Littoral and shoreline wood in mid-continent great rivers (USA)

RIVER RESEARCH AND APPLICATIONS

River. Res. Applic. 26: 261–278 (2010)

Published online 2 April 2009 in Wiley InterScience

LITTORAL AND SHORELINE WOOD IN MID-CONTINENT GREAT RIVERS(USA)y

TED. R. ANGRADI,* DEBRA L. TAYLOR, TERRI M. JICHA, DAVID W. BOLGRIEN,MARK S. PEARSON and BRIAN H. HILL

United States Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research

Laboratory, Mid-Continent Ecology Division, 6201 Congdon Boulevard, Duluth, Minnesota 55804, USA

(www.interscience.wiley.com) DOI: 10.1002/rra.1257

ABSTRACT

Woody debris has several important roles in running water. Less is known about the ecology of wood in great rivers than insmaller rivers and streams. We used a probability survey to estimate the abundance of littoral and shoreline wood along thefollowing mid-continent great rivers of the United States in summer 2004–2006: the Missouri River, Upper Mississippi River,and the Ohio River. We counted wood pieces >0.3 m in diameter from a zone between the bank full level out into the river 10 m.We categorized wood according to its origin and function as ‘‘beached’’ (transported from upriver but not providing aquatichabitat), ‘‘wet’’ (origin unknown and providing aquatic habitat; includes snags), or ‘‘anchored’’ (attached to the bank at itscurrent location and providing aquatic habitat). We counted 5900 pieces of wood at 447 sites across rivers. Approximately56 percent of pieces were beached, 30 percent were wet, and 14 percent were anchored. Overall, mean abundance of wood was2.6 pieces of wood 100 m�1 of shoreline (approximately 3.0 m3 100 m�1). Abundance of wood (pieces per unit distance of river)was much lower than has been reported for many smaller streams and rivers. There was more wood along the Upper MississippiRiver (3.3 pieces 100 m�1) than elsewhere (�2.4 pieces 100 m�1). The mean abundance of wood on the Ohio River decreasedsignificantly between the 2004 and 2005 survey periods due to high flows. Longitudinal patterns in wood abundance were weak.There was less anchored and wet wood along shorelines protected by revetment (e.g., rip rap). There was generally more woodalong shorelines where the riparian land use was characterized as forest rather than agriculture or developed. Mean abundance ofwood along forested, un-revetted shorelines was approximately four pieces 100 m�1 of shoreline (¼ 80 pieces km�1 of river).This estimate of mean wood abundance for what amounts to least disturbed riparian and shoreline conditions is relevant for greatriver bioassessment and management. Published in 2009 John Wiley & Sons, Ltd.

key words: great river; Missouri River; Mississippi River; Ohio River; wood; snags; riparian; land use

Received 18 August 2008; Revised 6 January 2009; Accepted 27 January 2009

INTRODUCTION

Wood in the channels and along the banks of large rivers provides ecosystem services at multiple scales, including

hard substrate for the production of aquatic invertebrates eaten by sport fish (Benke and Wallace, 2003), habitat for

sport fish (Crook and Robertson, 1999; Zalewski et al., 2003), and habitat for riparian organisms (Steel et al., 2003).

In some river channel types, wood can increase habitat heterogeneity at larger scales by causing bars, islands, and

pools to form (Abbe and Montgomery, 1996; Montgomery et al., 2003). Although the importance of wood in rivers

for maintaining habitat and biological complexity has been repeatedly demonstrated (Gurnell et al., 2005), the

public often perceives wood in rivers as untidy, unhealthy, and, therefore, undesirable (Petts and Welcomme, 2003;

Chin et al., 2008).

In the mid-continent great rivers of the United States, the Upper Mississippi River, Missouri River, and Ohio

River, much of the wood in channels is in the form of ‘‘snags’’ (also called ‘‘planters’’ or ‘‘sawyers’’). We cannot

improve on an early description of how a snag is formed when an undermined tree falls into the Missouri River:

*Correspondence to: Ted. R. Angradi, United States Environmental Protection Agency, Mid-Continent Ecology Division, 6201 CongdonBoulevard, Duluth, MN 55804, USA. E-mail: [email protected] article is a U.S. Government work and is in the public domain in the U.S.A.

Published in 2009 John Wiley & Sons, Ltd.

262 T. R. ANGRADI ET AL.

In most instances a large body of earth is attached to the roots of the tree, [and] it sinks that part to the bottom of

the river, whilst the upper part, more buoyant rises to the surface in an inclined posture, generally with the head

of the tree pointing down the river. Some of these are firmly fixed and immovable and are therefore termed

planters.

(Bradbury, 1817; cited in Gillespie, 2000)

During the steamboat era (c.1820–1890 in the United States, Funk and Robinson, 1974), snags were detrimental

to another important ecosystem service provided by these rivers—unobstructed navigation (Chittenden, 1962;

Fremling, 2005). Removal of snags from the channel has a long history on mid-continent rivers in the United States

and elsewhere (Funk and Robinson, 1974; Sedell and Froggatt, 1984; Triska, 1984; Wallace and Benke, 1984;

Erskin and Webb, 2003). In addition to direct removal of wood from the channel, conversion of temperate river

floodplains from forest to agriculture and into towns and cities has eliminated or reduced the riparian source of

wood in many reaches (Piegay, 2003). For example, on the Upper Missouri River, more than half of the original

floodplain forest was gone by 1980 (Johnson, 1992). Similar changes in land use have occurred on the Lower

Missouri River (Bragg and Tatschi, 1977). Impoundment by high dams on the Missouri River has eliminated down

river transport of wood for thousands of kilometers. Flow regulation by dams has also greatly reduced overbank

flooding and the lateral migration of channels into floodplain forest stands (NRC, 2002), the ultimate source of large

wood in rivers. Wood is still a habitat feature of many large rivers in the United States, but is probably present at a

small fraction of its historical abundance (e.g., before European settlement) in most reaches (Bodmer, 1833; Sedell

and Froggatt, 1984; Benke et al., 1985; Mestle and Hesse, 1993; Hesse, 1996; cf. Lehtinen et al., 1997; Piegay,

2003).

Its historical role in river ecosystems and its relationship to floodplain land use make wood an important

consideration for river and floodplain habitat rehabilitation (Abbe et al., 2003). River rehabilitation that is based on

virtually any conception of a more naturalized river system will include conservation and restoration of the wood

supply and of the natural distribution and dynamics of wood in the channel and on the riverbank. Rehabilitation

success will therefore require an understanding of the factors underlying the abundance, distribution, and dynamics

of wood (Johnson et al., 2006), all of which are poorly documented for great rivers.

As part of a large-scale assessment of environmental conditions in the mid-continent great rivers (Angradi et al.,

in press), we estimated abundance of wood in the littoral zone and along the shoreline at 447 sites along the

Missouri River, Upper Mississippi River, and Ohio River. We assigned each piece of wood to a category related to

its function and origin including beached pieces transported from upriver, snags and other inundated wood, and

pieces anchored to the bank and/or originating at their current location.

Ours is among the first studies to quantify wood in very large rivers. Piegay (2003) considered Triska’s (1984)

account of the nineteenth century ‘‘Great Raft’’ of wood on the Red River (Louisiana, USA) as the only study of

wood in a very large floodplain river so far. In this paper, we report the abundance of wood of each type along each

great river, temporal and longitudinal patterns in abundance, and the relationship of wood abundance to shoreline

modification and riparian land use.

STUDY REACHES AND METHODS

We counted large piece of wood (�5 m long and �0.3 m in diameter) on the ninth-order Ohio River from the

confluence of the Allegheny River and Monongahela River to the confluence with the Mississippi River at Cairo,

Illinois (ca. 1560 km); the tenth-order Upper Mississippi River from Lower St. Anthony Falls in Minneapolis,

Minnesota to the confluence with the Ohio River (ca. 1400 km); and the ninth-order Missouri River from Fort Peck

Dam in Montana to the confluence with the Mississippi River near St. Louis, Missouri River (ca. 2900 km).

Reservoirs on the Missouri River in North and South Dakota were not included in the study. The Missouri River,

Upper Mississippi River, and Ohio River have a mean annual discharge range (top of study reach–mouth) of 264–

2425; 337–5820; and 950–7869 m3 s�1; USGS, 2008a), and drain 1.37, 0.49, and 0.53 million km2, respectively

(Benke and Cushing, 2005). Mean (�95% CI) wetted width at sites on the Missouri River, Upper Mississippi River,

and Ohio River was 290� 17, 927� 154, and 562þ 41 m, respectively.

Published in 2009 John Wiley & Sons, Ltd. River. Res. Applic. 26: 261–278 (2010)

DOI: 10.1002/rra

WOOD IN GREAT RIVERS 263

The Upper Missouri River is a series of large main-stem reservoirs and two inter-reservoir tailwater reaches,

the Garrison Reach (2226–2066 river kilometer (rkm) from the mouth) and the Ft. Peck Reach (rkm 2833–2459).

The Lower Missouri River has a more naturalized hydrograph, but is completely channelized and extensively

revetted for commercial navigation (Galat et al., 2005). The Upper Mississippi River includes an impounded

reach (above rkm 327 as measured from the confluence with the Ohio River) that includes 26 navigation pools

and an un-impounded or ‘‘open river’’ reach (below rkm 327). The Ohio River is impounded into 19 navigation

pools.

All site locations were selected using a probabilistic sample design (Angradi et al., in press). Each probability

site was selected by a survey algorithm as a single point on the river centerline as defined by the National

Hydrography Dataset (USGS, 2008b). We counted wood in 2004–2006 during the period July–September (Angradi

et al., in press). This paper contains data from 476 visits to 447 unique sites (some sites were visited in more than

1 year). Unless otherwise noted, all analyses herein are based on the first visit to each unique site (n¼ 447).

At each site, wood meeting the minimum size criteria was counted on a 500-m transect along a randomly-picked

shoreline (right or left) usually from a boat in the river cruising as close to the shore as possible. The minimum size

for wood was �5 m long and �0.3 m in diameter at the large end. Wood was categorized by type, after Angradi

et al. (2004), as ‘‘wet’’: at least partly below the wetted edge; ‘‘beached’’: between the wetted perimeter and the

estimated bank full elevation but not having originated at its present location; or ‘‘anchored’’: partly below the

wetted perimeter (providing aquatic habitat) but originating at the present location. Anchored wood leaning over or

into the channel but not providing aquatic habitat was not counted. Anchored wood is typically a tree that has been

undermined by bank erosion and has slid or toppled into the river but which has not been washed away. Wind-

thrown and beaver-felled trees often become anchored wood before they enter the channel completely and become

snags or are transported down river. Each piece of wood was categorized as large (>0.6 m in diameter at the large

end) or small (0.3–0.6 m in diameter at the large end). For wet wood in deep water (also called snags), the diameter

category of the large end was often unobservable. In these cases, we estimated, based on the visible part of the snag,

whether the piece was in large or small diameter category. The number of pieces was estimated for logjams in which

some pieces were not visible.

Our methods are similar to but not identical to previous Environmental Protection Agency (EPA) methods (e.g.,

Lazorchak et al., 2000). Our method had fewer length (1 vs. 3) and diameter (2 vs. 4) categories than previous EPA

methods for non-wadeable streams. Our simplification of the methods was based on our observations of wood in the

Upper Missouri River in 2001–2002 (Angradi et al., 2004). During that study, we noticed that, unlike rivers of the

Pacific Northwest with their more common gigantic old-growth woody debris (e.g., Latterell and Naiman, 2007),

wood in the Missouri River was nearly all �1 m diameter at the large end and �20 m in length. Furthermore,

accurate estimation of piece length and maximum diameter was difficult for wood in the channel because usually

only a portion of the wood was visible.

In this paper, we report abundance of wood as the number of pieces 100 m�1 of shoreline. Since we only had two

diameter classes and only a minimum length category for wood, volume of wood (100 m3 m�1) could only be

approximated. Based on the formula for the volume of a cylinder, we estimated the nominal mean volume for a

small and large piece as 0.63 and 2.51 m3, respectively, using the method described in Kaufmann et al. (1999).

Wood abundance estimates in this paper can be converted to a rough estimate of volume (100 m3 m�1) using the

formula: mean volume 100 m�1¼ 1.21 (mean abundance 100 m�1) – 0.19. (r2¼ 0.89; RMSE¼ 1.31; n¼ 447).

At each site, we estimated the percent of the 500 m shoreline transect that was artificially revetted. Revetments

included blanket rock (rip rap), hard-point features (e.g., dikes, weirs), breakwalls, and trash (e.g., rubble, car

bodies). We also determined the dominant land use of the riparian zone at the site as either forest, agriculture

(including pasture and range), or developed (including urban, suburban, and commercial). We estimated the

proportion of the 500 m reach that was inside bend, outside bend, or neither. Finally, we used a convex canopy

densiometer to estimate total canopy coverage at the river margin. Field methods are described in more detail in

Angradi (2006).

We analyzed the data using analysis of variance (ANOVA) in SAS (Proc GLM, version 9.1, SAS Institute, Cary,

North Carolina). Wood abundance was log-transformed to correct for non-normality. We made pair-wise

comparisons using t-tests. We estimated regression parameters in SAS (Proc Reg). We tested for significant

coefficients of spatial (i.e., longitudinal downriver) autocorrelation (ra) in SAS (Proc Reg; Durbin–Watson option).


DOI: 10.1002/rra

Table I. Total number of wood pieces counted in the study (pooled across rivers) by size and type. See text for size and typedefinitions. Percentage of the total (5900 pieces) is shown in parentheses (n¼ 447 sites). Only pieces �5 m long and �0.3 m indiameter were counted

Size Anchored Wet Beached All wood

Small 576 (13) 1320(31) 2414 (56) 4310 (73)Large 278 (17) 408 (26) 904 (57) 1590 (27)


RESULTS

We counted 5900 pieces of wood at 447 sites (Table I). Most (73%) of the wood was in the small size category.

Approximately 56 percent of the wood was beached, 30 percent was wet and 14 percent was anchored to the

shoreline. The distribution of wood among types was similar between large and small wood so we combined size

categories for most analysis. The distribution of wood among size categories and types was almost identical among

the three rivers (Figure 1).

Figure 1. Mean abundance of wood by river, wood type, and size. Error bars are 95 percent confidence intervals. Percentage of the total for eachcategory is shown on the figure


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Figure 2. Mean daily discharge during the study. Vertical lines demarcate beginning and end of each summer sample season. Data downloadedfrom http://waterdata.usgs.gov/nwis/rt


River discharge during the summer survey periods was similar among years except on the Ohio River in

September 2004 when high flows associated with a hurricane occurred (Figure 2). On the Missouri River and Ohio

River, the highest flows during the study occurred between the 2004 and 2005 survey periods. The highest flows on

the Missouri River during the study (June 2005, Figure 2) were last exceeded in 2001, 4 years earlier; the highest

flows on the Ohio River (January 2005) during the study had not been exceeded since 1997, 8 years earlier (USGS,

2008a).

At the river-scale, there was a strong effect of year on wood abundance for the Ohio River, but not for the other

rivers (Figure 3, Appendix A). Between 2004 and 2005 sample periods, wood abundance decreased by two-thirds in

the Ohio River. Several sites were visited both in 2004 and 2005. Mean (�95%CI) loss of wood of all types at

revisited sites on the Upper Mississippi River between years was 0.7� 2.0 pieces 100 m�1 (n¼ 10). Mean loss on

the Missouri River was 1.0� 2.6 pieces 100 m�1 (n¼ 10); and mean loss on the Ohio River between 2004 and 2005

was 3.1� 3.2 pieces 100 m�1 (n¼ 9). The greater loss of wood at revisited Ohio River sites corroborates the annual

variation in river-scale estimates of abundance (Figure 3), but the differences between rivers are not significant,

probably due to the small number of revisited sites.

The overall abundance of wood was 2.6 pieces 100 m�1 of shoreline (ca. 3.0 m3100 m�1) (Table II). The

abundance of wood was higher in the Mississippi River (3.3 pieces 100 m�1, all types combined) than the other

rivers (<2.4 pieces 100 m�1). There was a higher percentage of sites with no wood on the Ohio River (20%) than on

the Missouri River (7%) or the Upper Mississippi River (11%). The effect of river on abundance depended on year,

however. There was a significant interaction between river and year for anchored, wet, and all types combined

(Appendix B). For these wood types, wood abundance on the Ohio River was at least as high as the other rivers in

2004, but was lower than the other rivers in 2005 and 2006, possibly due to the high flows on the Ohio River.


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Figure 3. River-scale inter-annual variation in the mean abundance of wood. Error bars are 95 percent confidence intervals. Symbols offset forclarity


We did not find strong longitudinal patterns in the total abundance of wood in any river (Figure 4). There were

some differences between reaches in the maximum abundance of wood observed. For example, unlike the Lower

Missouri River, no site on the Upper Missouri River (the Garrison and Ft. Peck reaches) had more than 10 pieces

100 m�1. Likewise, only one site on the un-impounded open river reach had more than 10 pieces 100 m�1. There

was little or no wood immediately below dams on the Missouri River, as would be expected, since the reservoirs

export no wood. We could not discern a larger-scale pattern in the distribution of wood within the tailwater reaches

of the Upper Missouri River or in the navigation pools of the Upper Mississippi River or Ohio River.

For readily transported wood, represented in our study by beached pieces, we would expect wood to accumulate

down river, especially on the Missouri River, where high dams prevent any wood input from upriver. We reason that


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Table II. Mean abundance (number of pieces 100 m�1 of shoreline), coefficient of variation (CV), and spatial autocorrelationcoefficient (r<sub>a) of wood in mid-continent great rivers. Spatial autocorrelation coefficient based on log-transformedabundance of wood

River n Anchored Wet Beached All types

Mean(�95%CI)

CV(%)

ra Mean(�95%CI)

CV(%)

ra Mean(�95%CI)

CV(%)

ra Mean(�95%CI)

CV(%)

ra

MissouriRiver

183 0.38� 0.12 215 �0.02 0.69� 0.16 162 �0.11 1.39� 0.27 137 0.07 2.46� 0.39 111 �0.05

UpperMississippiRiver

144 0.46� 0.13 169 �0.002 0.98� 0.30 187 0.001 1.88� 0.41 134 �0.07 3.31� 0.60 109 0.05

Ohio River 120 0.29� 0.17 312 0.14 0.66� 0.18 160 �0.05 1.16� 0.37 176 0.08 2.11� 0.50 131 0.14All 447 0.38� 0.08 218 NA 0.77� 0.13 178 NA 1.46� 0.21 146 NA 2.64� 0.29 117 NA

NA¼ not applicable.

Figure 4. Longitudinal variation in mean total abundance of wood by river. Vertical lines denote locations of high dams (Missouri River) andnavigation dams. Gaps in the Missouri River are main-stem reservoirs that were excluded from the study. Dashed horizontal lines are the grand

mean for the river pooled across years


DOI: 10.1002/rra


Figure 5. Longitudinal trends in the abundance of beached wood. Lines are simple linear regressions. Gaps in the Missouri River are main-stemreservoirs that were excluded from the study. There was no trend for the Upper Mississippi River


downriver transport would eventually deplete the supply of wood below dams because Missouri River dams

completely cut off wood imports. Transported wood would accumulate in lower reaches before it is finally trapped

above bankfull stage on the floodplain, reaches the sea, or meets some other fate. There was some evidence for this

pattern on the Missouri River and Ohio River where there was a weak but significant (slope 6¼ 0, p< 0.05) negative

relationships between abundance of beached wood and distance from the mouth of the river (Figure 5). We did not

detect this effect on the Upper Mississippi River.

The distribution of wood was extremely patchy. Total abundance ranged from 0 to >10 pieces 100 m�1 often at

adjacent sites. Coefficients of variation in wood abundance were >100 percent in every case (Table II) and were

highest for anchored wood and lowest for the nearly ubiquitous beached wood. There was no relationship between

the abundance of wood at a site and the abundance at the next upriver site: spatial autocorrelation coefficients (ra)

were� 0.15 for all wood types in all rivers (Table II).

Because our shoreline transects were relatively short (500 m), most sites were either 100 percent un-revetted or

100 percent revetted (Figure 6). We divided sites into three revetment classes: high revetment (�80% revetted),


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Figure 6. Frequency of percent revetment for the Missouri and Upper Mississippi River, combined (top panel), and the mean abundance bywood type for sites with a high and low degree of revetment. Error bars are 95 percent confidence intervals


medium revetment (21–79% revetted), and low revetment (�20% revetted). Only 14 Ohio River sites (11%) were

in the high or medium revetment class, so we omitted the Ohio River from this analysis.

Sites with low percent revetment had more wood (Figure 6) than did highly revetted sites. The effect was

strongest for anchored wood on the Mississippi River and wet wood on the Missouri River (Appendix C). The effect

of revetment on beached wood was not significant. Across rivers, there was approximately one-third more total

wood at sites without revetment than at highly revetted sites.

On the Missouri River, land use at most sites was agriculture (72%), including rangeland (Figure 7). On the

Upper Mississippi River and Ohio River, land use was most often forest (74 and 60%, respectively). There was more

anchored and total wood along forested reaches on the Upper Mississippi River and for all rivers combined than

along agricultural or developed reaches. Except for the Ohio River, the abundance of wood was generally highest

for forest land use, followed by developed land (Figure 7). There was a trend on the Missouri River and Upper

Mississippi River for the highest abundance of wood to be at sites with forest land use and low (usually no)

revetment, and the least wood to be at sites with agricultural land use and high degree of revetment (Figure 8). The

percentage of wood that was anchored on forested, un-revetted shorelines was slightly higher (approximately 20%


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Figure 7. Mean abundance of wood by river and land use for anchored wood and all types combined. Error bars are 95 percent confidenceintervals


anchored) than for all sites (14%). To examine the association between the condition of the riparian forest and the

abundance of wood entering the channel, we plotted riparian forest canopy density against abundance and

percentage of anchored wood. For the Missouri River and Upper Mississippi River, there was a significant positive

relationship between canopy density at the river’s edge and the abundance of wood and the percent of wood that was

anchored (Figure 9). Seventy-five sites on the Missouri River were characterized as being on an outside bend or on

an inside bend (Figure 10). There was more wet wood and wood of all types on inside bends than on outside bends

(p< 0.05, t-tests). Macro-habitat at most sites on the impounded Upper Mississippi River and Ohio River was

classified as pool, so we did not conduct this analysis for those rivers.

DISCUSSION

Wood was not abundant in any of the mid-continent great rivers. Overall, mean abundance of wood was 2.6 pieces

100 m�1. Approximately 12 percent of sites had no wood; fewer than 10 percent of sites had more than 10 pieces

100 m�1. Estimates of wood abundance for other large rivers are few and often complicated by different units and


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Figure 8. Mean abundance of wood by river, land use, and revetment class for all wood types combined. Error bars are 95 percent confidenceintervals. Sample sizes shown on bars

Figure 9. Linear relationships between riparian forest canopy density and the abundance and percentage of anchored wood for forested sites onthe Missouri River and Upper Mississippi River


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Figure 10. Mean abundance of wood on inside and outside bends of the Missouri River. Error bars are 95 percent confidence intervals. Samplesize shown on bars


size categories. Angradi et al. (2004), using very similar field methods, conducted a complete census of wood in the

Garrison Reach of the Upper Missouri River. Their estimate of 2.1 pieces 100 m�1 is within the confidence limits of

our estimate of wood abundance in the Garrison Reach (1.64� 1.07 100 m�1, from data in Figure 4). The

corroboration of our estimate by the earlier complete census suggests that the probabilistic survey provides an

accurate estimate of wood abundance.

Elliott and Jacobson (2006) estimated wood abundance in the National Recreational River (NRR) reach of the

Missouri River (rkm 1194–1399 on our Figure 4) using orthophotos. They estimated that 26 percent of the 52 wood

pieces km�1 of river was within 10 m of shore. This is equivalent to approximately 0.7 pieces of wood 100 m�1

of shoreline. Their estimate is low compared to our estimate of 3.8� 2.7 pieces 100 m�1 for the same reach (from

data in Figure 4). The resolution of their images apparently limited their ability to detect pieces � 1 m in diameter,

however. In addition, riparian vegetation may have partially obscured wood outside the wetted channel. Most (74%)

of the wood counted by Elliott and Jacobson (2006) was more than 10 m from the shoreline. This contrasts with our

observations of the Lower Missouri River, which is channelized for navigation and where most wood is close to

shore and outside of the navigation channel. The wide, shallow, and sandbar-filled NRR reach of the Missouri River

probably shares some geomorphic characteristics with the pristine river, suggesting that, historically, wood was

distributed more evenly across the channel than it is today.

Gurnell (2003) predicted the volume of wood in river channels based on channel width. Her regression included

data from a variety of stream types in the eastern United States, Alaska, Australia, and Europe, ranging in width

from <1 to 1000 m. The volume of wood predicted for our sites (channel width¼ 290–927 m) would be

approximately 38–56 m3 ha�1. We estimated the mean volume of wood in the littoral and shoreline area of river in

which we actually counted wood as 10–20 m3 ha�1. We consider this an underestimate of the true total because not

all submerged wood was visible to us when counting wood. Our estimates of mean wood volume based on the entire

width of the channel (and assuming no wood was >10 m from the bank) were much lower, 0.8–2.4 m3 ha�1. The

volume estimates in Gurnell’s dataset for the largest channels were from the Fiume Taliamento (Italy), a relatively

un-impacted braided gravel-bed river that is likely more retentive of transported wood than the deeper, channelized,

and impounded rivers we studied. We conclude (and we acknowledge the crudeness of our volume estimates) that

the mid-continent great rivers of today have less wood per unit of surface area than other wide rivers that have been

studied, but that the difference may be less than an order of magnitude. Clearly, more quantification of wood in the

largest rivers is needed.

Stoddard et al. (2005) estimated the abundance of wood along wadeable streams in the western United States

using methods very similar to ours. On average (� 95% CI), there were 15� 2 pieces 100 m�1 of stream channel.

This wood abundance is three-fold our estimate of just over five pieces of littoral wood 100 m�1 of great river. For

plains streams, Stoddard et al. (2005) estimated the abundance of wood to be 3.2� 0.7 pieces 100 m�1 of stream

channel. Our estimate for a Great Plains River, the Upper Missouri River (Garrison and Ft. Peck Reaches

combined) was 2.9� 0.9 pieces 100 m�1. These data suggest that while our estimates of wood abundance along

mid-continent great rivers are lower than for smaller (generally wadeable) streams, they are similar to estimates

from smaller streams draining non-forested landscapes.


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The Upper Mississippi River had more wood of each type than the other two rivers, but the variation among rivers

was not great. Total wood ranged from 2.1 (Ohio River) to 3.3 (Upper Mississippi River) pieces 100 m�1 of

shoreline. Based on the percentage of riparian land use characterized as forest, we would expect more wood in the

Ohio River (58% forested, Figure 7) than in the Missouri River (17% forested). Comparisons of the abundance of

wood in each river were confounded by inter-annual variation in discharge, however. The Ohio River had an

abundance of wood similar to the other rivers in 2004 (Figure 3), but after a high flow event on the Ohio River in

January 2005 (the highest flows in 8 year), the abundance of all wood types in the Ohio River was lower than in the

other rivers. The Upper Mississippi River and Missouri River, which did not experience extreme flow events during

the study, serve as a control for the flow effects on the Ohio. At the river scale, the abundance of wood on the Upper

Mississippi River and Missouri River did not change significantly during the study. We therefore consider the

reduced abundance of wood in the Ohio River after 2004 as circumstantial evidence for large-scale export of wood

from the Ohio River during the study. An alternative, but we think unlikely, explanation is that high flows moved

wood in the river prior to the 2005 sampling and concentrated it (above navigation dams, for example) rendering its

distribution so patchy that its abundance was not accurately estimated by our random sampling in 2005 and 2006.

We detected only a weak longitudinal effect for beached wood in the Missouri River and Ohio rivers. The

abundance of beached wood, especially the maximum abundance, increased downriver. In the Missouri River, the

pattern was driven by the low abundance of wood in the two tailwater reaches, the Fort Peck Reach and the Garrison

Reach. Wood abundance in these reaches depends on local and tributary inputs because the reservoirs formed by

Fort Peck Dam and Garrison Dam capture all wood in transport from upriver. Angradi et al. (2004) detected a

longitudinal pattern in the abundance of snags in the Garrison Reach; snags were nearly absent for 20 km below the

dam and were most abundant as the river flowed in tight bends through mature riparian forest at the down-river end

of the reach.

Beached wood was rare on the upper 400 km of the Ohio River, but the reasons for this apparent imbalance

between wood imported to (i.e., from the Allegheny River and Monongahela River) and exported from the Upper

Ohio River is not clear. We speculate that naturally rocky and generally urbanized shorelines of the Upper Ohio

River are less retentive of wood than downriver reaches. With the exceptions noted, there were no clear longitudinal

patterns in the abundance of wood. Benke and Wallace (1989) noted that although wood often moves in low

gradient rivers, these rivers lack the power to export wood laterally out of the channel, so it tends to accumulate in

the channel down river. This mechanism may apply in some flow-regulated great river reaches where overbank

flows no longer occur (e.g., the Garrison Reach; Angradi et al., 2004) but we doubt this effect is important at the

whole-river scale. We conclude that longitudinal patterns in wood abundance were weak or non-existent at the

whole-river scale. Exceptions (Figure 5) were due to local effects such as high dams on the Upper Missouri River or

the low abundance of beached wood in the upper 400 km of the Ohio River.

The whole-river scale of our study was not well suited for examining longitudinal patterns in wood within

individual navigation pools on the Upper Mississippi River or Ohio River. There were too few sites in most pools to

discern a pattern or confirm the lack of a pattern. The abundance of wood in several long pools on the Ohio River

(Figure 4) did not seem to exhibit any pattern. A strong pattern within navigation pools was not expected, however,

because unlike the high dams on the Upper Missouri River, the low-head dams on the Ohio River and Upper

Mississippi River do not alter peak flows and so, presumably, do not regulate transport of wood. At lower flows, the

dams control the base level of the river to ensure the 2.75–3 m deep channel needed for commercial navigation

(Delong, 2005; White et al., 2005).

Distribution of wood in the mid-continent great rivers was very patchy: coefficients of variation in abundance

were high and linear autocorrelation of abundance was low. We found however, that some of the variation in

abundance could be explained by human modifications of shorelines and riparia. There was more wood along

unprotected ‘‘natural’’ shorelines than along artificially revetted shorelines. Angradi et al. (2004) found the same

pattern for wood on the Garrison Reach of the Missouri River. They hypothesized several reasons for the pattern: (i)

riparian trees are often removed during the installation of bank protection, (ii) protected banks do not erode so

riparian trees are not undermined, (iii) protected shorelines are hydraulically smooth at high flows and are less

retentive of transported wood than natural vegetation-lined shorelines, and (iv) shoreline protection encourages

riparian development which often includes deforestation.


DOI: 10.1002/rra


Not surprisingly, there was more wood along forested shorelines than where agriculture or development was the

dominant land use, at least for the Upper Mississippi River and Missouri River. We found a general positive

relationship at forested sites between canopy density at the edge of the river and the abundance of anchored wood.

Piegay (1993) found less wood adjacent to abandoned farm fields than to forest in the sixth order Ain River

(France). Elosegi and Johnson (2003) cite other studies, most on smaller streams, demonstrating the negative

effects of agriculture and urban development on the abundance of wood. They point out that general patterns are

subject to local or regional conditions. For example, urban riverscapes with intact riparian corridors may retain

some natural ecosystems functions related to large wood, including wood inputs and retention of wood in transport.

Also, mature riparian forest protected from lateral channel migration by bank revetment may actually contribute

less wood to river channels than unprotected agricultural shorelines with few large trees.

Hughes and Thoms (2002) found that most wood in the Murray River, Australia was recruited on outside bend

shorelines because of erosion. Most pieces remained within the bend where they originated. In contrast, we found

more wet and total wood from outside bend shorelines on the highly modified Missouri River. We account for this

by the higher degree of revetment on outside bend shorelines (71% revetted) where erosion risk is higher than inside

bends (10% revetted). Also, re-circulating eddies associated with channel-training structures such as wing dams

and dikes along inside bends of the Missouri River may trap wood in transport, as was observed by Elliott and

Jacobson (2006).

Across rivers, more wood was stored between the bankfull level and the river’s edge (beached, 56%) than was

within 10 m of the rivers edge (wet, 30%) or anchored in place (15%). We reason that most pieces of wood that enter

the channel can float and that most wood entering rivers of this size is transported mainly during elevated flows

(Piegay, 2003) and is deposited above the base flow stage when high flows recede. Only the largest pieces of wood,

often whole trees with the root mat intact, will resist entrainment at high flows, become imbedded in the substrate,

and form snags (Abbe et al., 2003). Most wood entering the river from the bank or from tributaries is insufficiently

massive to form great river snags, thus explaining the greater abundance of beached wood compared to wet wood.

Our findings are probably typical of very large rivers where the length of all wood pieces is far shorter than the

channel width. According to Gurnell et al. (2002), ‘‘weak wood transport [in such rivers] results in most of the wood

pieces being isolated, positioned close to the bank, and often still anchored in it. Other wood pieces form ‘snags’

within the channel.’’ Although our observations accord with this statement qualitatively, our data show, more

specifically (e.g., Figure 1; Table II), that within the bankfull channels of mid-continent great rivers at base flow,

more than half the wood will be stored dry (beached), and of the remaining wood, most will be wet rather than

anchored. At the local scale, the percentage of wood that is anchored in the bank or anchored in the riverbed (snags)

is linked to river management, riparian land use, and shoreline modifications, which determine the size of the wood

and frequency with which pieces, enter the channel. For example, there was a positive relationship between the

percentage of wood that was anchored and riparian forest canopy density for the Upper Mississippi River and

Missouri River. Also, on reaches of the Upper Missouri River where dam-related bed degradation causes bank

erosion (Pokrefke et al., 1998), the proportion of wood that is anchored in the bank will likely be higher than

channelized reaches where shoreline erosion is mostly prevented by revetments (Angradi et al., 2004).

We presume that forested, un-revetted shorelines represent existing least-disturbed riparian conditions (sensu

Stoddard et al., 2006) along the mid-continent great rivers. Among forested great rivers sites, there was a trend for

sites with little or no revetment to have more wood than highly-revetted sites (Figure 8). The abundance of wood

along forested un-revetted shorelines was a little more than 4 pieces 100 m�1 (40 pieces km�1). In contrast, revetted

farmland and range, with 1–2 pieces km�1, represent most-disturbed condition with respect to wood at the river

scale. Many sites had more than 40 pieces km�1 of shoreline due to local factors and chance, but a stocking level of

40 pieces km�1 might be considered as an initial rehabilitation target for large mid-continent rivers. Currently,

approximately 30 percent of the length of the Upper Mississippi River and approximately 20 percent of the

Missouri River and Ohio River have this much wood.

ACKNOWLEDGEMENTS

We are indebted to the United States Geological Survey, state, and contract personnel who collected the data in the

field. Curt Seeliger assisted with data analysis. Comments by Phil Kaufmann, Mike Delong, and Mary Ann Starus


DOI: 10.1002/rra


improved the manuscript. The information in this document has been funded wholly by the United States

Environmental Protection Agency. It has been subjected to review by the National Health and Environmental

Effects Research Laboratory and approved for publication. Approval does not signify that its contents neither does

reflect the views of the agency nor does mention of trade names or commercial products constitute endorsement or

recommendation for use.

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APPENDIX A

One-way ANOVA results for the effect of year on the abundance of wood. Means test results shown if the year effect

was significant (p< 0.05). Wood abundance was log-transformed prior to analysis. Degrees of freedom (DF):

model, error. Ns¼ not significant (p> 0.05).

Wood type

Published in 2009 Joh

Name of the River

n Wiley & Sons, Ltd.

DF
F P
River. Re

Means tests (t)

Anchored
Upper Mississippi River 2, 138 1.02 Ns Missouri River 2, 180 3.20 0.04 2004> 2005, 2004> 2006 Ohio River 2, 116 15.89 <0.01 2004> 2005, 2004> 2006
Wet
Upper Mississippi River 2, 138 1.30 Ns Missouri River 2, 180 0.68 Ns Ohio River 2, 116 7.31 <0.01 2004> 2005, 2004> 2006
Beached
All wood
APPENDIX B

ANOVA results for the effect of river and the river�year interaction on the abundance of wood. Means test results

shown if river effect was significant (p< 0.05). Wood abundance was log-transformed prior to analysis. F-value

based on type III sums of squares for two-way ANOVA (river, year, river�year). Degrees of freedom (DF): model,

error. Ns¼ not significant (p> 0.05).

Wood type
Effect DF F P Least squares means tests (t)
Anchored
River 2, 434 1.94 Ns MS>OH River�year 4, 434 3.18 0.01
Wet
River 2, 434 1.26 Ns River�year 4, 434 3.75 <0.01
Beached
River 2, 434 3.67 0.03 MS>OH, MS>MO River�year 4, 434 1.14 Ns
All wood
River 2, 434 4.58 0.01 MS>OH, MS>MO River�year 4, 434 4.18 <0.01
APPENDIX C

One-way ANOVA results for the effect of land use and revetment on the abundance of wood. Data pooled across

years. Wood abundance was log-transformed prior to analysis. Medium revetment class not included ANOVAs.

Test of revetment effect for all rivers excludes Ohio River. Means test results shown if main effect was significant

(p< 0.05). Land use: F¼ forest, D¼ developed, A¼ agriculture. Revetment: L¼ 0–20 percent, H¼ 80–100 percent.

Degrees of freedom (DF): model, error. Ns¼ not significant (p> 0.05);

Wood type
Name of the River Effect DF F P
s. Applic. 26

Means tests (t)

Anchored
Upper Mississippi River Land use 2, 138 8.78 <0.01 F<D, F>A Revetment 1, 115 29.17 <0.01 L>H
Missouri River
Land use 2, 180 1.01 Ns Revetment 1, 150 0.00 Ns
Ohio River
Land use 2, 116 2.07 Ns
(Continues)

: 261–278 (2010)

DOI: 10.1002/rra


Appendix. (Continued)

Wood type

Published in 2009 J

Name of the River

ohn Wiley & Sons, Ltd.

Effect
DF F
River.

P

Res. Applic. 26

Means tests (t)

Wet
Upper Mississippi River Land use 2, 138 2.97 Ns Revetment 1, 115 2.55 Ns
Missouri River
Land use 2, 180 1.64 Ns Revetment 1, 150 20.86 <0.01 L>H
Ohio
Land use 2, 116 2.19 Ns Beached Upper Mississippi River Land use 2, 138 1.97 Ns
Revetment
1,115 1.79 Ns Missouri River Land use 2, 180 2.18 Ns
Revetment
1,150 0.01 Ns Ohio Land use 2, 116 1.72 Ns
All wood
Upper Mississippi River Land use 2, 138 7.38 <0.01 F>D, F>A Revetment 1, 115 9.41 <0.01 L>H
Missouri River
Land use 2, 180 2.61 Ns Revetment 1, 150 3.81 Ns
Ohio River
Land use 2,116 0.91 Ns All rivers Land use 2, 440 4.91 <0.01 F>D, F>A
Revetment
1, 268 11.88 <0.01 L>H
: 261–278 (2010)

DOI: 10.1002/rra

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Littoral and shoreline wood in mid-continent great rivers (USA)

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