737.

Komor, S.C. 1994. Geochemistry and hydrology of a calcareous fen in the Savage Fen wetlands complex, Minnesota. Geochimica et Cosmochimica Acta. 58: 3353–3367.

Mitsch, W.J.; Gosselink, J.G. 2007. Wetlands. 4th ed. New York: John Wiley and Sons. 582 p.

National Wetlands Working Group. 1997. The Canadian wetland classification system. Waterloo, Ontario: University of Waterloo, Wetlands Research Centre. 76 p.

Richardson, C.J. 2003. Pocosins: hydrologically isolated or integrated wetlands on the landscape? Wetlands. 23: 563–576.

Springer, A.E.; Stevens, L.E.; Anderson, D.E.; Parnell, R.A.; Kreamer, D.K.; Levin, L.; Flora, S.P. [et al.]. 2008. A comprehensive springs classification system: integrating geomorphic, hydrogeochemical, and ecological criteria. In: Stevens, L.E.; V. J. Meretsky, V.J., eds. Aridland springs in North America: ecology and conservation. University of Arizona Press, Tucson, AZ. pp. 49-75.

United States Department of Agriculture (USDA), Forest Service. 2010. Business Requirements Analysis for Groundwater-Dependent Ecosystems Inventory and Monitoring Protocols. El Paso, TX: Management and Engineering Technologies International, Inc. http://www.fs.fed.us/geology/bus_require_analysis_v5_2%5B1%5D.pdf .

Winter, T.C. 1988. A conceptual framework for assessing cumulative impacts on the hydrology of nontidal wetlands. Journal of Environmental Quality. 12: 605–20.

Winter, T.C.; Harvey, J.W.; Franke. O.L.; Alley, W.M. [et al.]. 1998. Ground water and surface water: a single resource: U.S. Geological Survey Circular 1139. 79 p. http://pubs.usgs.gov/circ/circ1139/.


http://www.fs.fed.us/geology/bus_require_analysis_v5_2%5B1%5D.pdf


Appendix 3-A – Groundwater-Dependent Ecosystem Types, Definitions and Classification Methods

The following information was originally developed as part of the Business Requirements Analysis for the Groundwater-Dependent Ecosystems Inventory Field Guide development process (Gurrieri and Coles-Ritchie 2009). It defines and describes types of groundwater-dependent ecosystems (GDEs) and how they may be classified. It includes a description of the GDEs intended to be inventoried using the protocols described in the GDE Inventory Field Guides.

Introduction

The USDA Forest Service Groundwater-Dependent Ecosystem Inventory Field Guides describe protocols for the inventory and monitoring of wetlands that are dependent on groundwater, or groundwater-dependent ecosystems (GDEs). This document outlines the scope of the GDE inventory protocols and provides general definitions of the ecosystems intended for these protocols.

The National Academy of Sciences defined wetlands in the following manner:

A wetland is an ecosystem that depends on constant or recurrent, shallow inundation or saturation at or near the surface of the substrate. The minimum essential characteristics of a wetland are recurrent, sustained inundation or saturation at or near the surface and the presence of physical, chemical, and biological features reflective of recurrent, sustained inundation or saturation. Common diagnostic features of wetlands are hydric soils and hydrophytic vegetation. These features will be present except where specific physicochemical, biotic, or anthropogenic factors have removed them or prevented their development (National Research Council 1995).

On National Forest System (NFS) lands the classification of wetlands is commonly defined by the National Wetland Inventory System (Cowardin et al. 1979), where groundwater-dependent wetlands are included in the Palustrine System, but little is said to distinguish fens or other groundwater-dependent wetlands as unique entities. One of the main purposes of this protocol is to provide a uniform framework for the characterization and description of groundwater-dependent wetlands throughout the United States.

This protocol focuses on minerogenous wetland systems (see text box below), which are normally situated at positions in the landscape lower than adjacent mineral terrain such that water and mineral elements are introduced by groundwater.

These minerogenous hydrological systems have a strong linkage with the regional groundwater system and the physical and chemical nature of the geological environment. In contrast, ombrogenous hydrological systems (see text box below) are not dependent on groundwater.

Ombrogenous hydrological systems are restricted geographically because of local climatic conditions. Minerogenous systems are not


Minerogenous: Water that originates on the land surface or as groundwater where it comes in contact with mineral soils and bedrock. The water is rich in total dissolved solids (National Wetlands Working Group. 1997).

Ombrogenous: Water that originates exclusively from precipitation (rain or snow) and has a low concentration of dissolved minerals (National Wetlands Working Group. 1997); “Literally rain fed, referring to wetlands that depend on precipitation as the sole source of water” (Mitsch and Gosselink 2007).


restricted by local climatic conditions because the groundwater source is generally sufficient to maintain soil saturation and therefore wetland processes.

In summary, the primary basis for determining which systems to include in the GDE protocol is hydrology, specifically the water source. This document provides a very general classification of wetlands to indicate which types of wetlands will be covered by the GDE protocol. This is not a classification based on geography, meaning that it is not a classification of specific sites or locations. It is also not a classification based on vegetation, although vegetation can be helpful in distinguishing the GDE types.

The Spring-Wetland Continuum

Nearly all permanent springs have associated wetlands of different types. Springs and wetlands are intimately intertwined across the landscape. The emergent water at a spring orifice merely represents one point in the hydrologic and ecologic continuum of groundwater discharge. This interrelationship is immediately apparent to anyone who tries to inventory these features in the field. Wetland classification systems have historically been dependent on vegetation type, soil type, or hydrologic conditions and thus there has been no distinct class for springs. For this reason springs have not been included in wetland classification schemes but have been treated as a distinct group of groundwater discharge features to be classified separately. The hazard of this separate classification is that field workers interested in springs ignore the rich ecology of a wetlands associated with springs, while wetland specialists ignore the rich ecology of springs associated with wetlands.

The interrelationship between springs and wetlands is evident in wetland classification terms like spring fen, spring swamp, spring marsh, and spring-seepage peatlands that are used to denote that an obvious spring is visible within a wetland. In reality, fens for example can be thought of as simply springs with a blanket of peat draped over the top. Spring occurrence in some geomorphic settings (e.g., cliff walls) can be far more complicated than wetlands, creating a wide array of microhabitats not observed in wetlands (Springer and Stevens 2008).

The study of springs and wetlands is inherently interdisciplinary, because they occupy the nexus between groundwater, surface water and ecology. Hence they have been studied by both physical scientists and biologists. Because research is typically conducted by experts from only one specialty or locality, there has grown a proliferation of different and varying classification and description systems specific to that specialty or locality. We hope to present a logical description for the continuum from spring to groundwater-dependent wetland.

Groundwater-Dependent Ecosystem Types

“A Hierarchical Framework Of Aquatic Ecological Units” has been developed by the Forest Service (Maxwell et al. 1995) and includes the following general hierarchy of GDE mapping units:

- Aquifers, which are “based on their geology, hydrology, and water quality;”- Aquifer zones, which “distinguish recharge areas from discharge areas;”

- Aquifer sites, which “delineate springs and sinks where the water table intersects the land surface.”

The GDE types described in this document would characterize wetlands at the scale of the “aquifer sites” described by Maxwell et al. (1995).



Three primary classes of GDEs have been proposed by Eamus et al. (2006): (1) aquifer and cave ecosystems; (2) all ecosystems dependent on the surface expression of groundwater; and (3) all ecosystems dependent on the subsurface presence of groundwater. This GDE protocol will focus on the second type, ecosystems dependent on the surface expression of groundwater.

Another wetland classification is the Canadian Wetland Classification System (National Wetlands Working Group 1997) that separates wetlands into various classes, forms and types. Wetland classes are recognized on the basis of the overall genetic origin of wetland ecosystems and the nature of the wetland habitat. The Canadian System presents the following general classes:

Fen Swamp Marsh Shallow water wetlands Bog

This GDE protocol will focus on the first three classes listed above for the Canadian Classification, which are those that are typically groundwater-dependent, at least to some degree. The scope of this GDE protocol is outlined in figure 3-A-1. The Canadian classification includes spring types within some of these classes (such as “spring fen” and “spring swamp”), but for the purposes of this protocol we distinguish springs as a distinct type, recognizing that there is a gradient from springs to the other wetland types (as discussed above). We exclude bogs, because they are not groundwater-dependent (although the protocol might well be useful to inventory and monitor bogs). The “Shallow water wetlands” class of the Canadian Classification is similar to the classes of groundwater-dependent “Lakes” and “Streams” types in our scheme (fig. 3-A-1). Bog, lake, and stream systems are not within the scope of this GDE protocol, but we anticipate that they could be inventoried with this protocol. The ecosystem types to be covered by the GDE protocol are summarized in table 3-A-1.

Figure 3-A-1–Ecosystem types covered by the GDE Inventory Field Guides



Table 3-A-1–Groundwater-dependent ecosystem types intended to be inventoried using the GDE Inventory Field Guides.

GDE Type HydrologyPosition of

WaterTable

Soils and PeatDepths

Oxygen conditions

Water movement

within wetland

Water Chemistry Vegetation

SpringsMinerogenous; completely groundwater-dependent

At ground surface

Mostly mineral soils; rarely accumulation of peat

Oxygenated Standing or flowing water

Highly variable; from acidic to basic, temperatures vary, can be thermal

Graminoids, forbs, shrubs and trees; rarely qualifies as wetland vegetation

Peatlands(dependent on groundwater)

Minerogenous; always groundwater-dependent

At ground surface

Accumulation of peat up to several meters; little or no mineral soil

Anoxia develops slightly below the surface, leading to the accumulation of peat

Water table usually slightly below the surface, so no water movement detectable

Minerotrophic, acidic (poor fens) to basic (circumneutral or strongly alkaline), can be iron-rich or calcareous

Bryophytes, graminoids (sedges and grasses), low shrubs; lichens, sometimes trees. Always wetland vegetation

Other wetlands (dependent on groundwater)

Minerogenous; depend on groundwater, precipitation and sometimes stream inflow

At, above, or below surface; fluctuates dramatically; periodic standing water

Usually little or no peat accumulation; sometimes wood-rich peat

Temporary soil anoxia during times of high water table

Periodic standing or flowing water

Highly variable; from acidic to basic; mineral-rich

Tall woody plants and forbs (swamps) or emergent graminoids and floating aquatic macrophytes (marshes)

Wetland types Not Covered by the GDE Inventory Field Guides

Certain groundwater-dependent ecosystems are not intended for protocols described in the GDE Inventory Field Guides, such as:

Groundwater-dependent lakes; Base-flow streams; and Phreatophytic systems (including some riparian areas).

Because of the distinct characteristics of those systems it was not practical to include them in these protocols. It is hoped that other protocols will cover those systems. Protocols do exist, or are in development, for inventorying and monitoring those systems, although they focus on surface water and not groundwater conditions and processes.

Wetland systems that look similar to some GDEs, but that are not dependent on groundwater may be inventoried using the Field Guides or some protocols included in the Field Guide. These include:



Bogs; Pocosins, a type of bog in the Southeastern United States (described in Richardson 2003); Carolina bays, of the southeastern United States Coastal Plain (described in Sharitz 2003); and Other wetlands not supported by groundwater.

Descriptions of Wetlands Intended for the GDE Inventory Field Guides

The GDE protocol covers the following wetland ecological systems:

Springs/Seeps Peatlands supported by groundwater Other groundwater-supported wetlands (such as swamps and marshes).

Below is a general description of these GDE systems.

Springs/Seeps

Springs are ecosystems in which groundwater reaches the earth’s surface. At the point of emergence the physical geomorphic setting allows some springs to support large arrays of aquatic, wetland, and terrestrial species and assemblages (Springer and Stevens 2008). There is no clear distinction between springs and wetlands (as described above in the section “The Spring-Wetland Continuum”). Therefore it is important to include both springs and groundwater-dependent wetlands in the same protocol for inventory and monitoring GDEs.

While not a classification itself, a useful system for classifying spring types has been proposed by Springer et al. (2008) who list the various settings of springs or “spheres of discharge” as:

Cave Exposure Fountain Geyser

Gushet Hanging garden Helocrene Hillslope

Hypocrene Limnocrene Mound form Rheocrene

Peatlands

Peatlands are “…any wetland [that] accumulates partially decayed plant material (peat)” (Mitsch and Gosselink 2007). The Canadian Wetland Classification (National Wetlands Working Group 1997) refers to peatlands as “organic wetlands.” Fens are a type of peatland that have a relatively constant supply of groundwater, which saturates the soil and slows decomposition to the point that peat accumulates. Fens and other peatlands supported by groundwater are the focus of the GDE Inventory Field Guide protocols. Some peatlands are not supported by groundwater, such as bogs, and therefore are not the focus of these protocols, although the protocol might have some utility for such systems.

Swamps (and less commonly marshes) have a little peat development, but would not be considered as peatlands for this protocol.

Fens Verses Bogs

Peatlands are generally divided into two main categories, bogs and fens, although the use of these terms varies (Bedford and Godwin 2003). A bog is “a peat-accumulating wetland that has no significant inflows or outflows and supports acidophilic mosses, particularly Sphagnum” (Mitsch and



Gosselink 2007). A fen is “a peat-accumulating wetland that receives some drainage from surrounding mineral soil and usually supports marshlike vegetation” (Mitsch and Gosselink 2007).

Fens are separate from bogs based upon their hydrologic characteristics; bogs are fed almost entirely by atmospheric precipitation, while fens are fed primarily by groundwater, although they receive precipitation and surface water as well. Fens are wetlands distinguished by their strong connection to groundwater. A wetland whose vegetation, water chemistry, and soil development are not determined, in large part, by the flows of groundwater is not a fen.

There are two lines of thinking for peatlands. From a biological perspective the distinction occurs at the level of water chemistry. Bogs and poor fens group together functionally because they have similar water chemistries that are low in pH and base cations and are ombrotrophic. Bogs are this way because most of their water comes from precipitation. Poor fens are this way because they get water from geologic deposits with low solubility like granite. Medium, rich, and extreme rich fens group together because the biology is controlled by the higher pH, more buffered waters with higher concentrations of base cations – this minerotrophic water all comes from groundwater.

From a landscape/hydrogeologic perspective, it is important to divide fens from true bogs in terms of their water sources (precipitation vs. groundwater). Reversals in groundwater head gradient can happen in peatlands. At certain times of the year there is an upward gradient where groundwater discharges to the rooting zone. At other times a downward gradient develops. It seems tidy to divide the hydrology into sources; however, the interactions of groundwater and precipitation may be more complicated. Because bogs are not groundwater related features and are also rather rare in the United States outside of Alaska, they will not be considered in this protocol.

A wetland that is similar to a bog is a “pocosin.” A pocosin is a “peat-accumulating, nonriparian freshwater wetland, generally dominated by evergreen shrubs and trees and found on the southeastern coastal plain of the United States” (Mitsch and Gosselink 2007). Pocosins are supported by rainfall (Richardson 2003) and therefore, like bogs are not included in this GDE protocol.

Fens

Fens are minerotrophic peatlands with the water table slightly below, at, or just above the surface. Usually there is slow internal groundwater seepage in these systems, but sometimes they have over-surface flow. Peat thickness is variable, although a common criterion for fens is that they have at least 40 centimeters of peat (National Wetlands Working Group 1997, Weixelman and Cooper 2009). Two broad fen types are basin fens and sloping fens. Fens are usually open but can be wooded where transitioning into a swamp forest. The dominant vegetation is bryophytes, graminoids, or low shrubs. The surface may be firm or with floating or quaking mats. They can be acidic to basic.

The primary characteristics of fens are: (1) an accumulation of peat; (2) surface is level with the water table, with water flow on the surface and through the subsurface; (3) fluctuating water table which may be at, or a few centimeters above or below, the surface; (4) minerogenous; (5) decomposed sedge or brown moss peat; and (6) graminoids and shrubs characterize the vegetation cover.

The following definition of fens by Bedford and Godwin (2003) is consistent with this protocol:

“…wetlands that develop where a relatively constant supply of ground water to the plant rooting zone maintains saturated conditions most of the time and the water chemistry reflects



the mineralogy of the surrounding and underlying soils and geological materials. …like many factors structuring ecosystems, the degree to which ground water dominates the fen water budget is a continuum. In all cases used here, the influence of ground water exceeds that of precipitation and surface water, either in quantity or in terms of effects on water chemistry in the plant rooting zone.”

The following is a list of field tools for identifying fens:

1. Determine if organic peat soils are saturated year-round.2. Look for indicator species (especially bryophytes).3. Check the landscape position where you might expect fens to develop.4. Measure groundwater discharge into the rooting zone using nested piezometers (not a quick

field tool, but this is obviously the definitive way to do it).5. Measure pH and conductivity (can be used to differentiate between poor fens/bogs and med-

rich-extreme rich fens).

Examples of fen sub-types based largely on National Wetlands Working Group (1997) include:

Riparian fen Slope fen String fen Basin fen

Horizontal fen Spring fen Poor fen Rich fen

Intermediate rich fen Extreme rich fen Iron fen

Other Wetlands

Wetlands in this category are those that have no (or minimal) peat accumulation, and also are described as “mineral wetlands” by the National Wetlands Working Group (1997). These non-peat groundwater-dependent wetlands include what often are referred to as swamps and marshes. Wetlands referred to as “depressional wetlands” in the southeastern United States, if they are groundwater dependent, would fit in this category as well.

Swamps and marshes that are groundwater dependent have a variable water table, which is above, at, or below the surface. They are either seasonally or permanently flooded and vary widely in the volume of groundwater inflow. There is usually little or no peat accumulation, except in the case of some swamps (discussed below). Woody vegetation is a characteristic that is commonly used to distinguish swamps from marshes, with swamps typically being forested (with coniferous or deciduous trees) or sometimes thicketed (with shrubs), whereas marshes typically have submerged, floating or emergent vegetation (graminoids such as rushes, reeds, grasses, and sedges). When swamps have a water table that is well below the surface the soil is aerated which leads to accumulations of wood-rich peat (National Wetlands Working Group 1997, Mitsch and Gosselink 2007).

Examples of swamp and marsh sub-types include:

Discharge swamp Flat swamp Inland salt swamp Mineral-rise swamp Riparian swamp Slope swamp

Tidal swamp Cypress domes & strands* Wet meadow Spring marsh Slope marsh Riparian marsh

Hummock marsh Lacustrine marsh Basin marsh Estuarine marsh Tidal marsh Carolina bays

*As described by Florida Department of Environmental Protection



GDE Classification Methods

Because many management questions span jurisdictional boundaries, the ability to organize data and conduct analyses across administrative boundaries is also a consideration in inventory and monitoring designs. One of the principal tools used to compare data on GDEs across large areas and different ownerships or administrative jurisdictions is the use of classification systems.

The characterization of a GDE feature within a recognized classification system can also be used to help understand its ecology and function. Classification systems have evolved to support a variety of business needs and are used to interpret basic field data consistently between different GDEs in different locations and jurisdictions. Data inputs needed to use these classification systems for analysis and comparison are important considerations in the development of GDE inventory and monitoring protocols.

An examination of the data inputs necessary to use these classification systems for understanding and comparing GDEs within and between administrative units or different land ownerships will assist in identifying data collection priorities.

The following is a summary of the principle classification systems in use and data inputs used in each classification. Following this summary, table 3-A-5 provides a comparison of data inputs necessary to utilize various classification systems.

Cowardin, et al. (1979) Classification of Wetlands

The Cowardin et al. (1979) classification of wetlands is a hierarchical classification. Table 3-A-2 summarizes levels used within this hierarchy.

Table 3-A-2–Hierarchical Levels and descriptions used in the Cowardian Classification System.

Level Categories or Description

Systems Marine, Estuarine, Riverine, Lacustrine, and Palustrine based on physiogeographic location

Subsystems There are 0 to 4 for each System based on physiogeographic location

Classes Varies by subsystem and are defined by substrate material and flooding regime, or on vegetative life form (subclasses can also be defined)

Modifiers Developed by individual users of the classification based on water regime, water chemistry, and soil information. Dominant plant species (dominance types) can also be used to further classify.

This system was used as the foundation for the Forest Service’s “Hierarchical Framework of Aquatic Ecological Units” (Maxwell et. al. 1995). The Forest Service hierarchy expands the Cowardin classification, which has been adopted by the Federal Geographic Data Committee as the federal standard.

The Palustrine System of Cowardin et al. (1979) is the most applicable to GDEs covered by the Forest Service protocols (USDA Forest Service 2012). “The Palustrine System includes all nontidal wetlands dominated by trees, shrubs, persistent emergents, emergent mosses or lichens, and all such wetlands that occur in tidal areas where salinity due to ocean-derived salts is below 0.5%” as well as some non-



vegetated wetlands. The Palustrine System has no subsystems. The class level avoided “terms such as such as marsh, swamp, bog, and meadow…because of wide discrepancies in the use of these terms.”

The Palustrine System has the following 8 classes:

1. Rock Bottom 2. Moss-Lichen Wetland3. Unconsolidated Bottom 4. Emergent Wetland5. Aquatic Bed 6. Scrub-Shrub Wetland7. Unconsolidated Shore 8. Forested Wetland

Data required to classify a wetland according to the Cowardin et al (1979) classification are:

Location or physiographic setting (marine, riverine, etc.) Substrate (general) Vegetation (dominant life form)

Canadian Wetland Classification System

The Canadian Wetland Classification System (National Wetlands Working Group 1997) contains three hierarchical levels: (1) class, (2) form, and (3) type. Five classes are recognized on the basis of the overall genetic origin of wetland ecosystems. Forms are differentiated on the basis of surface morphology, surface pattern, water type and morphology of underlying mineral soil. Types are classified according to vegetation physiognomy.

Data required to classify a wetland using the Canadian Wetland Classification include:

Water table elevation, general information such as presence of surface water Location or physiographic setting (marine, riverine, etc.) Water characteristics: whether rich in dissolved minerals (minerogenous or groundwater-

dependent) or not (ombrogenous or precipitation dependent); alkalinity Peat accumulation Vegetation types (bryophytes, graminoids, trees, shrubs, forbs, and submerged or floating

aquatic plants)

Springer, et al. (2008) Springs Classification System

This system for classification of springs by Springer et al. (2008) is based on a number of criteria, which are listed in Appendix 3-A. The major categories of characteristics that need to be determined to classify springs are summarized in table 3-A-3.



Table 3-A-3–Spring characteristics used in Springer, et. al. (2008) classification system.

Data Category Characteristics

Geomorphic Considerations

a. Hydrostratigraphic unit type (sedimentary, igneous, metamorphic, mixed)b. Emergence environment (cave, sub-glacial, etc.)c. Orifice geomorphologyd. Sphere of dischargee. Spring channel dynamics

Flow Characteristics a. Persistenceb. Flow consistencyc. Flow rated. Flow variability

Water Quality a. Water temperatureb. Geochemistry

Ecological a. Habitat (Synoptic climate, surrounding ecosystems, biogeographic location, habitat size, microhabitat diversity)b. Biota (species composition, vegetation, faunal diversity)

Management Management activities affecting the spring

Significant data on the five categories listed above are required to classify springs using this system. GDE Level II inventories require identification of these spring types.

Hydrogeomorphic Classification (HGM)

The HGM classification (Brinson 1993) is based on geomorphic and hydrologic properties of wetlands. The classification does not consider vegetation, although vegetation is often an indicator of the abiotic properties that are used. HGM has three core components to the classification as shown in table 3-A-4.

Table 3-A-4–Hydrogeomorphic classification components and characteristics.

Data Category Characteristics

Geomorphology Depressional, riverine, fringe, and extensive peatlands

Water Source Precipitation, surface or near-surface flow, and groundwater discharge

Hydrodynamics Direction and strength of water movement within a wetland

Of the three components of wetlands listed above, the first (geomorphology) is relatively easy to determine. The other two components—dealing with hydrology—would likely be more difficult to determine and could require significant field data.

U.S. Army Corps of Engineers Wetlands Delineation Manual (1987)

This Manual (U.S. Army Corps of Engineers 1987) is used to determine whether a site is a jurisdictional wetland under the Clean Water Act. A wetland must have hydrophytic vegetation, hydric soils, and wetland hydrology to qualify as jurisdictional. Determinations for each factor and necessary data inputs are described as:



Vegetation: It is necessary to establish whether the prevalent vegetation is hydrophytic vegetation. This requires a measure of the abundance of the dominant plant species at a site.

Soils: It must be determined whether hydric soils are present. This requires evaluation of the soil (surface and/or profile) to determine if there are features indicative of saturated soil conditions.

Hydrology: It must be determined whether the site is periodically inundated or has soils saturated to the surface at some time during the growing season. A variety of characteristics can be identified to determine wetland hydrology, which includes observations at the site or recorded data (such as gage data).

Fen Classification Systems

The following regional fen classifications have been identified:

Fens of Grand Mesa, Colorado: Characterization, impacts from human activities, and restoration (Austin 2008)

Fens of Yellowstone National Park, USA: Regional and local controls over plant species distribution (Lemly 2007)

These studies classified fens for a given area, but they do not provide classifications that can be readily applied to other sites.

Table 3-A-5 summarizes data attributes and components used in spring/wetland classification systems.



Table 3-A-5–Summary of data requirements for various classification systems.

Data Category Attribute Description

Hydrology

General- Location information- Physiographic setting (marine, riverine, etc.)

Physical description- Hydrology- Water table elevation- Water characteristics (dissolved minerals, alkalinity, etc.)- Flow characteristics- Water quality- Water source- Hydrodynamics- If wetland hydrology

Geology and Soils

Substrate (general)Peat accumulationGeomorphic considerations related to springs (including sphere of discharge)If hydric soils (hydrologic indicators)Soil characteristics

Ecological

Vegetation- Dominant life form- Types (bryophytes, graminoids, trees, shrubs, forbs, and submerged or floating

aquatic plants)- Species list- Species abundance (cover, basal area, etc.)- Hydrophytic (wetland vegetation) or not

Aquatic biota- Presence- Abundance- Species list

Management Management activities and impacts



References

Austin, G. 2008. Fens of Grand Mesa, Colorado: Characterization, impacts from human activities, and restoration. Thesis. Prescott College, Prescott, AZ.

Brinson, M.M. 1993. A hydrogeomorphic classification for wetlands. U.S. Army Corps of Engineers, Technical Rep. WRP-DE-4. Washington, DC. Wetlands Research Program.

Bedford, B.L.; Godwin, K.S. 2003. Fens of the United States: distribution, characteristics, and scientific connection verses legal isolation. Wetlands. 23(3): 608–629.

Cowardin, L.M., Carter, V.; Golet, F.C.; LaRo, E.T. [et al.]. 1979. Classification of wetlands and deepwater habitats of the United States. U.S. Fish and Wildlife Service, Department of the Interior, Washington, DC. FWS/OBS-79/31.

Eamus, D.; Froend, R.; Loomes, R.; Hose, G.; Murray, B. [et al.]. 2006. A functional methodology for determining the groundwater regime needed to maintain the health of groundwater-dependent vegetation. Australian Journal of Botany. 54: 97–114.

Gurrieri, J.; Coles-Ritchie, M. 2009. Scope and Definition of Wetland Types to be Covered by the Groundwater-Dependent Ecosystem Inventory Protocol Development. Appendix to Business Requirements Analysis for Groundwater-Dependent Ecosystems Inventory and Monitoring Protocols. http://www.fs.fed.us/geology/bus_require_analysis_v5_2%5B1%5D.pdf .

Lemly, J.M. 2007. Fens of Yellowstone National Park, USA: Regional and local controls over plant species distribution. Thesis. Colorado State University, Fort Collins, CO.

Maxwell, J. R., C. J. Edwards, M. E. Jensen, S. J. Paustian, H. Parrott, and D. M. Hill. 1995. A hierarchical framework of aquatic ecological units in North America (Nearctic Zone). North Central Forest Experiment Station, St. Paul, MN.

Mitsch, W.J.; Gosselink, J.G. 2007. Wetlands. 4thed. New York: John Wiley and Sons.

National Research Council. 1995. Wetlands: characteristics and boundaries. Washington, DC: National Academy Press.

National Wetlands Working Group. 1997. The Canadian Wetland Classification System. University of Waterloo, Wetlands Research Centre, Waterloo, Ontario, Canada.

Richardson, C.J. 2003. Pocosins: hydrologically isolated or integrated wetlands on the landscape? Wetlands 23: 563–576.

Springer, A.E.; Stevens, L. 2008. Spheres of discharge of springs. Hydrogeology Journal. 17: 83–93.

Springer, A.E.; Stevens, L.E.; Anderson, D.E.; Parnell, R.A.; Kreamer, D.K.; Levin, L.; Flora, S.P. 2008. A comprehensive springs classification system: integrating geomorphic, hydrogeochemical, and ecological criteria. In: Stevens, L.E.; V. J. Meretsky, V.J., eds. Aridland springs in North America: ecology and conservation. University of Arizona Press, Tucson, AZ. pp. 49-75.

U.S. Army Corps of Engineers. 1987. Full citation will be provided following review.


http://www.fs.fed.us/geology/bus_require_analysis_v5_2%5B1%5D.pdf


U.S. Department of Agriculture (USDA), Forest Service. 2012. Groundwater-dependent ecosystems: level II inventory field guide: inventory methods for project design and analysis. Gen. Tech. Rep. WO-86b. Washington, DC: U.S. Department of Agriculture, Forest Service. http://www.fs.fed.us/geology/GDE_Level_II_FG_final_March2012.pdf.

Weixelman, D.A.; Cooper, D.J. 2009. Assessing proper functioning condition for fen areas in the Sierra Nevada and Southern Cascade Ranges in California: a user guide. U.S. Department of Agriculture, Forest Service, Pacific Southwest Region, Vallejo, CA.

Additional References

Barquín, J.; Scarsbrook, M. 2008. Management and conservation strategies for coldwater springs. Aquatic Conservation: Marine and Freshwater Ecosystems. 18: 580–591.

Cooper, D.J. 1998. Classification of Colorado's wetlands for use in HGM functional assessment: A first approximation. Section 3, 47 pp.in D. C. Noe, editor. Characterization and functional assessment of reference wetlands in Colorado. Colorado Department of Natural Resources, Colorado Geological Survey, Denver, CO.

Florida Department of Environmental Protection http://www.dep.state.fl.us/water/wetlands/delineation/wetcomm/cypdome.htm

NatureServe 2008. International Ecological Classification Standard: Terrestrial Ecological Classifications, NatureServe Central Databases, Arlington, VA, U.S.A. Data current as of 07 June 2008.

Sada, D.W., J.E. Williams, J.C. Silvey, A. Halford, J. Ramakka, P. Summers, and L. Lewis. 2001. A Guide to Managing, Restoring, and Conserving Springs in the Western United States. USDI Bureau of Land Mangement, Denver, CO.

Sharitz, R. R. 2003. Carolina Bay Wetlands: Unique Habitats of the Southeastern United States. Wetlands 23:550-562.

Vitt, D.H. 2000. Peatlands: Ecosystems dominated by bryophytes. Pages 312-343 in A. J. Shaw and B. Goffinet, editors. Bryophyte biology. Cambridge University Press, Cambridge, UK.


http://www.dep.state.fl.us/water/wetlands/delineation/wetcomm/cypdome.htm

http://www.fs.fed.us/geology/GDE_Level_II_FG_final_March2012.pdf


Appendix 3-B – Inventory Sampling Design Examples

The following case studies provide three examples of different approaches to inventory sample design.

Stratified random sampling of known spring locations using a list frame with random start was used in the Spring Mountains National Recreation Area to design a 5-year Level II inventory program. The project area is divided into strata (based on geography or some other variable), and within each strata sites are randomly selected so that each strata is accurately represented.

Stratified random sampling design using the Generalized Random Tessellation Stratified (GRTS) method developed by the U.S. Environmental Protection Agency (Olsen 2005, U.S. EPA 2008) for aquatic resources was used to sample potential peatlands within the Grand Mesa-Uncompahgre-Gunnison National Forests using an inventory protocol equivalent to the Level II Field Guide.

A complete sample of all GDEs within a watershed was conducted in the Frasier Experimental Forest, managed by the Rocky Mountain Research Station, using the Level I Field guide supplemented with additional data collection to meet inventory requirements.

Information included in each of the case studies only illustrates the sampling design (including objectives) and does not discuss the results of the inventory or include information on resulting inventory costs.

3-B.1 Stratified Random Sampling of Known Springs

The sampling design used by the Spring Mountains National Recreation Area (SMNRA) was intended to establish a 5-year program to sample all known springs within the SMNRA to provide a representative sample across major watersheds in each of the sampling years. This design provided the SMNRA the ability to compare inventory data between each of the sampling years and the ability to characterize springs within the SMNRA once the first sample year was completed.

The following provides an overview of the management setting and methods used in designing a random stratified sample over the five-year program period. To facilitate inventory design, springs were stratified using 4th level hydrologic unit code (HUC) and a 20 percent sample of the springs was selected for inventory using a design technique known as a “list frame with random start.” This method can also be applied to develop a single sample that could be accomplished over multiple years.

Case Study – Spring Mountains National Recreation Area

The Spring Mountains National Recreation Area (SMNRA) includes approximately 316,000 acres of National Forest System lands managed by the Humboldt-Toiyabe National Forest. The SMNRA is located approximately 20 miles northwest of Las Vegas, NV and is situated on Great Basin/Mojave Desert ecological subsection boundary. The Spring Mountains’ ecosystem has long been recognized as an island of endemism, harboring flora and fauna found nowhere else in the world. Conservation of the species endemic to and resident in the Spring Mountains is a goal described in the Organic Act for the SMNRA (Public Law 102-63, August 4, 1993).



Springs and riparian areas within the SMNRA provide habitats for and sustain a disproportionate number of species compared to general uplands. The SMNRA landscape analysis (ENTRIX 2008) identified a total of 149 springs within the SMNRA (see fig. 3-B.1-1).

Figure 3-B.1-1–Distribution of springs within the SMNRA.

Recognizing the importance of these sites to the sustainability of many species identified as species of concern and species of interest, the SMNRA inventory and monitoring strategy (Solem et al. 2008) focused additional attention on these areas. A complete sample of all springs within the SMNRA using a 5-year sampling program was established. To ensure information resulting from the sampling could be used as soon as possible, a 20 percent random sample stratified by major watershed (4 th level hydrologic unit code) was specified for each sample year.

Sampling Program Selection Summary

The methodology used to develop the 5-year sampling program utilized a “list frame with a random start” to develop a systematic (stratified random) sampling schedule. The primary factor considered during the development of the sampling schedule was a balanced geographic representation across the four 4th code hydrologic units (or HUCs) within the SMNRA. The 4th code hydrologic units were used as strata so that:

1. Each HUC would be an equal proportion of its sites selected each year, which allows for statistical inference to be made about each HUC each year;

2. A regional event (such as fire) would not affect a disproportionate amount of sites for a HUC, or the ability to collect data in a HUC in a given year.



In summary, the first step involves organizing or stratifying the spring sites to be inventoried by 4 th code hydrologic unit. Annual sampling “quotas” for each 4th code hydrologic unit were determined based on the number of sites within each 4th code hydrologic unit. Sites were assigned a random 5-digit number and then selected by sample year using a random start within the list frame (see table 3-B.1-1) until each HUC quota was met. The results by 4th Code Hydrologic Unit are shown in table 3-B.1-3.

Site Selection Process

Step 1 – A list frame (table 3-B.1-1) was established by assigning 5 digits random numbers to each sample site provided by the SMNRA. Sample sites were then sorted by ascending order of the random numbers. The 4th code hydrologic unit was identified for each sample site.

Step 2 – The starting point was determined for each 4th code hydrologic unit in each sample year using the right hand digit of the random number assigned to each site. The first “1” for a sample site for each 4th code hydrologic unit determined the starting point for sample year 1. Successive sample years used the first “2”, “3”, etc. to determine the sample point. This process progressed from right to left within the random number digits until a starting point was determined.

Step 3 – For sites not selected as a starting point, a sample year was assigned using the right hand digit of the random number assigned to a sample site using the following rule:

0 and 5 = Sample Year 11 and 6 = Sample Year 22 and 7 = Sample Year 33 and 8 = Sample Year 4

4 and 9 = Sample Year 5

Step 4 – Using the starting point as the first site in each 4th code hydrologic unit in each sample year, sample sites were selected in descending order until the following annual quotas were reached:

15010015 = 11 Sites16060015 = 14 Sites16060014 = 3 or 4 Sites

18090202 = 1 Site

If the quota was exceeded, those sites constituted a pool from which sites were selected when the quota could not be reached. These sites were assigned to a sample year based on the next digit to the left until a sample year’s quota was achieved.

Step 5 –An annual sampling schedule was developed which included each site’s name, 6 th code hydrologic unit, access zone, and other location information.

Step 6 –The location of sample sites for each sample year and access zone was calculated to determine if any sample year had a disproportionate number of high-cost, difficult access sites. The resulting site selection did not result in a disproportionate number of difficult access sites within any specific sample year so no adjustment was made at this point.



Table 3-B.1-1–SMNRA List Frame.

List Frame Structure and Key

1. Random numbers are assigned to each spring and springs are listed by ascending random number.2. Within the Sample Schedule Selection columns, numbers represent springs selected based on assigned random numbers using the criteria described above.3. Samples in each year are limited by a quota (20%) of springs/HUC/Yr. Starting point for each HUC by sample year identified by color and designated as: 1 Sample sites assigned to other sample years because a quota has been reached are designated as:

4. Within the Sample Year by HUC columns, numbers represent the Sample Year for each spring based on the sample schedule selections.

SPRING NAME Random #

Sample Schedule Selection Sample Year by HUCYear

1Year

2Year

3Year

4Year

5HUC 4

15010015HUC 4

16060014HUC 4

16060015HUC 4

18090202No Name - 36 01335 1 4WOOD SPRING 01739 1 4No Name - 68 02403 10 4CRYSTAL SP 02807 14 3No Name - 78 03212 1 2COUGAR SP 03471 1 1MARY JANE F 03875 9 1No Name - 88 04280 10 1No Name - 35 04539 2 5JAYBIRD SP 04943 1 4No Name - 10 05607 1 5No Name - 105 06012 1 2No Name - 112 06675 10 1No Name - 69 07743 11 4No Name - 134 08148 1 3No Name - 174 09216 2 2No Name - 98 09880 11 1No Name - 120 10284 1 5No Name - 77 10689 1 5No Name - 38 10948 1 5No Name - 101 11352 1 4No Name - 81 12016 1 1No Name - 57 12420 12 3TROUT SPRING 13084 2 5COAL SPRING 13893 2 4BIG TIMB SP 14557 3 5No Name - 94 17097 9 3CC SPRING 17357 2 3No Name - 26 18166 1 3No Name - 129 18425 10 3





1Year

2Year

3Year

4Year

5HUC 4

15010015HUC 4

16060014HUC 4

16060015HUC 4

18090202WILLOW SP 19493 2 4HRSSHUTM SP 20302 3 3No Name - 12 20561 1 1No Name - 89 22438 3 4No Name - 17 22697 4 3TROUGH SP 23102 5 3MUMMY SP 23765 11 2No Name - 74 24170 1 3No Name - 58 24574 2 5No Name - 156 24833 4 4No Name - 32 25238 3 4No Name - 83 25642 6 3SNTA CRZ SP 25902 7 3CAVE SPRING 2 26306 3 2POTOSI SP 26711 4 2BILL SMI SP 27374 3 5No Name - 102 27779 3 5HORSE SP 28038 5 4No Name - 30 29915 2 1BIG FALLS 30174 4 5No Name - 121 30983 2 4No Name - 177 32715 2 1No Name - 130 33119 5 5DEER CRK SP 33379 6 5No Name - 175 34188 6 4FLETCHER SP 34447 2 3No Name - 124 34851 1 1MAZIE SP 35919 7 5MULE SP 36324 4 5No Name - 46 36583 7 4No Name - 171 36987 8 3LEE SPRING 37392 9 3No Name - 20 38719 5 5No Name - 71 39787 3 3GUZZLER 40855 3 1No Name - 118 41664 8 5LITTLE FALL 42328 3 4No Name - 123 42328 4 4No Name - 106 43801 2 2No Name - 22 45128 8 4COLD CRK SP 45532 2 3No Name - 51 46196 3 2ROCK SPRING 47005 2 1



No Name - 144 49141 5 2No Name - 56 49805 2 1





1Year

2Year

3Year

4Year

5HUC 4

15010015HUC 4

16060014HUC 4

16060015HUC 4

18090202No Name - 108 50210 3 1No Name - 170 50469 6 5No Name - 172 50873 9 4No Name - 103 51941 4 2No Name - 104 52346 6 2No Name - 24 53009 7 5No Name - 28 53414 8 5No Name - 115 53673 10 4No Name - 135 54078 5 4No Name - 162 54482 10 3No Name - 73 54741 5 2No Name - 145 55146 7 2No Name - 40 55550 4 1BUCK SPRING 56618 11 4No Name - 66 56877 4 3No Name - 125 57282 5 3No Name - 53 57686 8 2GOLD SPRING 57946 1 2No Name - 84 58350 3 1No Name - 99 58755 4 1No Name - 100 59014 9 5No Name - 127 60082 11 3No Name - 62 61554 10 5No Name - 54 62218 12 4No Name - 39 63286 9 2YOUNTS SP 63691 10 2No Name - 61 64354 11 5ROSEBUD SP 65423 13 4LW DR CR SP 65827 6 3No Name - 91 67963 14 4WHISKEY SP 68627 3 3No Name - 72 69031 6 2No Name - 165 69695 4 1LOST CBN SP 70763 12 5No Name - 163 71831 11 2No Name - 21 72236 12 2No Name - 164 72899 9 5No Name - 19 74372 12 3RAINBOW SP 75036 13 2PEAK SPRING 76104 10 5No Name - 65 77172 7 3No Name - 114 78240 5 1No Name - 48 78645 6 1



No Name - 167 79308 11 1No Name - 15 79713 12 1





1Year

2Year

3Year

4Year

5HUC 4

15010015HUC 4

16060014HUC 4

16060015HUC 4

18090202No Name - 27 80781 2 2MCFARLND SP 82513 4 4No Name - 142 82917 13 3No Name - 97 83985 5 1No Name - 109 84649 11 3STANL B SP 85053 6 4No Name - 33 86122 3 2No Name - 86 86785 7 1KIUP SPRING 87853 13 5No Name - 82 88258 7 4No Name - 76 89326 7 2No Name - 50 89585 6 1No Name - 126 89990 7 1EDNA GRY SP 91721 8 2CLARK SPRING 92126 14 2WHEELR WELL 92530 8 1No Name - 44 92789 11 5ROSES SPRING 93598 13 1No Name - 79 93858 8 4No Name - 7 94262 1 2No Name - 113 94926 9 2No Name - 67 95330 8 1No Name - 146 96398 14 1No Name - 85 97062 8 3No Name - 117 97871 10 2No Name - 11 98130 1 3WOOD CYN SP 98535 9 1CAVE SPRING 99198 14 5No Name - 49 99603 9 4



Sampling Schedule

Table 3B.1-2 displays sites in the SMNRA to be sampled the first year of the 5-year program. Similar tables were generated for the other four years of the program. The sites are listed by watershed (4 th code hydrologic unit) and by 6th code hydrologic unit to facilitate crew scheduling.

Table 3-B.1-2–Springs to be sampled during Program Year 1.

Watershed (HUC-4) HUC-6 Spring Name Distance ZoneLas Vegas Wash

150000151001 No Name - 50 <1/2 mileNo Name - 56 <1/2 mile

150100152002 Mary Jane Falls 1/2 mile - 1 mileNo Name - 108 1/2 mile - 1 mileNo Name - 112 <1/2 mileNo Name - 124 <1/2 mileNo Name - 126 <1/2 mileNo Name - 67 <1/2 mileNo Name - 97 1/2 mile - 1 mileNo Name - 98 1/2 mile - 1 mileNo Name - 99 1/2 mile - 1 mile

Sand Spring-Tikaboo Valleys160600149001 Guzzler <1/2 mile160600149002 Cougar Spring <1/2 mile

No Name - 30 1/2 mile - 1 mileNo Name - 40 <1/2 mile

Ivanpah-Pahrump Valleys160600151001 No Name - 15 <1/2 mile

No Name - 48 1 mile - 2 milesNo Name - 84 1/2 mile - 1 mileNo Name - 86 1/2 mile - 1 mileNo Name - 88 <1/2 mileWood Canyon Sp 1/2 mile - 1 mile

160600151002 No Name - 114 1 mile - 2 milesNo Name - 81 <1/2 mileWheeler Well <1/2 mile

160600151004 No Name - 165 1/2 mile - 1 mileNo Name - 167 1 mile - 2 milesNo Name - 177 1/2 mile - 1 mileRoses Spring 1 mile - 2 miles

160600151005 No Name - 146 1 mile - 2 milesUpper Amargosa

180902021514 No Name - 12 <1/2 mile180902027003 Rock Spring <1/2 mile

Similar tables were constructed for each of the five inventory program years. Table 3-B.1-3 displays the number of sites sampled during each program year.



Table 3-B.1-3–Sampling schedule by 4th Code Hydrologic Unit (HUC).

Region HUC-4 Name HUC-4 Year 1 Year 2 Year 3 Year 4 Year 5 TOTAL

Lower Colorado

Las VegasWash 15010015 11 11 12 11 11 56

Great Basin Sand Spring-TikabooValleys 16060014 4 3 3 4 3 17

Great Basin Ivanpah-PahrumpValleys 16060015 14 14 14 14 14 70

California UpperAmargosa 18090202 2 1 1 1 1 6

TOTAL 31 29 30 30 29 149

Accessibility of sample sites was assessed to determine if there was a disproportionate number of sites with difficult access (and higher costs) within any sample year from NFS roads. The goal of this evaluation was to balance access costs across sample years to avoid large changes in inventory costs from year to year. Table 3-B.1-4 summarizes the results of this site access evaluation.

Table 3-B.1-4–Distribution of springs sampled by year by access zone.

Access Zones Year 1 Year 2 Year 3 Year 4 Year 5 Total< ½ mile 15 18 18 21 18 90

½ mile – 1 mile 11 7 7 5 5 351 mile – 2 miles 5 4 4 3 3 19

> 2 miles 0 0 1 1 3 5Total 31 29 30 30 29 149

Program Adjustments

After the first year of inventory, a decision was made to modify the sample schedule to inventory “clusters” of springs at the same locations to minimize travel costs to the same location over the course of the inventory program. Other adjustments were made by the crew leader to provide for crew safety (e.g., abandoning attempts to access springs on cliff faces or other hazardous terrain) or to avoid drug enforcement operations. In these instances, inventory of the sites were deferred until the sites could be safely accessed or a decision was made not to inventory sites that were extremely hazardous to access.



References

ENTRIX, Inc. 2008. Spring Mountains National Recreation Area landscape analysis. Unpublished report submitted to the U.S. Department of Agriculture, Forest Service, Humboldt-Toiyabe National Forest, Las Vegas, NV.

Olsen, A.R. 2005. Generalized random tessellation stratified (GRTS) spatially-balanced survey designs for aquatic resources. Corvallis, OR: U. S. Environmental Protection Agency. http://epa.gov/nheerl/arm/documents/ presents/grts_ss.pdf.

Solem, S.J., et al. 2008. Comprehensive inventory and monitoring strategy for conserving biological resources of the Spring Mountains National Recreation Area. El Paso, TX; Management and Engineering Technologies International, Inc. (METI) and Albuquerque, NM: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 125 p.

Solem, S.J.; Pendleton, B.K.; Coles-Ritchie, M.; Ledbetter, J.; McKelvey, K.S.; Berg, J.; Nelson, K.; Menlove, J. 2011. 2010 annual report: monitoring and evaluation for conserving biological resources of the Spring Mountains National Recreation Area. El Paso, TX: Management and Engineering Technologies International, Inc. (METI) and Albuquerque, NM: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 117 p.

U.S. Environmental Protection Agency (EPA). 2008. Specific design information –illustrative examples. Web page. last updated April 6, 2011. Retrieved January 17, 2012, from http://www.epa.gov/nheerl/arm/designing/design_intro.htm.


http://epa.gov/nheerl/arm/documents/


3-B.2 Grid-Based Stratified Random Sampling Design of Potential Peatlands

This design method is useful if you do not know the locations of potential GDE sites within a large analysis area and you have similar inventory objectives related to GDE distribution, characterization, condition, and are concerned about management effects on these resources. This sampling design uses the Generalized Random Tessellation Stratified (GRTS) method developed by the U.S. Environmental Protection Agency (Olsen 2005, U. S. Environmental Protection Agency 2008) for aquatic resources. Procedures used are summarized and a full report is available at: http://www.fs.usda.gov/detailfull/gmug/landmanagement/resourcemanagement/?cid=stelprdb5363685&width=full

Case Study – Grand Mesa, Uncompahgre, and Gunnison National Forests

Note: The following information is excerpted from the information provided on the website and in the report.

The Grand Mesa, Uncompahgre, and Gunnison National Forests (GMUG) began an effort in 2008 to better understand the abundance and distribution of fens on lands managed by the GMUG. To complete this effort, the forest assembled a multi-disciplinary team composed of specialists in soil science, geology/hydrogeology, hydrology, botany, and range management. This group was directed by forest leadership to provide information in three areas:

Distribution and characterization of fens Evaluation of the condition of fens Land management implications for fens

The inventory report details the results of efforts to better characterize the unique and important fen resource present on GMUG lands. It is intended to inform local resource specialists on the GMUG, as well as others interested in wetland and fen research, of the methods and results of all fen investigation efforts that have been conducted on the GMUG.

Inventory Design

Prior to the selection of a field verification sample set, the Forest was divided into twelve landscape areas based on similarities of geologic and hydrologic settings, climate, and glaciation. Photointerpretation of the entire Grand Mesa, Uncompahgre, and Gunnison National Forests for potential fens was completed in 2009, identifying 3,270 potential fen sites covering 17,485 acres, about 0.65% of the Forest. A 1 x1 grid was overlaid on each landscape area and those potential sites that occurred at a grid intersection were identified for sampling. As a result about two hundred 1 × 1 km cells across the Forest were selected for inventory using a spatially balanced sampling process.

During the field seasons of 2009 and 2010, 204 of those cells and 336 potential fens were visited and sampled. One hundred forty-seven fens were documented and complete data collected. From this sample it can be estimated with 95% confidence that there are approximately 1,738 (±827) fens covering 11,034 (±6,936) acres on GMUG lands.


http://www.fs.usda.gov/detailfull/gmug/landmanagement/resourcemanagement/?cid=stelprdb5363685&width=full

http://www.fs.usda.gov/detailfull/gmug/landmanagement/resourcemanagement/?cid=stelprdb5363685&width=full


Photo interpretation

Several monitoring and research projects conducted in the past decade identified fens on selected portions of the Grand Mesa, Uncompahgre, and Gunnison National Forests. These studies have resulted in knowledge about some fens on the Grand Mesa, the northern San Juan Mountains, and the Taylor Park area (Bathke 2000-2001-2003, Austin 2008, Chimner et al. 2008). Those results provided a starting point for development of a geographic information system (GIS) layer representing potential fens. They also served to develop a “search or training image” by examining the aerial photo characteristics (color, texture, landform position) of known fens (notably those of Bathke 2000-2001-2003, Austin 2008). Because fens are a narrow subset of wetlands and the complex pattern in which they normally occur, a broad wetland search image was used during the photointerpretation phase.

Strictly as a matter of convenience, the National Forests were subdivided into seven geographic “photointerpretation areas” to facilitate the photointerpretation process. To assure forest-wide consistency, previously identified fens were reviewed and included or omitted from the geodatabase; and new sites were delineated and added.

The photointerpretation step of this inventory used 10 × 10 inch prints of natural-color aerial photographs, taken of the National Forests in 2005, at an approximate scale of 1:16,000. Each photo was scanned with a magnifying glass; if an area was found that might possibly fit the search image, that portion of the photo was examined using a hand stereoscope (10-15×). Based on the search training image described above, all potential fen sites (PFS) were delineated that were visible on the aerial photographs. There were no specified lower limits on size of delineated sites; the smallest site delineated was about 0.05 acre (0.02 hectare). Potential fen sites were delineated on-screen into a geodatabase in ArcMap® (ESRI 2009), with NAIP imagery, 1 m resolution, 2005 (USDA Farm Service Agency 2010) as a background. In this report, the term potential fen site (PFS) is used to refer to the results of the photointerpretation.

A total of 3,270 potential fen sites were identified on National Forest System lands, covering an estimated 17,485 acres, about 0.6 % of the land under administration of the Grand Mesa, Uncompahgre, and Gunnison National Forests.

Sampling Design

To adequately sample the variety of settings on the National Forests, a stratification method was based on geology, climate, ecological landscape units, and glaciation, as described above used. This stratification resulted in twelve landscape areas.

A regular grid network of 1 Km × 1 Km cells was superimposed across the forest. This grid was stratified into two classes:

1. Those cells that had potential fen sites in them2. Those cells that did not.

Suggestions from statisticians at the Rocky Mountain Research Station to concentrate sampling effort to the cells where potential fen sites are known to be present, and minimize the effort in areas where potential fen sites are uncommon were then incorporated into the design.



A sample was developed utilizing the Generalized Random Tessellation Stratified (GRTS) method, as commonly used for aquatic resources by the U. S. Environmental Protection Agency (Olsen 2005, U. S. Environmental Protection Agency 2008). A spatially balanced sample of 198 1 × 1 Km cells was then selected from the set of grid cells containing photo-interpreted potential fen sites using the GRTS sampling method. Cells were sampled at an equal proportion for all the landscape areas, since different landscape areas had different numbers and sizes of potential fen sites. The sample size of 198 cells was constrained by funding and field time available to conduct field work. It was thought that 198 cells was a sample that could be visited by two field crews in a single field season.

Figure 3-B.2-1 displays the results of the stratification and selection process that determined the 198 cells for field examination across the twelve landscape areas on the GMUG NF. The objective of the field verification was to visit each cell in the sample to evaluate all photo-interpreted potential fen sites as well as to identify any fens within the cell that may have been omitted during photointerpretation. Almost 18% of the National Forests is covered by cells that contain potential fen sites.

*Note: Solid-colored cells show the 198 cells that make up the GRTS sample. The gray-outlined cells are cells with potential fen sites remaining after the GRTS sample was chosen.

Figure 3-B.2-1–GRTS sample sites for the twelve landscape areas.*

In several cases, it was necessary to substitute another cell for a selected cell. This usually occurred because most of the cell was on private land or was not safely accessible by field crews. In these cases,



the GRTS method allows the next available cell in the sampling sequence to be chosen while maintaining a spatially balanced sample. Seven cells needed to be substituted from the original sample.

Photo Interpretation Accuracy Assessment Using an Independent Review

The GRTS sampling methodology was used to select a sample for a second photointerpretation examination of cells that didn’t contain any PFS. A total of 242 cells were selected for review (2% of all cells without PFS identified). The distribution of those cells is shown in figure 3-B.2-2. The purpose was to use an independent photo-interpreter to identify the possible extent of ‘missed’ potential fen sites as a measure of the quality of the initial photointerpretation. The same methods and materials were utilized as in the original photointerpretation process. Eight potential fen sites within seven separate cells were identified, which represents slightly less than 3% of the 242 cells reviewed. These results suggest that the initial photointerpretation delineated almost all of the potential fen sites.

* Note: The green squares show the 2 percent of cells without potential fen sites selected for validation

Figure 3-B.2-2–Cells without Potential Fen Sites (PFS) selected for sampling.*

Field Sampling

The GMUG designed and tested a protocol for investigating each 1 × 1 Km cell, and gathering appropriate information about each fen within that cell. The methodology used was part of the



foundation for developing the GDE Inventory Field Guides and includes many of the elements used in Level II inventory procedures.



References

Austin, G.T.; Leary, P.J. 2008. Laval host plants of butterflies in Nevada. Hol Lepid. 12: 1–134

Bathke, David M. 2000. Report on wetlands survey, Gunnison National Forest, Summer 2000. Report to Gunnison Ranger District, USDA Forest Service, Gunnison, Colorado.

Bathke, David M. 2001. Report on wetlands survey, Gunnison National Forest, Summer 2001. Report to Gunnison Ranger District, USDA Forest Service, Gunnison, Colorado.

Bathke, David M. 2003. Report on wetland site W33 (Lily Pond) and nearby sites. Report to Gunnison Ranger District, USDA Forest Service, Gunnison, Colorado.

Chimner, R.A.; D.J. Cooper; K. Nydick; and J. Lemly. 2008. Final report: Regional assessment of fen distribution, condition, and restoration needs, San Juan Mountains. 212 pp. Silverton, CO: Mountain Studies Institute. http://www.mountainstudies.org/Research/pdf/Fen05_EPAFinalReport_ALL.pdf.

ESRI. 2009. ArcMap®, Version 9.3. Redlands, CA: Environmental Systems Research Institute.

Olsen, A.R. 2005. Generalized random tessellation stratified (GRTS) spatially-balanced survey designs for aquatic resources. Corvallis, OR: U. S. Environmental Protection Agency. http://epa.gov/nheerl/arm/documents/ presents/grts_ss.pdf.

U.S. Environmental Protection Agency (EPA). 2008. Specific design information –illustrative examples. Web page. last updated April 6, 2011. Retrieved January 17, 2012, from http://www.epa.gov/nheerl/arm/designing/design_intro.htm.

USDA Farm Service Agency. 2010. National Agriculture Imagery Program (NAIP). Salt Lake City, UT: USDA Farm Service Agency. http://www.fsa.usda.gov/FSA/apfoapp?area=home&subject=prog&topic=nai/.


http://www.fsa.usda.gov/FSA/apfoapp?area=home&subject=prog&topic=nai/

http://epa.gov/nheerl/arm/documents/

http://www.mountainstudies.org/Research/pdf/Fen05_EPAFinalReport_ALL.pdf


3-B.3 Complete Project Area Sampling Approach

The sampling approach used in the Fraser Experimental Forest was designed to provide a complete inventory of GDEs to support research objectives. Although this is not a typical approach that would be used on most NFS lands, it does provide an example of how to accomplish this type of inventory for a portion of an administrative unit.

Case Study – Fraser Experimental Forest

The Fraser Experimental Forest (FEF) is part of the national network of experimental forests and ranges, a land base authorized by Congress and designated by the Chiefs of the Forest Service as locations for long-term research (Adams et al. 2004). FEF was established in 1937 as a representative site for conducting research in alpine and subalpine ecosystems of the Rocky Mountains. It is located on the Arapaho National Forest, CO, about 112 km northwest of Denver, on the west side of the Continental Divide, and is co-managed by the Sulfur Ranger District and the U.S. Forest Service Rocky Mountain Research Station. The west, east, and southern boundaries of FEF essentially delineate the upper portion of the St. Louis Creek watershed (fig. 3-B.3-1), which includes 18 sub-basins (table 3-B.3-1). FEF is 9,308 ha in area.

Past research at FEF has focused on hydrologic relationships, ecosystem function, and biogeochemical processes. Current research addresses questions about linkages between forests, riparian areas, and streams, focusing on mechanisms important in nutrient cycling, snow hydrology, and ecosystem carbon dynamics. A recent study conducted at FEF highlighted the importance of groundwater as part of headwater stream networks (La-Perriere et al. 2011), and the need to consider springs and groundwater-dependent wetlands in aspects of ongoing research. Implementation of the draft GDE protocol at FEF provided the opportunity to test and evaluate the basic methods in the field, and also to collect information that would directly inform and benefit current and future research at FEF.

Our goal was to conduct a complete inventory of springs and groundwater-dependent wetlands within the FEF boundary (fig. 3-B.3-1) to address the following research questions:

How are springs and wetlands at FEF distributed relative to slope, aspect, elevation, distance to streams, underlying geology, and locations of snowpack accumulation?

What are the basic characteristics of the springs and wetlands (GDEs), including size, geomorphic features and location (hydrogeomorphic classes), and hydrologic features (presence of channels, extent of standing water, flow, proximity to late-melting snowpacks)?

How many of the GDEs are fens that may support rare plant or animal taxa (e.g., Boreal Toads and other amphibians)?

For fens (groundwater-dependent peatlands), what is the extent of accumulated peat (peat depth) in relation to geomorphic setting, elevation, and physical characteristics?

To meet research objectives, some aspects of the draft GDE protocols were not implemented, and others were modified. The FEF spring and wetland inventory was conducted over three field seasons (2009–2011).

In 2009, aerial photographs of the FEF were examined to locate potential wetland locations. The photo interpretation was done on 10 x 10 inch prints of natural-color aerial photographs at an approximate scale of 1:16,000. A search image using color, texture, and landform position was developed, and the photos were examined using a magnifying glass and hand stereoscope (10–15X). Potential wetland



locations were noted for each sub-basin, and served as the basis for planning field sampling. This method worked reasonably well for identifying locations of alpine wetlands and large, open wetlands. However, the location of most springs and forested wetlands could not be determined using aerial photos.

Essentially, each sub-basin in the FEF was systematically hiked to locate springs and those wetlands that were not readily apparent on aerial photos – a very intensive approach in terms of both time and effort. U.S. Geological Survey topological maps were loaded onto hand-held GPS units, and contours and topographic lines were used as guides to infer the drainage patterns of zero-order catchments and the potential locations of contributing springs. Sub-basins were mostly sampled by hiking adjacent to the stream, with at least one field crew member on each side of the channel, and following any contributing hillslope water to the source, usually a spring. In the open alpine areas, wetlands (apparent on aerial photos) were mostly located in depressions and supported by multiple springs. When field crews arrived at a wetland, they followed any contributing springs to the source and sampled them. In the channel initiation areas of each of the FEF streams (table 3-B.3-1, fig. 3-B.3-1), multiple springs occurred; however, numerous hillslope springs also contributed to most streams throughout each drainage. For some basins, the higher elevation portions, i.e. near channel initiation, were approached from above (alpine ridges) to decrease hiking time.

Field crews consisted of 2-4 people, working together for maximum coverage of a single sub-basin, and staying in contact via hand-held radios. Each sub-basin was hiked and sampled systematically until all portions were covered; the sub-basins that were sampled in each field season are shown in figure 3-B.3-1.

Table 3-B.3-1–Areas of the sub-basins sampled in the Fraser Experimental Forest, CO as part of the spring and wetland inventory (2009–2011).

Basin Area (ha) Basin Area (ha)Short Creek 69.22 Byers Creek 333.27Ental Creek 102.5 Deadhorse Creek 350.19Birthday Creek 103.03 Fool Creek 394.56Lexen Creek 137.08 Upper St. Louis Creek 656.32Spruce Creek 220.89 West St. Louis Creek 659.54King Creek 236.41 Range Creek 776.32Mine Creek 253.91 Iron Creek 786.48Gordon Creek 277.37 East St. Louis Creek 979.61Lunch Creek 290.32 St. Louis Creek (main stem) 2709.21



Figure 3-B.3-1–Location of sampled springs in the Fraser Experimental Forest, 2009–2011.

References

Adams et al. 2004. Full citations will be provided following review.

LaPerriere-Nelson et al.2011. Full citations will be provided following review.



APPENDIX 3-C – SAMPLE COST ESTIMATION WORKSHEETS

Cost estimation worksheets using 2010 cost information for Level I and Level II inventories.

3-C.1: Sample Level I Cost Estimation Worksheet

Work Breakdown Time Estimates (Hours)

Task/Activity Project Sponsor

Crew Leader (Hydro/Bio)

Hydrologist or Botanist

1.0 Training and Inventory Logistics/Planning 36 84 281.1 GDE Inventory Training (Webinar/On-Site) 16 8 81.2 Inventory Program Planning 4 16 01.3 Logistics 4 16 01.4 Field work prep/planning/polygon delineation 8 40 16

Travel Time 4 4 42.0 Spring Inventories (60 sites) 30 180 1682.1 Group A (20 sites/week) 0 40 402.2 Group B (20 sites/week) 0 40 402.3 Group C (20 sites/week) 0 40 402.4 QA/QC 18 0 02.5 GDE Data Download (MS Access)/Inventory Files 0 36 24

Travel Time 12 24 243.0 Data Analysis and Compilation 20 48 123.1 Site Reports 4 16 43.2 Planning/Analysis Area Report 16 32 84.0 After Action Evaluation 12 8 44.1 Protocol Evaluation and Recommended Changes 4 4 44.1 Protocol and Sampling Design Modification 8 4 0

Totals 78 272 212

Inventory Cost EstimationForest Service Staff Hours Rate/Hr. TotalsProject Sponsor - GS 9/11/12 District or Forest Staff 78 $27.31 $2,130.18Crew Leader - GS 7/9 (Hydrologist/Botanist) 272 $27.31 $7,428.32Hydrologist or Biological Technician (GS 7/9) 212 $22.57 $4,784.84Total Employee Labor Costs Subtotal $14,343.34

Operational ExpensesField Travel/Per Diem 36 days $55/day $3,960.00

Subtotal Travel $3,960.00Field Data Recorder $1,000.00

Field Equipment $500.00Vehicles $3,000.00

Miscellaneous Expenses $250.00Subtotal Equipment/Other Expenses $4,750.00

Total Operational Expenses $8,710.00Total Employee and Operational Expenses $23,053.34

Project Administration 10% $2,305.33

Total Inventory Costs $25,358.67Salary Rates = Cost to Government (example uses bold GS rates) Cost/Site $422.64



3-C.2: Sample Level II Cost Estimation Worksheet

Work Breakdown Time Estimates (Hours)

Task/Activity Project Sponsor Crew Leader Hydrologist or

GeologistBotany or Bio

Tech.1.0 Training and Inventory Logistics/Planning 52 152 36 201.1 GDE Inventory Training (Webinar/On-Site) 24 16 16 161.2 Inventory Program Planning 8 16 0 01.3 Logistics 8 16 0 01.4 Field work prep/planning/polygon delineation 8 100 16 0

Travel Time 4 4 4 42.0 Spring Inventories (30 sites) 30 180 168 1682.1 Group A (10 sites/week) 0 40 40 402.2 Group B (10 sites/week) 0 40 40 402.3 Group C (10 sites/week) 0 40 40 402.4 QA/QC 18 0 0 02.5 GDE Data Download (MS Access)/Inventory Files 0 36 24 24

Travel Time 12 24 24 243.0 Data Analysis and Compilation 20 48 12 123.1 Site Reports 4 16 4 43.2 Planning/Analysis Area Report 16 32 8 84.0 After Action Evaluation 20 12 4 44.1 Protocol Evaluation and Recommended Changes 4 4 4 44.1 Protocol and Sampling Design Modification 16 8 0 0

Totals 102 344 220 204

Inventory Cost Estimation

Forest Service Staff Hours Rate/Hr. Totals

Project Sponsor - GS 11/12 District or Forest Staff 102 $32.72 $3,337.44

Crew Leader - GS 9/11 344 $27.31 $9,394.64

Hydrologist or Geology Technician (GS 9/11) 220 $22.57 $4,965.40

Botanist/Biology Technician (GS 9/11) 204 $22.57 $4,604.28

Total Employee Labor Costs Subtotal $22,301.76

Operational Expenses

Field Travel/Per Diem 36 days/3 $55/day $5,940.00



Subtotal Travel $5,940.00

Field Data Recorder $1,000.00

Field Equipment $500.00

Vehicles $3,000.00

Miscellaneous Expenses $250.00

Subtotal Equipment/Other Expenses $4,750.00

Total Operational Expenses $10,690.00

Total Employee and Operational Expenses $32,991.76

Project Administration 10% $3,299.18

Total Inventory Costs $36,290.94

Salary Rates = Cost to Government (example uses bold GS rates) Cost/Site $1,209.70



APPENDIX 3-D – SAMPLE REPORTS

Examples of standard reports generated from the GDE Inventory Database as are provided for Level I Inventories (3-D.1) and Level II inventories (3-D.2). These reports are generated once inventory data are loaded into the database.

An example of an area-wide report generated using data summaries from the GDE Inventory Database (3-D.3) is provided for the Spring Mountains National Recreation Area. This reports compiles information on 77 springs surveyed during 2010–2012.

An example of a site report associated with a mining project on the Kootenai National Forest (3-D.4) uses data from the GDE Level II inventory protocols. A contractor developed this report prior to completion of the GDE database, as a result they could not rely on the use the GDE database report generation tools.

Note: To the extent possible, the original formatting of these reports has been retained with the exception of figure and table numbers. Text has been extracted verbatim and not edited during inclusion in this document.

Note To Reviewers: The sample reports and text included in this appendix were extracted from published reports and are provided as examples, therefore, editorial suggestions are not appropriate. Please focus on whether these examples are useful illustrations of different types of reports.



3-D.1: Level I Site Report Example – Wallowa-Whitman National Forest

Site Name: Grouse SpringSite ID: 1182461443294Land Status: USDA Forest Service

Region, Forest: 6, Wallowa-WhitmanDistrict: WhitmanState, County: OR, Baker

Survey Date: 8/5/2010GDE Type (primary): rheocreneGDE Type (secondary): wetlandAspect: West facingElevation: 1885 mArea: 0.1 haDominant Surrounding Vegetation: Tree dominatedSurficial Material: ColluviumLithology: MetamorphicWater Table Type: ApparentInflow Pattern: Ground water dominatedOutflow Pattern: Surface water dominatedOccurrence of Surface Water: Developed channel(s) with flowing water


Dominant Plant Species

Actea rubra

Alnus incana

Carex sp.

Circaea alpina

Glyceria sp.

Picea engelmannii

Ribes lacustre

Urtica dioica

Vegetation Life-form Abundance

Shrub and sub-shrub Most abundant

Forb/herb 2nd most abundant

Graminoid 3rd most abundant

Tree 4th most abundant

Bryophyte 5th most abundant

Plant Species of Interest

Comment

Cirsium arvense invasive

Soil Variable Result

Location of Soil Sample (single location) Center of site

Redoximorphic Features None

Organic Layer Thickness 1 cm fibric, 3 cm hemic

Depth of Hole Gravel at 25 cm

Notes on Soil Patchy soil conditions, rocky substrates with organics


Site Name: Grouse SpringSite ID: 1182461443294Land Status: USDA Forest Service

Region, Forest: 6, Wallowa-WhitmanDistrict: WhitmanState, County: OR, Baker

Hydrologic Variable Result

Water Table Depth (single location) 25 cm

Flow 10.5 gpm

Water Quality (single location)

pH 7.1

Conductivity 138 microS

Temperature 48.6 F

Dissolved Oxygen (DO) 7.1 mg/l

Oxygen-Reduction Potential (ORP) 199 mV

Faunal Category Observation

Vertebrates

Invertebrates Leech

Disturbance Category Observation

Hydrologic Alteration None observed

Soil Alteration Gully erosion

Structures Old skid trail near spring, vegetation mostly healed.

Recreation Impacts None observed

Animal Impacts Grazing or browsing (by ungulates), Wild animals, Trails by animals (includes people)

Miscellaneous Tree cutting

Cultural or Historic Use

Notes Yarding and skid trail above one orifice. Gully possibly from skid trail. Recovering from past logging.

Management Indicators ObservedDegradation from uplandsHydrologic alteration in watershedAdjacent site characteristics do not support site



3-D.2: Level II Site Report Example – Spring Mountains NRA

Site Name: Mack’s Canyon 1Site ID: R4HTSMNRAH2O092Land Status: USDA Forest Service

Region, Forest: 4, Humboldt-ToiyabeDistrict: SMNRAState, County: NV, Clark

Survey Date: 9/28/2010GDE Type (primary): hillslope springGDE Type (secondary): helocreneAspect: 301 degrees (northwest)Elevation: 2497 mArea: 745 square metersDominant Surrounding Vegetation: Tree dominatedSurficial Material: Alluvium, Colluvium, ResiduumLithology: Sedimentary, LimestoneWater Table Type: UnknownInflow Pattern: Groundwater inflow dominatedOutflow Pattern: Surface water outflow dominatedOccurrence of Surface Water: Developed channel(s) with flowing water, Patches of standing water

Mack’s Canyon 1.

Vegetation Attribute Results

Prevalence Index (based on wetland indicator status) 1.8Tree Diameter, Density and Basal Area by species noneBryophyte cover (%) 30.4

Plant Species Cover (%)

Primula fragrans 26.3

Abies concolor 15.3

Apiaceae family 12.0

Carex sp. 10.4

Equisetum laevigatum 7.6

Poa sp. 7.4

Maianthemum stellatum 4.9

Viola sororia 3.8

Juniperus scopulorum 3.3

Aquilegia formosa 2.3

Platanthera sparsiflora 2.1

Parnassia sp. 1.7

Carex subfusca 1.4

Ribe cereum 1.1

Carex aurea 0.6

Rosa woodsii 0.3

Ground Cover Cover (%)

Litter 52.0

Bryophyte 38.5

Basal vegetation 4.7

Water 3.4

Bare soil 0.7

Wood 0.7

Bedrock 0

Boulder 0

Cobble 0

Gravel 0

Stone 0



Site Name: Mack’s Canyon 1Site ID: R4HTSMNRAH2O092Land Status: USDA Forest Service

Region, Forest: 4, Humboldt-ToiyabeDistrict: SMNRAState, County: NV, Clark

Soil Attributes ResultsDepth of organic layer 5 cmThickness of organic layer >50 cmDepth of mineral layer NAList of redoximorphic features redox concentrationsTexture and color sandy loam, 10YR2/2

Hydrologic Attributes ResultsWater table depth average 7 cmFlow 0.13 L/secWater quality

- pH 7.55- Conductivity (uS/cm) 337- Oxygen-reduction potential (ORP) NA- Dissolved oxygen (mg/L) NA- Temperature (degrees C) 6.82

Faunal Category Species Observed

Vertebrates Clark's nutcracker, common raven, crossbill sp., dark-eyed junco, elk, mountain chickadee, northern flicker, redtail hawk, Swainson's thrush

Invertebrates Succineidae Catinella, Planariidae, Elmidae, Limnephilidae, Lycaenidae

Disturbance Category Disturbances Observed

Hydrologic alteration Diversion

Soil alteration Pedestals animal, Pipes, Trails

Structures Fence

Recreation effects Litter, shotgun shells, and a golf ball at site

Animal effects Grazing, Trails, Trampling, Wild animals

Other disturbances Refuse, Tree cutting

Management Indicators Observed

Altered natural surface or subsurface flow patterns

Adjacent site characteristics do not support favorable site conditions



3-D.3: Level II Area-wide Report Example – Spring Mountains NRA

The following example was presented in Appendix D of the Spring Mountains National Recreation Area’s inventory and monitoring Final Program Report for 2010-2012 (USDA Forest Service 2013).

Spring Mountains NRA Inventory and Monitoring Report (Excerpt)

For the 77 springs inventoried from 2010–2012, the average size was 487 square meters (m2 ), the median was 117 m2, and the size range was from 0.75 m2 (Unnamed 41 Spring) to 8,100 m2 (Mountain Springs 4).

Eight different spring types (Springer and Stevens 2008) were observed in the surveys, as well as an “unknown” category. Many sites (44) had just one spring type, while 30 sites had two spring types recorded, and three sites were listed as "unknown" because the sites had been so impacted by human activities that it was not possible to determine the spring type (see table 3-D.3-1). For example, Gold Spring was likely a hillslope spring, but it was excavated to form a pool. Younts Spring was likely a helocrene, but water was pumped and diverted, and there was an extensive amount of earth movement. Unnamed Spring 21 was probably a hillslope spring, but now it is a culvert.

The most common spring types observed were hillslope (spring and/or wetland on a hillslope, generally 20- to 60-degree slope, often with indistinct or multiple sources of groundwater) which was observed at 40 sites, and rheocrene (a flowing spring that emerges directly into one or more stream channels) which was observed at 39 sites. Those two spring types (hillslope and rheocrene) were often observed at the sames site (in 16 cases) and was the most frequently observed combination of spring types.

Table 3-D.3-1–Spring types observed between 2010 and 2012.

Observed Spring Types SitesCave 1Cave, Hanging garden 1Gushet, Hillslope 1Hanging garden 7Hanging garden, Rheocrene 2Helocrene, Hillslope 4Helocrene, Rheocrene 2Hillslope 18Hillslope, Hypocrene 1Hillslope, Rheocrene 16Hypocrene 1Hypocrene, Rheocrene 3Mound-form 1Rheocrene 16Unknown 3TOTAL 77



Vegetation

This summary of the vegetation of springs of the SMNRA uses the combined data from the 2010–2012 inventories. There were 244 vascular plant species recorded during the sampling of the 77 spring sites. The total number of species in the SMNRA is reported to be 1,015 by Niles and Leary (2007). That would indicate that the springs contained 24% of all the species of the SMNRA. An additional small number of plants could not be identified to species, primarily because of limited plant material (including a lack of flowers or fruits) often because of grazing by horses. There were an average of 8.5 species observed per site.

Herbaceous species that were most abundant were scented shootingstar (Primula fragrans, also known as Dodecatheon redolens) with 4.6% cover, Western Columbine (Aquilegia formosa) with 2.7% cover, baltic rush (Juncus balticus) with 1.2% cover, stinging nettle (Urtica dioica) with 0.8% cover, desert baccharis (Baccharis sergiloides) with 0.8% cover, and scratchgrass (Muhlenbergia asperifolia) with 0.7% cover. Moss (byrophyte) cover averaged 5.4%.

The shrub species that were most abundant were Woods' rose (Rosa woodsii) with 7.2% cover, arroyo willow (Salix lasiolepis) with 4.9% cover, desert baccharis (Baccharis sergiloides) with 4.3% cover, fivepetal cliffbush (Jamesia americana) with 2.0% cover, canyon grape (Vitis arizonica) with 1.9% cover, stretchberry (Forestiera pubescens) with 1.3% cover, and narrowleaf willow (Salix exigua) with 1.1% cover. The woody vine western white clematis (Clematis ligusticifolia) had 0.8% cover.

The tree species that were most abundant were white fir (Abies concolor) with 4.5% cover, ponderosa pine (Pinus ponderosa) with 4.2% cover, Rocky Mountain juniper (Juniperus scopulorum) with 3.4% cover, Utah juniper (Juniperus osteosperma) with 1.6% cover, quaking aspen (Populus tremuloides) with 0.9% cover, and Gambel oak (Quercus gambelii) with 0.7% cover. In terms of tree counts, 20 sites (26%) had trees (greater than 5 cm in diameter-at-breast-height or DBH) within the site, and each of those sites had 1 to 21 individual trees. The average DBH of trees observed was 26.8 centimeters and the largest DBH was 107 centimeters. Sites with individual tree species smaller than 5 centimeters DBH were not included in these calculations. The total basal area of trees, at sites with trees, ranged from 0.0007 m2 to 1.8 m2. Some sites had cover from trees that were just outside the site, but had no trees within the site. Eight sites had a standing dead tree (the maximum was two trees). Every site that had standing dead trees also had live trees.

Woody vegetation (shrub or tree) cover was recorded at 90.0% of sites. The average amount of canopy cover of shrubs and trees was 41.6%. A few sites averaged over 100% canopy cover because of multiple layers of woody vegetation (i.e., different species). The maximum canopy cover value was 141.2%.

Non-native species were recorded at 52% of sites. There were a total of 29 non-native plant species observed. The average cover of non-native species at a site was 3.0%. A different but related category of plants are invasive species, which are determined by states or other entities. The only plants observed from the State of Nevada Noxious Weed List were saltcedar (Tamarix ramosissima) and tamarisk (Tamarix chinensis). Other observed species that are considered invasive in other administrative jurisdications were: red brome (Bromus rubens), cheatgrass (Bromus tectorum), dandelion (Taraxicum officianale), yellow sweetclover (Melilotus officianalis), water speedwell (Veronica anagallis aquatica), common reed (Phragmites australis), annual rabbitsfoot grass (Polypogon monspeliensis), and common mullein (Verbascum thapsus).



The only CA species encountered during the 2010–2012 springs surveys were Charleston Mountain angelica (Angelica scabrida) and trianglelobe moonwort (Botrychium ascendens).

Vegetation data were used to calculate a “prevalence index” which is a commonly used method to describe the abundance of wetland vegetation for a site and to determine if a site is a wetland (National Research Council 1995). The prevalence index has been described as a way of characterizing the "wetlandness" of a site (Tiner 1999). The prevalence index is calculated using a weighted average of the species abundance (cover in this case) and the wetland indicator status value (Reed 1988) to characterize a site's vegetation on a scale of 1 (all obligate wetland species) to 5 (all upland species). A value below three is generally considered to be a wetland. For the 77 SMNRA spring sites where vegetation data were collected, the range in the prevalence index values was 1.0 to 4.1, and the average for all sites was 2.4.

Vegetation data for each site were compared to community type classifications described by Manning and Padgett (1995), Nachlinger and Reese (1996), and Weixelman et al. (1996). The dominant vegetation for each site matched relatively well with a community types described in these classifications. The number of sites with each community types is presented in table 3-D.3-2.

Table 3-D.3-2–Vegetation types of the springs inventoried in the SMNRA during 2010–2012.*

Vegetation Type 2010 2011 2012 Total

Aquilegia formosa-Smilacina stellata/Rosa woodsii var. ultramontana Association (Nachlinger and Reese 1996) 4 10 8 22

Baccharis sergiloides Association (Nachlinger and Reese 1996) 4 4 6 14Cirsium clokeyi/Juniperus communis var. depressa Association (Nachlinger and Reese 1996) 3 3 6

Jamesia americana/Petrophytum caespitosum-Ivesia jaegeri Association (Nachlinger and Reese 1996) 1 1

Juncus balticus Community Type (Manning and Padgett 1995) 3 3Juniperus scopulorum/ Epilobium ciliatum Habitat (Nachlinger and Reese 1996) 1 1

Conifer/Rosa woodsii Community Type (Manning and Padgett 1995) 2 2

Rosa woodsii var. ultramontana Association (Nachlinger and Reese 1996) 1 5 4 10

Salix exigua-Peraphyllum ramosissimum Habitat (Nachlinger and Reese 1996) 1 1

Salix lasiolepis/Rosa woodsii var. ultramontana Community Type (Manning and Padgett 1995) 2 4 4 10

*Note: Seven sites had little or no vegetation, and are not included in these totals.

Ground Cover

Ground cover data describe what is on the ground surface and is summarized here as litter and wood (dead plant material, including leaves and branches), rock and gravel (including gravel, cobble, boulder and bedrock), bryophytes, water, or basal vegetation (where the plant emerges from the ground). If there was none of those ground cover types then it was recorded as bare ground. Significant bare ground at a spring could be an indicator of excessive disturbance. The average ground cover for the



springs of the SMNRA is represented in figure 3-D.3-1, with litter and wood being the most abundant type.

Litter & Wood56%

Rock & Gravel16%

Bare13%

Water6%

Bryophyte6%

Basal Vegetation3%

Figure 3-D.3-1–Average ground cover data for the 77 spring sites sampled from 2010–2012.

Soil

Most spring sites in the SMNRA did not have organic soil. At five sites a peat layer was recorded that was 1 to 50 centimeters thick. Among all the sites surveyed, the soil texture was commonly sand and silt and soil colors were 10Y, 10YR, 5G, 5Y, and 5YR. Redoximorphic features were detected at three sites (Mack’s Canyon 1, Mountain Springs 3, and Unnamed 45). A hydrogen sulfide odor was detected in the soil at two sites (Mack’s Canyon 1 and Unnamed 45). At one site (Mountain Springs 3) the soil reacted to HCL. Holes dug for soil sampling averaged 12.7 centimeters in depth.

Hydrology

Measurement of water table depth is primarily intended for wetlands, not for springs, therefore that was generally not measured at the SMNRA sites. At the 10 sites where a water table depth was measured, the average was 6.6 cm.

Flow was measured at springs or runout channels of wetlands at 45 sites (58% of all sites). The average flow was 0.32 L/second, the median flow was 0.13 L/second, with a range of 0.002 to 1.9 L/second. At the other sites there was either no discernible flow or the flow was diffuse and could not be measured.

Table 3-D.3-3 presents data on water quality and various box and whisker plots (see figs. 3-D.3-2 to 3-D.3-6) show the distribution of the hydrologic data for all spring sites sampled during 2010–2012.



Table 3-D.3-3–Water quality data from springs sampled in 2010–2012.

Attribute Minimum Median Average Maximum Sites Measured

Temperature (centigrade) 3.0 11.3 12.0 19.5 n=65

pH 6.5 7.5 7.5 8.6 n=67

Specific Conductance (microsiemens/centimeter) 136.0 496.0 533.2 1011.3 n=64

Oxygen-reduction potential (mV) -76.9 147.0 139.7 270.6 n=48

Dissolved oxygen (mg/L) 1.9 6.0 5.8 10.3 n=36

Note: Not all of the 77 sites had measurements, primarily because of a lack of standing or flowing water.

Temperature of spring water can be an indirect indicator of flow path conditions and recharge events. The large range of spring water temperatures, from 3.0 to 19.5ᵒC (see fig.3-D.3-2), indicates there is a significant variety in spring recharge sources. The coldest springs are likely snowmelt emerging after a short flow path, whereas the highest temperature springs are likely karst or thermal springs – where the water has been transported very rapidly (karst systems) or was brought up from depth where temperatures are much higher.

Figure 3-D.3-2–Distribution of water temperature (centigrade) sampled during 2010–2012.

Mean value is solid blue line and median value is dashed blue line.

Values of pH are an indicator of the acidic/basic condition of the water and explain some variability in the life supported at a site. The moderate range of pH values, from 6.5 to 8.6 (see fig. 3-D.3-3) could be one reason for the high diversity of animals and plants at the springs in the SMNRA.



Figure 3-D.3-3–Distribution of pH values for springs sampled during 2010–2012.


Specific conductance estimates total dissolved solids, and is an indicator of water quality. The range of specific conductance values was 136.0 to 1011.3 µS/cm (see fig. 3-D.3-4). Values of specific conductance can differ greatly from spring to spring because of the contributing groundwater “shed,” regional characteristics, and surficial inputs. The springs with high specific conductance values were likely discharging from karst systems or in areas with grazing ungulates that have added to the dissolved material.

Figure 3-D.3-4–Distribution of specific conductance (microsiemens/centimeter) in water sampled during 2010–2012.


Oxygen-reduction potential (ORP) measures the water’s ability to acquire electrons and, therefore be reduced, which is an indicator of water quality. Values for ORP ranged from -76.9 to 270.6 mV (see fig.3-D.3-5). The springs with higher values likely have well-aerated waters, discharge with more turbidity or have a geochemical composition similar to local precipitation. The springs with lower values are likely those discharging at the end of a long flow path with no aeration.



Figure 3-D.3-5–Distribution of oxidation-reduction potential (ORP) in water sampled during 2010–2012.*

Mean value is solid blue line and median value is dashed blue line.*Note: In 2010 only one site had ORP data.

Dissolved oxygen (DO) affects the types of organisms that can survive in that water. DO values (see fig. 3-D.3-6) ranged from 1.9 to 10.3 mg/L. Low values of DO are likely from water with long, deep flow paths that have little to no access to oxygen (such waters can even be anoxic). Some spring waters are first exposed to oxygen at the spring emergence zone. The level of turbidity at the site also has a strong effect on the amount of DO.

Figure 3-D.3-6–Distribution of dissolved oxygen sampled during 2010–2012.*


*Note: In 2010 only 1 site had dissolved oxygen data).

Fauna

Aquatic macroinvertebrates were found through spot searches at the spring sites. The macroinvertebrates identified to family that were observed most frequently were the following families: caddisflies, order Trichoptera, family Limnephilidae (19% of sites); bee flies, order Diptera, family Bombyliidae (17% of sites); ground beetles, order Coleoptera, family Carabidae (16% of sites); and crane



flies, order Diptera, family Tipulidae (16%). Other macroinvertebrate taxa that were identified to a more general level that were observed most frequently were flatworms, class Turbellaria (26% of sites); flies, order Diptera (40% of sites); beetles, order Coleoptera (27% of sites); and caddisflies, order Trichoptera (26% of sites). It is noteworthy that springsnails (genus Pyrgulopsis, family Hydrobiidae) were found at 7 of 77 (9%) springs (genetic samples were collected unless noted): Crystal Springs (only a few; so no genetic sample), Unnamed 49 Spring, Unnamed 50 Spring (many, but group of horses interfered with collection of genetic sample), Standley B 3 Spring (no genetic sample), Upper Horse Springs, Willow Spring, and Wood Canyon Spring. Through genetic analyses it was determined that both CA species of springsnails, Spring Mountains pyrg (Pyrgulopsis deaconi) and Southeast Nevada pyrg (Pyrgulopsis turbatrix) were present at the spring sites.

Terrestrial vertebrates were observed at a number of spring sites, through observation and spot searches. Over 70 species of animals were observed during the inventories of the 77 sites during 2010–2012. The animals that were most commonly observed (greater than 9% of sites) are listed in the figure 3-D.3-7, while many additional species (mostly birds) were observed at less than 9% of sites.CA terrestrial animal species observed at spring sites were Acastus checkerspot (Chlosyne acastus robusta), Spring Mountains common skipper (Hesperia colorado mojavensis) and Nevada admiral (Limenitus weidemeyerii nevadae).

Figure 3-D.3-7–Percentage of spring sites (n = 77) where the most common terrestrial vertebrates were observed during 2010–2012.

Note: Species observed at less than 9% of sites are not included.



Disturbances

At each site disturbances observed were noted and a summary of the most commonly observed disturbances is presented in figure 3-D.3-8. An additional 27 disturbance types were observed at less than 12% of sites.

Figure 3-D.3-8–Percentage of spring sites (n = 77) where the listed disturbances were observed during 2010-2012.

Note: Disturbances observed at less than 12% of sites are not included.



Management Indicator Tool

A summary of responses to the 25 Management Indicator Tool questions is presented in figure 3-D.3-9 (in the order they appear in the GDE Level II Inventory Field Guide (USDA Forest Service 2012). The responses represented by the bars generally indicate adverse alteration to spring sites. The categories in the lower part of the graph relate to the “administrative context” which was considered to be the same for nearly all sites in the SMNRA.

Figure 3-D.3-9–Percentage of spring sites (n = 77) where management indicators were observed during 2010–2012.

Water rights not filed and/or outstandingWater uses adversely affecting site

Environmental compliance not occurringLand Mgt Plan not providing protection

Other landowner actions affecting siteLand ownership not FS in and around site

Cultural values affect site managementOther disturbances adversely affecting site

Recreation adversely affecting siteHerbivory adversely affecting site

Fencing does not function properlyConstruction & roads adversely affecting

Flow regulation adversely affecting siteInvasive species established

TES, SOI/SOC, focal fauna not as anticipatedFaunal species not as anticipated

TES, SOI/SOC, focal flora not as anticipatedVegetation condition not healthy

Vegetation composition not as anticipatedSoil integrity altered

Runout channel not functioning naturallyLandform stability altered

Water quality changes affecting siteWatershed (surface water) altered

Aquifer (groundwater) altered

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentage of Spring Sites



References

Manning, M.E.; Padgett, W.G. 1995. Riparian community type classification for Humboldt and Toiyabe National Forests, Nevada and eastern California. R4-Ecol-95-01. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Region. 306 p.

Nachlinger, J.; Reese, G.A. 1996. Plant community classification of the Spring Mountains National Recreation Area Clark and Nye Counties, Nevada. The Nature Conservancy, Reno, NV.

National Research Council. 1995. Wetlands: characteristics and boundaries. Washington, DC: National Academy Press.

Niles, W.E.; Leary, P.J. 2007. Annotated checklist of the vascular plants of the Spring Mountains, Clark and Nye Counties, Nevada. Mentzelia. 8: 1–72.

Reed, P.B., Jr. 1988. National list of plant species that occur in wetlands: Intermountain (Region 8). USDI Fish and Wildlife Service, Washington, DC.

Springer, A.E.; Stevens, L. 2008. Spheres of discharge of springs. Hydrogeology Journal. 17: 83–93.

Tiner, R.W. 1999. Wetland indicators: a guide to wetland identification, delineation, classification, and mapping. Boca Raton, FL: Lewis Publishers. Tousignant, M.-Ê.; Pellerin, S.; Brisson, J. 2010

U.S. Department of Agriculture (USDA), Forest Service. 2012. Groundwater-dependent ecosystems: level II inventory field guide: inventory methods for project design and analysis. Gen. Tech. Rep. WO-86b. Washington, DC: U.S. Department of Agriculture, Forest Service. http://www.fs.fed.us/geology/GDE_Level_II_FG_final_March2012.pdf.

U.S. Department of Agriculture (USDA), Forest Service. 2013. Final program report for 2010–2012 monitoring and evaluation for conserving biological resources of the Spring Mountains National Recreation Area. Prepared for the Humboldt-Toiyabe National Forest. El Paso, TX: Management and Engineering Technologies International, Inc. and Albuquerque, NM: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 184 p.

Weixelman, D. A.; Zamudio, D.C; Zamudio, K.A. 1996. Central Nevada riparian field guide. Toiyabe National Forest, Sparks, NV.



3-D.4: Case Study – Montanore Mine GDE Inventory & Monitoring Report

A GDE Level I inventory was conducted of groundwater dependent ecosystems in areas predicted to be affected by dewatering from the proposed Montanore Mine Project, which would involve underground mining of a copper-silver deposit. The project is in the upper Libby Creek drainage in the Cabinet Mountains Wilderness, Kootenai National Forest located in northwest Montana. GDEs in this area include springs, streams, wetlands, and seeps in avalanche chutes. Analysis of the level I inventory data resulted in a Level II inventory and long-term monitoring at one particular site, a spring complex called Spring-8 near the base of an avalanche chute (see fig. 3-D.4-1).

This report presents the results of the Level II inventory as well as supplemental work to support the development of a long-term monitoring program. Long-term monitoring of Spring-8 is designed to detect dewatering effects from mining using piezometers, flow measurements, and vegetation transects.

Figure 3-D.4-1–Photo of Spring-8 (September 23, 2010).

Table 3-D.4-1 presents a site report for the Level II site survey for Spring-8 conducted in September 2010.



Table 3-D.4-1–Site report for Spring-8.

LocationSite Name: Spring-8Survey Date: 9/23/2010Region, Forest: R1, Kootenai NFState: MontanaGeneral AttributesGDE Type: Spring, Helocrene, fenElevation: 4346 ftArea Approx. 75 ft by 100 ft (0.17 acres)Surrounding Vegetation Tree dominatedSurficial Material Alluvium, ColluviumLithology QuartziteGeologic Structures Located on a cross valley faultSoil The soil is hydric; upper 4 in. are roots and organic material; from 4 to 12 in. is a silty

loam with mottling and gleying; from 12 to 16 in. is a fine clay/loam with gleying and a H2S odor; gravel and rocks below 16 to 18 inches. Soil is saturated to or near the surface in most areas. The low chroma, mottling, and gleying are indicators of hydric soils that are anaerobic for a significant part of the growing season.

Fen Characteristics Fen characteristics observed (peat)Hydrologic AttributesWater table type ArtesianInflow pattern Dominated by groundwater inflowOutflow pattern Dominated by surface water outflowSurface water Channels and small poolsWater table depth 0.25 to 1.3 ftFlow estimate 20 to 30 gal/minute

Water Quality (site average)pH 6.05Specific conductance (uS/cm) 15Dissolved oxygen (mg/L) 11.4Oxygen-reduction potential (mv)

230

Temperature (C) 4.92

Fauna No fauna observations were recorded

Human DisturbancesHydrologic alteration NoneSoil alteration NoneStructures NoneRecreation effects Hiking trailAnimal effects Terrestrial animal grazingOther disturbances NoneManagement Indicators Not done



Piezometers – vertical hydraulic gradient monitoring

Four piezometers were installed at the Spring-8 site in September 2010 (see fig. 3-D.4-2). Each drive-point piezometer has a 6-inch long screen interval at the bottom. Depth to water in the upgradient piezometers (8B) was less than 0.4 foot below ground surface, and was 1.0 to 1.3 feet below ground surface in the downgradient piezometers (8A). Based on the water level pairs at each site, vertical hydraulic gradient is slightly upward at the upgradient site (8B) and downward at the downgradient site (8A) (see table 3-D.4-2). The four piezometers will remain at the site to allow future monitoring of groundwater levels and magnitude of the vertical hydraulic gradient.

Figure 3-D.4-2–Spring 8 Trigger Plant monitoring site.

Table 3-D.4-2–Water levels in piezometers and calculated vertical hydraulic gradients.

ID No. Depth(ft bgs)

Casing Stickup(ft bgs)

Depth to Water(ft bgs)

Vertical Hydraulic Gradient (ft)

Piezometer 8A-d 5 1 1.300.25 (downward)Piezometer 8A-s 3 3 1.05

Piezometer 8B-d 5 1 0.250.07 (upward)Piezometer 8B-s 3 3 0.32



Groundwater fingerprinting using oxygen and hydrogen Isotopes, and tritium

Two water samples were collected in September 2010 for analysis of oxygen and hydrogen stable isotopes (oxygen-18 and deuterium) and tritium (for age-dating). The purpose of this sampling is to determine if the groundwater discharging to Spring-8 is older, deep regional groundwater that could be affected by the mine or if it is recent rain or snowmelt derived groundwater less affected by mine dewatering. One of the samples was collected from Spring-8 located in the upper Libby Creek drainage, and the other sample was collected from groundwater inside the Libby Adit (5,220 feet down the adit decline; approximate elevation 3800 feet). The Libby Adit sample was taken from a drill-hole previously used to measure characteristics of a water-bearing fracture system at this location. The results are summarized in table 3-D.4-3.

Table 3-D.4-3–Isotope and age-dating results for two water samples, Montanore Project.

Sample Site Deuterium(relative to VSMOW)

Oxygen-18(relative to VSMOW)

Tritium(Tritium Units or TU)

Spring-8 -116.7 ‰ -15.68‰ 7.34 ± 0.22

Libby Adit -121.5 ‰ -16.41 ‰ 4.35 ± 0.18

VSMOW = Vienna Standard Mean Ocean Water; ‰ = per mil or parts per thousand.

Sample results indicate that the oxygen-18 and deuterium values are similar to results obtained previously from samples collected in 1998/1999/2005 from the Rock Lake area collected during the months of June through October at an elevation of approximately 4950 feet. The range of oxygen-18 and deuterium values for the Rock Lake area samples is approximately -13.5 to -17.5 ‰ and -100 to -128‰, respectively. In general, the lower isotope values indicate more contribution from snow (i.e. June-July-August samples), and the higher isotope values indicate more contribution from rain (i.e. September-October samples). Isotope samples representing ambient groundwater were collected from the Heidelberg Adit (located downgradient from Rock Lake at elevation of approximately 4100 feet) in 1998-1999 (June through October), with resulting oxygen-18 and deuterium values of -15.5 to -16.1‰ and -114.2 to -118.7‰, respectively.

The sample collected from Spring-8 in September 2010 has higher concentrations of oxygen-18 and deuterium than the Libby Adit sample. The relative difference between the values at these two sites is relatively small. However, the difference in values indicates that Spring-8 water may have more contribution from rain; whereas, the lower values for the Libby Adit sample indicates that there may be a greater component of snow recharge (i.e., infiltration of snow melt into bedrock fractures in the high elevation mountain areas).

Sample results for tritium show that the Spring-8 sample has a higher concentration (7.34 Tritium Units (TU)) than the Libby Adit sample (4.35 TU). In general, groundwater that is recharged from precipitation before 1952 when nuclear bomb testing started should have a tritium concentration less than about 0.8 TU; whereas, post-1952 groundwater would have higher tritium concentrations. An exception is that the tritium concentration in very recent precipitation typically is in the range of about 1 to 5 TU. The Spring-8 tritium concentration of 7.34 TU indicates that the water likely is a combination of very recent precipitation from runoff (<5 TU) and slightly older water (in the range of about 5 to 15 TU) that has moved through the subsurface.



The Libby Adit groundwater tritium concentration of 4.35 TU indicates the source could be very recent or a mixture of recent and pre-1952 water. Because of the sample location at a depth of about 1,250 feet below ground surface and 5,220 feet down the adit decline in bedrock, it is concluded that this water likely is supported by some recent precipitation and some older water stored in bedrock fractures.

Assessment of groundwater contribution to Libby Creek

A synoptic flow event was completed along approximately 10,000 feet of upper Libby Creek on September 3, 2010, to identify gaining reaches supported by discharge from the regional groundwater system (see fig. 3-D.4-3). Flow measurements started in the morning at the upper end of Libby Creek, extending down to station LB¬200 by the end of the day. In general, flow increased from the upper station (Wpt-167 = 0.10 ft3/sec) to the point of highest flow (Wpt-184 = 4.84 ft3/sec) (see figure below). This area of highest flow occurs in the vicinity of a section of channel comprised of bedrock where no surface flow can go subsurface.

There are a few locations where side channels, mostly on the west side, contribute flow to Libby Creek, totaling about 1.25 ft3/sec. Flow at the lowest station (LB-200) was 1.87 ft3/sec, indicating that over half of the September 3, 2010 stream flow at this location was flowing subsurface within the alluvial deposits (i.e., cobbles, gravel, and sand) that make up the stream bed.

A significant gain in flow was detected between Wpt-171 and LB-50 where a cross valley fault may be contributing groundwater to the stream and also between Wpt-177 and Wpt-180 where Spring-8 is located.

Gaining reaches of the stream will be targeted for flow long-term monitoring stations to track mine dewatering effects on stream baseflow.

Figure 3-D.4-3–Results of synoptic flow event in Libby Creek.



Vegetation Monitoring

The observed plant cover values from three transects were averaged and the results are presented in table 3-D.4-4.

Table 3-D.4-4–Observed plant cover, wetland indicator type, and native status.

Plant Species Average Cover (%)

Wetland Indicator Status* Native Status (U.S.)

Abies lasiocarpa 0.37 FACU NativeAlnus sinuata 43.53 FACW NativeAthyrium filix-femina 5.40 FAC NativeCalamagrostis canadensis 2.43 FACW NativeCinna latifolia 0.40 FACW NativeCircaea alpina 0.30 FAC NativeDryopteris filix-mas 0.03 UPL NativeEpilobium glaberrimum 0.37 FACW NativeGalium triflorum 0.07 FACU NativeGeum macrophyllum 0.07 FACW NativeGlyceria striata 1.87 OBL NativeGymnocarpium dryopteris 2.50 FAC NativeLycopodium annotinum 0.03 FAC NativeMenziesia ferruginea 0.17 FACU NativePicea engelmannii 1.93 FAC NativeRubus parviflorus 0.03 FAC NativeSphagnum squarrosum 12.97 OBL NativeTiarella trifoliata 1.30 FAC NativeVaccinium globulare 0.50 FACU NativeViola glabella 0.10 FACW Native

Note: Wetland Indicator Status categories are defined by: http://plants.usda.gov/wetinfo.html#new_categories

The vegetation data were used to calculate the wetland vegetation Prevalence Index, which represents the abundance of wetland vegetation, on a scale of 1 (all obligate wetland species) to 5 (all upland species). The Prevalence Index for Spring-8 was 1.99 (see fig. 3-D.4-4). Annual monitoring of prevalence index will be done to track mine dewatering effects on vegetation.

Figure 3-D.4-4–Observed wetland vegetation Prevalence Index.


http://plants.usda.gov/wetinfo.html#new_categories

groundwater and groundwater-dependent … · web viewat other times a downward gradient develops....

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