SOURCES AND DYNAMICS OF LARGE LOGS IN A TEMPERATE FLOODPLAIN RIVER

Ecological Applications, 17(4), 2007, pp. 1127–1141� 2007 by the Ecological Society of America

SOURCES AND DYNAMICS OF LARGE LOGSIN A TEMPERATE FLOODPLAIN RIVER

JOSHUA J. LATTERELL1

AND ROBERT J. NAIMAN

School of Aquatic and Fishery Sciences, University of Washington, Box 355020, Seattle, Washington 98195 USA

Abstract. Large logs, important agents of biophysical heterogeneity in temperatefloodplain rivers, have been virtually eliminated from modified systems. Our purpose was toquantify the sources and dynamics of large logs (�1 m diameter) in the mainstem of a nearlypristine system: the Queets River, Washington, USA. Erosion of forests by the river supplies0.40 logs�(100 m)�1�yr�1 to the channel. Most (72%) are new logs entering the river for the firsttime as the river undercuts mature fluvial terraces dominated by large conifers. Retrospectiveairphoto analyses demonstrate that, over 63 years, the Queets River recruits 95% of new logsfrom a riparian corridor extending 265 m laterally on both banks, mostly through channelmeandering. However, input rates are patchy, with 10% of the valley length supplying 38% ofthe new logs. As the river moves laterally, remnant logs are left on channel surfaces that laterdevelop riparian forests and reenter the river when those forests erode. Remnant logs lying onthe floodplain forest floor surface or buried in alluvium constitute 21% and 7% of the annualinputs from bank erosion, respectively. We estimate that 50% of logs deposited in the channelin a given year, including those underpinning logjams, are transported downriver within fiveyears. Over the next 55 years, bank erosion reclaims an additional 23%, leaving 27% of the logsstable for .60 years. Simulations indicate that recurrent transport is common, with half of thelarge conifers being deposited in �3 locations and transported �1.5 km prior to disintegrating.One in ten logs links distant reaches by occupying �7 locations spanning �12.0 km. Instreamsupplies are therefore a mixture of new and old logs from nearby and upstream forests,sustained by the recapture and transport of stockpiled remnant logs during periods when newinputs are low. We propose that patchy input rates and the periodic rearrangement of largelogs are important drivers of temporal variation in river valley habitats, adding to the spatialcomplexity created by stable logs. These findings underscore the importance of extensivemature forests and connectivity in temperate floodplain rivers.

Key words: connectivity; floodplain; flow regime; heterogeneity; large woody debris; Queets River,Washington State (USA); riparian ecosystem; spiraling.

INTRODUCTION

The ecological vitality of laterally unstable floodplain

rivers in temperate regions is underpinned, to a large

degree, by natural flow variability and the delivery of

large wood from riparian forests to the channel (Naiman

et al. 2005a, b). These processes support high levels of

biocomplexity, a widely valued trait now lacking in

many developed rivers (Poff et al. 1997, Gurnell et al.

2001, 2005). The goal of this study was to inform

conservation of temperate floodplain rivers and riparian

forests by quantifying the delivery of large logs to the

river through bank erosion (e.g., Piegay et al. 1999) and

their cycling within the channel and floodplain over time

(1939–2002) and space in the near pristine Queets River,

Washington, USA, in Olympic National Park (Fig. 1).

We focused on large logs that play an irreplaceable role

in underpinning logjams (key pieces or key members)

but have declined precipitously in most modified rivers

(Gregory et al. 2003, Gurnell et al. 2005, Naiman et al.

2005b). Our specific objectives were to (1) quantify the

rate at which trees are delivered to the channel for the

first time by the undercutting of mature forests

(becoming ‘‘new’’ logs) as well as the lateral extent of

the source areas, (2) quantify the retention and transport

dynamics of instream logs, and (3) estimate the relative

importance of inputs of remnant logs lying on the

surface of floodplain forests, or buried in the alluvium.

The natural history of large wood in floodplain rivers

has been often described (see photos in Appendix A) but

rarely quantified, hindering understanding of these

dynamic systems. River-deposited logs are most con-

spicuous in the river channel but also pervade the forests

and alluvium of the river valley floor (Fig. 2; Maser et al.

1988). Large logs entering the channel via bank erosion

function as key pieces by trapping additional wood,

promoting sediment deposition, and shaping the sur-

rounding channel (Keller and Swanson 1979, Abbe and

Montgomery 1996). Resulting logjams can initiate

lateral channel migration by increasing the elevation of

the streambed or water surface (Brummer et al. 2006).

Some logs are temporarily stranded on gravel bars and

Manuscript received 7 June 2006; revised 13 October 2006;accepted 27 October 2006. Corresponding Editor: J. A. Antos.

1 E-mail: [email protected]

1127

subsequently flushed downstream (van der Nat et al.

2003a). Other logs (hereafter, ‘‘remnant logs’’) remain

where they were deposited by the river and, over several

years, become veiled by stands of pioneering vegetation

growing in the old channels (Fetherston et al. 1995,

Abbe and Montgomery 1996). These logs remain on the

forest floor (i.e., ‘‘surface remnants’’) until they disinte-

grate or are buried under alluvium (Guyette et al. 2002,

Montgomery and Abbe 2006), hereafter referred to as

‘‘buried remnants.’’ The net result is that river-deposited

logs exist in most patches composing the forested

floodplain mosaic (Latterell et al. 2006). This is

important because, when the laterally migrating channel

eventually returns, remnant logs that persist can reenter

the channel (Nanson et al. 1995, Hyatt and Naiman

2001, Guyette et al. 2002) and potentially underpin new

logjams (Collins and Montgomery 2002).

Observations from intact low-gradient rivers suggest

the ongoing loss of wood substantially reduces bio-

complexity (Gurnell et al. 2005) and alters key

biophysical patterns in developed rivers. When present,

logs enhance instream complexity and promote flood-

plain inundation (Kellerhals et al. 1976, Abbe and

Montgomery 1996, Brooks et al. 2003). Large logs are

central to organic matter retention (Bilby and Likens

1980, Bilby 1981), to pool formation (Abbe and

Montgomery 1996, Beechie and Sibley 1997), and to

nutrient uptake (Aumen et al. 1990, Valett et al. 2002).

Remnant logs provide habitat for a variety of terrestrial

organisms (Bull 2002, Steel et al. 2003) and facilitate

conifer establishment (Fetherston et al. 1995, Fetherston

2005, Van Pelt et al. 2006). Most logs reside in

floodplain river valleys for decades, though some

fraction lasts for centuries or more (Nanson et al.

1995, Hyatt and Naiman 2001, Guyette et al. 2002,

Montgomery and Abbe 2006). Those remaining stable

over long periods may represent a sizeable carbon

reservoir (Guyette et al. 2002) and aid in replenishing

supplies of new large logs by protecting developing

forests from erosion long enough for trees to grow large

(Montgomery and Abbe 2006). In the absence of large

wood, few structures in low-gradient rivers are suitable

ecological surrogates for these functions.

Sustaining large wood in rivers is both a scientific and

a practical challenge that exemplifies the difficulty of

protecting river environments while meeting human

needs (Nilsson and Berggren 2000). Floodplain rivers

face burgeoning threats (Hughes 2003; Tockner et al., in

press) as logjams are extracted to improve navigation

and reduce bridge damage; future supplies of large logs

diminish as mature riparian forests are cleared for

agriculture and development; and recruitment processes

are cut off as channel movement and flooding are

artificially restricted to prevent loss of life and property

(Sedell and Froggatt 1984, Bilby and Bisson 1998,

Collins et al. 2002, 2003). Not surprisingly, these factors

have transformed riverine-riparian ecosystems at the

global scale (Nilsson and Berggren 2000, Nilsson et al.

2005) and are expected to intensify as regional water

scarcity is exacerbated by population and economic

growth and climate change (Vorosmarty et al. 2004).

The net result is that large logs, associated jams, and

habitats they sustain are virtually eliminated, and once

lost, are difficult to replace at meaningful scales. Our

hope is that results of this study will be useful in

informing conservation efforts aimed at maintaining or

restoring a self-sustaining supply of large wood to

floodplain rivers.

STUDY AREA

The Queets River, Washington, USA, is located at

4783201700 N, 12481805200 W NAD27 in Olympic Nation-

al Park (Fig. 1). The river drains ;1200 km2 before

reaching the Pacific Ocean. Although a wide range of

biophysical characteristics is evident in rivers of the

Pacific coastal rain forest (Naiman and Anderson 1997,

Naiman et al. 2005b), the Queets River possesses many

characteristics typical of pristine lower floodplains,

FIG. 1. Map of the mainstem of the Queets River, Washington, USA (bold), and its tributaries, indicating the extent ofOlympic National Park (shaded) and the locations of four intensively studied 2-km study reaches (open circles).

JOSHUA J. LATTERELL AND ROBERT J. NAIMAN1128 Ecological ApplicationsVol. 17, No. 4

which often meander through a wide U-shaped valley

flanked by old forests on glacial landforms (Thackray

2001). The climate is mild and wet with mean annual air

temperatures of 108C and precipitation averaging 387

cm/yr. Typical riparian vegetation consists of willow

(mostly Salix sitchensis Sanson), red alder (Alnus rubra

Bong.), Sitka spruce (Picea sitchensis [Bong.] Carr),

black cottonwood (Populus balsamifera L. ssp. tricho-

carpa [Torrey and A. Gray] Brayshaw), bigleaf maple

(Acer macrophyllum Pursh), and vine maple (Acer

circinatum Pursh) (Balian and Naiman 2005). Western

hemlock (Tsuga heterophylla [Raf.] Sarg.), Douglas-fir

FIG. 2. Aerial view of a representative reach of the upper mainstem of the Queets River, Washington, USA. This photo depictsnewly formed jams near the channel on the left, and several remnant logs in the early stages of incorporation by pioneeringvegetation on the upper right.

June 2007 1129FLOODPLAIN RIVER WOOD DYNAMICS

(Pseudotsuga menziesii [Mirbell] Franco), and western

redcedar (Thuja plicataDonn.) are also present (Naiman

et al. 2005a, Van Pelt et al. 2006). Coastal Sitka spruce

forests rarely burn, and fires have not been observed in

the Queets valley floor (Agee 1993). The fire return

interval is not well-defined, but is estimated to exceed

1100 years (Agee 1993, Greenwald and Brubaker 2001).

Terraces and hillslopes are dominated by western

hemlock (Franklin and Dyrness 1988). The channel is

gravel-dominated, low gradient (slope¼ 0.006 m/m) and

laterally active (i.e., moving 13 m/yr on average;

Latterell et al. 2006). The channel averages 128 m in

width (64 SE), but ranks in the fifth-order (based on

streams mapped at 1:24 000 scale) due to the elongate,

rectangular shape of the basin (e.g., Benda et al. 2004).

Daily flows average 124 m3/s, and annual peak flows

range from 931 to 3764 m3/s from rainstorms and rain-

on-snow events (Station 12040500, U.S. Geological

Survey 2005). Flooding is the primary disturbance

affecting the riparian forest. Human disturbances in

the valley prior to the establishment of the Park were

minor, limited to forest clearing around homesteads

established after 1890 and abandoned prior to 1953.

METHODS

We integrated airphoto analyses over the entire

mainstem river inside Olympic National Park, with

intensive studies of log dynamics and burial at four

randomly selected 2-km study reaches draining 207–565

km2 (Appendix B). We define large logs as those �1 m in

diameter at breast height (dbh; or 1.4 m from the root

mass), which approximates the observed median size of

key pieces in the Queets River mainstem (Latterell 2005).

Prior studies demonstrate that the capacity of a log to

remain stable is related, in part, to channel size

(Lienkaemper and Swanson 1987, Braudrick and Grant

2001, Abbe and Montgomery 2003). We reasoned that

many of the logs meeting or exceeding the observed

median diameter of key pieces are likely to eventually

initiate jams in some mainstem reaches even if that

function is not yet realized, and are thus potential key

pieces (e.g., Collins et al. 2002).

Inputs of new and remnant logs

We quantified delivery of new large logs by mapping

mature fluvial terraces as they existed in 1939 and

measuring the cumulative erosion of these patches by

the channel over subsequent years from georeferenced

digital airphotos (0.4–1.5 m ground resolution). Mature

fluvial terraces contain heterogeneous forest canopies

dominated by conifers from ;130 to .330 years old.

Living trees �1 m dbh are almost exclusively found in

these patches (Balian and Naiman 2005, Latterell et al.

2006, Van Pelt et al. 2006). We used ArcMap (ESRI,

Redlands, California, USA) to quantify the cumulative

erosion of mature fluvial terraces over six to seven

intervals, depending on the spatial extent of available

photos. Photos from 1939, 1950, 1954, 1968, 1973, 1993,

2000, and 2002 were used in the first 21.2 km of the

valley upstream from the Park boundary. The remaining

portion of the valley was analyzed with photos from

1939, 1968, 1976, 1981, 1993, 2000, and 2002. We

assumed relationships from multiyear comparisons were

applicable at an annual scale (as in Piegay et al. 1999,

Richter and Richter 2000). We quantified longitudinal

patterns in the delivery of new logs by subdividing the

river valley into 0.2 km long sections (n¼257), following

O’Connor et al. (2003). Transects perpendicular to the

valley axis delineated the upstream and downstream

boundaries of each section. We estimated delivery rates

(pieces�100 m�1�yr�1) by multiplying the area of each

eroded patch (from each section and interval) by an

independent estimate of stem density. Van Pelt et al.

(2006) estimated that mature fluvial terraces in the

Queets River contain 36.3 6 5.8 stems/ha (mean 6 SD)

�1 m dbh, which were mostly (91%) living trees. We

assumed this variable was normally distributed and

drew consecutive, independent estimates of stem density

from this distribution to simulate spatial variation.

Finally, we quantified mean annual delivery rates over

time for each section and overall.

The first step in quantifying the rate at which remnant

logs reentered the channel through erosion of younger

forested patches (i.e., pioneer bars to transitional fluvial

terraces) was to estimate the density of surface and

buried remnant large logs (pieces/ha) in each forested

patch type. Latterell et al. (2006) estimated the density of

surface remnant (or abandoned) large logs in each patch

type. We quantified the density of buried remnant large

logs in riparian forests by mapping key pieces (logs

underpinning jams) in airphotos while they were visible

in the active channel, tracking them through time as

forests developed around them, and determining which

were eventually buried. Hereafter, we use the term

‘‘cohort’’ in reference to a group of individual logs

fluvially deposited (or present) in the unvegetated river

channel in the same year. Cohorts of instream logs were

identified at each 2-km study reach in eight years where

instream logs were clearly visible at those locations (i.e.,

1939, 1950, 1962, 1968, 1990, 1993, 1996, and 1997).

Maps of the active channel in subsequent years indicated

which members of each cohort the river had displaced.

Logs remaining stable in 2002 were located with a

geographic positioning system (GPS) and we determined

whether the logs were buried or remained visible on or

protruding from the forest floor. This enabled us to

model the relationship between cohort ‘‘age’’ (years since

deposition) and the buried percentage (percentage of

initial cohort) with regression analysis. We had to

assume that (1) burial usually occurred after initiation

of vegetative patches, which was (2) coincident with log

deposition; (3) the initial remnant log density in forested

patches was equivalent to that observed in pioneer bars;

and that (4) remnant logs did not disintegrate complete-

ly in �63 yr, but (5) instead remained visible until the

time of observation unless the surrounding forest was


eroded or the log was buried. If so, the density of buried

remnant logs in each forested patch type should be equal

to the product of the initial log density and buried

percentage predicted by the regression model from the

mean age of each patch type, which was adapted from

Van Pelt et al. (2006).

Estimating the density of buried remnant logs in

mature fluvial terraces required a more complex

approach because many of the surface remnant large

logs were expected to decay prior to being buried.

Simulations identified the fraction of the initial number

of large logs that would decompose prior to burial. This

entailed generating functional lifetimes (described in

following sections) for 1000 logs (conifers only, for

simplicity), which we assumed were buried at the

empirically determined burial rate, described before.

We assumed that because wood decay slows after burial

(Guyette et al. 2002), logs buried prior to reaching their

estimated minimum functional lifetime retain their

functional capacity when later exhumed. In the case

that the predicted functional lifetime was reached prior

to burial, we assumed the log was no longer a potential

key piece. Inputs to the channel were estimated from the

product of buried remnant log density and the mean

annual area of mature fluvial terrace eroded by the river.

The resulting estimates of buried remnant logs in mature

terraces must be considered preliminary because extrap-

olation of the burial model beyond the range of

observations introduces substantial uncertainty.

For all other patch types, the next step was to estimate

the area of each patch type eroded by the river each

year, thereby returning some quantity of remnant logs to

the channel. Due to ongoing disturbance and plant

succession, we assumed the relative area of each patch

type at the reach scale mirrored that at the valley scale

(reported by Latterell et al. 2006) over the long term

because the area of each patch type fluctuates among

decades at the reach scale. Patch area was scaled to that

of the channel in each study section. Latterell et al.

(2006) present negative exponential models of patch

longevity on the Queets River, which indicate the

fraction of each patch type that is eroded annually.

Thus, the quantity of remnant logs annually returned to

the channel in each section was the product of the

estimated eroded area of each patch type in that section

and the patch specific estimates of surface and buried

remnant log densities.

Lateral source areas and input mechanisms

We quantified lateral source areas and the relative

importance of various physical types of channel change

for the delivery of new large logs in the entire mainstem.

We accomplished this by measuring the lateral recruit-

ment distance, defined as the shortest distance between

the center of each eroded patch (n ¼ 1341 patches) and

the initial channel margin (as it existed in 1939). These

measurements produced a frequency histogram illus-

trating the lateral extent of large log source areas over

six decades. This approach differs from prior studies

based on the distance between the growth location of

individual trees and the present margin of relatively

stable channels (McDade et al. 1990, Van Sickle and

Gregory 1990). Contributions of new large logs from

channel meandering, cutoffs or avulsions, and island

dissection (Knighton 1998) were evaluated with air-

photo interpretation. Each eroded patch was attributed

to one of these mechanisms or else to indeterminate

erosion.

We used regression analysis to determine whether

input rates of new large logs were related to the

proximity of mature forests to the channel or channel

movement rates. Source area proximity, defined as the

lateral distance (m) from the center of the low-flow

channel to the nearest mature fluvial terrace patch in

1939, was measured for each 0.2-km section in

unconfined channel reaches. We compared the mean

annual delivery rate in each section to the mean annual

lateral movement rate of the primary low-flow channel,

as reported for each section by Latterell et al. (2006). We

deemed relationships were significant at P � 0.05.

Dynamics of large logs

We quantified the cycling of key pieces and large logs,

in general, as a series of spirals in space and time (Fig.

3). The spiraling metaphor is well established in river

ecology, and usually invoked to describe nutrient uptake

and release by organisms or transport of particulate

organic matter (e.g., Newbold et al. 1982, Newbold

1992, Fisher et al. 1998). In this application, we consider

each spiral to represent the reciprocal transfer of a log

between the channel and forest patches in the valley

floor.

The process of wood spiraling begins when a tree falls

into the channel for the first time and ends when the log

can no longer initiate jams due to fragmentation or

decay (Fig. 3). This is a simple adaptation of the lifetime

transport distance metric (n) from recent conceptual

advances in wood budgeting (Benda and Sias 2003).

Benda and Sias (2003) propose that the mean distance a

log is transported before disintegrating (n) is a function

of the mean distance between transport-impeding jams,

the ratio of piece to jam longevity, and the proportion of

the channel spanned by a jam. Their model applies to

rivers where wood transport is primarily limited by jam

spacing (e.g., Martin and Benda 2001), and is not

intended for floodplain systems where large logs are

commonly deposited between preexisting jams and

become temporarily incorporated into riparian vegeta-

tion. We modified the model form and parameters to

reflect the spiraling metaphor.

We estimated large log turnover length (Fig. 3, nLL;the total downstream distance from the initial point of

entry into the channel to loss of function) from empirical

observations of large log retention time (in situ; aLL) andannual transport distance (JLL). Large log retention time

(aLL) is the duration of log stability (years) at one


location, in contrast to ‘‘residence time,’’ which refers to

the duration over which a log resides in the river system

(e.g., Hyatt and Naiman 2001). This metric is compa-

rable to jam longevity ‘‘a’’ (Benda and Sias 2003), except

that it includes the time spent in the riparian forest. We

quantified short-term retention for three cohorts (2002,

2003, 2004) in each study reach by mapping (63 m),

measuring, tagging (n ¼ 222) instream key pieces, and

relocating the tagged logs in each reach and year of the

study. We integrated long-term retention by mapping all

visible instream key pieces (n¼ 1285) in airphotos from

11 prior years (cohorts), across the entire valley in the

Park. The number of logs visible in photos varied among

years, depending on photo clarity and extent. We

therefore determined the proportion (rather than the

absolute number) of mapped logs comprising each

cohort that were retained. Map overlays of the active

channel in subsequent years after log deposition

indicated whether logs were retained or reentered the

channel. The annual transport distance (JLL) is how far

logs move after displacement or recapture, and is

comparable to the distance between jams (J; Benda

and Sias 2003). The difference is that large log transport

was empirically derived rather than assumed to be

limited by jam-spacing. We quantified JLL by tracking

mobile logs (that previously functioned as key pieces)

between 2002 and 2005 in each study reach and over

;25 km of the mainstem; the stream distance between

the initial and new locations was measured in ArcMap.

The number of spirals (pLL) corresponds to the

number of locations a large log resides, which is

restricted by log lifetime (qLL), the duration (years)

over which a large log retains the capacity to initiate

jams. The qLL is comparable to the lifetime of a piece in

Benda and Sias (2003) but refers to a functional

threshold. Logs can spiral repeatedly until either (1)

the sum of their retention times aLL at each deposition

point meets or exceeds qLL or (2) they are transported

out of the system (e.g., past the river mouth to the

ocean). Martin and Benda (2001) speculated that wood

becomes mechanically weak and disintegrates in streams

when it is 95% decayed. We speculated that large logs

are unlikely to initiate logjams in a floodplain river when

they lose 75% of their mass, recognizing that mass or

size alone does not determine key piece functionality (see

Abbe 2000 for further details).

We simulated probability distributions for nLL, qLL,

and pLL from 1000 trials, each representing an

individual large log (adapted from Martin and Benda

2001). The process of wood decay in rivers is poorly

understood, and estimates for k are quite rare (but see

Graham and Cromack 1982 and Bilby et al. 1999). We

used species-specific decay constants (k) from ongoing

decomposition studies at the Cascade Head and H. J.

Andrews Experimental Forests in Oregon, USA (i.e.,

CHEF and HJAF; Harmon and Fasth 2005) to simulate

the lifetime (qLL) of individual logs. These sites are mild

and very wet, similar to the Queets River valley. We

assumed k was normally distributed about a mean of

0.023 for P. sitchensis and T. heterophylla, which

compose most key pieces (Latterell 2005), and ignored

potential variation from differences in log diameter. We

thought this was justified because our study is limited to

large logs, and a study in a neighboring valley concludes

that decay rates for P. sitchensis and T. heterophylla (the

dominant species of key pieces) are similar, and

differences among diameter classes are not statistically

FIG. 3. Conceptual diagram of the dynamics of large logs ina temperate floodplain river. The spiraling process begins whena log enters the active channel for the first time (e.g., fromerosion of a mature fluvial terrace). The log is deposited in thechannel, where it is retained for a period (retention time; aLL).This value corresponds to the width of a single spiral (the timeelapsed between transport events). Some become remnant logsas floodplain forests develop on old channel surfaces after thechannel migrates laterally. At a later time, the log is displacedor reenters the river through bank erosion and movesdownstream (JLL). The turnover length (nLL) is the totaldistance (the sum of all JLL) between the point of entry and thepoint where the log reaches the end of its functional lifetime(qLL, the number of years elapsed before decay inhibits theability of a log to underpin a jam). The number of spiralscompleted is pLL, which corresponds to the number of locationsin which the log resides. Values pLL are influenced by theconsecutive values of aLL between transport events. Themaximum value for pLL is restricted by the difference betweenaLL and qLL, or by the distance to the boundary of the systemof interest. If aLL exceeds qLL, the log will not be recapturedprior to disintegration (or become buried; pLL ¼ 1).


significant (Graham and Cromack 1982). Prior studies

considering the influence of log diameter on decay ratesin upland forests have reached inconsistent conclusions(see Laiho and Prescott 2004 for a review). In some

cases, large logs appear to decay slowest, but wood-boring insects may preferentially attack them and causethem to decay faster (Edmonds and Eglitis 1989). The

standard deviation of the distribution around k (6.63 3

10�3) was derived from time series regressions of decay

for Tsuga heterophylla at HJAF. In each trial, a valuefor k was drawn from this distribution, and used in anegative exponential decay model to estimate the time

(years) required to lose 75% of the wood mass. This wasalso done for hardwoods, such as A. rubra (k¼0.055), toevaluate the influence of qLL on nLL. The fitted

nonlinear model for aLL was used to generate a discreteprobability function (i.e., annual time steps) from whichindependent samples were drawn at random until the

simulated qLL was met or exceeded for each log. Thenumber of samples was tallied to calculate pLL for eachtrial. Independent samples (n) of the natural logarithm

of observed qLL were drawn at random from a two-parameter lognormal distribution (l¼ 5.26, r¼ 2.07) sothat n¼pLL and summed to determine nLL for each trial.

RESULTS

Inputs of new and remnant logs

The average annual input from bank erosion from1939 to 2002 was 0.40 large logs�100 m�1�yr�1 (along the

valley axis) across years and sections, primarily new logsfrom eroding mature fluvial terraces (Table 1). Mature

fluvial terraces were eroded at an average rate of 7.8 3

10�3 ha�100 m�1�yr�1 across sections. We estimated thatthis generated 0.29 6 0.34 new large logs�100 m�1�yr�1(mean 6 SD) representing 72% of the annual input tothe channel, though input rates varied substantiallyamong locations (Fig. 4). In comparison, 21% were

surface remnants and 7% were buried remnants that

were recaptured by bank erosion at a combined rate of

0.11 logs�100 m�1�yr�1 across years and sections (Table

1). Most remnant log inputs originated from the erosion

of pioneer bars and developing floodplain patches

(Table 1), which are eroded frequently, relative to older

patches (Latterell et al. 2006). Most remnant logs are

conifers with the potential to function as key pieces

when recaptured by the channel, based on the simulated

distributions for the functional lifetimes of large

conifers. However, we estimate ,10% of the remnant

hardwood logs recaptured from established floodplains

and transitional fluvial terraces retain the potential to

initiate jams.

We observed a positive, linear relationship (r2¼ 0.88)

between the burial rate and estimated cohort age (Fig.

5):

y ¼ 0:88t � 4:11 ð1Þ

where y is the percentage of the remnant (stable) logs

from a cohort that are buried t years after initially being

deposited. This relationship holds for six decades.

Whether it eventually plateaus over long time periods

is unknown. If the existing linear model (Eq. 1) is

extrapolated beyond the range of observations (in the

absence of known historical data), all remaining logs are

predicted to be buried within roughly 120 yr. Simula-

tions suggested that, in transitional fluvial terraces, 14%

of large logs in the initial cohort reach the end of their

functional lifetime prior to burial. This percentage is

predicted to grow to 43% in mature fluvial terraces, and

is reflected in estimated standing stocks and inputs of

buried remnant logs (Table 1). In spite of these losses,

roughly 60% of the buried remnant logs recruited by the

channel may originate from mature fluvial terraces

because they compose 48% of the valley floor (Latterell

et al. 2006). As mentioned earlier, we caution that these

burial estimates are based on several simplifying

TABLE 1. Mean quantities and sources of large logs (�1 m diameter; new, surface remnant, and buried remnant) in forest patchesof the Queets River, Washington, USA, in Olympic National Park.

Forest patch type

Variable, by source of logs

Standing stock(no./ha)

Input rate(no. logs�100 m�1�yr�1)�

Relative importance of inputs(% of total)

Newlogs

Surfaceremnant

Buriedremnant Total

Newlogs

Surfaceremnant

Buriedremnant Total

Newlogs

Surfaceremnant

Buriedremnant Total

Pioneer bar 4 0.1 4.1 0.026 0.0006 0.027 0.0 6.4 0.1 6.6Developing floodplain 3 0.2 3.2 0.042 0.0031 0.045 0.0 10.4 0.8 11.2Established floodplain 3 0.7 3.7 0.015 0.0036 0.019 0.0 3.7 0.9 4.6Transitional fluvialterrace

1 1.5� 2.5 0.0024 0.0034� 0.0058 0.0 0.6 0.8� 1.4

Mature fluvial terrace§ 36.3 2.3� 38.6 0.29 0.018� 0.31 71.8 0.0 4.5� 76.2

Notes: The relative importance of each source is given as the percentage of the total mean annual lateral input of large logs frombank erosion. Estimates for the standing stock of new logs are from Van Pelt et al. (2006), and surface remnant logs are fromLatterell (2005).

� Measured as m/yr along valley axis.� Values have been reduced by the estimated quantity of logs reaching the end of their functional lifetime prior to reentering the

channel or to being buried, based on simulations for conifer logs.§ Downed trees from stand mortality could not be differentiated from those deposited by the river.


assumptions warranting validation and therefore repre-

sent a first attempt at quantification.

Lateral source areas and input mechanisms

Bank erosion associated with channel meandering was

the primary input mechanism for new large logs,

contributing 82% of the total, whereas erosion from

cutoffs and avulsions delivered 14%, and only 4% came

from island dissection and indeterminate erosion com-

bined. Meanders just beginning to form at the earliest

time of observation with cutbanks fringed by mature

forests often functioned as ‘‘wood hotspots’’; sites

contributing disproportionately high numbers of new

logs to the channel. Specifically, these were sections with

input rates at or above the 90th percentile (i.e., �0.7 newlarge logs�100 m�1�yr�1). Wood hotspots represented

10% of the valley length but contributed 38% of the new

large logs (Fig. 4). They were distributed up to 8.4 km

apart (along the valley axis) though one-half were

separated by �1.6 km (median). Lateral source areas

extended nearly 0.5 km from the initial (1939) channel

margin by 2002 (Fig. 6). One-half of all new large logs

recruited by bank erosion from 1939 to 2002 originated

�92 m from the 1939 channel margin, though 95% were

from �265 m.

Spatial variation in new large log input rates (Fig. 4)

was weakly related to the proximity of mature fluvial

terraces. Relationships between large log delivery to the

mainstem and the mean annual lateral movement rate of

the low-flow channel were not detected (P . 0.05),

though channel movement rates were greater at hotspots

than in the remainder of the valley (Mann-Whitney U

test; P¼ 0.01). In unconfined sections (n¼ 214), mature

fluvial terraces were closer to the channel (median ¼ 32

m) at hotspots than other sections (median ¼ 47 m)

(Mann-Whitney U test; P , 0.01). Regression analyses

indicated that input rates declined in unconfined reaches

as source areas became more distant (P¼ 0.02), but this

factor explained little of the variation (r2 ¼ 0.05). The

relationship is given by the following model:

y ¼ �1:12 3 10�3d þ 0:40 ð2Þ

where y represents the mean number of new large logs

delivered to the channel (logs�100 m�1�yr�1) and d is the

distance (m) between the center of the low flow channel

and the margin of the nearest mature fluvial terrace in

each section. Confidence intervals (95%) for the model

coefficient ranged from �1.8 3 10�3 to �4.3 3 10�4.

Dynamics of large logs

Key pieces (n ¼ 273) averaged 109 6 3.1 cm dbh

(mean 6 SE, range 28–243 cm) and 26.0 60.9 m long

(range 2–65 m). Jams averaged 10.6 6 0.6 m (range 1–67

m) across the center of mass upstream from the key

piece, containing 16 6 1.1 pieces (range 1–129 pieces) of

large woody debris �2 m long and 10 cm diameter. As in

previous studies (Abbe and Montgomery 1996), nearly

all key pieces (97%) had attached rootwads. Most (75%)

were relatively undecayed, with hard, intact sapwood

and 82% were Sitka spruce, western hemlock, or

Douglas-fir. Red alder (9%), bigleaf maple (5%), or

black cottonwood (4%) sometimes functioned as key

pieces, as well.

A negative power function (r2 ¼ 0.60) quantified

retention of 14 cohorts of large logs spanning 1939–2004

(Fig. 7):

FIG. 4. Spatial and temporal variation in annual input rates (mean 6 SE) of new large logs (�1 m dbh) from the erosion ofmature fluvial terraces in the mainstem of the Queets River, Washington, USA, from 1939 to 2002 (SE is across years), fromdownstream (left) to upstream (right). The right-hand panel illustrates the percentage (y-axis) of sections of river channel (200 m)with mean input rates equal to or lower than the corresponding value on the x-axis. Values on the line represent input rates at 10%increments, to simplify interpretation.


y ¼ 75:4t�0:25 ð3Þ

where y is the percentage of large logs in a cohort

remaining stable t years after initially being deposited in

the channel. Approximately one-half remained stable for

at least five years, 42% for �10 yr, and 27% for �60 yr;

and those remaining stable were incorporated into

emerging forests. The river moved 81 of the key pieces

tagged in 2002–2004, and we relocated 28 (35%). The

rest were either transported outside the Park, hidden in

logjams or buried. The stability of tagged key pieces

could not be predicted solely from the size of the log or

jam (P � 0.05; logistic regression) because mean

dimensions of stable and mobilized pieces were indis-

tinguishable, including dbh (P¼ 0.91; t test), length (P¼0.66; t test), and volume (P ¼ 0.92; Mann-Whitney U

test). Jams formed by stable and mobilized logs were

also similar in size (P ¼ 0.46; Mann-Whitney U test).

Spiraling simulations suggested that conifers are likely

to be transported further and deposited in more

locations than hardwoods, which decay faster, all else

being equal (Fig. 8). The median functional lifetime

(qLL) was estimated to be 60 yr for conifers and 25 yr for

hardwoods. There was a 50% probability that coniferous

logs would spiral (pLL) �3 times (up to 16 times) before

disintegrating, and have turnover lengths (nLL) �1520m. In comparison, 50% of the hardwoods were predicted

to spiral � 2 times (up to 11 times) and be transported

�916 m, reflecting shorter qLL (Fig. 8). The interquartile

ranges of nLL were 334–5094 m for conifers and 206–

3291 m for hardwoods. Conifers had a 90% chance of

traveling �76 m and 10% chance of traveling �11 959 m

(Fig. 8). In comparison, hardwoods had a 90% chance of

traveling �49 m and a 10% chance of traveling �9746m. After their initial deposition, aLL is expected to

exceed the median qLL for 27% of conifers and 33% of

hardwoods, meaning they will disintegrate before the

channel returns unless buried or otherwise preserved.

DISCUSSION

Mature forests and longitudinal and lateral connec-

tions are vital factors shaping the abundance and

distribution of large logs in the Queets River. Instream

supplies of large logs rely on inputs from the undercut-

ting of adjacent and upstream mature forests but also

logs displaced from upstream reaches or recaptured

FIG. 6. (A) Lateral recruitment distances of new large logs(�1 m dbh) delivered to the mainstem of the Queets River,Washington, USA, through erosion of mature fluvial terracesover 63 years (i.e., 1939–2002). (B) The aerial photo depicts theQueets River in 1939 to illustrate these distances. Matureforests within 265 m (solid line) of the channel margincontributed 95% of the new large logs entering the channelover the following 63 years. Half of the new logs originatedfrom forests �92 m (dotted line) from the channel margin, as itexisted in 1939.

FIG. 5. Burial rate of remnant large logs deposited in thechannel of the Queets River, Washington, USA, over 70 years.The relationship indicates the percentage of the remnant(stable) logs in a cohort (a group of large logs) that are buriedt years after being deposited by the river. The average numberof large logs in a cohort for this analysis was 28, ranging from 6to 66.


through the erosion of young floodplain forests by the

river. Our results support the hypothesis that large log

inputs are patchy in space and time due, in part, to local

variation in channel movement patterns and the

proximity of mature forests. Large log abundance and

distribution fluctuates over time at individual reaches,

and these changes may not be synchronized. We

hypothesize that these fluctuations enhance riverine

biocomplexity and system integrity, and stabilize the

availability of wood-formed habitats in the river valley

by promoting a state of dynamic equilibrium over

decades to centuries.

The importance of mature forests

Mature forests are nonsubstitutable sources of new

large logs, and their variable proximity to channels

contributes to local heterogeneity in input rates, as

expected. Our findings demonstrate that patches of

mature forests currently hundreds of meters from the

channel can eventually become important sources of

large logs because the river can potentially erode them in

the future. For example, input rates vary widely

throughout the valley (Fig. 4), but the Queets River

recruits 95% of the large logs from a riparian corridor

extending �265 m laterally on both banks within only 63

years (Fig. 6). Stands .400 m from the channel

contribute little over six decades, but it would be

erroneous to conclude outlying areas are unimportant

over the long term. The lateral extent of mature forests

needed for a self-sustaining system is probably greater

than we observed over 63 years because, in the Queets

River, stands containing large-diameter trees are often

centuries old (Van Pelt et al. 2006).

The importance of connectivity

Lateral and longitudinal connectivity supports the

recruitment, transport, storage, and recapture of large

logs (the spiraling process) in the Queets River (see Plate

1). Widespread channel meandering delivers most new

large logs but episodic cutoffs and avulsions are locally

important. We contribute empirical evidence that a

temperate floodplain river often rearranges and trans-

ports large logs downstream, including those previously

underpinning logjams (even those exceeding 2.4 m dbh

and 60 m in length). In the Queets River, large logs often

reside in several locations hundreds of meters apart

before disintegrating, linking the structure and distur-

bance history of widely separated reaches (Fig. 8). This

finding concurs with both Marcus et al. (2002) and van

der Nat et al. (2003a), who observed high rates of wood

turnover, though total quantities remained stable.

Whereas stable logs promote spatial complexity in the

river landscape, we propose that the periodic rearrange-

ment of large logs contributes to system resilience by

driving temporal fluctuations in habitat availability that

are asynchronous among stream reaches. The river often

moves some of the large logs in the first few years after

FIG. 8. (A) Cumulative probability of turnover lengths(nLL, note log scale) for large logs in the mainstem of the QueetsRiver, Washington, USA. The two lines represent predictionsfor logs with decomposition rates typical of conifers (bold line)and of hardwoods (thin line). (B) The percentage of large logsthat would exhibit turnover lengths meeting or exceeding thedistance between the ‘‘input site’’ and the approximate locationin the river indicated by each arrow. For example, 10% of thelogs from the input site are predicted to be transported (or‘‘spiral’’) at least as far as the last arrow on the left within theirfunctional lifetime.

FIG. 7. Relationship between large log retention (percent-age remaining stable) and the years elapsed (t) since the cohortwas deposited in the active channel in the mainstem of theQueets River, Washington, USA. Each point represents adifferent cohort (n¼ 14). The average number of large logs in acohort was 108, ranging from 12 to 361 logs.


deposition. The remaining fraction persist as remnants

in dense stands of pioneering vegetation (Fig. 6, Gurnellet al. 2000a, b). Some logs remain stable for decades ormore. The ecological importance of these stable logs is

well established (see Abbe and Montgomery 1996,2003); a small but important fraction is buried andremains for centuries, protecting associated vegetation

from erosion (Montgomery and Abbe 2006). However,many logs are eventually recaptured by ongoing lateral

channel movements, so that instream supplies consist ofa mixture of fresh, new logs as well as remnants from thedistant past (e.g., Hyatt and Naiman 2001). This

transient storage of logs in the floodplain likely ensuresthat jams are continually present in the active channel,

even during periods with low inputs of new logs.Similarly, the periodic rearrangement of large logs

may stabilize the availability of important habitats at

large spatial scales. Both aquatic and riparian habitatsare highly dynamic in floodplain rivers (Piegay et al.1999, Arscott et al. 2002, van der Nat et al. 2003b,

Gurnell et al. 2005, Latterell et al. 2006). Temporalheterogeneity in the distribution of pools (Naiman and

Latterell 2005) and pioneer bars (Latterell et al. 2006) inthe Queets River may be attributable, in part, tofluctuations in the abundance and distribution of large

logs. These habitats fluctuate over time, but the patternsof change are asynchronous among reaches, dampening

the degree of change at the valley scale. In this way, the

periodic rearrangement of large logs may contribute to

the resilience of riverine communities that utilize these

habitats for parts of their life cycle.

Our spiraling analyses suggest that floodplain storage

increases the probability that some pieces move only

short distances because retention is not solely restricted

by the longevity of instream jams. For example, Martin

and Benda (2001) estimate that smaller pieces of wood in

a 20–30 m wide low-gradient Alaskan river are

transported between existing jams and have a 90%

probability of traveling �300 m. In contrast, large logs

in the much wider Queets River have a 90% chance of

traveling only �76 m because they often come to rest

between existing jams and may enter floodplain stock-

piles. However, the river is simultaneously capable of

moving large logs substantial distances. Large logs in the

Queets River have a 10% chance of traveling �11 959 m

(Fig. 8), whereas wood in the Alaskan stream has the

same chance of traveling only �2500 m. This finding is

consistent with the notion that potential transport

distances are relatively high in rivers where channel

width exceeds the height of the tallest riparian trees (see

Gurnell 2003).

Recommended improvements

Most field studies of wood movement, including ours,

are limited by an inability to recover a large percentage

PLATE 1. Large log in the Queets River, Olympic National Park, Washington, USA. This log, shown in its original location inAppendix A, was displaced and transported by the river during the study. Photo credit: J. J. Latterell.


of the tagged pieces (e.g., Lienkaemper and Swanson

1987, Jacobsen et al. 1999). This is inevitable because

mobile logs in large rivers cannot be trapped as they exit

the reach or system of interest (e.g., like leaves, Speaker

et al. 1984). We suspect that some were lost to the ocean.

If so, JLL and nLL (Fig. 3) are actually higher than

reported and therefore wood retention is overestimated.

It seems more reasonable that most were hidden instead

in side channels and among abundant logjams (i.e.,

.600 logjams in the portion of the river that was

searched). Regardless, our simulations account for the

possibility that the river moves some large logs further

than we observed in field trials. Additional determina-

tions of how nLL and pLL vary among rivers and regions,

and whether these differences reflect system retentive-

ness and the decay resistance of tree species, will tell

much about the generic capacity of rivers to retain and

process wood.

Field studies are required to better understand the

actual transport dynamics of wood in rivers (e.g., Young

1994, Jacobsen et al. 1999, van der Nat et al. 2003a) and

to put our observations from the Queets River into a

broader context. Studies of larger rivers will be

particularly valuable because wood dynamics in small

streams are increasingly well known (e.g., Lienkaemper

and Swanson 1987, Murphy and Koski 1989, Berg et al.

1998, Martin and Benda 2001, May and Gresswell

2003). The physical basis for log stability in rivers (and

flumes) has been clearly articulated in previous studies in

the field and in experimental flumes (Abbe 2000,

Braudrick and Grant 2001, Abbe and Montgomery

2003, Wallerstein and Thorne 2004). Predicting the long-

term stability of logs in a dynamic river environment is

particularly challenging because so many covariates may

be involved, and few hold steady over time or among

locations (Appendix A).

The accuracy of the spiraling simulations in this study

would be greatly improved by a better understanding of

how large logs decay in floodplains and beneath alluvium.

The true functional lifetime of large logs is currently

unknown but is likely quite variable, depending on key

factors influencing the decay rate (i.e., wood chemistry or

substrate quality, temperature, moisture, and aeration;

Melillo et al. 1984, Laiho and Prescott 2004), as well as the

initial size of the log relative to local channel dimensions

(e.g., Abbe 2000), and colonization by wood-boring

invertebrates (J. Latterell, unpublished data). We speculate

that these factors vary substantially as logs are subjected

to changing conditions throughout vegetative succession,

recapture, or eventual burial (see Appendix A). In this

study, we use decay coefficients that fell within the upper

and lower bounds for Picea (0.023–0.028), Tsuga (0.018–

0.026), and Alnus (0.055–0.083) across experimental

forests throughout the western USA (Harmon and Fasth

2005), though none were from riparian or instream

environments. Nonetheless, we view the 75% decay

threshold as a reasonable first approximation.

Implications for river conservation and restoration

How can natural, self-sustaining processes supplyingand retaining wood in floodplain river systems in

temperate forests be restored in densely populated rivervalleys? Solutions must provide sustained delivery of

large logs, variable flows (including some floods), andsufficient room for some of the riverbed to be

abandoned long enough to grow mature forests, whichrequires considerable time. Existing mature riparian

forests warrant protection (especially in developedrivers) because they have high ecological value (Franklin

et al. 1981) and take many years to produce (e.g.,generally .100–300þ years in the Queets River valley;

Balian and Naiman 2005, Van Pelt et al. 2006). Wherelarge logs are lacking, Collins and Montgomery (2002)

proposed a ‘‘restoration succession’’ strategy, couplingartificial logjams (e.g., Brooks et al. 2004) and levee

setbacks or removals with riparian reforestation usingboth fast- and slow-growing (but durable) trees toensure wood supplies would become self-sustaining. In

regulated rivers, the provision of flood flows isimportant because high flow events play an important

role in wood recruitment and redistribution (Keller andSwanson 1979, Piegay and Bravard 1997, Marcus et al.

2002, Piegay 2003, van der Nat et al. 2003a, Pettit andNaiman 2005). Managing the channel and floodplain

forest as a unified system is also advisable (Junk et al.1989, Mac Nally et al. 2002, Angradi et al. 2004) because

when they are connected, the river may tap andreplenish stockpiles of remnant logs in the floodplain

(Piegay et al. 1999, Gurnell et al. 2001).Wood hotspots (Fig. 4) warrant special consideration

in land use planning because they supply a dispropor-tionate number of large logs to the river. Ecological

theory suggests that the loss of organisms withdisproportionately large ecological effects relative to

their abundances results in substantial, sometimesdetrimental changes to ecosystem structure or organi-

zation (Power et al. 1996). We suspect that restrictingthe river’s access to wood hotspots may have similarconsequences. In the Queets River, hotspots tend to

occur in unconfined alluvial valley segments (Montgom-ery and Buffington 1997) with mature forests in close

proximity to laterally migrating channels. We cautionthat the spatial distribution of individual hotspots

within these segments will likely shift over decades tocenturies. If so, establishing an interconnected system of

large, strategically located (see Roni et al. 2002, Berg etal. 2003, Lorang et al. 2005) riparian reserves spanning

entire stream segments would be preferable to restrictingriparian protections to short reaches presently function-

ing as hotspots.We acknowledge that significant challenges remain.

Floodplain reclamation (from development) and pres-ervation are prohibitively expensive and significant

technical, social, and political obstacles exist. Surmount-ing these challenges demands a deeper ecological

understanding of floodplain rivers but also unprece-


dented innovation in alleviating human impacts in

developed systems. In our view, successful conservation

efforts will be guided, in part, by the principle that our

actions must evolve over time, addressing present

conditions while planning for the anticipated future,

and by embracing change as a fundamental attribute of

temperate floodplain rivers (Naiman and Latterell 2005).

ACKNOWLEDGMENTS

We thank L. Benda, R. E. Bilby, P. A. Bisson, and D.Peterson for their comments on versions of this manuscript, andL. Conquest for statistical advice. Comments from twoanonymous reviewers improved the manuscript and aregratefully acknowledged. Research support from the PacificNorthwest Research Station of the USDA Forest Service,Weyerhaeuser Company, the Andrew W. Mellon Foundation,and the National Science Foundation is gratefully acknowl-edged. Field assistance was provided by E. Meehan, N.Hurtado, A. Dotolo, J. T. Jackson, and M. G. Logsdon. Fieldresearch was conducted from 2002 to 2005 within OlympicNational Park under research permits OLYMP-0047 andOLYM-0096. We thank the U.S. Department of the InteriorNational Park Service, especially S. Acker, B. Bacchus, J.Freilich, C. Hoffman, and R. Hoffman at Olympic NationalPark. We also thank J. O’Connor and L. Fueste of the U.S.Geological Survey for sharing geospatial data and historicalairphotos, respectively.

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APPENDIX A

Photographs illustrating the natural history of large logs in the Queets River, Washington, USA (Ecological Archives A017-040-A1).

APPENDIX B

Physical characteristics of study reaches used in quantifying log burial and large log dynamics in the Queets River, Washington,USA (Ecological Archives A017-040-A2).


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SOURCES AND DYNAMICS OF LARGE LOGS IN A TEMPERATE FLOODPLAIN RIVER

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