Prepared in cooperation with the Northern and Southern Colorado Plateau Park Networks 

Field-Based Evaluations of Sampling Techniques to 

Support Long-Term Monitoring of Riparian Ecosystems 

along Wadeable Streams on the Colorado Plateau 

Michael L. Scott and Elizabeth W. Reynolds 

Open-File Report 2007-1266 

U.S. Department of the Interior 

U.S. Geological Survey 
ii

U.S. Department of the Interior 

DIRK KEMPTHORNE, Secretary 

U.S. Geological Survey 

Mark D. Myers, Director 

U.S. Geological Survey, Reston, Virginia 2007 

For product and ordering information: 

World Wide Web: http://www.usgs.gov/pubprod 

Telephone: 1-888-ASK-USGS 

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

resources, natural hazards, and the environment: 

World Wide Web: http://www.usgs.gov 

Telephone: 1-888-ASK-USGS 

Suggested citation: 

Scott, M.L., and Reynolds, E.W., 2007, Field-based evaluation of sampling techniques to support long-term 

monitoring of riparian ecosystems along wadeable streams on the Colorado Plateau: U.S. Geological 

Survey Open-File Report 2007-1266, 57 p. 

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement 

by the U.S. Government. 

Although this report is in the public domain, permission must be secured from the individual copyright 

owners to reproduce any copyrighted material contained within this report.
Contents 

Project Summary................................................................................................................................................................ 1

Acknowledgments ............................................................................................................................................................. 2

Introduction, Background, and Objectives.................................................................................................................... 2

Methods ............................................................................................................................................................................... 3

Study Areas ..................................................................................................................................................................... 3

Range of Natural Variation ....................................................................................................................................... 3

Defining Geomorphic Surfaces................................................................................................................................ 4

Field Sampling................................................................................................................................................................. 7

Sampling Reach Selection and Transect Layout.................................................................................................. 7

Nested Quadrats......................................................................................................................................................... 9

Line Intercept ............................................................................................................................................................ 10

Belt Transects ........................................................................................................................................................... 10

Population Census of Legacy Riparian Trees...................................................................................................... 13

Plant Species Identification.................................................................................................................................... 14

Field Data ....................................................................................................................................................................... 14

Field Data Collection and Entry .............................................................................................................................. 14

Data Analyses ............................................................................................................................................................... 14

Results................................................................................................................................................................................ 15

Reach Selection and Transect Layout...................................................................................................................... 15

Nested Quadrats........................................................................................................................................................... 16

Species Richness, Frequency, and Species Area Curves ................................................................................ 16

Shrub Cover in the 10-m2

 Quadrats ....................................................................................................................... 21

Nested Quadrats and Geomorphic Surfaces ...................................................................................................... 27

Geomorphic Surface Cover .................................................................................................................................... 27

Line Intercept ................................................................................................................................................................ 32

Total Woody Cover ................................................................................................................................................... 32

Comparing Line-Intercept Versus 10-m2 Quadrats for Estimating Shrub Cover............................................ 37

Comparing Line-Intercept and Survey Data ........................................................................................................ 37

Belt Transects and Riparian Forest Structure ........................................................................................................ 38

Comparing Tree Quadrats Versus Belt Transects.............................................................................................. 38

Comparing 10-m Versus 20-m Wide Belt Transects .......................................................................................... 39

Overall Results—10-m Belt Transects ................................................................................................................. 40

Census Counts for Riparian Legacy Trees............................................................................................................... 42

Sampling Times............................................................................................................................................................. 45

Discussion ......................................................................................................................................................................... 45

Reach Selection and Transect Layout...................................................................................................................... 45

Nested Quadrats........................................................................................................................................................... 46

Species Richness ..................................................................................................................................................... 46

Species Frequency................................................................................................................................................... 46

Species Area Curves ............................................................................................................................................... 46

i
Nested Quadrats and Geomorphic Surfaces ...................................................................................................... 47

Shrub Cover in the 10-m2

 quadrats........................................................................................................................ 48

Line Intercept ................................................................................................................................................................ 48

Comparing Line-Intercept and Survey Data ........................................................................................................ 48

Belt Transects and Riparian Forest Structure ........................................................................................................ 48

Census of Riparian Legacy Trees.............................................................................................................................. 49

References Cited.............................................................................................................................................................. 49

Appendix ............................................................................................................................................................................ 51 

List of Figures 

Figure 1. Illustration of geomorphic surfaces defined in 2006 riparian pilot studies............................................ 5

Figure 2. Illustration of reach-scale layout of transects for sampling geomorphic surfaces and riparian 

vegetation....................................................................................................................................................................... 8

Figure 3. Right bank endpoint or head pin for a riparian transect at Capulin Creek, BAND ............................... 9

Figure 4. Arrangement of the 0.01-m2

, 0.1-m2 and 1-m2 nested frequency quadrats........................................... 10

Figure 5. Location and spacing of nested quadrats relative to the zero point of the transect, defined as 

the left head pin........................................................................................................................................................... 11

Figure 6. Layout of a 10-m-wide belt along a transect, starting at the left head pin ......................................... 13

Figure 7. The number of herbaceous and shrub species encountered versus the number of quadrats 

sampled, for two quadrat sizes at each of the four pilot sites............................................................................ 22

Figure 8. The number of herbaceous and shrub species encountered versus the number of quadrats 

sampled, for two quadrat sizes at each of the four pilot sites............................................................................ 23

Figure 9. The number of herbaceous and shrub species encountered versus minutes of sampling effort 

for two quadrat sizes at each of the four pilot sites ............................................................................................. 24

Figure 10. The number of herbaceous and shrub species encountered versus minutes of sampling effort 

for two quadrat sizes at each of the four pilot sites ............................................................................................. 25

Figure 11. Average width of major geomorphic surface types as measured by line intercept along 11 

transects at ARCH....................................................................................................................................................... 30

Figure 12. Average width of major geomorphic surface types as measured by line intercept along 11 

transects at BAND ...................................................................................................................................................... 30

Figure 13. Average width of major geomorphic surface types as measured by line intercept along 11 

transects at CACH....................................................................................................................................................... 31

Figure 14. Average width of major geomorphic surface types as measured by line intercept along 11 

transects at GLCA ....................................................................................................................................................... 31

Figure 15. Proportion ± standard error of total woody cover at each site averaged across 11 sample 

transects from line intercept..................................................................................................................................... 33

Figure 16. Plot of the mean proportion of the riparian zone with woody cover, as measured by the lineintercept method, along 11 transects at each of the pilot study sites .............................................................. 34

Figure 17. Plot of the mean proportion of the riparian zone tree cover by size class for the four pilot study 

locations ....................................................................................................................................................................... 35

Figure 18. Plot of the mean proportion of the riparian zone shrub cover by height class for the four pilot 

study locations............................................................................................................................................................. 35

ii
Figure 19. Overlay geomorphic surfaces determined from line-intercept sampling on topographic survey 

information at BAND, transect 9 .............................................................................................................................. 38

Figure 20. Direct comparisons of mean basal area (m2

/ha) and stem density (stems/ha) as measured in 

10-m and 20-m belt transects at ARCH and GLCA................................................................................................. 39

Figure 21. Mean ± standard error basal area (m2/ha), by tree-size class, at all pilot sites ............................... 41

Figure 22. Mean ± standard error stem density (stems/ha), by tree size class, at pilot sites........................... 41

Figure 23. Comparison of mean stem density (stems/ha) for riparian legacy trees as measured by reachscale population census versus estimates from 10-m belt transects.............................................................. 44

Figure 24. Comparison of mean stand basal area (m2/ha) for riparian legacy trees as measured by reachscale population census versus estimates from 10-m belt transects.............................................................. 44

List of Tables 

Table 1. Description of riparian stream reaches sampled during 2006 field season............................................ 4

Table 2. Descriptions used for geomorphic and transitional surfaces along the perennial streams 

sampled in this pilot study .......................................................................................................................................... 6

Table 3. Cover-classes used to estimate cover in 1-m2 and 10-m2 quadrats ....................................................... 11

Table 4. Size and height classes for trees and shrubs used in pilot sampling ..................................................... 12

Table 5. List of woody species, by scientific and common name, that were considered shrubs during the 

pilot study ..................................................................................................................................................................... 12

Table 6. Summary of data analyses and decision rules governing those procedures. ..................................... 14

Table 7. List of study reach lengths by site. Comments relating to the establishment of the study reaches 

are included ................................................................................................................................................................. 16

Table 8. Richness estimates from 1-m2 and 10-m2 quadrats across four site samples in the 2006 riparian 

pilot study. .................................................................................................................................................................... 17

Table 9. Additional information on rare species detection in the 1-m2

 and 10-m2 quadrats ............................. 17

Table 10. Species found in >10 percent of 88 quadrats at Capulin Creek, Bandelier National Monument, 

2006, in descending order of frequency in the 10-m2 quadrats........................................................................... 18

Table 11. Species found in >10 percent of 74 quadrats at Tsaile Creek, Canyon de Chelly National 

Monument, 2006, in descending order of frequency in the 10-m2

 quadrats..................................................... 19

Table 12. Species found in >10 percent of 135 quadrats at Coyote Gulch, Glen Canyon National 

Recreation Area, in descending order of frequency in the 10-m2

 quadrats..................................................... 20

Table 13. Species found in >10 percent of 93 quadrats at Courthouse Wash, Arches National Park, in 

descending order of frequency in the 10-m2

 quadrats......................................................................................... 20

Table 14. Percent cover of all shrub species, by site, from the 10-m2

 quadrats and sample size (quadrats) 

required to achieve 10 and 20 percent precision in estimates of site-level means ....................................... 26

Table 15. Percent total shrub cover, by geomorphic surface, from the 10-m2

 quadrats and sample size 

(quadrats per surface) required to achieve 20 percent precision in estimates of surface-level means ... 28

Table 16. The distribution of 1 m2 quadrats for geomorphic surfaces at each site. Parentheses under site 

code indicate total number of quadrats.................................................................................................................. 29

Table 17. Number and percent of all 1-m2 and 10-m2 quadrats at the four riparian sites sampled in the 

2006 pilot that straddled two or more geomorphic surfaces .............................................................................. 29

Table 18. Number of occurrences and mean width (m) of transitional and infrequent geomorphic 

surfaces, detected using line-intercept method, at each site............................................................................ 32

iii
iv

Table 19. Summary of total cover for woody species across all transects (n = 11) at each pilot site 

sampled......................................................................................................................................................................... 33

Table 20. Summary of mean total cover for each woody species sampled, ranked by the number of 

transects on which the species occurred.............................................................................................................. 36

Table 21. Percent shrub cover from the 10-m2

 quadrat and the line-intercept method and sample size 

required to achieve 10 and 20 percent precision in estimates of site-level means ....................................... 37

Table 22. Analysis of variance for effects of site and sampling method on percent shrub cover values...... 37

Table 23. Comparison of sampling measures and sampling times for riparian forest-stand structure, 

using 5-m x 20-m tree quadrats versus 10-m wide belt transects ..................................................................... 38

Table 24. Results of a nonparametric signed rank test comparing estimates of tree basal area and stem 

density obtained using 10-m and 20-m wide belt transects................................................................................ 39

Table 25. Summary of sampling times for 10-m versus 20-m belt transects for estimating riparian foreststand structure ............................................................................................................................................................ 40

Table 26. Basal area (m2/ha) of pole-size stems, averaged by site........................................................................ 42

Table 27. Basal area (m2

/ha) of pole-size stems by species and site.................................................................... 42

Table 28. Summary of complete reach-scale stand census of riparian legacy trees at three of the pilot 

study sites..................................................................................................................................................................... 43

Table 29. Summary of sampling times for each method at all four pilot sites ..................................................... 45
Field-Based Evaluations of Sampling Techniques to 

Support Long-Term Monitoring of Riparian 

Ecosystems along Wadeable Streams on the 

Colorado Plateau 

Project Summary 

To better plan for and implement long-term ecological monitoring, we measured riparian 

vegetation and fluvial geomorphic features at pilot study sites on four wadeable perennial stream 

reaches, representative of drainages across the Colorado Plateau. Our primary objectives were to 

(1) collect field data, (2) evaluate the efficiency and effectiveness of various ecological measures 

and measurement techniques for riparian ecosystems, and (3) use field-based sampling to inform 

and refine the development of standard operating procedures for use in implementing integrated, 

long-term monitoring of riparian ecosystems. Ultimately, this work was aimed at providing NPS 

staff with some of the information and methods needed to design and implement long-term 

monitoring of NPS riparian resources, which is both relevant to management, and fully 

operational within institutional resource constraints. 

Our results suggest that selecting sampling reaches and establishing a sampling frame of 

11 transects, across a range of stream types, is feasible given a limited set of decision rules. A 

distinctive feature of richness across all sites was the high percentage of rare species, defined 

here as species having a single occurrence at a site. Rare species represented from 33 percent to 

47 percent of the species total across the four pilot sites. Our data show that the two smallest 

quadrat sizes, 0.01 m2

 and 0.1 m2, rarely had any species that occurred in the desired frequency 

range and can be omitted from the monitoring protocol. Few species fell within the 30–70 

percent range in the 1-m2 quadrats, but this quadrat size appears to be useful at the Tsaile Creek 

(CACH) site. We recommend continuing to collect information at the 1-m2

 scale and reevaluating its usefulness after more data are available from different types of sites. The 10-m2

quadrat is adequate for monitoring changes in frequencies of very common species at all sites. 

Based on pilot study results, we conclude that at sites with low total species numbers (< 60 

species), 40–60, 10-m2

 quadrats, would be sufficient to characterize overall species diversity for 

relatively common species. At sites with higher total numbers of species (> 100), 60–80, 10-m2

quadrats would be required to characterize overall species diversity. Rare species of interest 

should be monitored using alternative approaches, such as a site inventory and/or mapping (see 

Elzinga and others, 1998). A large number of the systematically placed 10-m2 quadrats span two 

or more geomorphic surfaces, especially adjacent to the channel. This makes resolution of 

species affinities with distinct geomorphic landforms difficult. Thus, we provide an amendment 

to improve characterization of herbaceous and shrub species on narrow, near-channel surfaces by 

sampling additional 0.5-m by 1-m quadrats on those surfaces. It appears that for sites in narrow 

valley settings where riparian zones average less than approximately 40 m, the number of 10-m2

quadrats systematically placed on 11 transects will not provide shrub cover estimates at 20 

1
percent precision. In such cases, additional sample reaches should be added in order to attain a 

minimum of 130 to 140 10-m2 shrub quadrats. 

The line-intercept technique can provide a relatively rapid, reach-scale quantification of 

proportional cover for woody vegetation and geomorphic surface types and that variance in these 

measures stabilizes by the eighth or ninth transect sampled. An overlay of the distribution of 

geomorphic surface data derived from line-intercept sampling on topographic survey information 

indicates that delineation of geomorphic surfaces could be done in conjunction with the 

topographic survey of each transect, obviating the need to record surface breaks using the line 

intercept. To include geomorphic surface identifications with the topographic survey, surface 

breaks and transitional surfaces should be included and identified in the survey, in addition to 

systematically placed survey points. 

Compared to 5-m by 20-m tree quadrats, belt transects were shown to provide similar 

estimates of stand structure (stem density and stand basal area) in less than 30 percent of the 

time. Further, for the streams sampled, there were no statistically significant differences in stem 

density and basal area estimates between 10-m and 20-m belt transects and the smaller belts took 

approximately half the time to sample. There was, however, high variance associated with 

estimates of stand structure for infrequently occurring stems, such as large, relict or legacy 

riparian trees. Legacy riparian trees occurred in limited numbers at all sites sampled. A reachscale population census of these trees indicated that the 10-m belt transects tended to 

underestimate both stem density and basal area for these riparian forest elements and that a 

complete reach-scale census of legacy trees averaged less than one hour per site. 

Acknowledgments 

We thank Rebecca Harms Weissinger, Steve Monroe and Jodi Norris (NPS-SCPN) for 

their invaluable expertise and companionship in the field. Their efforts greatly facilitated the 

completion of this project. Fred Hampel, Tamsin McCormick (NPS-NCPN), and Sean Clawson 

(NPS-NCPN) provided much-appreciated help with field data collection. Thanks also to Chris 

Peltz and Heidijo Erickson for data entry and Bill Coar and Greg Auble for assistance with 

programming and data analyses. Thanks to Craig Allen and Kay Beeley, USGS, at Bandelier, N. 

Mex., for providing long-term precipitation data for Bandelier and Terry Kenny, hydrologist, 

USGS, Salt Lake City, for provisional data on recurrence intervals for storm flows following the 

event of October 6th and 7th, 2006, in southern Utah. Finally, we thank NPS personnel at 

Bandelier, Canyon de Chelly, Glen Canyon National Recreation Area, and Arches National Park 

for site information and access. Funding for this project was provided by the Northern and 

Southern Colorado Plateau Networks of the NPS Inventory and Monitoring Program. 

Introduction, Background, and Objectives 

This project summarizes the results of a field-based pilot study designed to evaluate a set 

of measures (metrics) and measurement techniques to be used in the long-term monitoring of 

riparian ecosystems typical of the Colorado Plateau Physiographic Province (Scott and others, 

2005). The National Park Service’s Inventory and Monitoring Program (NPS-IM Program), in 

collaboration with 32 monitoring networks, are charged with developing a vital-signs monitoring 

program. Vital signs represent a select set of physical, chemical, and biological elements and 

processes of park ecosystems that are chosen to represent the overall health and condition of a 

park’s resources. Together, the Northern and Southern Colorado Plateau Networks (NCPN and 

SCPN) have developed conceptual models of key ecosystems and identified an integrated set of 

2
vital signs for tracking resource conditions at 35 NPS units within or near the Colorado Plateau 

(Thomas and others, 2005; O’Dell and others, 2005). In order to select a monitoring approach 

that best matches management objectives and the attributes of NCPN and SCPN ecosystems to 

be monitored, there is a need to evaluate the effectiveness of various possible measures and 

measurement techniques related to chosen vital signs. Such evaluations are often done as fieldbased pilot studies in which problems with certain field methods are revealed and refinements in 

sampling design are identified (Elzinga and others, 1998). Thus, our overall objectives are to 

implement monitoring of riparian ecosystems as a pilot study, designed to do the following: 

1. Collect field data and evaluate the utility and efficiency of a set of possible ecological 

measures and measurement techniques, used to meet NPS monitoring needs, across a range 

of riparian ecosystems characteristic of the Colorado Plateau; 

2. Quantify within-site variability and sampling effort for selected measures to assist NPS in 

the design and implementation of efficient and effective long-term monitoring protocols; 

3. Based on this field-based pilot study, refine standard operating procedures (SOPs) that are 

likely to be used in implementing long-term riparian monitoring. 

This report summarizes field data collected during the 2006 field season. Statistical 

analyses are used to evaluate the efficiency of various sampling methods, based on the time 

required to characterize within-site variability in measures of species diversity, tree-basal area 

and tree-stem density. Species area or accumulation curves are used to evaluate the effectiveness 

of quadrat size and number in characterizing within-site species richness and frequency for the 

herbaceous community, relative to minutes of sampling effort. Finally, variance in estimates of 

cover for herbaceous vegetation will be evaluated for different quadrat sizes. 

Methods 

Study Areas 

Streams for pilot sampling were identified in consultations between the NPS and USGS, 

to represent a range of Colorado Plateau stream types likely to be included in future NCPN and 

SCPN vital signs monitoring efforts (table 1). On the Colorado Plateau, riparian vegetation 

structure and diversity are typically best developed along alluvial reaches of perennial streams. 

Thus, the initial set of streams considered had perennial or intermittent flow that contained 

alluvial valley segments. 

Range of Natural Variation 

Riparian ecosystems in arid regions are inherently dynamic and highly variable in both 

spatial and temporal dimensions. It is worth noting that the 2006 field season included unusual 

precipitation events across the region, which had direct influence on riparian vegetation in some 

of the sampled reaches. For example, precipitation recorded at Bandelier, N. Mex., headquarters 

in 2006 was below average from January through June, followed by strong monsoonal 

precipitation in July and August, producing the fifth and first wettest months, respectively, over 

the last 30 years. This likely contributed to the high cover and diversity of herbaceous 

3
Table 1. Description of riparian stream reaches sampled during 2006 field season. Stream type 

classification follows Graf (1987). 

Park unit Code Stream name Flow/stream type Valley setting 

Northern Colorado Plateau Network 

Arches NP ARCH Courthouse 

Wash 

Intermittent/local stream Confined alluvial 

Southern Colorado Plateau Network 

Bandelier, N. Mex. BAND Capulin Creek Perennial/local stream Confined alluvial to 

colluvial 

Canyon de Chelly, N. 

Mex. 

CACH Tsiale Creek Perennial/local stream Confined alluvial 

Glen Canyon NRA GLCA Coyote Gulch Perennial/local stream Confined alluvial 

vegetation observed in pilot sampling at Capulin Creek (C. Allen, USGS, Bandelier, N.Mex., 

oral personal commun.). In contrast, heavy rains in southern Utah from the storm event of 

October 6th and 7th, caused widespread flash flooding across the region. Provisional data from 

the USGS suggests that the recurrence interval for flood peaks resulting from this storm on 

regional streams ranged from a >5-yr event on Pine Creek near Escalante, Utah to a 100-yr event 

on the Dirty Devil River above Poison Spring Wash near Hanksville, Utah (Terry Kenny, 

hydrologist, USGS, Salt Lake City, Utah). Sampling on Courthouse Wash and Coyote Gulch 

followed significant flooding, which caused channel erosion and flood-plain deposition within 

both study reaches. This disturbance was an important factor correlated with the low cover and 

low diversity of herbaceous vegetation within these study reaches. Riparian vegetation patterns 

observed across these sites illustrates the potential range of short-term natural variation in these 

systems. 

Defining Geomorphic Surfaces 

There is tight linkage between fluvial geomorphic surfaces and cross-valley patterns in 

riparian vegetation along Colorado Plateau streams. Accordingly, sampling of riparian 

vegetation in this pilot study was carried out in relation to defined geomorphic surfaces, which 

have been previously described for a range of plateau streams (fig. 1). For example, the riparian 

zone, as defined in this study for a typical perennial stream, included the following elements: (1) 

the channel bed, including depositional bars; (2) the active channel shelf (a frequently inundated 

surface between the channel bed (or depositional bar) and the bank slope of the flood plain; (3) 

the flood plain, which is inundated by recurring high flows and may contain topographic 

irregularities including flood-plain bars and swales; and (4) riparian terraces. Riparian terraces 

typically support stands of relict cottonwoods (Populus fremontii) but no longer or rarely flood; 

thus, they are characteristically dominated by upland species in the understory. Riparian terraces 

have been described by previous researchers on the plateau and represent former flood-plain 

surfaces that were abandoned during widespread arroyo cutting, which began on the plateau in 

the mid to late 1800s (Hereford, 1984; Graff, 1987). Riparian terraces were observed along all 

of the streams sampled. Upland terraces are older alluvial surfaces that support only upland 

vegetation. These, along with colluvial deposits or outcrops of bedrock (fig. 1) were considered 

upland and therefore not included in the pilot sampling. Transitional surfaces also were 

4
identified and typically represented relatively steep, narrow transitions between geomorphic 

surfaces of different elevations. Transitional surfaces most commonly included flood-plain 

banks and terrace risers. Table 2 provides additional descriptions of geomorphic surfaces 

encountered and defined during the course of this study. 

UT

CO

RT

FP FP

high flow channel

ACS BR BR ACS

CB

DB

Figure 1. Illustration of geomorphic surfaces defined in 2006 riparian pilot studies . Symbols 

represent the following geomorphic features: BR=bedrock, CO=colluvium, UT=upland terrace, 

RT=riparian terrace, FP=flood plain, CB=channel bed, DB=depositional bar, and ACS=active 

channel shelf. Physiographic descriptions of surfaces based on Hupp and Osterkamp (1985), 

Graff (1987), Hupp (1988), Everett (1995), and Birkeland (1996). It should be noted that at any 

particular channel cross section, not all features would be expected to occur. 

5
Table 2. Descriptions used for geomorphic and transitional surfaces along the perennial streams 

sampled in this pilot study (see table 1). These surfaces also are illustrated in figure 1. 

Geomorphic surface Description Citations 

Dominant geomorphic surfaces 

Channel bed and 

depositional bars 

On a perennial stream, the channel bed is that portion of the 

channel that is inundated by flows below the mean 

discharge. At least a portion of the channel bed along a 

perennial stream remains wet at all times. Depositional 

bars are part of the active channel bed but slightly higher in 

elevation than the low-flow or base-flow water stage. They 

are typically devoid of woody vegetation. 

Hupp and 

Osterkamp (1985) 

Active channel shelf The active channel shelf is a horizontal to sloping surface 

between the bank slope of the flood plain and the lower 

limit of persistent vegetation that marks the edge of the 

channel bed or a depositional bar. Along streams in more 

humid regions, these surfaces are frequently inundated and 

support a mix of flood-tolerant woody species. 

Hupp and 

Osterkamp (1985), 

Hupp (1988) 

Flood plain That portion of the riparian zone that is typically inundated 

by recurrent high flows and dominated by woody riparian 

vegetation. Flood plains of many Colorado Plateau streams 

are topographically complex, including flood-plain swails

and flood-plain bars. 

Everett (1995) 

Transitional/ infrequent geomorphic surfaces 

Flood-plain bank A relatively steep transitional surface between the channel 

bed, depositional bar, or active channel shelf and the flood 

plain 

Hupp and 

Osterkamp (1985) 

Riparian terrace Terraces are relict flood plains whose surfaces are rarely if 

ever inundated by flows of the modern river. Many 

Colorado Plateau streams have terraces that were formed by 

channel incision in the late 1800s to early 1900s. These 

terraces are typically 3 to 10 m above the current channel 

and often support large, remnant cottonwoods (legacy 

trees); although the understory vegetation is typically 

dominated by upland vegetation. Such terraces are here 

defined as riparian terraces because of the presence of 

legacy cottonwoods or other relict woody riparian species. 

Hupp (1988), 

Graff (1987), 

Hereford (1984) 

Upland terrace Upland terraces are higher, older terraces that formed from 

channel incision of valley fills dating back a minimum of 

800 years. Because of their age, these terraces, where they 

occur, are dominated by upland vegetation and are thus not 

considered part of the riparian zone. 

Hereford and 

others (1996) 

Terrace riser A relatively steep transitional slope rising from lower 

elevation surfaces such as the active channel shelf or flood 

plain to a terrace surface. 

Colluvium Material transported and deposited by the action of gravity. 

Streams of the Colorado Plateau confined within bedrock 

valleys often have colluvial deposits of rock and soil 

material that bound the edges of flood plains or terraces. 

These surfaces are dominated by upland vegetation. 

Scott and others 

(2005) 

Bedrock Extensive bedrock exposures of largely sandstones, 

limestones, and shales characterize the Colorado Plateau 

and confine the valleys of many of the region's rivers and 

streams. In extreme cases, stream flow is completely 

confined within bedrock. In less constrained valley 

settings, flood plains may be bounded by side-valley 

exposures of bedrock. 

Scott and others 

(2005) 

6
Field Sampling 

Sampling Reach Selection and Transect Layout 

In consultation with NPS, it was agreed prior to field sampling that establishment of a 

sampling frame for each stream reach would be modified from existing EMAP and NAQWA 

protocols and would be based on width of the riparian zone rather than wetted channel width. 

Specific sampling reaches for the SCPN streams were selected by NPS personnel using a 

Generalized Random Tessellation Stratified (GRTS) selection design 

(http://www.epa.gov/nheerl/arm/designpages/monitdesign/survey_design.htm). 

The sampling location for the NCPN stream (Courthouse Wash) was chosen subjectively, 

based on alluvial valley setting that was considered representative of stream reaches throughout 

the region. Sampling reaches for the SCPN streams were selected using GRTS as follows. The 

middle of the sampling reach (centroid) was located by navigating to the predetermined GRTS 

point using a GPS unit and a printout of the 1-m DOQQ or digital air photo imagery of the point 

and surrounding landscape features. GPS reception typically was not available or reliable in 

deep, narrow canyons; thus, the imagery was used to assist in pin-pointing the location of the 

centroid. Once located, the reach was evaluated for its suitability. In the process of selecting 

sample reaches, two important decision rules were established. First, no more than 25 percent of 

the sampling reach should include a distinctly different valley setting or stream type. Second, no 

more than 25 percent of the sampling reach should be located above or below a major tributary 

junction (see SOP 4). If a reach met the above criteria, sample reach length was determined by 

measuring the width of the riparian zone at five points—one at the centroid, two upstream, and 

two downstream of the centroid—at a spacing equal to the riparian zone as measured at the 

centroid. The sample reach length was obtained by averaging the five width measurements and 

multiplying that value by 10. In the event that this method produced excessively short or long 

sample reaches, minimum and maximum reach lengths of 300 and 800 m were defined. 

Transect layout design was based on existing protocols (Peck and others 2003). Eleven 

systematically spaced transects represented the sampling frame (fig. 2). This frame was centered 

on transect 6 (the centroid) in a reach that was relatively uniform with respect to valley setting 

and channel slope. Transects were numbered in ascending order, starting with the downstreammost transect. Spacing between transects was determined by dividing reach length by 10 and 

measuring distance between transects with a tape along the thalweg or lowest point along the 

channel. Transect layout began at the centroid and proceeded upstream and downstream from 

this point. Each transect was positioned orthogonal to the channel and were therefore generally 

orthogonal to the riparian zone and the valley. Transects endpoints were defined by the width of 

the riparian zone, identified by the transition from surfaces supporting riparian vegetation to 

bedrock valley walls or surfaces dominated by upland vegetation; for example, colluvial deposits 

(fig. 1, table 2). 

In one instance (Coyote Gulch), transect placement immediately upstream of a sharp, 90o 

bend in the channel and valley axis, resulted in the transect running parallel to the channel and 

valley in the downstream direction. For this and similar situations arising from channel 

sinuosity, we developed the decision rule that in laying out transects, if a transect situated 

orthogonal to the channel does not intersect the riparian-upland transition or valley wall before 

coming within 20 m of an adjacent transect, the spacing of that transect along the centerline of 

the stream should be increased until it is separated by at least 20 m from the adjacent transect. 

Transects located subsequent to the repositioned transect resume the original along-stream 

spacing (fig. 2). 

7
0 100 200 m

flow

X

X

X X X X

5 6

4

7

2 3 1

8 9

10 11

X X X X

X X

X

X X X X X X X

X X

Scale

X

5

X

Figure 2. Illustration of reach-scale layout of transects for sampling geomorphic surfaces and 

riparian vegetation. Thick solid lines represent the stream channel. Dashed line is the channel 

centerline, and the dotted line represents the riparian-upland transition. Transect spacing is 

measured along the centerline, extending upstream and downstream from the centroid (transect 

6). Transects (thin solid lines) are numbered in ascending order starting with the downstreammost transect and positioned orthogonal to the channel. Transect endpoints (X) are located at 

the valley wall or the transition from riparian to upland vegetation. Minimum distance between 

transects is 20 m. Initial layout of transect 5 (gray) violates this systematic spacing and is 

increased to maintain separation (transect 5, black). Systematic spacing resumes following 

transect repositioning. 

Once transect location and orientation were determined, transects were delineated by 

stretching a Kevlar tagline and meter tape taut between two, 60-cm-long pieces of 1.2-cmdiameter rebar. Where possible, the transect endpoints or head pins were positioned one to two 

meters upslope of the upland-riparian transition (fig. 3). The left bank endpoints (stream bank on 

the left while facing downstream) were defined as the zero point for each transect. To minimize 

the effects of trampling on vegetation, care was taken to walk on the upstream side of each 

transect. Following transect layout, sampling proceeded as follows: nested quadrats, line 

intercept, belt transects, and census of legacy trees. 

8
Head Pin

Figure 3. Right bank endpoint or head pin for a riparian transect at Capulin Creek, BAND. The 

head pin is positioned approximately 2 m above the riparian-upland transition. In this photograph, 

the stream channel is hidden below the fallen ponderosa pine in the middle of the photo. 

Nested Quadrats 

Nested quadrat sampling was used to estimate frequency of understory herbaceous 

vegetation, cover of soil-surface features, and cover of woody shrubs and tree seedlings. This 

sampling occurred at all sites and quadrats consisted of nested sampling areas measuring 0.01 

m2

, 0.1 m2, 1 m2 and 10 m2. The 1-m2 quadrat was constructed of 2.5-cm PVC pipe and colored 

marks were placed on the frame with permanent markers to delineate corners of the 0.01-m2

 and 

0.1-m2

 quadrats (fig. 4). Steel pins and a 25-m tape initially were used to lay out the 10-m2

quadrats; however, we suggest that lightweight, breakdown tent poles, held together with shock 

cord, would be a more efficient way to lay out these quadrats (see SOP 7). To minimize 

trampling effects, the 0.01-m2, 0.1-m2, and 1-m2 quadrats were placed on the downstream side of 

the transect. The 10-m2

 quadrat was centered on the transect; however, we suggest that all 

quadrats be placed on the downstream side of transects to avoid trampling in all cases. The 

nested quadrats were spaced regularly or systematically along each transect, beginning at the 

zero point, defined as the left head pin (fig. 5). To track the distribution of quadrats by 

geomorphic surface, we recorded the dominant surface for each 1-m2 quadrat and the meter on 

the transect at which the quadrats were placed. 

Minimum spacing between quadrats was 1 m. However, to ensure all geomorphic 

surfaces were sampled, maximum spacing between nested quadrats was 4 m. Wherever possible, 

spacing was adjusted to obtain a minimum of eight to ten sets of nested quadrats per transect. 

9
1 m

Markings on frame to 

denote sub-quadrats

0.01-m2 quadrat

0.1-m2 quadrat

1-m2 sampling frame

Figure 4. Arrangement of the 0.01-m2, 0.1-m2 and 1-m2 nested frequency quadrats. Marks on the 

corner of the 1-m2

 quadrat were used to define the smaller quadrats. 

Following frequency sampling, cover of all vascular herbaceous plants was recorded in 

the 1-m2

 and 10-m2 quadrats, based on seven cover classes (table 3). Finally, cover of woody 

shrubs, in two size classes, and tree seedlings (table 4) were recorded in the 10-m2

 quadrat, based 

on the same cover classes. Table 5 lists those woody species treated as shrubs for this study. 

Line Intercept 

The line-intercept method, as described by Bonham (1989) and Elzinga and others 

(1998), was used to measure canopy cover of woody trees and shrubs by height and size class 

(tables 3 and 5) and the proportion of geomorphic surfaces across the riparian zone. Transects 

were the sampling unit, and along each transect the cover of each tree species, by size class, was 

recorded as start and stop points where overlying or underlying canopies intersected a tape 

stretched along the transect. Canopy intersections had to be greater than 1 cm and canopy gaps 

less than 20 cm were not recorded (see SOP 8). A telescoping survey rod with a level was used 

to improve the vertical projection of tall canopies down to the transect. The proportion of the 

riparian zone occupied by a geomorphic surface type (table 2) was similarly evaluated by 

recording start and stop points for each surface type beneath the transect. 

Belt Transects 

Belt transects were used to measure density and stand basal area of tree stems above the 

seedling size class (table 3). Both of these stand-structure metrics are expressed on a unit area 

basis and originally were to be measured in 5×20 m quadrats placed systematically along each 

transect. However, after evaluating the time involved in laying out and measuring tree quadrats 

on two transects at BAND, the decision was made to measure stand structure for the remaining 

pilot sites using belt transects centered on the transects and extended across the entire riparian 

zone from head pin to head pin (fig. 6). Where riparian tree stems were small and dense 

10
4

left headpin

“0” meter mark

1-m2 sampling frame

5-m tent poles

2-m tent pole

2-m tent pole

meter tape

1 2 3 5

upstream downstream

4

left headpin

“0” meter mark

1-m2 sampling frame

5-m tent poles

2-m tent pole

2-m tent pole

meter tape

1 2 3 5

upstream downstream

4

left headpin

“0” meter mark

1-m2 sampling frame

5-m tent poles

2-m tent pole

2-m tent pole

meter tape

1 2 3 5

upstream downstream

Figure 5. Location and spacing of nested quadrats relative to the zero point of the transect, 

defined as the left head pin. Transects are oriented orthogonal to the stream channel. The 0.01-

m2, 0.1-m2, and 1-m2 quadrats are arrayed on the downstream side of the transect to minimize 

trampling. The 10-m2 quadrat is centered on the transect. Quadrats are systematically spaced 

along transects, with spacing based on transect length. Minimum spacing between quadrats is 1 

m, as depicted, and maximum spacing is 4 m. 

Table 3. Cover classes used to estimate cover in 1-m2 and 10-m2 quadrats. 

Cover class Range of cover (%) Class midpoints (%) 

1 <1 0.5 

2 1–5 3.0 

3 5–10 7.5 

4 10–25 17.5 

5 25–50 37.5 

6 50–75 62.5 

7 75–100 87.5 

11
Table 4. Size (diameter at breast height [dbh]) and height classes for trees and shrubs used in 

pilot sampling. 

Shrub Trees 

height classes Size class Criteria 

<2 m Seedling <1.37 m tall or ≥ 2.5 cm dbh 

≥2 m Pole ≥ 1.37 m and 2.5–15 cm dbh 

Overstory tree ≥ 15 cm and <50 cm dbh 

Legacy tree ≥ 50 cm dbh 

Table 5. The list of woody species, by scientific and common name, that were considered shrubs 

during the pilot study. Three species, Quercus gambelii, Q. grisea, and Salix exigua, may 

occasionally achieve tree-like stature, as noted. Growth habit information from Welsh and others 

(2003). 

Scientific name Common name Growth habit Site 

Artemisia tridentata big sagebrush Shrub to 3 m tall ARCH, BAND, CACH 

Baccharis salicina Great Plains false willow Shrub 1–3 m tall ARCH, GLCA 

Chrysothamnus 

depressus longflower rabbitbrush Low, spreading shrub CACH 

Chrysothamnus 

nauseosus 

rubber rabbitbrush Low to tall shrub ( up to 3 m tall) ARCH, GLCA 

Chrysothamnus sp. rabbitbrush species Low to moderate shrub (up to 1 m tall) ARCH, CACH, GLCA 

Chrysothamnus 

viscidiflorus yellow rabbitbrush Low to moderate shrub (up to 1 m tall) ARCH 

Cornus sericea redosier dogwood Clump-forming shrub CACH 

Forestiera pubescens stretchberry Shrub up to 2 m tall BAND 

Gutierrezia sarothrae broom snakeweed Profusely branched shrub up to 0.9 m tall BAND 

Ptelea trifoliata common hoptree Large shrub up to 3 m tall BAND 

Quercus gambelii Gamble oak Clonal shrub to small tree (2–4 m), rarely up to 10 m 

tall BAND, CACH, GLCA 

Quercus grisea gray oak Small to large tree, up to 25 m tall in protected sites BAND 

Rhus aromatica fragrant sumac Clump-forming shrub up to 2.5 m tall BAND, CACH, GLCA 

Ribes sp. currant Low to moderate shrub BAND 

Rosa woodsii Wood's rose Shrub up to 2.5 m tall BAND, CACH, GLCA 

Salix exigua narrowleaf/coyote willow Clonal shrub up to 3 m tall; rarely treelike to 8 m tall ARCH, CACH, GLCA 

Salix lasiandra green leaf willow Shrub or small tree from 2–15 m tall CACH 

Sherpherdia argentia silver buffaloberry Shrub with spreading, opposite branches up to 4 m tall ARCH 

Symphoricarpos 

oreophilus mountain snowberry Shrub up to 1.5 m tall CACH 

12
01 2 3 4 5

5-m tent poles, positioned 

on the ground, 

perpendicular to transect, 

to establish edge of 10 -m 

wide belt transect

left head pin downstream upstream

meter tape 

and tag line

a

b

01 2 3 4 5 6 7 8 9 10

5-m tent poles, positioned 

on the ground, 

perpendicular to transect, 

to establish edge of 10 -m 

wide belt transect

left head pin downstream upstream

meter tape 

and tag line

a

b

6 7 8 9 10

Figure 6. Layout of a 10-m-wide belt along a transect, starting at the left head pin. Five-m 

collapsible tent poles are used to establish the edge of the belt at points along the transect. Belt 

transects were established at the left head pin and extended across the entire riparian zone to 

the right head pin (not shown). All trees (irregular polygons) within the belt (gray shading) are 

sampled. If more than 50 percent of a tree stem (dashed circle) was outside of the belt it was not 

included; for example, trees a and b would not be sampled. 

 (BAND) or where transects were closely spaced (CACH), 10-m-wide belts were measured. At 

ARCH and GLCA, 10-m- and 20-m-wide belts were measured along each transect and compared 

for sampling efficiency. Outside edges of the belts were established by measuring out 5 m or 10 

m from the transect at multiple points, using 5-m lengths of Kevlar line, held orthogonal to the 

transect. Boundary decisions regarding whether a tree was considered in or out of the belt 

transect were as follows: if more than 50 percent of the rooted stem was in the quadrat, it was 

included; if not, it was excluded. Decision rules also had to be established for measuring stems 

at breast height (see SOP 9). 

t 5 m or 10 

m from the transect at multiple points, using 5-m lengths of Kevlar line, held orthogonal to the 

transect. Boundary decisions regarding whether a tree was considered in or out of the belt 

transect were as follows: if more than 50 percent of the rooted stem was in the quadrat, it was 

included; if not, it was excluded. Decision rules also had to be established for measuring stems 

at breast height (see SOP 9). 

Population Census of Legacy Riparian Trees 

Legacy riparian trees, cottonwood in particular, were present within all pilot sample 

reaches as small isolated stands or scattered individuals. We compared density and basal 

area estimates of legacy trees obtained from belt transects with the values determined from 

census counts. All legacy trees in the sampling reach were counted and measured for diameter at 

breast height (dbh). Breast height is defined as being 1.37 m above the ground surface. Census 

area was calculated by multiplying reach length by average transect width. Census methods are 

ideal for monitoring since they provide a true estimate of the population without sampling error, 

assuming the census is accurate (Elzinga and others, 1998). Legacy trees at the pilot sites were 

well suited for a census because (1) the census area of the reach was constrained within relatively 

area estimates of legacy trees obtained from belt transects with the values determined from 

census counts. All legacy trees in the sampling reach were counted and measured for diameter at 

breast height (dbh). Breast height is defined as being 1.37 m above the ground surface. Census 

area was calculated by multiplying reach length by average transect width. Census methods are 

ideal for monitoring since they provide a true estimate of the population without sampling error, 

assuming the census is accurate (Elzinga and others, 1998). Legacy trees at the pilot sites were 

well suited for a census because (1) the census area of the reach was constrained within relatively 

13
narrow valleys, (2) there were few individuals within the census area, and (3) they were 

distinctively large and easy to spot while walking the reach. 

Plant Species Identification 

Plants were identified by sight in the field. When a species call was tentative, it was 

indicated as such by a question mark, and to minimize the collection of specimens, these species 

were identified or verified in the field whenever possible using the following floras: Arizona 

Flora (Kearney and Peebles, 1960), A Utah Flora (Welsh and others, 2003), Intermountain 

Flora (Cronquist and others, 1994), Flowering Plants of New Mexico (Ivey, 1999). 

Unknown species were labeled on the datasheets with unique descriptive names and 

number codes, and specimens, collected outside of the sample area when possible, were 

correspondingly labeled and pressed. The pressed unknowns were taken to Herbaria at Northern 

Arizona University or Colorado State University for subsequent identification. We used the 

USGS Plants Database (http://plants.usda.gov/) as our taxonomic authority in preparing final 

species lists. 

Field Data 

Field Data Collection and Entry 

Field data were entered by hand on forms that had been designed in advance and 

modified based on field experience following each pilot study. Current drafts of the field forms 

are provided in the appendixes of SOP nos. 8, 9, and 10. Field data were entered into Xcel 

spreadsheets from the field forms and printouts of the electronic files were proofread for errors, 

checked against the field forms, and corrected in the Xcel file. Updates to the species lists were 

also entered at this time. 

Data Analyses 

Statistical summaries and analyses were performed on data and sampling times collected 

for the nested quadrats, line intercept, belt transects, and riparian legacy tree census. The 

analyses and decision rules associated with each of these procedures are summarized in table 6. 

Table 6. Summary of data analyses and decision rules governing those procedures. 

Analyses Decision rules for procedures 

All except species 

area curves 

SAS version 9.1, MEANS, FREQ, and UNIVARIATE procedures used to 

generate summary statistics. 

Species area curves 

SAS version 9.1 used to convert Xcel data files for species area curve (SAC) 

analysis in PCORD (for the 1-m2

 and 10-m2 quadrats only). Then graph SACs for 

shrub and herb species (with and without rare species) as a function of (1) number 

of quadrats and (2) minutes of sampling effort. Rare species were defined as 

having only a single occurrence at a site. 

Species area curves 

(sampling effort) 

Sampling effort is measured in minutes based on estimates of three components: 

time to layout transects, time to move among quadrats, and time to sample 

quadrats. Average measured transect setup time was 40 minutes per transect with 

11 transects at each site. Average travel time between quadrats was 0.5 minutes 

per quadrat. We measure total time to sample each fully nested (0.01, 0.1, 1, and 

10 m2

) quadrat set and calculated an average time per nested set at each site. We 

then measured relative time for the different size quadrats on a trial set of nested 

quadrats to determine a set of proportions (summing to 1) that break the average 

14
Table 6. Summary of data analyses and decision rules governing those procedures. 

Continued 

time for a nested quadrat down into the average time for each quadrat size. We 

divided the total time required to setup all transects at a site by the full number of 

quadrats we sampled at that site in order to get a transect setup time per quadrat. 

We then constructed species-effort curves using a calculation of number of 

quadrats multiplied by the per quadrat time (transect setup, travel among quadrats, 

and sampling time). Using this portioning of time per quadrat, the ratios between 

sampling effort for 10-m2

 versus 1-m2 quadrats was 1.96, 2.14, 1.91, and 2.49 

minutes at each site, with an average across sites of 2.12 minutes. 

Tables by subclassifications 

In many tables, it was necessary to create records with a zero value for transects 

for sites where a particular subgroup only occurred on some transects. Records 

were created ONLY for those subclasses that occurred at that site. Subclasses 

included are size classification and species. 

Intercept total cover 

Units summarized are on a transect level. 

Sum over start/stop to achieve a value for each individual transect. Since 

start/stop overlap, these percent-covers can be greater than 100 percent. 

Intercept canopy 

cover 

Units summarized are the individual start/stop values. 

Total intercept 

confidence intervals 

Estimation with accumulating numbers of transects. For each number of transects 

j, j=1...11, j randomly selected without replacement transects selected to be 

summarized. 

Individual canopy 

cover confidence 

intervals 

Same procedure as total cover. 

Estimating sample 

sizes at 10 and 20 

percent precision 

Sample size estimates were calculated using PASS (power and sample size; 

http://www.ncss.com). For these analyses, we define estimation precision as 

one-half the width of the 95 percent confidence interval for the mean. 

Tables by belt size Site averages are broken down by belt size to avoid double counting (since 

information from the 10-m belt is also included in the 20-m belt). 

Differences between 

belt sizes Sign rank test for differences, using SAS version 9.1, UNIVARIATE procedure. 

Basal area 

Cross-sectional area was calculated for each stem. 

Values summarized are total cross-sectional area at a transect level (may be 

broken down by classification, but value is still per transect). 

Density Number of stems counted, again at the transect level. 

Intercept times ARCH, BAND, and GLCA only. 

10-m belt times For GLCA and ARCH, time for a 10-m belt is assumed to be one-half the 20-m 

belt time. BAND 10-m belt also used. 

20-m belt times Only GLCA and ARCH have 20-m belt times. 

Quadrat times Times summarized on a per quadrat and per transect level. 

Census 

Census area calculated by average transect length × reach length. Average 

transect length calculated by eliminating any records that contained the words 

“UPLAND” or “COLLUVIAL” in surface type from individual transect lengths. 

CACH—select only SPP=POPDEL and DBH >50 cm. ARCH—only use legacy 

trees excel data to determine census value. 

RESULTS 

Reach Selection and Transect Layout 

Final reach lengths and comments regarding the establishment of each sampling reach are 

presented in table 7. Reach lengths ranged from the minimum of 300 m to 580 m. At GLCA, 

transect 5 had to be repositioned, according to the rules described above in the discussion on 

methods for transect layout and illustrated in figure 2, to avoid overlapping with adjacent 

transects. At two sites, transects ending at vertical sandstone walls raised the issue of how to 

secure transect endpoints in such situations. Further, establishing the tag-line on transects 

15
Table 7. A listing of study reach lengths by site. Comments relating to the establishment of the 

study reaches are included. 

Site Reach length 

(m) Comments 

ARCH 300 

Variable bottomland elevations across the canyon made running the tag-line difficult. 

Transect tag-line often extended in two stages, running across the flood terraces to the 

terrace edge closest to the channel and then running a separate line across the portion 

of the channel that was lower in elevation. Attaching the tag-line where the transect 

ends at a sheer canyon wall is an important issue. Attaching to some kind of cryptic 

climbing bolt or attachment would be ideal, but installing such devices would be a 

concern at many parks. 

BAND 300 

It took approximately three hours to establish the study reach. It was very difficult to 

walk along and across the channel due to large amounts of coarse woody debris 

(CWD). Approximately one-half hour was required to establish transect 1.

CACH 300 

GRTS pt. 3 selected by network was only 21 m in width, so the site at GRTS pt. 4 was 

examined; it was only 16 m and it was discussed whether these points should be 

rejected because valley width was less than 25 m. The next set of GRTS points, in a 

wider portion of the canyon, was considered, but ultimately opted not to since the 

network is specifically interested in the reach type that pts. 3 and 4 include. 

GLCA 580 

The first GRTS sample point was rejected because >25 percent of the reach was in a 

bedrock valley setting. The second GRTS point met selection criteria. Establishing 

transects was the most time consuming part of the sampling process, often taking more 

than an hour. The primary reason for this was that many transects were from 75 to 

over 100 m in length and it was difficult to keep the tag-line straight and taught 

through the trees and CWD. It will continue to be a problem to setup such long 

transects, especially if new patches of woody vegetation establish on surfaces spanned 

by the transects. Transects were adjusted within 1 m of the pre-selected transect 

location in order to maintain a reasonably clear line across the riparian zone. Sliding 

transects in this way has the effect of biasing the surface roughness estimates to be 

lower than they would be if allowed to bend around stems and CWD. However, there 

was consensus that the basal roughness/gap intercept approach did not adequately 

capture what was happening in the reach relative to flow roughness. As at ARCH, 

more than one transect ended at vertical sandstone wall. In establishing transects, one 

had to be repositioned because of a sharp bend in the channel. 

approaching or exceeding 100 m in length was difficult because of intervening tree stems and 

wracks of coarse woody debris. 

Nested Quadrats 

Species Richness, Frequency, and Species Area Curves 

Table 8 summarizes the total number of species observed in each quadrat size as well as 

the number of rare species observed at each pilot site. For a complete listing of all species 

encountered, see appendix A. Rare species are defined as those having a single occurrence at a 

site. Because quadrats were nested, the 10-m2 quadrats contained all of the species observed at a 

site. Thus, there were no species unique to smaller plots. BAND and CACH had similar and a 

relatively high number of species (128 and 130, respectively) whereas ARCH and GLCA had 

similar but low numbers of species (52 and 58, respectively). The contrast in species richness in 

part results from above average monsoonal precipitation at BAND (and likely CACH) and flash 

flooding immediately prior to sampling ARCH and GLCA. CACH had the greatest number of 

rare species (40), in part because grazing had removed flowering material, making positive 

species identification difficult. However, rare species accounted for 35 percent to 47 percent of 

the species total across all sites. 

16
Table 8. Richness estimates from 1-m2

 and 10-m2 quadrats across four site samples in the 2006 

riparian pilot study. Rare species are defined as having a single occurrence at a site. 

1-m2 quadrats 10-m2 quadrats 

Site 

Total 

number of 

quadrats 

Total 

number 

species 

observed 

Number 

species 

observed 

Number 

rare 

species 

No. species 

excluding 

rare species 

Number 

species 

observed 

Number 

rare 

species 

No. species 

excluding rare 

species 

ARCH 93 52 31 10 21 52 23 29 

BAND 88 128 83 40 43 128 45 83 

CACH 79 130 80 36 44 130 60 70 

GLCA 135 58 41 19 22 58 22 36 

Table 9 contrasts the utility of the 1-m2 and 10-m2 quadrats for capturing rare species at 

each pilot site. Numbers of rare species are naturally high in riparian areas, and 10-m2 quadrats 

were more efficient at accumulating additional rare species compared with 1-m2 quadrats. 

Detailed information on species frequencies are described below. 

Overall frequencies were low in all four pilot sites (tables 10–13), which reflects the 

patchy nature of riparian vegetation in these narrow canyon settings. Very few species, across 

all sites, reached the desired 30 percent frequency range in either the 1-m2 or the 10-m2 quadrat 

sizes, which is, again, related to the patterns of riparian vegetation in the bottomland, typically 

linked to flood disturbance and moisture availability. BAND and CACH were relatively speciesrich and had the greatest number of species that reached the 30 percent frequency range. Species 

diversity was diminished at ARCH and GLCA, resulting from recent floods. No species at 

ARCH and only one species at GLCA (Bromus tectorum) reached the 30 percent frequency 

range, and there were few species overall that occurred in more than 10 percent of the quadrats. 

In all cases, the 10-m2 quadrats had higher percent frequency for a species than the other quadrat 

sizes.

Table 9. Additional information on rare species detection in the 1-m2 and 10-m2 quadrats. 

Site 

Number 

additional 

species in 

10-m2

quadrats 

Percent 

species 

unique to 

10-m2

quadrats 

Number rare 

species in 1-m2

quadrats with >1 

occurrence in 

10-m2 quadrats 

Number species 

unique to 10-m2

quadrats with >1 

occurrence 

Number rare 

species 

unique to 10-

m2 quadrats 

ARCH 21 40.38 4 4 17 

BAND 45 35.15 18 22 23 

CACH 50 38.46 19 7 43 

GLCA 17 29.31 9 5 12 

17
Table 10. Species found in >10 percent of 88 quadrats at Capulin Creek, Bandelier National 

Monument, 2006, in descending order of frequency in the 10-m2

 quadrats. Twenty eight out of 120 

species (23.3 percent) total are included in the table. Shading indicates the quadrat size in which 

a species reached >30 percent frequency. Additional species are included as indicators of 

relatively common species that are not adequately captured by the tested quadrat sizes. 

Gram=graminoid habit. 

Species Habit % freq 

0.01 m2

% freq 

0.1 m2

% freq 

1 m2

% freq 

10 m2

Lactuca serriola Forb 0.00 1.14 17.05 47.73 

Forestiera neomexicana Shrub 0.00 0.00 0.00 46.59 

Bromus tectorum Gram 13.64 23.86 31.82 45.45 

Taraxacum spp Forb 3.41 3.41 22.73 40.91 

Geranium caespitosum Forb 6.82 11.36 20.45 37.50 

Parthenocissus quinquefolia Vine 1.14 5.68 13.64 37.50 

Verbascum thapsus Forb 0.00 2.27 14.77 36.36 

Elymus elymoides Gram 1.14 6.82 19.32 31.82 

Piptatherum micranthum Gram 2.27 6.82 15.91 30.68 

Bromus inermus Gram 1.14 4.55 11.36 30.68 

Tragopogon spp Gram 1.14 4.55 11.36 28.41 

Brickellia brachyphylla Forb 1.14 2.27 10.23 28.41 

Dactylis glomerata Gram 3.41 3.41 17.05 25.00 

Conyza canadensis Forb 1.14 1.14 5.68 20.45 

Bahia dissecta Forb 0.00 1.14 5.68 19.32 

Clematis ligusticifolia Vine 2.27 3.41 10.23 18.18 

Cicuta douglasii Forb 0.00 0.00 6.82 18.18 

Bromus ciliatus Gram 0.00 2.27 6.82 17.05 

Equisetum arvense Gram 0.00 1.14 7.95 17.05 

Galium aparine Forb 1.14 2.27 3.41 14.77 

Poa combo (pratensis/compressa) Gram 0.00 0.00 7.95 14.77 

Agrostis stolonifera Gram 0.00 2.27 5.68 13.64 

Chenopodium fremontii Forb 0.00 0.00 3.41 13.64 

Elymus canadensis Gram 0.00 1.14 6.82 12.50 

Urtica dioica Forb 0.00 0.00 3.41 12.50 

Rosa woodsii Shrub 0.00 0.00 0.00 12.50 

Artemisia ludoviciana Forb 0.00 0.00 2.27 11.36 

Cirsium vulgare Forb 0.00 0.00 1.14 11.36 

18
Table 11. Species found in >10 percent of 74 quadrats at Tsaile Creek, Canyon de Chelly National 

Monument, 2006, in descending order of frequency in the 10-m2

 quadrats. Thirty three out of 135 

species (24.4 percent) total are included in the table. Shading indicates the quadrat size in which 

a species reached >30 percent frequency. Additional species are included as indicators of 

relatively common species that are not adequately captured by the tested quadrat sizes. 

Gram=graminoid habit. 

Species Name Habit % freq 

0.01 m2

% freq 

0.1 m2

% freq 

1 m2

% freq 

10 m2

Medicago lupulina Forb 11.39 27.85 50.63 77.22 

Poa sp Gram 22.78 30.38 49.37 62.03 

Equisetum laevigatum Gram 5.06 15.19 39.24 60.76 

Symphyotrichum adscendens Forb 6.33 16.46 39.24 59.49 

Erigeron flagellaris Forb 6.33 25.32 37.97 51.90 

Taraxacum officinale Forb 0.00 7.59 25.32 51.90 

Poa palustris Gram 18.99 22.78 35.44 44.30 

Heterotheca villosa Shrub 1.27 15.19 29.11 43.04 

Achillea millefolium Forb 5.06 7.59 13.92 34.18 

Salix exigua Shrub 2.53 8.86 21.52 32.91 

Plantago lanceolata Forb 0.00 1.27 6.33 29.11 

Agrostis stolonifera Gram 11.39 15.19 18.99 25.32 

Artemisia ludoviciana Forb 1.27 2.53 8.86 25.32 

Trifolium repens Forb 2.53 5.06 11.39 24.05 

Gutierrezia sarothrae Shrub 1.27 3.80 8.86 24.05 

Eleocharis palustris Gram 1.27 2.53 7.59 22.78 

Melilotus sp. Forb 1.27 3.80 10.13 21.52 

Melilotus alba Forb 0.00 1.27 3.80 20.25 

Melilotus officinalis Forb 0.00 2.53 6.33 18.99 

Mentha arvensis Forb 1.27 1.27 3.80 18.99 

Bromus tectorum Gram 6.33 7.59 11.39 17.72 

Equisetum arvense Gram 2.53 5.06 6.33 17.72 

Rosa woodsii var ultramontana Shrub 0.00 2.53 6.33 17.72 

Plantago major Forb 0.00 0.00 6.33 15.19 

Juncus baliticus var. montanus Gram 1.27 1.27 5.06 15.19 

Ipomopsis aggregata Forb 0.00 0.00 3.80 15.19 

Quercus gambelii Shrub 0.00 0.00 5.06 13.92 

Rumex crispus Forb 0.00 0.00 2.53 12.66 

Pseudotsuga menziesii Tree 0.00 0.00 1.27 11.39 

Rudbeckia lacinata Forb 0.00 0.00 1.27 11.39 

Elymus elymoides Gram 0.00 1.27 6.33 10.13 

Senecio lobed Forb 0.00 0.00 3.80 10.13 

Prunella sp Forb 0.00 1.27 2.53 10.13 

19
Table 12. Species found in >10 percent of 135 quadrats at Coyote Gulch, Glen Canyon National 

Recreation Area, in descending order of frequency in the 10-m2

 quadrats. Eight out of 62 species 

(12.9 percent) total are included in the table. Shading indicates the quadrat size in which a 

species reached >30 percent frequency. Additional species are included as indicators of 

relatively common species that are not adequately captured by the tested quadrat sizes. 

Gram=graminoid habit. 

Species Name Habit % freq 

 0.01 m2

% freq 

0.1 m2

% freq 

1 m2

% freq 

10 m2

Bromus tectorum Gram 11.11 20.00 41.48 59.26 

Melilotus spp Forb 2.96 5.19 14.07 25.93 

Salix exigua Shrub 0.00 1.48 2.22 20.74 

Equisetum hyemale Gram 3.70 7.41 15.56 18.52 

Chrysothamnus nauseosus Shrub 0.00 0.00 2.96 17.04 

Artemisia ludoviciana ssp. mexicana Forb 0.74 2.96 6.67 16.30 

Baccharis salicifolia Shrub 0.00 0.00 0.00 11.11 

Elymus canadensis Gram 0.00 0.74 4.44 10.37 

Table 13. Species found in >10 percent of 93 quadrats at Courthouse Wash, Arches National 

Park, in descending order of frequency in the 10-m2 quadrats. Fourteen out of 51 species (27.5 

percent) total are included in the table. Additional species are included as indicators of relatively 

common species that are not adequately captured by the tested quadrat sizes. Gram=graminoid 

habit. 

Species name Habit % freq 

0.01 m2

% freq 

0.1 m2

% freq 

1 m2

% freq 

10 m2

Equisetum hyemale Gram 3.23 9.68 19.35 26.88 

Heterotheca villosa Shrub 1.08 6.45 12.90 22.58 

Euthamia occidentalis Forb 1.08 2.15 7.53 21.51 

Chrysothamnus nauseosus Shrub 0.00 0.00 2.15 21.51 

Juncus balticus Gram 4.30 6.45 15.05 20.43 

Elymus canadensis Gram 1.08 4.30 12.90 20.43 

Populus fremontii Tree 0.00 1.08 3.23 18.28 

Achnatherum hymenoides Gram 0.00 1.08 6.45 16.13 

Sporobolus cryptandrus Gram 1.08 2.15 5.38 13.98 

Distichlis spicata Gram 1.08 6.45 9.68 12.90 

Senecio spartioides Forb 0.00 1.08 5.38 12.90 

Unknown Aster, blue Forb 0.00 1.08 2.15 12.90 

Melilotus species Forb 0.00 1.08 4.30 11.83 

Salix exigua Shrub 0.00 0.00 0.00 11.83 

20
21

Species area curves for herbaceous and shrub species were generated for the two largest 

quadrat sizes (1 m2 and 10 m2), based on a species’ presence in the sample quadrat. In this 

analysis, we excluded all quadrats that fell outside of the riparian zone (that is, were dominated 

by upland plant species). As would be expected, the number of species increases more rapidly 

for the 10-m2 quadrats if equal numbers of quadrats are sampled (fig. 7). This was especially true 

at BAND and CACH, where species richness was highest and none of the curves have begun to 

asymptote. Sampling efficiency is also sensitive to rare species, and figure 8 illustrates the effect 

of eliminating species with only a single occurrence. These results suggest that with the 

exception of rare species, both the 1-m2

 and 10-m2 quadrats did an adequate job of characterizing 

species richness at sites with comparatively low numbers of species (ARCH and GLCA; table 8), 

whereas only the 10-m2 quadrats adequately characterized species richness at sites with higher 

numbers of species (BAND and CACH; table 8). 

Sampling effort was measured in minutes based on estimates of three components: (1) 

time to layout transects, (2) time to move among quadrats, and (3) time to sample quadrats. 

Average measured transect setup time was 40 minutes per transect with 11 transects at each site. 

Average travel time between quadrats was 0.5 minutes per quadrat. We measured total time to 

sample each fully nested (0.01, 0.1, 1, and 10 m2

) quadrat set and calculated an average time per 

nested set at each site. We then measured relative time for the different size quadrats on a trial 

set of nested quadrats to determine a set of proportions (summing to 1) that break the average 

time for a nested quadrat down into the average time for each quadrat size. 

We did this by dividing the total time required to setup all transects at a site by the full 

number of quadrats we sampled at that site in order to get a transect-setup time per quadrat. We 

then constructed species-effort curves using a calculation of number of quadrats multiplied per 

quadrat time (transect setup, travel between quadrats, and quadrat sampling time). Using this 

portioning of time per quadrat, the ratios between effort for 10-m2

 versus 1-m2 quadrats was 1.96, 

2.14, 1.91, and 2.49 for each of the four sites, with an average across sites of 2.12. Based on this 

formulation of sampling effort, the 10-m2 quadrats were somewhat more effective at 

characterizing number of species at three of the sites (ARCH, BAND and CACH) when rare 

species were included (fig. 9). With the exclusion of rare species, the 1-m2

 and 10-m2 quadrats 

were comparable in accumulating species per sampling, except at BAND, the most species-rich 

site (fig. 10). 

Shrub Cover in the 10-m2 Quadrats 

Shrub cover, summarized in table 14, was evaluated for the 10-m2 quadrats. Similar to 

frequencies of herbaceous species, shrub cover was highly variable both by species and by site 

because of the naturally patchy distribution of shrubs in the riparian zone. Our results suggest 

that the number of 10-m2

 quadrats at a site are sufficient to characterize only a few riparian shrub 

species, with relatively uniform cover, at 20 percent precision. This was especially true at 

GLCA, which had the greatest number of quadrats distributed across a relatively wide flood 

plain. We also estimated shrub cover using the line-intercept technique and a comparison of 

these two methods is provided in the Line Intercept section below. 
Courthouse Wash, Arches NP Capulin Creek, Bandelier NM

Upper Canyon del Muerto, Canyon de Chelly NM Coyote Gulch, Glen Canyon NRA

Figure 7. The number of herbaceous and shrub species encountered versus the number of quadrats sampled, for each of the four pilot sites. Upland quadrats are excluded. Quadrat sizes are as follows: red=1.0 m2 and blue=10 

22
pp p

Courthouse Wash, Arches NP Capulin Creek, Bandelier NM

Upper Canyon del Muerto, Canyon de Chelly NM Coyote Gulch, Glen Canyon NR

Figure 8. The number of herbaceous and shrub species encountered versus the number of quadrats sampled, for each of the four pilot sites. Upland quadrats and species with only one occurrence are excluded. Quadrat sizes 

red=1.0 m2 and blue=10 m2. 

r 

each of the four pilot sites. Upland quadrats and species with only one occurrence are excluded. Quadrat sizes red=1.0 m2 and blue=10 m2. 

23
Courthouse Wash, Arches NP Capulin Creek, Bandelier NM

Upper Canyon del Muerto, Canyon de Chelly NM Coyote Gulch, Glen Canyon NRA

Figure 9. The number of herbaceous and shrub species encountered versus minutes of sampling effort for two quthe four pilot sites. Sampling effort is based on time to layout transects, time to move between quadrats, and time Upland quadrats are excluded. Quadrat sizes are as follows: red=1.0 m2 and blue=10 m2. 

fort for two qu

the four pilot sites. Sampling effort is based on time to layout transects, time to move between quadrats, and time Upland quadrats are excluded. Quadrat sizes are as follows: red=1.0 m2 and blue=10 m2. 

24
Figure 10. The number of herbaceous and shrub species encountered versus minutes of sampling effort for two q

of the four pilot sites. Sampling effort is based on time to layout transects, time to move between quadrats, and tiquadrats. Upland quadrats and species with only one occurrence are excluded. Quadrat sizes are as follows: reblue=10 m2.

Courthouse Wash, Arches NP Capulin Creek, Bandelier NM

Upper Canyon del Muerto, Canyon de Chelly NM Coyote Gulch, Glen Canyon NRA

25
Table 14. Percent cover of all shrub species, by site, from the 10-m2

 quadrats and sample size 

(quadrats) required to achieve 10 and 20 percent precision in estimates of site-level means. 

Sample size 

(by precision) 

Site 

(total no. of 

quadrats) 

Species n* Mean Std. 

dev. 

Lower 

95% CI 

Upper 

95% CI CV 

10% 20% 

CHRNAU 23 2.33 3.14 0.97 3.69 135.11 698 177 

SALEXI 11 14.32 24.05 -1.84 30.47 167.96 1084 274 

BACSAL 3 5.17 4.04 -4.87 15.21 78.22 237 62 

CHRVIS 1 7.50 0.00 

ARCH 

(93) 

ARTTRI 1 0.50 0.00 

FORNEO 40 15.70 21.47 8.83 22.57 136.74 719 183 

PTETRI 8 2.63 6.01 -2.40 7.65 228.97 2007 504 

RHUTRI 8 3.13 3.62 0.10 6.15 115.93 517 131 

ROSWOO 11 9.23 7.17 4.41 14.04 77.71 235 61 

QUEGRI 2 4.00 4.95 -40.47 48.47 123.74 591 150 

BAND 

(88) 

ARTTRI 1 7.50 0.00 

SALEXI 26 19.23 22.29 10.23 28.23 115.89 519 132 

CHRDEP 7 3.50 3.74 6.96 0.04 106.90 442 113 

GUTSAR 19 1.61 2.62 0.34 2.87 163.37 1018 257 

RHUTRI 7 11.21 12.92 -0.73 23.16 115.20 513 130 

ROSWOO 14 3.00 3.48 0.99 5.01 116.02 520 132 

CORSER 1 7.50 0.00 

SYMORE 2 4.00 4.95 -40.47 48.47 123.74 591 150 

SALLAS 4 13.25 16.50 -13.01 39.51 124.53 599 152 

CACH 

(79) 

ARTTRI 1 0.50 0.00 

RHUTRI 3 11.83 9.82 -12.55 36.22 82.94 268 69 

BACSAL 19 11.50 10.26 6.56 16.44 89.20 309 79 

SALEXI 28 11.46 12.02 6.80 16.13 104.87 426 109 

GLCA 

(135) CHRNAU 23 5.63 5.05 3.45 7.81 89.66 312 80 

*Number of quadrats in which a species occurred. 

For each site, we also evaluated the distribution of total shrub cover by geomorphic 

surface (table 15). Each 10-m2

 quadrat was assigned to a surface based on the distribution of 

surfaces recorded along each transect as line-intercept data. If approximately 75 percent of a 

quadrat fell on a single surface, then it was considered representative of that surface. Quadrats 

with less than 74 percent cover on any one surface were considered transitional and were 

grouped accordingly in table 15. Total shrub cover was sparse at all the sites and distributed 

unevenly across geomorphic surfaces. Only the flood plain had shrub cover at all four sites. The 

active channel shelf, typified by Salix and/or Baccharis species cover, also had relatively high or 

frequent shrub cover at all sites, except CACH. Here, upstream flow regulation appears to have 

greatly limited shrub recruitment on existing geomorphic surfaces. Again, the inherently patchy 

and non-uniform distribution of shrub cover along the relatively narrow riparian corridors at the 

pilot sites contributes to high variability in shrub cover estimates. This is especially true when 

26
27

analyzed at the scale of geomorphic surfaces, most of which were less than 10 m in width (figs. 

11–14), and very high sample sizes were required for cover estimates with 20 percent precision. 

Only on the relatively wide flood-plain surfaces at GLCA did the number of flood-plain quadrats 

exceed the number of quadrats estimated as necessary for a 20 percent level of precision (table 

15). 

Nested Quadrats and Geomorphic Surfaces 

To track the distribution of systematically placed nested quadrats by geomorphic surface, 

we recorded the occurrence of each 1-m2

 quadrat by surface at each site (table 16). The presence 

of specific surface types varied by site, and the number of quadrats per surface was a function of 

the percent of the bottomland each surface occupied. For example, Coyote Gulch, at GLCA is a 

comparatively wide alluvial valley containing a large number of quadrats on the flood plain. 

Conversely, riparian terraces were narrow, infrequent or absent at some sites resulting in very 

few occurrences of quadrats on this surface type. Transitional surfaces (table 2), which were 

typically narrower and less common than the dominant surfaces, had even fewer occurrences 

(table 16). 

Because nested quadrats are placed systematically along transects, a certain number of 

quadrats inevitably span two or more different surface types. Table 17 presents the number and 

percent of all 1-m2 and 10-m2 quadrats at each site that straddled two or more geomorphic 

surfaces. Approximately 10 to 15 percent of the 1-m2

 quadrats straddled two or more surfaces 

compared with 25 to 30 percent of the 10-m2

 quadrats. Of these, more than half of both quadrat 

sizes included two or more surfaces when quadrats were place in or adjacent to the channel, 

where surfaces tended to be narrower (see Geomorphic Surface Cover section below). 

Geomorphic Surface Cover 

Figures 11–14 summarize the distribution of the most common geomorphic surfaces 

across the four pilot sites. Each site also had infrequent or transitional surfaces, which are 

described below. All sites were dominated by the same general geomorphic surface features, in 

different proportions. Depositional bars were relatively small at all sites, typically narrower than 

5 m. The flood plain (see fig. 1) was the dominant surface feature at three sites, ranging from an 

average of 6 m in width at CACH to an average of 15 m at GLCA. At BAND, a relatively 

narrow channel, incised into recent alluvial deposits resulting from the Dome wildfire, averaged 

only 3 m in width. Riparian terraces and terraces average 7 m and 5 m in width at CACH and 

BAND, respectively. 
Table 15. Percent total shrub cover, by geomorphic surface, from the 10-m2 quadrats and sample size (quadrats p

to achieve 20 percent precision in estimates of surface-level means. Parentheses after site code indicate the totaat each site. 

ARCH (93) BAND (88) CACH (79) 

Surface n* Mean SD n for 20% n Mean SD n for 20% n Mean SD n for 20% n 

Active channel shelf 13 6.82 18.62 716 6 0.77 2.14 740 7 Channel 1 1.59 Channel bed 9 0.05 3 1 13 Cut bank 1 3.43 Depositional bar 2 0.05 Flood plain 19 2.80 7.73 732 32 5.66 5.02 78 42 9.57 15.01 239 83 Flood plain (lower) 20 0.39 1.12 793 Flood plain (upper) 16 1.05 2.45 526 Flood-plain bank 2 0.73 2.25 913 3 Flood-plain bank (lower) 2 1.36 3.03 481 Flood-plain bank (upper) 1 Riparian terrace 2 0.68 12 1.31 2.4 325 Riparian terrace riser Terrace 21 3.55 4.75 175 1 1 Terrace riser 8 8 4.15 12.36 852 12 Transitional quadrats 7 1.14 3.05 17 1.09 2.57 14 15.41 19.45 12 

*Total number of quadrats on each geomorphic surface. 

28
Table 16. The distribution of 1-m2

 quadrats for geomorphic surfaces at each site. Parentheses 

under site code indicate total number of quadrats. Note that not all surfaces were present at all 

sites. 

ARCH 

(n=93) 

BAND 

(n=88) 

CACH 

(n=79) 

GLCA 

(n=135) Dominant surfaces 

Number of 1-m2 quadrats 

Active channel shelf 18 19 11 

Channel bed 11 1 10 15 

Depositional bar 1 

Flood plain 20 33 48 83 

Flood plain (lower) 20 

Flood plain (upper) 17 

Riparian terrace 2 7 

Terrace 23 3 

Transitional surfaces Number of 1-m2 quadrats 

Bedrock 1 

Cutbank 1 

Flood-plain bank (lower) 2 

Flood-plain bank (upper) 2 1 9 

Riparian terrace riser 6 

Terrace riser 8 8 12 

Table 17. Number and percent of all 1-m2 and 10-m2 quadrats at the four riparian sites sampled in 

the 2006 pilot that straddled two or more geomorphic surfaces. Of those quadrats intersecting 

two or more surfaces, the number and percent of those quadrats that were located adjacent to 

the channel also are tabulated. 

Number (percent) of quadrats straddling 

two or more geomorphic surfaces 

Number (percent) of quadrats 

straddling two or more geomorphic 

Site surfaces adjacent to channel 

Total number 

of quadrats 

per site 1 m2 10 m2 1 m2 10 m2

ARCH 93 9 (9.6) 24 (25.8) 6 (66.7) 12 (50.0) 

BAND 88 14 (15.9) 28 (31.8) 10 (71.4) 16 (57.1) 

CACH 79 12 (15.2) 23 (29.1) 10 (83.3) 15 (65.2) 

GLCA 135 18 (13.3) 31 (22.9) 9 (50.0) 13 (41.9) 

29
Courthouse Wash, Arches NP, dominant surfaces

Surface type

ACS CB DB FP FPl FPu

Surface width (m)

0

5

10

15

20

25

Figure 11. Average width of major geomorphic surface types as measured by line intercept along 

11 transects at ARCH. Surface types are as follows: ACS=active channel shelf, CB=channel bed, 

DB=depositional bar, FP=flood plain, FPl=lower flood plain, FPu=upper flood plain. 

Surface type

ACS

0

5

10

15

20

25

Surface width (m)

Capulin Creek, Bandelier NM, dominant surfaces

CB FP T

Figure 12. Average width of major geomorphic surface types as measured by line intercept along 

11 transects at BAND. Surface types are as follows: ACS=active channel shelf, CB=channel bed, 

FP=flood plain, T=terrace. 

30
0

5

10

15

20

25

Upper Canyon del Muerto, Canyon de Chelly NM, dominant surfaces Surface width (m)

Surface type

CB FP RT

Figure 13. Average width of major geomorphic surface types as measured by line intercept along 

11 transects at CACH. Surface types are as follows: CB=channel bed, FP=flood plain, RT=Riparian 

terrace.

0

20

40

60

80

Surface type

ACS CB FP

Surface width (m)

Coyote Gulch, Glen Canyon NRA, dominant surfaces

Figure 14. Average width of major geomorphic surface types as measured by line intercept along 

11 transects at GLCA. Surface types are as follows: ACS=active channel shelf, CB=channel bed, 

FP=flood plain. Note scale of Y-axis differs from figures for the other sites. 

31
Transitional or infrequent geomorphic surfaces are presented in table 18. With the 

exception of terrace risers, transitional surfaces were encountered less frequently than the 

dominant surface types (table 2), and they were relatively narrow. Trails were notable features at 

CACH and GLCA. Because head pins are located on upland surfaces when possible, terraces or 

terrace risers are expected to represent a small proportion of each transect, except at ARCH 

where the riparian zone was constrained within a narrow bedrock canyon. 

Line Intercept 

Total Woody Cover 

The line-intercept method was used to measure cover of woody trees and shrubs as well 

as geomorphic surfaces. Cover is expressed as a proportion of the total length of the sample 

transect. Since transects spanned the riparian zone at each site, cover is, in essence, the 

proportion of the riparian zone or bottomland occupied by a cover type. Across sites, there was 

notable variability in total cover of woody species (fig. 15, table 19). ARCH and CACH had 

total covers representing less than half of the riparian zone, whereas GLCA and BAND had 

mean total covers of 69 percent and 73 percent, respectively. 

Total cover was variable, especially at CACH, where one transect had no woody cover, 

in contrast to other transects that had comparatively high cover values for Salix exigua, the 

dominant woody species at this site. In general, tree cover at CACH was sparse. 

Table 18. Number of occurrences and mean width (m) of transitional and infrequent geomorphic 

surfaces (see table 2) detected using line-intercept method, at each site. Parentheses under site 

code provide average transect length at each site. 

ARCH 

(40.3 m) 

BAND 

(27.0 m) 

CACH 

(23.4 m) 

GLCA 

(60.2 m) Surface type 

n* mean width 

(m) n 

mean width 

(m) n 

mean width 

(m) n 

mean width 

(m) 

Bedrock 3 1.80 

Colluvium 2 2.55 

Cutbank 1 3.10 

Flood-plain bank 6 2.29 6 1.79 

Flood-plain bank (lower) 2 5.85 

Flood-plain bank (upper) 2 1.75 

Riparian terrace 2 8.33 

Riparian terrace riser 1 1.80 1 1.90 

Upland terrace 1 1.6 

Terrace riser 4 7.59 13 2.37 26 2.57 

Terrace-slope toe 1 1.80 

Trail 9 0.44 1 1.80 

Upland 1 1.10 

*Number of occurrences during intercept sampling of all 11 transects. 

32
ARCH BAND CACH GLCA

Mean proportion total cover

0.0

0.2

0.4

0.6

0.8

1.0

ARCH BAND CACH GLCA

Mean proportion total cover

0.0

0.2

0.4

0.6

0.8

1.0

Figure 15. Proportion ± standard error of total woody cover at each site averaged across 11 

sample transects from line intercept. 

Table 19. Summary of total cover (mean, standard error (SE), and 95% confidence interval (CI)) 

for woody species across all transects (n=11) at each pilot site sampled. 

Site Number of 

transects Mean Standard deviation SE Mean Lower 95% CI 

Upper 

95% CI 

ARCH 11 0.32464 0.15698 0.047330 0.21918 0.43010 

BAND 11 0.73357 0.23518 0.070910 0.57557 0.89157 

CACH 11 0.35754 0.27108 0.081733 0.17543 0.53966 

GLCA 11 0.69034 0.27049 0.081557 0.50862 0.87206 

In spite of high overall variability in mean total cover, a plot of the mean and standard 

error of the mean, recalculated after the addition of each successive and randomly selected 

transect, indicates that mean total cover, and the variance around that mean, appear to stabilize 

after the eighth or ninth transect sampled (fig. 16). Thus, the sampling of cover using the lineintercept method at each of the 11 transects in a sample reach provides a reasonably good 

estimate of total riparian zone woody cover. 

33
Mean proportion total cover

Courthouse Wash, Arches NP

0 1 2 3 4 5 6 7 8 9 10 11

0.25

0.30

0.35

0.40

0.45

0.50

0 1 2 3 4 5 6 7 8 9 10 11 12

0.5

0.6

0.7

0.8

0.9

1.0

1.1

0.8

Tsaile Creek, Canyon de Chelly NP

Number of transects

0 1 2 3 4 5 6 7 8 9 10 11

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Mean proportion total cover

Coyote Gulch, Glen Canyon NRA

0 1 2 3 4 5 6 7 8 9 10 11 12

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

Number of transects

Capulin Creek, Bandelier NP

Figure 16. Plot of the mean proportion of the riparian zone with woody cover, as measured by the 

line-intercept method, along 11 transects at each of the pilot study sites. Mean and standard 

error of the mean were recalculated with the one-by-one addition of each transect with recorded 

cover. See table 5 for additional statistics. 

Total cover was further broken down by size and height class to reflect vertical structural 

diversity for trees and shrubs at each site (figs. 17 and 18). All sites show the same general 

pattern with cover in all size classes; the majority of which occurs in the pole and overstory size 

classes. BAND had relatively high cover of pole-size alder (Alnus oblongifolia), which lined the 

channel throughout the sample reach and likely represents recruitment following the Dome 

wildfire in 1996 (Veenhuis, 2002). It was noted, but not recorded, that the reach included five to 

ten large, dead alder stems that had presumably been killed by fire. GLCA had high cover of 

overstory cottonwoods, which dominated the wide flood plain at the downstream end of the 

sample reach. Shrub cover was more variable across sites. CACH had high cover of tall sand 

bar willow (Salix exigua). 

Total proportional cover by species across sites also was variable, and this variability was 

as much a function of the number of transects at which a species occurred as the uniformity of 

cover across transects where it was encountered (table 20). For example, sand bar willow 

34
ARCH BAND CACH GLCA

Mean proportion of total tree cover

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Seedling

Pole

Overstory

ARCH BAND CACH GLCA

Mean proportion of total tree cover

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Seedling

Pole

Overstory

Figure 17. Plot of the mean proportion of the riparian zone tree cover by size class for the four 

pilot study locations. Error bars are standard error of the mean. 

ARCH BAND CACH GLCA

Mean proportion of total shrub cover 

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

< 2 m

> 2 m

ARCH BAND CACH GLCA

Mean proportion of total shrub cover 

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

< 2 m

> 2 m

Figure 18. Plot of the mean proportion of the riparian zone shrub cover by height class for the 

four pilot study locations. Error bars are standard error of the mean. 

35
Table 20. Summary of mean total cover (with 95% confidence interval (CI)) for each woody 

species (spp) sampled, ranked by the number of transects on which the species occurred. 

SPP Number of 

occurrences 

Mean Standard 

deviation 

Lower 

95% CI 

Upper 

95% CI 

Coefficient of 

Variation 

POPFRE 19 0.39751 0.17556 0.31289 0.48212 44.16 

SALEXI 18 0.11021 0.12309 0.049 0.17143 111.69 

ACENEG 12 0.13775 0.1338 0.05274 0.22276 97.13 

QUEGAM 11 0.0741 0.07163 0.02598 0.12222 96.67 

ALNOBL 10 0.3724 0.13141 0.2784 0.46641 35.29 

FORNEO 10 0.14906 0.08414 0.08887 0.20925 56.45 

SALGOO 9 0.14057 0.11518 0.05204 0.22911 81.94 

RHUTRI 8 0.04487 0.05624 -0.00215 0.09189 125.34 

ROSWOO 6 0.10087 0.08217 0.01464 0.18711 81.46 

BACSAL 5 0.1028 0.07787 0.00611 0.19948 75.75 

JUNSCO 5 0.10313 0.08638 -0.00413 0.21038 83.76 

CHRDEP 4 0.02428 0.01074 0.00718 0.04137 44.23 

JUNMON 4 0.16097 0.16663 -0.10417 0.42611 103.52 

PSEMEN 4 0.16447 0.04726 0.08927 0.23966 28.73 

PTETRI 3 0.01684 0.01669 -0.02461 0.0583 99.11 

BACC 2 0.02232 0.00159 0.008 0.03664 7.12 

CHRNAU 2 0.02832 0.01509 -0.10725 0.1639 53.28 

PINPON 2 0.28487 0.03724 -0.04968 0.61942 13.07 

ARTTRI 1 0.09865 . . . . 

BACEMO 1 0.00607 . . . . 

FRAANA 1 0.00448 . . . . 

JUNOST 1 0.03856 . . . . 

PHIMIC 1 0.00627 . . . . 

PINEDU 1 0.0129 . . . . 

POPDEL 1 0.01119 . . . . 

PSME 1 0.0694 . . . . 

QUEGR 1 0.04396 . . . . 

RAMBET 1 0.01282 . . . . 

SALLAE 1 0.24523 . . . . 

(Salix exigua), which occurred on 18 transects had a high coefficient of variation primarily 

because it exhibited high cover values on some transects (for example, at CACH) with little or 

no cover on other transects. In contrast, ponderosa pine, which had a low coefficient of 

variation, occurred on only two transects (BAND), each as single, large stems with similar crown 

cover values. 

36
Comparing Line-Intercept Versus 10-m2 Quadrats for Estimating Shrub Cover 

Table 21 compares estimates of mean percent shrub cover from the 10-m2 quadrat and 

line-intercept data. Estimates were similar despite relatively high variability in shrub cover. 

Site, but not method, had a significant effect on mean percent shrub-cover values (table 22). 

Post hoc tests (Tukey’s HSD) indicate that ARCH, which had only sparse shrub cover, was 

significantly different from the other three pilot sites. 

Table 21. Percent shrub cover from the 10-m2

 quadrat and the line-intercept method and sample 

size (transects) required to achieve 10 and 20 percent precision in estimates of site-level means. 

In these analyses, quadrat data were first averaged for each transect and then by site. 

Sample size 

Site Method n Mean Standard (by precision) 

deviation 

Coefficient of 

variation 10% 20% 

ARCH 10-m2 quadrat 11 5.43 6.54 120.44 558 140 

intercept 11 3.00 5.16 171.82 1137 285 

BAND 10-m2 quadrat 11 11.09 8.74 78.8 239 60 

intercept 11 18.98 10.83 57.08 128 34 

CACH 10-m2 quadrat 11 9.55 9.12 95.48 353 91 

intercept 11 12.97 12.74 98.29 374 96 

GLCA 10-m2 quadrat 11 9.05 5.11 56.51 125 34 

intercept 11 15.16 17.84 117.65 535 136 

 

Table 22. Analysis of variance for effects of site and sampling method on percent shrub-cover 

values. Only site had a significant effect on percent cover values. The effects of method and the 

interaction of site and method were nonsignificant. SS = sums squares; df = degrees of freedom; 

MS = mean squares. 

Effect SS df MS F p 

Site 1326.68 3 442.23 4.86 0.0038 

Method 179.90 1 179.90 1.98 0.16 

Site * method 294.83 3 98.28 1.08 0.36 

Error 7194.77 79 91.07 

Comparing Line-Intercept and Survey Data 

Figure 19 compares the geomorphic surface data, collected using the line-intercept 

method, to the total station survey of transect nine at BAND. The active channel shelf, as 

defined here, has an average elevation of 0.6 m relative to the channel thalweg. In contrast, the 

flood plain has an average elevation of 1.5 m above the thalweg. Defining mean elevations for 

surface features and monitoring surface- and ground-water stage elevations over time, allows for 

establishment of quantitative expressions that link and define surface features in terms of surface 

and ground-water dynamics. For example, where these relationships have been quantified, 

active channel shelves are typically inundated from 5 to 25 percent of the time and flood plains 

are inundated by floods with average return times of 1 to 3 years (Hupp and Osterkamp 1985; 

Hupp, 1988). 

37
T9 ELEVATION (M)

1843

1844

1845

1846

1847

1848

1849

1850

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Terrace riser Channel

Channel 

shelf

Channel 

shelf Flood Plain

Distance (m)

Elevation (m)

X= 0.61 ± 0.26

X= 1.52 ± 0.41

Figure 19. Overlay geomorphic surfaces determined from line-intercept sampling on topographic 

survey information at BAND, transect 9. 

Belt Transects and Riparian Forest Structure 

Comparing Tree Quadrats Versus Belt Transects 

The results of a comparison between estimates of stand structure using 5-m × 20-m tree 

quadrats versus 10-m-wide belt transects, are summarized in table 23. The comparison, based on 

two transects at BAND, makes clear that estimates of density for quadrats and belt transects are 

very close for both transects as is the estimate of basal area (BA) for transect 1. The higher 

estimate of BA at transect 7 resulted from the inclusion of a single large ponderosa pine in the 

quadrat. Based on the largely comparable results, and the fact that quadrats took an average of 

45 minutes longer to setup, the decision was made to use belt transects to estimate riparian 

forest-stand structure for the remainder of the transects at BAND, as well as for the other pilot 

sites. 

Table 23. Comparison of sampling measures and sampling times for riparian forest-stand 

structure, using 5-m × 20-m tree quadrats versus 10-m wide belt transects. The comparison was 

made at two transects within the sampling reach of Capulin Creek, BAND. 

Sampling metrics Quadrat-T1 Belt-T1 Quadrat-T7 Belt-T7 

Basal area (m2/ha) 0.55 0.62 0.92 0.36 

Density (stems/ha) 0.19 0.17 0.18 0.18 

Setup time (total, min) 00:60 - 00:28 - 

Sample time (total, min) 00:18 00:20 00:11 00:13 

38
Comparing 10-m Versus 20-m Wide Belt Transects 

Figure 20 compares estimates of mean basal area and stem density, respectively, at 

ARCH and GLCA, where we made direct comparisons between 10-m and 20-m belt transects. 

These estimates appear comparable across a range of basal areas and stem density values. The 

sampling efficiency of 10-m and 20-m-wide belt transects were next compared statistically. 

Table 24 provides results from a sign-rank test comparing estimates of basal area and stem 

density, based on measurements from 10-m and 20-m belt transects. We used the more 

conservative sign-rank test because it is more appropriate for data that are collected using 

repeated measures. In addition to comparability of estimates for basal area and stem density, 

10-m belts took an average of 15 minutes to sample compared to an average to 31 minutes for 

the 20-m belts (table 25). 

Coyote Gulch, Glen Canyon NRA

seedling pole overstory legacy

0

2

4

6

8

10

12

14

10m belt

20m belt

Courthouse Wash, Arches NP

seedling pole overstory legacy

Mean basal area (m2/ha) 0

1

2

3

4

5

6

10m belt

20m belt

Courthouse Wash, Arches NP

seedling pole overstory legacy

Mean density (stems/ha)

0

200

400

600

800

1000

1200

1400

1600

10m belt

20m belt

Coyote Gulch, Glen Canyon NRA

seedling pole overstory legacy

0

50

100

150

200

250

300

10m belt

20m belt

Figure 20. Direct comparisons of mean basal area (m2/ha) and stem density (stems/ha) as 

measured in 10-m and 20-m belt transects at ARCH and GLCA. 

Table 24. Results of a nonparametric signed-rank test comparing estimates of tree basal area 

and stem density obtained using 10-m and 20-m wide belt transects. 

Tree basal area (m2/ha) Tree stem density (stems/ha) 

Site Signed-rank 

statistic, difference 

p-value of signedrank statistic Signed-rank 

statistic, difference 

p-value of signedrank statistic 

ARCH 15.0 0.20605 -12.5 0.23242 

GLCA -5.5 0.62500 -7.5 0.49219 

39
Table 25. Summary of sampling times for 10-m versus 20-m belt transects for estimating riparian 

forest-stand structure. 

Belt size 

(m) Site Number oftransects 

Total 

time Mean Standarddeviation SE Mean 

10 ARCH 10 2:53:30 0:17:21 0:12:32 0:03:58 

BAND 10 2:15:00 0:13:30 0:03:04 0:00:58 

GLCA 11 2:34:30 0:14:03 0:06:54 0:02:05 

20 ARCH 10 5:47:00 0:34:42 0:25:04 0:07:55 

GLCA 11 5:09:00 0:28:05 0:13:49 0:04:10 

Overall Results—10-m Belt Transects 

Stand structure across all pilot sites is summarized for basal area (fig. 21) and stem 

density (fig. 22) using data from the 10-m belt transects. Stem-basal area varies widely across 

stem-size classes both within and among sites. In general, basal area is greatest in the overstorysize class with many large cottonwoods at GLCA accounting for nearly five times the basal area 

compared with the other sites (fig. 21). At BAND, basal area in the pole and legacy tree-size 

classes exceeds that at the other sites; although variance is high, especially for legacy trees. The 

comparatively high basal area for legacy-size trees (>50 cm, dbh) at BAND is the result of a few 

very large ponderosa pines. Whereas ponderosa pine occupies upland sites across the Colorado 

Plateau, they do occasionally occur on flood-plain and riparian terrace surfaces throughout the 

region. High pole-size-class basal area at BAND resulted from high densities of alder stems (fig. 

22), which, as noted earlier, likely established following the Dome wildfire in 1996. Finally, 

comparatively high densities of seedling and pole-size stems at ARCH, suggest that there has 

been relatively recent active recruitment of stems at this site. This pattern contrasts with CACH 

and GLCA, where low densities of seedlings and poles indicate that there is little active 

recruitment at these sites. 

Table 26 summarizes basal area data for pole-size trees by site. Both GLCA and CACH 

exhibit high variability in basal area of this size class, but the large number of poles at ARCH 

and BAND, due to relatively recent recruitment events, contributed to low variability at these 

sites. At CACH, only 2 percent of the pole-size trees captured in the 10-m belt were riparian 

species. Douglas fir (Pseudotsuga menziesii), pinyon pine (Pinus edulis), and Juniperus species 

account for the majority of the pole basal area at CACH. Table 27 provides species-specific 

information by site. 

40
seedling pole overstory legacy

Mean basal area (m

2/ha)

0

2

4

6

8

10

12

14

ARCH

BAND

CACH

GLCA

seedling pole overstory legacy

Mean basal area (m

2/ha)

0

2

4

6

8

10

12

14

ARCH

BAND

CACH

GLCA

Figure 21. Mean ± standard error (SE) basal area (m2/ha), by tree-size class, at all pilot sites. 

seedling pole overstory legacy

Mean density (stems/ha)

0

500

1000

1500

2000

2500

ARCH

BAND

CACH

GLCA

seedling pole overstory legacy

Mean density (stems/ha)

0

500

1000

1500

2000

2500

ARCH

BAND

CACH

GLCA

Figure 22. Mean ± standard error (SE) stem density (stems/ha), by tree size class, at pilot sites. 

41
Table 26. Basal area (m2

/ha) of pole-size stems, averaged by site. 

Site n 

Mean 

basal 

area 

Standard 

deviation 

Lower 

95%CI 

Upper 

95% CI 

Coefficient of 

variation 

ARCH 11 0.0856 0.036 0.0614 0.1098 42.06 

BAND 11 0.123 0.0296 0.1031 0.1429 24.09 

CACH 11 0.4037 0.6347 -0.0227 0.8301 157.23 

GLCA 11 0.1055 0.079 0.0524 0.1586 74.88 

Table 27. Basal area (m2/ha) of pole-size stems by species and site. 

Sample size 

Site Species n Mean St dev. (by precision) Lower 

95% CI 

Upper 

95% CI CV 

10 20 

ARCH POPFRE 270 0.0759 0.0822 0.066 0.0857 8.22 453 116 

ARCH JUNMON 2 0.1504 0.0282 -0.1033 0.4042 18.77 16 6 

ARCH ACENEG 2 0.0432 0.0076 -0.0251 0.1114 17.61 15 6 

ARCH CELRET 1 0.0634 

BAND ALNOBL 397 0.1332 0.1206 0.1213 0.1451 90.53 318 82 

BAND ACENEG 156 0.077 0.0866 0.0606 0.0674 78.7 489 124 

BAND BETOCC 8 0.1142 0.0823 0.0454 0.183 72.08 202 53 

BAND SALIRO 7 0.048 0.0118 0.0371 0.0589 24.5 26 9 

BAND QUEGAM 1 0.0204 

BAND QUEGRI 1 0.0193 

CACH JUNMON 9 0.4082 0.6024 -0.0548 0.8712 147.56 837 212 

CACH PSEMEN 8 0.4147 0.5055 -0.0079 0.8373 121.9 1173 574 

CACH QUEGAM 6 0.7499 1.2467 -0.5584 2.0582 166.24 1062 268 

CACH JUNSCO 4 0.2456 0.2037 -0.0785 0.5697 82.94 267 69 

CACH PINEDU 2 0.0628 0.027 -0.1794 0.3049 42.94 74 21 

CACH ALNOBL 2 0.531 0.3043 -2.2027 3.2647 57.3 129 34 

GLCA POPFRE 57 0.103 0.0981 0.077 0.1291 95.27 351 90 

GLCA SALGOO 52 0.1074 0.0991 0.0798 0.135 92.27 330 85 

GLCA ACENEG 16 0.0697 0.0583 0.0386 0.1008 83.74 272 70 

GLCA QUEGAM 8 0.0537 0.0869 -0.0189 0.1264 161.72 1006 254 

GLCA AMEUTA 5 0.1025 0.0352 0.0589 0.1462 34.31 48 3 

GLCA JUNOST 2 0.1402 0.0097 0.0534 0.2271 6.89 2 2 

GLCA TAMRAM 1 0.0282 

Census Counts for Riparian Legacy Trees 

Legacy trees, primarily cottonwoods, were found at all pilot sites. At BAND, there were 

large alders, some of near legacy diameter (>50 cm, dbh), all of which were dead and 

presumably killed by the Dome wildfire in 1996. BAND also was the only site with large, 

legacy-size ponderosa-pine stems on riparian terrace surfaces. Although these trees likely 

established on flood-plain surfaces, we did not include these individuals in the census of legacy 

trees. We included only those species that are largely restricted to riparian zones; therefore, the 

census was of riparian legacy trees. BAND was the only site without living riparian legacy trees. 

42
The number of riparian legacy trees ranged from five at ARCH to 17 at GLCA and mean 

population density ranged from 4.1 stems/ha at ARCH to 14.3 stems/ha at CACH. Mean 

population basal area ranged from 1.1 m2/ha at ARCH to 6.3 m2/ha at CACH (table 28). 

Estimates of mean population stem density and basal area for riparian legacy trees were 

calculated at the three sites where they occurred, based on the 10-m belt transects. At ARCH 

and CACH only a single legacy tree fell within the sampling area of the belt transects; thus, 

estimates represent a single observation. Based on the belt transects, population-mean stem 

density was underestimated at ARCH and CACH by 28 percent and 65 percent, respectively. 

The population mean was overestimated at GLCA, but was well within the standard error of the 

mean (fig. 23). Estimates of basal area paralleled those of stem density (fig. 24). 

Table 28. Summary of complete reach-scale stand census of riparian legacy trees at three of the 

pilot study sites. Census area was defined as reach-averaged transect distance (average reach 

width) by reach length. All riparian legacy trees were counted and measured for diameter at 

breast height (dbh). Stem density (stems/ha) and stand basal area (m2/ha) were then summarized 

for the reach. 

Site 

Reach 

length 

(m) 

Average 

transect 

distance (m) 

Area of 

census 

(hectares) 

Number of 

legacy 

trees 

Census density 

of legacy trees 

(stems/ha) 

Total 

basal 

area 

(m2) 

Census basal area: 

total basal 

area/area of 

census (m2/ha) 

ARCH 300 40.25 1.21 5 4.13 1.31 1.09 

CACH 300 23.32 0.70 10 14.28 4.39 6.27 

GLCA 580 59.38 3.44 17 4.94 7.81 2.27 

43
ARCH CACH GLCA

Mean density (stems/ ha) of legacy trees

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

Belt transect mean

Population mean

Figure 23. Comparison of mean stem density (stems/ha) for riparian legacy trees as measured by 

reach-scale population census (open circles) versus estimates from 10-m belt transects (closed 

circles). Error bar represents standard error of the mean. 

ARCH CACH GLCA

Mean basal area of legacy trees (m2/ha)

0

1

2

3

4

5

6

7

Belt transect mean

Population mean

Figure 24. Comparison of mean stand basal area (m2/ha) for riparian legacy trees as measured by 

reach-scale population census (open circles) versus estimates from 10-m belt transects (closed 

circles). Error bar represents standard error of the mean. 

44
Sampling Times 

Sampling times per method are summarized in table 29 for all pilot sites. Total travel 

time varies significantly by site and only ARCH did not require backpacking to the sample reach. 

Total reach layout time ranged from an hour at ARCH, where the channel was relatively clear of 

vegetation and debris, to three hours at BAND, where travel near the channel is difficult due to 

large amounts of course woody debris. Mean transect setup times were similar across sites, 

although a few transects at GLCA were over 100 m and took a significant amount of time to 

establish (>1 hour). Mean sampling times for nested quadrats were also similar, except at CACH 

where recent flooding and heavy grazing made plant identification difficult, thus increasing 

mean sampling time significantly. Conducting line intercept and 10-m-belt transect sampling did 

not result in significantly different mean sampling times between sites. Mean sampling time for 

line intercept ranged from 10:44 minutes per transect at BAND to 35:00 minutes at ARCH. 

However, it should be noted that collection times at ARCH were for two people, whereas three 

people were involved in sampling at the other sites. 

Table 29. Summary of sampling times for each method at all four pilot sites. Note that all 

sampling at ARCH was conducted by two people. Sampling at BAND was by conducted three 

people at all but three transects, where a fourth person participated. All data at CACH and GLCA 

were collected by four people, with the exception of four transects at GLCA that were sampled by 

a team of two. 

Total time Mean time 

Site 

Mean 

transect 

length (m) 

Travel to 

site 

Reach 

layout 

Legacy 

tree 

census 

Transect 

setup 

Quadrat 

sampling 

Line 

intercept 

10-m belt 

transect 

ARCH 40.25 0:15:00 1:00:00 0:12:00 0:25:00 0:09:29 0:35:00 0:17:21 

BAND 26.95 2:30:00 3:00:00 0:00:00 0:30:00 0:11:59 0:10:44 0:13:30 

CACH 23.42 1:00:00 0:30:00 ----- 0:20:00 0:19:51 0:20:44* ----- 

GLCA 60.17 3:00:00 2:00:00 0:10:00 0:40:00 0:06:11 0:20:27 0:14:03 

*Sample time includes collecting sparse 10-m belt transect data. 

Discussion 

Reach Selection and Transect Layout 

The role of GRTS in selecting sites for long-term riparian monitoring is still an open 

question. GRTS points were used to select pilot sampling sites at BAND, CACH, and GLCA, 

with the use of rule sets allowing rejection of sample reaches that included distinctly different 

valley settings or large tributary junctions. Rule sets also were established for determining 

sample reach length along with definition of minimum and maximum reach lengths. 

Layout of transect locations can be time consuming if the channel and flood plain have 

high volumes of coarse woody debris, like BAND, or if the channel is sinuous, causing transect 

overlap. Rules were established to prevent overlap of adjacent transects and sample areas 

associated with those transects. 

Establishment of transect endpoints and alignment can be difficult, especially for 

transects in excess of 100 m in length. Monumenting and relocation of head pins is also a 

45
question that needs further consideration, especially in deep canyons with poor GPS reception 

and transects that end at bedrock valley walls. However, establishing semipermanent endpoints 

is critical to implementing efficient, spatially repeatable long-term monitoring. 

Nested Quadrats 

Species Richness 

Species diversity ranged widely across sites from highs of 128 and 130 at BAND and 

CACH, respectively, to lows of 52 and 58 at ARCH and GLCA, respectively. These differences 

result in part from above average monsoonal precipitation at BAND to flash flooding at ARCH 

and GLCA immediately prior to sampling. Thus, these values reflect the range of natural 

variation in species richness that might be expected to occur at a site over time in these 

physically dynamic systems. A distinctive feature of richness across all sites was the high 

percentage of rare species, defined here as species having a single occurrence at a site. Rare 

species represented from 33 percent to 47 percent of the species total across the four pilot sites. 

This is significant, since rare species are difficult to quantify using metrics like frequency and 

cover and have strong influence on species area curves, as discussed below. 

Species Frequency 

Our data show that the two smallest quadrat sizes, 0.01 m2 and 0.1 m2, rarely had any 

species that occurred in the desired frequency range and can be omitted from the monitoring 

protocol. Few species fell within the 30–70 percent range in the 1-m2 quadrats, but this quadrat 

size appears to be useful at the Tsaile Creek (CACH) site. We recommend continuing to collect 

information at the 1-m2

 scale and re-evaluating its usefulness after more data are available from 

different types of sites. The 10-m2 quadrat is adequate for monitoring changes in frequencies of 

very common species at all sites. However, less common species do not occur with enough 

frequency even in the largest quadrats to allow for adequate monitoring of changes in frequency 

over time. Species that fall within the desired frequency range make up only about 10–25 

percent of the total species at each site. 

Species Area Curves 

Species area curves can be used to determine sampling adequacy in characterizing plant 

communities. Generally, an area that is relatively uniform is over-sampled, at random. This 

sample is then subsampled to determine the point at which additional samples contribute only 

minor increases in the number of new species found (McCune and Grace, 2002). These 

assumptions are questionable in riparian settings because high patch disturbance and sharp 

environmental gradients create strong patterns in the distribution of vegetation. Because riparian 

vegetation is often highly patterned by hydrologic disturbance gradients (Auble and others, 

2005) and because quadrats were sampled systematically along cross-valley transects, species 

accumulation rates in these pilot studies would be expected to be relatively high. 

Species accumulation rates for herbs and shrubs in the riparian zone were relatively high, 

especially at BAND, where above-average monsoonal precipitation had notably increased 

species cover and diversity (C. Allen, USGS, Bandelier, New Mex., oral personal commun.). In 

contrast, species cover and diversity were comparatively low at ARCH and GLCA, where 

flooding prior to sampling had removed and buried species across the riparian zone (see Range 

of Natural Variability subsection). When rare species were included in the species accumulation 

46
curves for herbs and shrubs, neither the 1-m2

 nor 10-m2 quadrats adequately characterized site 

species diversity, especially at BAND and CACH. However, when rare species were excluded 

from the analysis, the species accumulation curves indicate that the 10-m2 quadrats represented 

overall species diversity across all sites, requiring 40–60 quadrats at ARCH, CACH, and GLCA 

and 60–80 quadrats at BAND. Based on these results, we suggest that rare species are not 

adequately assessed using quadrats of the size and number used in the pilot studies. 

We also used sampling effort in minutes to compare different sampling intensities for 1-

m2 and 10-m2 quadrats. There are valid arguments for using this, or other, approaches in 

partitioning sampling effort across quadrats. However, the general behavior is that as more upfront, “fixed” effort is included in a per quadrat calculation of effort (such as, transect setup, 

camping time at a site, travel time to a site, and office planning) the less relatively important 

differences in actual quadrat sampling time become in the overall comparison. Based on our 

comparison, the 10-m2

 quadrats were, overall, the most efficient at characterizing diversity of 

more common species, in terms of sampling effort, particularly at sites with relatively high 

numbers of species (>100 species). 

Based on our pilot study results, we conclude that at sites with low species numbers (<60 

species total), 40–60 10-m2 quadrats, would be sufficient to characterize overall species diversity 

for relatively common species. At sites with higher total numbers of species (>100), 60–80 10-

m2 quadrats would be required to characterize overall species diversity. Rare species of interest 

should be monitored using alternative approaches, such as a site inventory and/or mapping (see 

Elzinga and others, 1998). 

Nested Quadrats and Geomorphic Surfaces 

Systematic placement of quadrats along transects provide a number of advantages for 

long-term monitoring, including repeatability and proportional sampling of the bottomland. 

Further, the 10-m2

 quadrats have been shown here to be the most efficient in terms of 

characterizing species richness for herbs and shrubs as well as being suitable for monitoring 

changes in frequency of relatively common species. However, in riparian systems, vegetation 

patterns are structured by cross-valley physical disturbance and moisture gradients. Distinct 

vegetation distribution patterns are shown to relate to specific geomorphic landforms and 

develop primarily in response to hydrologic variables such as inundation duration, flooding 

frequency, and depth to the alluvial water table (Hupp and Osterkamp, 1985; Stromberg and 

others, 2006). Integrated monitoring of riparian ecosystems requires linkages among hydrologic, 

geomorphic, and vegetation metrics. However, relating vegetation to specific geomorphic 

surface types through the systematic placement of large quadrats becomes problematic along 

small streams like those examined in this pilot where important geomorphic surfaces are often 

narrow and discontinuous. For example, the active channel shelf ranged from <1 to <5 m in 

width across sites. Our results indicate that a large number of the 10-m2

 quadrats span two or 

more geomorphic surfaces, especially adjacent to the channel. This makes resolution of any 

species affinities with distinct geomorphic landforms difficult. Thus, we provide the following 

amendment to improve characterization of herbaceous and shrub species on narrow, nearchannel surfaces. For any distinct geomorphic surface adjacent to the channel and less than 5 m 

in width, establish a second transect perpendicular to the first in the approximate center of the 

surface. Along the second transect locate four 0.5-m by 1-m quadrats, typically two upstream 

and two downstream from the main transect. Establish these quadrats within 10 m of the main 

transect and in them record cover and frequency of herbs and cover of shrubs (see SOP 8 for 

additional methodological details). 

47
Shrub Cover in the 10-m2

 Quadrats 

As with frequency of herbaceous and shrub species, shrub cover was highly variable by 

species and by site owing to inherently patchy distribution and wide ranges in cover values for 

many species. This variation was evident in estimates of cover using the line-intercept and 10-

m2

 quadrats, which yielded similar results that were not statistically different. Using shrub cover 

data from 10-m2

 quadrats, we determined that only at GLCA, where a total of 135 quadrats were 

needed to sample the comparatively wide bottomland, were quadrat numbers adequate to 

characterize shrub cover for most of the common species with 20 percent precision. Whereas the 

minimal spacing between 10-m2

 quadrats was used at BAND and CACH; the bottomland was so 

narrow (mean transect length=27 m and 23.4 m, respectively) that the total number of quadrats at 

these sites (88 and 79, respectively) was approximately half of what is needed to characterize 

shrub cover with 20 percent precision. Based on these results, it appears that for sites in narrow 

valley settings where riparian zones average less than approximately 40 m, the number of 10-m2

quadrats systematically placed on 11 transects will not provide shrub cover estimates at 20 

percent precision. In such cases, additional sample reaches should be added in order to attain a 

minimum of 130 to 140 10-m2

 shrub quadrats. 

Line Intercept 

In spite of relatively high natural variability in the data and potential imprecision 

associated with making highly repeatable line interception calls (Elzinga and others, 1998), this 

method appears to be an efficient way of describing and monitoring cross-valley scale change in 

cover of woody vegetation and geomorphic surface types. Variance in total cover estimates 

stabilized somewhere between eight and nine transects, depending on the site, and sampling 

times ranged from approximately 11 minutes to 35 minutes per transect. Larger scale changes in 

surface types, like that associated with channel widening and narrowing processes, and 

accompanying changes in vegetation (Birkeland, 1999), could be well represented using this 

method. Further, data from this method are likely to scale-up well to remotely sensed estimates 

of vegetation cover where GIS coverage exists. Estimates of cover by size class for trees and 

shrubs are likely to have high variance but provide an index of stand structural diversity, which 

would be important for wildlife species, especially avian populations. 

Comparing Line-Intercept and Survey Data 

An overlay of the distribution of geomorphic surface data derived from line-intercept 

sampling on topographic survey information from one of the transects at BAND demonstrated 

close agreement. Based on this result, it appears that delineation of geomorphic surfaces could 

be done in conjunction with the topographic survey of each transect, obviating the need to record 

surface breaks using the line intercept. To include geomorphic surface identifications with the 

topographic survey, surface breaks and transitional surfaces should be included and identified in 

the survey job, in addition to systematically spaced survey points (see SOP 5 for survey 

procedures). 

Belt Transects and Riparian Forest Structure 

Based on a limited comparison at BAND, it was determined that belt transects provide a 

more efficient estimate of riparian forest-stand structure (stem density and stand basal area by 

size class) than do the originally proposed 5-m × 20-m quadrats. The increased efficiency of 

belts results primarily from reduction in the amount of time involved in laying out belt transects 

48
compared with quadrats. However, because of high cross-valley environmental gradients, and 

strong patterns in vegetation (Hupp and Osterkamp, 1985; Bendix, 1994; Auble and others, 

2005), the continuous nature of belt transects also provides a more efficient way of capturing this 

inherent variability. 

A more robust comparison of 10-m to 20-m belt transects at ARCH and GLCA suggests 

that for wadeable streams in bedrock canyons, 10-m belt transects produce similar standstructure estimates in less than half the time. Overall results from 10-m belts suggest, however, 

that estimates for large and/or rare individuals are likely to be highly variable. This is especially 

true for riparian legacy trees, which occurred in limited numbers at all pilot sites, including 

BAND, although all the riparian legacy trees at this site had been killed by wildfire. Thus, for 

infrequent individuals, like legacy trees, a reach-wide census of the population is likely to be the 

most accurate and efficient method for obtaining stand-structure information on these species. 

Census of Riparian Legacy Trees 

We compared reach-scale estimates of stem density and stand basal area for legacy trees, 

using 10-m belt transects, against population means produced by doing a complete census of all 

riparian legacy trees. These results indicated that the belts tended to underestimate both stem 

density and basal area with high variance. The total number of legacy trees ranged from five at 

ARCH to 17 at GLCA. Not counting the time involved in walking the reach to locate trees, the 

time it took to count and measure dbh on all legacy trees within a reach ranged between 10 

minutes and 30 minutes. Given the potential error in estimating stand-structure information on 

riparian legacy trees, a complete census of the population seems worth the sampling effort. 

References Cited 

Auble, G.T., Scott, M.L., and Friedman, J. M., 2005, Use of individualistic streamflowvegetation relations along the Fremont River, Utah, USA, to assess impacts of flow alteration 

on wetland and riparian areas: Wetlands, v. 25, p. 143–154. 

Bendix, J., 1994, Scale, direction, and pattern in riparian vegetation-environment relationships: 

Annals of the Association of American Geographers, v. 84, p. 652–665. 

Birkeland, G.H., 1999, Flood power, riparian vegetation, and channel change in canyons of the 

Escalante River Basin, Utah: Tempe, Arizona State University, Ph.D. dissertation, 210 p. 

Bonham, C. D., 1989, Measurements for terrestrial vegetation: New York, Wiley, 338 p. 

Cronquest, A., Holmgren, A.H., Holmgren, N.H., Reveal J.L., and Holmgren, P.K., 1994, The 

Monocotyledons, vol. six: New York, The New York Botanical Garden, 584 p. 

Elzinga, C.L., Salzer, D.W., and Willoughby, J.W., 1998, Measuring and monitoring plant 

populations: Denver, Colo., Bureau of Land Management, Tech. Reference 1730-1, 

BLM/RS/ST-98/005+1730. 

Everitt, B. L., 1995, Hydrologic factors in regeneration of Fremont cottonwood along the 

Fremont River, Utah, in Costa, J.E., Miller, A.J., Potter, K.W., and Wilcox P.R., eds., Natural 

and anthropogenic influences in fluvial geomorphology: Washington, D.C., American 

Geophysical Union, p. 197–208. 

Graf, W.L., 1987, Late Holocene sediment storage in canyons of the Colorado Plateau: 

Geological Society of America Bulletin, v. 99, p. 261–271. 

Greig-Smith, P., 1983, Quantitative plant ecology, 3rd ed.: Berkeley, Calif., University of 

California Press, 359 p. 

49
Hereford, R., 1984, Climate and ephemeral-stream processes: Twentieth-century 

geomorphology and alluvial stratigraphy of the Little Colorado River, Arizona: Geological 

Society of America Bulletin, v. 95, p. 654–668. 

Hupp, C.R., 1988, Plant ecological aspects of flood geomorphology and paleoflood history, in

Baker, V.R., Kochel, R.C., and Patton, P.C., eds., Chichester, N.Y., Wiley, p. 335–356. 

Hupp, C.R., and Osterkamp, W.R., 1985, Bottomland vegetation distribution along Passage 

Creek, Virginia, in relation to fluvial landforms: Ecology, v. 66, p. 670–681. 

Ivey, R.D., 1999, Flowering plants of New Mexico, 3rd. ed.: Albuquerque, New Mex., Rio 

Rancho Printing, 505 p. 

Kearney, T.H., and Peebles, R.H., 1960, Arizona flora, 2nd ed.: Berkeley, Calif., The University 

of California Press, 1,085 p. 

McCune, B., and Grace, J.B., 2002, Analysis of ecological communities: Gleneden Beach, Oreg., 

MjM Software Design, 300 p. 

Miller, M., 2005, Study plan for field-based evaluations of measures and measurement 

techniques to support long-term monitoring of terrestrial ecosystems in Colorado Plateau 

National Park Service Units: Kanab, Utah, 59 p. 

O’Dell, T.E., Garman, S.L., Evenden, A., Beer, M., Nance, E., Wight, A., Powell, M., Perry, D., 

DenBleyker, R., 2005, Northern Colorado Plateau inventory and monitoring network, vital 

signs monitoring plan: Moab, Utah, National Park Service, Inventory and Monitoring 

Network, 174 p. 

Peck, D.V., Lazorchak, J.M., and Klemm, D.J., eds, 2001, Unpublished draft, environmental 

monitoring and assessment program—Surface waters: Western pilot study field operations 

manual for wadeable streams: Washington, D.C., U.S. Environmental Protection Agency, 

EPA/XXX/X-XX/XXXX. 

Scott, M.L., Brasher, A.M.D., Reynolds, E.W., Caires, A.M., and Miller, M., 2005, The structure 

and functioning of riparian and aquatic ecosystems of the Colorado Plateau–conceptual models 

to inform monitoring: U.S. Geological Survey, 99 pp. 

Stromberg, J.C., Beauchamp, V.B., Dixon, M.D., Lite, S.J., and Parazick, C., 2007, Importance 

of low-flow and high-flow characteristics to restoration of riparian vegetation along rivers in 

arid southwestern United States: Freshwater Biology, v. 52, p. 651–679. 

Thomas, L., Hendrie, M. (ed.), Lauver, C., Monroe, S., Tancreto, N., Garman, S., and Miller, M., 

2005, Vital signs monitoring plan for the southern Colorado Plateau network: Phase III report: 

Flagstaff, Ariz., National Park Service, Southern Colorado Plateau Network, 116 p. 

Veenhuis, J.E., 2002, Effects of wildfire on the hydrology of Capulin and Rito De Los Frijoles 

Canyons, Bandelier National Monument, New Mexico: U.S. Geological Survey WaterResources Investigations Report 02-4152, 39 p. 

Welsh, S.L., Atwood, N.D., Goodrich, S., and Higgins, L.C., eds., 2003, A Utah flora, 3rd ed., 

revised: Provo, Utah, Print Services, Brigham Young University, 912 p. 

50
Appendix 

Appendix A. List of species and location. Site codes follow table 1. Species in bold represent 

the new synonomy based on the USDA Plants Database. 

Spp code Species name Family ARCH BAND CACH GLCA 

ACENEG Acer negundo Aceraceae x x 

ACHMIL Achillea millefolium Asteraceae x x 

ACHHYE Achnatherum hymenoides Poaceae x x 

AGRSTR Agrimonia striata Rosaceae x 

AGRSMI Agropyron smithii Poaceae x 

AGRTRA Agropyron trachycaulum Poaceae x 

AGROSTIS SP Agrostis sp Poaceae x 

ARGSTO Agrostis stolonifera Poaceae x x x 

ALLIUM Allium sp Liliaceae x 

ALNOBL Alnus oblongifolia Betulaceae x x 

AMAHYB Amaranthus hybridus Amaranthaceae x 

AMBACH Ambrosia acanthicarpa Asteraceae x 

AMEUTA Amelanchier utahensis Rosaceae x 

APOCAN Apocynum cannabinum Apocynaceae x 

ARTDRA Artemesia dracunculus Asteraceae x 

ARTLUD Artemesia ludoviciana Asteraceae x 

ARTTRI Artemesia tridentata Asteraceae x x x 

ARTCAM Artemisia campestris Asteraceae x 

ARTFRI Artemisia frigida Asteraceae x 

ARTLUD Artemisia ludoviciana Asteraceae x x x 

UNKN - ARTEM 

green Artemisia very green Asteraceae x 

ASTER SP Aster species Asteraceae x 

BACSAL Baccharis salicina Asteraceae x x 

BACC SP Baccharis sp Asteraceae x 

BAHDIS Bahia dissecta Asteraceae x 

BETULA Betula occidentalis Betulaceae x 

BORAG SPP Boraginaceae sp Boraginaceae x 

BOUCUR Bouteloua curtipendula Poaceae x 

BOUERI Bouteloua eriopoda Poaceae x 

BOUGRA Bouteloua gracilis Poaceae x x 

BRIBRA Brickellia brachyphylla Asteraceae x 

BRICAL Brickellia californica Asteraceae x 

BRIGRA Brickellia grandiflora Asteraceae x 

BROANO Bromus anomalus Poaceae x 

BROCAR Bromus carinatus Poaceae x 

BROCIL Bromus ciliatus Poaceae x 

BROINE Bromus inermus Poaceae x 

BROMUS SP Bromus sp Poaceae x x 

BROTEC Bromus tectorum Poaceae x x x x 

CALSCO Calamagrostis scopulorum Poaceae x 

51
CONVUL SPP Calystegia sp Convolvulaceae x 

CARMIC Carex microptera Cyperaceae x 

CARPRA Carex praegracilis Cyperaceae x 

CAREX SP Carex sp Cyperaceae x 

CASLIN Castilleja linariifolia Scrophulariaceae x 

CERARV Cerastium arvense Caryophyllaceae x 

CERFON Cerastium fontanum Caryophyllaceae x 

CHASER Chamaesyce serpyllifolia Euphorbiaceae x 

CHAMAESYCE SP Chamaesyce sp Euphorbiaceae x 

CHEFRE Chenopodium atrovirens Chenopodiaceae x 

CHEGRA Chenopodium graveolens Chenopodiaceae x 

CHRDEP Chrysothamnus depressus Asteraceae x 

CHRNAU Chrysothamnus nauseosus Asteraceae x x 

CHRVIS Chrysothamnus viscidiflorus Asteraceae x 

CICDOU Cicuta douglasii Apiaceae x 

CIRCHE Cirsium chellyense Asteraceae x 

CIRNEO Cirsium neomexicanum Asteraceae x 

CIRSIUM SP Cirsium sp Asteraceae x x 

CIRVUL Cirsium vulgare Asteraceae x x 

CLELIG Clematis ligusticifolia Ranunculaceae x x x 

COMDIA Commelina dianthifolia Commelinaceae x 

CONCAN Conyza canadensis Asteraceae x x 

CONSCH Conyza schidenea Asteraceae x 

CORSER Cornus sericea Cornaceae x 

CORAUR Corydalis aurea Fumariaceae x 

CYP SPP Cyperaceae sp (broad-leaf) Cyperaceae x 

CYPARI Cyperus aristatus Cyperaceae x 

CYPESC Cyperus esculentes Cyperaceae x 

DACGLO Dactylis glomerata Poaceae x x 

DISSPI Distichlis spicata Poaceae x x 

ECHCRU Echinochloa crusgalli Poaceae x 

ELEPAL Eleocharis palustris Cyperaceae x 

ELYCAN Elymus canadensis Poaceae x x x 

ELYELY Elymus elymoides Poaceae x x 

ELYREP Elymus repens Poaceae x x 

ELYMUS SP Elymus sp Poaceae x x 

ELYTRA Elymus trachycaulus Poaceae x x 

EPICIL Epilobium ciliatum Onagraceae x 

EPIL SPP Epilobium sp Onagraceae x 

EQUARV Equisetum arvense Equisetaceae x x x 

EQUHYE Equisetum hyemale Equisetaceae x x x 

EQULAE Equisetum laevigatum Equisetaceae x x 

EQU SP Equisetum sp Equisetaceae x 

ERIFLA Erigeron flagellaris Asteraceae x x 

ERIG SPP Erigeron sp Asteraceae x 

ERIONEURON SP Erioneuron sp Poaceae x 

EROCIC Erodium cicutarium Geraniaceae x x 

EUPDEN Euphorbia dentata Euphorbiaceae x 

52
EUTOCC Euthamia occidentalis Asteraceae x x 

FESARI Festuca arizonica Poaceae x 

FESTOCT Festuca octoflora Poaceae x 

FESTUC SPP Festuca sp Poaceae x 

FORNEO Forestiera neomexicana Oleaceae x 

GALAPA Galium aparine Rubiaceae x 

GALIUM SP Galium sp Rubiaceae x 

GALWRI Galium wrightii Rubiaceae x 

GERCAE Geranium atropurpureum Geraniaceae x 

GER SP Geranium sp Geraniaceae x 

GRISQN Grindelia nana Asteraceae x 

GUTSAR Gutierrezia sarothrae Asteraceae x x 

HELMUL Helimerus multiflora Asteraceae x 

LINEM SP Hesperolinon sp Linaceae x 

HEITVIL Heterotheca villosa Asteraceae x x x 

HYMFIL Hymenopappus filifolius Asteraceae x 

IPOAGR Ipomopsis aggregata Polemoniaceae x x x x 

JUNBAL Juncus baliticus Juncaceae x x x 

JUNSP Juncus sp Juncaceae x x x 

JUNMON Juniperus monosperma Cupressaceae x 

JUNOST Juniperus osteosperma Cupressaceae x 

JUNSCO Juniperus scopulorum Cupressaceae x 

JUN SPP Juniperus sp Cupressaceae x 

LACSER Lactuca serriola Asteraceae x 

LAPOCC Lappula occidentalis Boraginaceae x 

MACGRI Machaeranthera gracilis Asteraceae x 

MAHREP Mahonia repens Berberidaceae x 

MEDLUP Medicago lupulina Fabaceae x 

MEDSAT Medicago sativa Fabaceae x 

MELILOTUS Melilotus sp Fabaceae x x x 

MENARV Mentha arvensis Lamiaceae x 

MENMUL Mentzelia multiflora Loasaceae x 

MIMFRE Mimulus fremontii Scrophulariaceae x 

MIM SPP Mimulus sp Scrophulariaceae x 

MIRLIN Mirabilis linearis Nyctaginaceae x 

MIRMUL Mirabilis multiflora Nyctaginaceae x 

MIROXY Mirabilis oxybaphoides Nyctaginaceae x 

MULASP Muhlenbergia asperifolia Poaceae x x x 

MUHMIN Muhlenbergia filiformis Poaceae x 

MUHPOR Muhlenbergia porteri Poaceae x 

MUHLENB SP Muhlenbergia sp Poaceae x 

ROR SPP Nasturtium sp Brassicaceae x 

OENBIE Oenothera biennis Onagraceae x x 

OENPAL Oenothera pallida Onagraceae x x 

OENETH SPP Oenothera sp Onagraceae x x x 

OPUNTIA CHOLLA Opuntia cholla Cactaceae x 

OPUNTIA SP Opuntia sp Cactaceae x x 

OXAVIO Oxalis violacea Oxalidaceae x 

53
PANBUL Panicum bulbosum Poaceae x 

PARQUI Parthenocissus quinquefolia Vitaceae x 

PENLIN Penstemon lentus Scrophulariaceae x 

PENSTEMON Penstemon sp Scrophulariaceae x x x x 

PHAARU Phalaris arundinacea Poaceae x 

PHIMIC Philadelphus argenteus Hydrangeaceae x x 

PHRAUS Phragmites australis Poaceae x 

PHYHED Physalis hederifolia Solanaceae x 

PINEDU Pinus edulis Pinaceae x 

PINPON Pinus ponderosa Pinaceae x 

PIPMIC Piptatherum micranthum Poaceae x 

PLALAN Plantago lanceolata Plantaginaceae x 

PLAMAJ Plantago major Plantaginaceae x 

POA COMB Poa combo (pratensis/compressa) Poaceae x x 

POAFEN Poa fendleriana Poaceae x x 

POAPAL Poa palustris Poaceae x x 

POA SP Poa sp Poaceae x x x 

POLPER Polygonum persicaria Polygonaceae x 

POPACU Populus acuminata Salicaceae x 

POPFRE Populus fremontii Salicaceae x x x 

POPULUS SP Populus sp Salicaceae x 

POTAMOGETON SP Potamogeton sp Potamogetonaceae x 

POT SPP Potentilla sp Rosaceae x 

PRUNELLA SP Prunella sp Lamiaceae x 

PRUVUL Prunella vulgaris Lamiaceae x 

PSEMEN Pseudotsuga menziesii Pinaceae x 

PTETRI Ptelea trifoliata Rutaceae x 

QUEGAM Quercus gambelii Fagaceae x x x 

QUEGRI Quercus grisea Fagaceae x 

RANAQU Ranunculus aquatilis Ranunculaceae x 

RANCYM Ranunculus cymbalaria Ranunculaceae x 

RANMAC Ranunculus macounii Ranunculaceae x 

RHUTRI Rhus aromatica Anacardiaceae x x x 

RIBS SPP Ribes sp Grossulariaceae x 

UNKN RIB-col Ribes unknown-collected Grossulariaceae x 

ROSWOO Rosa woodsii Rosaceae x x x 

RUBIDE Rubus ideaus Rosaceae x 

RUDLAC Rudbeckia lacinata Asteraceae x 

RUMCRI Rumex crispus Polygonaceae x x 

SALEXI Salix exigua Salicaceae x x x 

SALGOO Salix gooddingii Salicaceae x 

SALLAE Salix laevigata Salicaceae x 

SALTRA Salsola tragus Asteraceae x 

SAXRHO Saxifraga rhomboidea Saxifragaceae x 

SCHPUN Schoenoplectus pungens Cyperaceae x x 

SCHOENOPLECTUS 

SP Schoenoplectus sp Cyperaceae x 

SCIRPUS SP Scirpus sp Cyperaceae x 

SENSPA Senecio riddellii Asteraceae x 

54
SOLJAM Solanum jamesii Solanaceae x 

SONASP Sonchus asper Asteraceae x 

SPHAERALCEA Sphaeralcea sp Malvaceae x x x 

SPOCRY Sporobolus cryptandrus Poaceae x x x x 

SPOR SP Sporobolus sp Poaceae x 

SYMORE Symphoricarpos oreophilus Caprifoliaceae x 

TAMRAM Tamarix ramosissima Tamaricaceae x 

TAROFF Taraxacum officinale Asteraceae x 

TARAX SP Taraxacum sp Asteraceae x x 

THAFEN Thalictrum fendleri Ranunculaceae x x 

THAARV Thlaspi arvense Brassicaceae x 

TOXRYD Toxicodendron rydbergii Anacardiaceae x 

Tragopogon lamottei Asteraceae x 

TRAG SPP Tragopogon sp Asteraceae x 

TRIREP Trifolium repens Fabaceae x 

TRIGLOC Triglochin sp Juncaginaceae x 

TYPLAT Typha latifolia Typhaceae x 

UNKN heart Unknown heart-shaped x 

URTDIO Urtica dioica Urticaceae x 

VERTHA Verbascum thapsus Scrophulariaceae x 

VERANA Veronica anagallis-aquatica Scrophulariaceae x 

VERONICA Veronica sp Scrophulariaceae x 

VICAME Vicia americana Fabaceae x 

VIOLA SP Viola sp Violaceae x x 

XANSTR Xanthium strumarium Asteraceae x x 

ANNUAL SETARIA x 

UNKN BIGMUL x 

LITTLE BLUE 

STEM x 

LOBEY 

COTYLEDON x 

LOBEY SPROUT x 

RED STEMMED 

COTY x 

SHRUBBY ASTER 

ROSETTE x 

SPHAERALCEA x 

UKNWN LITTLE 

PENSTEMON x 

UKNWN LITTLE 

SEED GRASS x 

UNKN 

BRASSICACEA x 

UNKN 

COTYLEDON x 

UNKN 

COTYLEDON 2 x 

UNKN 

COTYLEDON 3 x 

UNKN 

COTYLEDON 4 x 

55
UNKN 

COTYLEDON 5 x 

UNKN DALEA SP x 

UNKN GLICK-LIKE 

COL x 

UNKN GRASS x 

UNKN POINTY 

COTYL x 

UNKN ROSETTE x 

UNKWN ANN 

GRASS x 

UNKWN ASTER 

BLUE x 

UNKWN ASTER 

HAIRY LEAF x 

UNKWN BASAL 

ROSETTE LINEAR x 

UNKWN 

COMPOSIT 

ROSETT DIVIDED 

x 

UNKWN 

COMPOSIT 

STELLATE 

x 

UNKWN 

COMPOUND 

PINNATE COL 

x 

UNKWN 

CRENULATE 

PUBESCENT 

ROSETTE 

x 

UNKWN 

EUTHORBIA x 

UNKWN 

GLABROUS 

CIRSIUM 

x 

UNKWN 

GLANDLAR HAIRY 

LEAF 

x 

UNKWN 

GLANDULAR MAT 

GROUND COVER 

x 

UNKWN GRASS x 

UNKWN GRAY 

BASAL x 

UNKWN GRAY 

BASAL ROSETTE x 

UNKWN 

LEATHERY BASAL 

ROSETTE 

x 

UNKWN LITTLE 

SHEATH GRASS x 

UNKWN PLAIN 

SPATULATE 

ROSETTE 

x 

UNKWN ROSETTE 

GREEN x 

56
57

UNDER/PURPLE 

TOP 

UNKWN ROSETTE 

LOBED x 

UNKWN ROSETTE 

SPATULATE x 

UNKWN 

SCHP/ELGANS x 

UNKWN SENCIO 

PURPLE SERRATE x 

UNKWN SENECIO x 

UNKWN SENECIO 

LOBED x 

UNKWN SENECIO 

PURPLE x 

UNKWN SENECIO 

SP x 

UNKWN SENECIO 

SP PURPLE x 

UNKWN SILVER 

LEAF ROSETTE x 

UNKWN SPIRAL 

BURR ANNUAL x 

UNKWN 

SPORABOLIS BIG x 

UNKWN SUCC 

GRVOVY x 

UNKWN 

SUCCLENT COL x 

UNKWN TOOTHED 

COMPOSITE x 

UNKWN WHITE 

MIDRIB ROSETTE x 

UNKWN YELLOW 

LEAF COMPOSITE x 

UNNWN SPAT 

ROSETTE x 

UPLAND GRAY 

MAT FORMING 

SHRUB 

x