-
Geomorphology xxx (2016) xxx–xxx
GEOMOR-05561; No of Pages 9
Contents lists available at ScienceDirect
Geomorphology
j ourna l homepage: www.e lsev ie r .com/ locate /geomorph
The waterfall paradox: How knickpoints disconnect hillslope and
channelprocesses, isolating salmonid populations in ideal
habitats
Christine May a,⁎, Josh Roering b, Kyle Snow a, Kitty Griswold
c, Robert Gresswell da James Madison University, Department of
Biology, MSC 7801, Harrisonburg, VA, 24401, USAb University of
Oregon, Department of Geological Sciences, 325C Cascade Hall,
Eugene, OR 97403, USAc Idaho State University, Department of
Biological Sciences, 921 S. 8th Ave., Pocatello, ID, 83209, USAd
U.S. Geological Survey, Northern Rocky Mountain Science Center,
2327 University Way, Suite 2, Bozeman, MT, 59715, USA
⁎ Corresponding author.E-mail addresses: [email protected] (C. May),
jroering@
[email protected] (K. Griswold), [email protected] (R. G
http://dx.doi.org/10.1016/j.geomorph.2016.03.0290169-555X/© 2016
Elsevier B.V. All rights reserved.
Please cite this article as: May, C., et al., Thepopulations in
ideal habita..., Geomorpholog
a b s t r a c t
a r t i c l e i n f o
Article history:Received 9 July 2015Received in revised form 22
March 2016Accepted 25 March 2016Available online xxxx
Waterfalls create barriers to fish migration, yet hundreds of
isolated salmonid populations exist above barriersand have
persisted for thousands of years in steepmountainous terrain.
Ecological theory indicates that small iso-lated populations in
disturbance-prone landscapes are at greatest risk of extirpation
because immigration and re-colonization are not possible. On the
contrary, many above-barrier populations are currently
thrivingwhile theirdownstream counterparts are dwindling. This
quandary led us to explore geomorphic knickpoints as a mecha-nism
for disconnecting hillslope and channel processes by limiting
channel incision and decreasing the pace ofbase-level lowering.
Using LiDAR from the Oregon Coast Range, we found gentler channel
gradients, widervalleys, lower gradient hillslopes, and less
shallow landslide potential in an above-barrier catchment
comparedto a neighboring catchment devoid of persistent
knickpoints. Based on this unique geomorphic template,above-barrier
channel networks are less prone to debris flows and other episodic
sediment fluxes. Theseabove-barrier catchments also have greater
resiliency to flooding, owing towider valleys with greater
floodplainconnectivity. Habitat preferencemodels further indicate
that salmonid habitat is present in greater quantity andquality in
these above-barrier networks. Therefore the paradox of the
persistence of small isolated fish popula-tionsmay be facilitated
by a geomorphicmechanism that both limits their connectivity to
larger fish populationsyet dampens the effect of disturbance by
decreasing connections between hillslope and channel processes
abovegeomorphic knickpoints.
© 2016 Elsevier B.V. All rights reserved.
Keywords:KnickpointsSalmonid habitatDisturbance ecologyShallow
landslides
1. Introduction
One of the most pressing conservation questions for Pacific
salmonand trout (Oncorhynchus sp.) is the role of episodic
disturbances instructuring stream habitat and triggering extreme
fluctuations in popu-lation abundance. From an ecological
perspective, disturbances can bedefined as ‘any relatively discrete
event in time that disrupts ecosystem,community, or population
structure and changes resources, substrateavailability, or the
physical environment’ (White and Pickett, 1985).Rivers in steep
mountainous landscapes are subject to severe distur-bances such as
landslides, debris flows, fires, floods, and droughts.These
geomorphic processes are important drivers of landscape evolu-tion
but pose a significant ecological challenge for organisms to
survivein these highly variable systems. Indeed, the concept of
riverscapes rec-ognizes that unique geomorphic features can have
overriding effects onstream fish (Fausch et al., 2002) and that
large infrequent disturbancesmay become the dominant force
structuring the system, creating the
uoregon.edu (J. Roering),resswell).
waterfall paradox: How knicky (2016), http://dx.doi.org/10
template upon which subsequent ecological processes and
interactionsamong species occur (Frissell et al., 1986; Reeves et
al., 1995; Turner andDale, 1998). To facilitate long-term
persistence, many fish populationsare dependent upon connected
habitats to provide opportunities fordispersal and recolonization
following localized extirpations caused bydisturbances (e.g.,
Lamberti et al., 1991; Schlosser, 1991; Northcote,1997; Gresswell,
1999; Roghair et al., 2002), and therefore, fragmenta-tion of the
mountainous landscape (intrinsic and anthropogenic) canreduce
dispersal and may render fish populations less resilient to
epi-sodic disturbances (Kruse et al., 2001; Guy et al., 2008).
Understanding the linkages between geomorphic disturbance
pro-cesses and riverine habitat is particularly important for
Pacific salmo-nids because these fish are intricately tied to
Pacific Rim topography(Montgomery, 2000;Waples et al., 2008;May et
al., 2013). Disturbancesplay such an important role in this region
because hillslope and channelprocesses are tightly coupled in terms
of routing water and sediment.This type of connectivity throughout
the landscape can lead to largeshort-term fluxes of sediment such
as debris flows and post-fire surfaceerosion (e.g., Benda and
Dunne, 1997; Jackson and Roering, 2009), aswell as long-term fluxes
driven by channel incision triggered by chang-es in base-level.
Lithologic knickpoints may play a unique role in the
points disconnect hillslope and channel processes, isolating
salmonid.1016/j.geomorph.2016.03.029
http://dx.doi.org/10.1016/j.geomorph.2016.03.029mailto:[email protected]
logohttp://dx.doi.org/10.1016/j.geomorph.2016.03.029http://www.sciencedirect.com/science/journal/0169555Xwww.elsevier.com/locate/geomorphhttp://dx.doi.org/10.1016/j.geomorph.2016.03.029
-
2 C. May et al. / Geomorphology xxx (2016) xxx–xxx
landscape by functioning to disconnect hillslope and channel
processesthat are driven by baselevel lowering (Crosby and Whipple,
2006;Ouimet et al., 2009; Hurst et al., 2012).
Wehypothesize that the restriction of base-level lowering
imposed bywaterfalls (i.e., geologic knickpoints) inhibits channel
incision, resulting inwider than anticipated valleys, lower than
anticipated channel slopes,lower hillslope angles, and reduced
shallow landslide potential. Thesemorphologic conditions would in
turn lead to the development of idealfish habitat and dampen the
incidence of landslides and debris flows inabove-barrier channel
networks.
The Oregon Coast Range is an ideal landscape to explore these
ideasbecause a large portion of this humid, steep, soil-mantled
landscape isunderlain by the Tyee sandstone formation and presents
a uniformridge-and-valley landscape where sediment transport is
dominated byshallow landslides and debris flows (e.g., Stock and
Dietrich, 2003).Within the Tyee Formation; however, resistant
igneous dikes crop outlocally, often forming persistent waterfalls
(Oxford, 2006). Variation intributary networks and slopemorphology
above and below knickpointsindicate that the rate of
knickpointmigration is slow comparedwith thetimescale of landform
adjustment (Sweeney et al., 2012). This providestime for the
above-barrier channel and valley network to adjust to base-level
lowering that proceeds more slowly than the surrounding
terrain.
Within a stream network the place for greatest potential overlap
be-tween debris flow disturbance and fish habitat is in small
headwaterstreams, which provide habitat for resident and anadromous
salmonids(May and Lisle, 2012). In the Oregon Coast Range, Coastal
CutthroatTrout (Oncorhynchus clarkii clarkii) populations are
present above nu-merous waterfalls that limit connectivity with
downstream popula-tions, with an estimated 269 barrier isolated
populations in westernOregon (Gresswell et al., 2006). Similarly,
waterfalls created by isostaticrebound in Alaska have isolated
numerous populations of coastal cut-throat for thousands of years
(Whiteley et al., 2010). Ecological theoryindicates that small
isolated populations in disturbance-prone ecosys-tems are at
greatest risk of extirpation because immigration and
recolo-nization are not possible and because small populations are
subject togenetic drift, inbreeding, and basic demographic factors
that reducetheir survival potential (e.g., Lande, 1988; Purvis et
al., 2000; Woffordet al., 2005). In the Oregon Coast Range;
however, above-barrier popu-lations of coastal cutthroat trout have
persisted over long timescales,potentially millennia (Guy et al.,
2008).
The location of suitable habitat for salmonids in the Pacific
North-west is predicted for habitat conservation plans (e.g.,
Agrawal et al.,2005) using Intrinsic Potential (IP) modeling
(Burnett et al., 2007).Based upon topographic analysis, this
approach identifies streamreaches of high potential for developing
productive habitat, specificallyareas with broad valleys and low
gradient channels within the range ofvarious salmonid species. We
hypothesize that a network of unusuallybroad valleys will be
present upstream of knickpoints in the OregonCoast Range; and we
further hypothesize that when normalized fordrainage area, channel
slopes will be lower because of reduced verticalincision and
increased lateral erosion. An overall reduction in channelslope
would be associated with more productive habitat (e.g.,
reducedwater velocity and increased nutrient retention) and would
allow foran increased spatial distribution of fish by making more
of the networkaccessible as a result of slope-induced limits to
their upstreamextent. Inaddition, we hypothesize that hillslope
angles will be lower above theknickpoint due to the decreased pace
of base-level lowering, reducingthe frequency of landslide and
debris flow disturbance to channels.
Our approach to test these hypotheses about knickpoint effects
onchannel development and disturbance potential uses high
resolutionlight detection and ranging (LiDAR) derived topography in
a paired wa-tershed comparison. The pattern of valleywidening,
drainage area depen-dent channel slope, hillslope angles, and
shallow landslide potential arequantified for a basin above a
knickpoint (Kentucky Falls) and a neighbor-ing basin absent of
knickpoints (Harvey Creek). This type of pairedwater-shed
comparison holds great promise in the Oregon Coast Range (OCR)
Please cite this article as: May, C., et al., The waterfall
paradox: How knickpopulations in ideal habita..., Geomorphology
(2016), http://dx.doi.org/10
because of the uniformity of the landscape (Gresswell et al.,
2004;Sweeney et al., 2012; May et al., 2013; Marshall and Roering,
2014); inthe absence of deep-seated landslides and gabbro dikes
that regulatebase-level lowering and upstream geomorphic processes
for a small frac-tion (b20%)of catchments in theOCR. Past studies
haveobserved remark-ably consistent hillslope angles, slope-area
channel network metrics, andshallow landslide potential for OCR
catchments (Montgomery, 2001;Kobor and Roering, 2004; Montgomery
and Dietrich, 1994). In fact, theobserved uniformity of steep,
dissected terrain in western Oregon in-spired a suite of geomorphic
studies that sought to minimize local varia-tions in lithology,
climate, vegetation, and the pace of uplift/erosion inorder to
isolate the influence of geomorphic processes on topography(Reneau
and Dietrich, 1991; Seidl and Dietrich, 1992; Roering et al.,1999;
Heimsath et al., 2001; Stock and Dietrich, 2003, 2006). The
limitedavailability of LiDAR derived topography prevented us from
investigatingnumerous above-waterfall basins; therefore, the
results are limited to apaired watershed study where the generality
of the results remain to betested.
2. Methods
Paired basins were selected based on the availability of LiDAR
data forthe entire drainage network (101 km2). TheNorth Fork Smith
River (basinarea 27.6 km2) resides above an ~100 mwide gabbroic
dike that forms a70 m high knickpoint at Kentucky Falls (Fig. 1).
Of the estimated 269 ba-sins above waterfalls in western Oregon,
basin area ranged from 5.4 to57.5 km2with an average size of 14.2
km2 (Gresswell et al., 2006). NearbyHarvey Creek (basin area 21.7
km2) contains no sizable knickpoints(Marshall and Roering, 2014)
and was selected as the reference basin torepresent typical
ridge-valley topography in the absence of variationfrom lithology
or baselevel lowering.
2.1. Measuring valley width
To map valley width, we used the approach by May et al.
(2013)where the gridded bare earth LiDAR data was smoothed with a
movingwindow algorithm (Wood, 1996). At each grid node, we fit a
second-order weight polynomial to a 15x15 node matrix of
neighboring pointsand calculated slope gradient from the polynomial
coefficients. Fromthese slope maps, flat valley floors can be
clearly distinguished fromthe adjacent steep hillslopes, which
transition abruptly from the valleyfloor. Next we measured cross
sections on the slope map perpendic-ular to the valley along the
mainstem and several major tributariesin the drainage network of
Harvey Creek to construct the baselinerelation between drainage
area and valley width. Measurementspacing corresponded to
individual stream reaches in a synthetic channelnetwork developed
by Clarke et al. (2008) and described below. AboveKentucky Falls,
valley width was also measured at cross sections on theslope map
along the mainstem and major tributaries.
We tested for a difference in the regression coefficients
between thetwo basins using multiple linear regression of the
log-transformed var-iable. Differences in intercepts of the
regression lines were evaluated byusing a variable that identified
the basin; differences in slope of theregression lines were
evaluated by adding an interaction term to the re-gression (basin ∗
drainage area). Effect size of thewaterfall on upstreamvalley
widthwas calculated from the difference between Kentucky
FallsandHarvey Creek,whichwas divided by the value fromHarvey Creek
asa reference point. These values were calculated over a range of
drainageareas using the regression equations for the width-area
relations. Wehypothesized that the above-waterfall basin would have
broader val-leys for a given drainage area compared to the ambient
landscape, asrepresented byHarvey Creek. Data from basins b0.1
km2were excludedfrom the Harvey Creek data set because of the
scaling break identifiedby May et al. (2013).
points disconnect hillslope and channel processes, isolating
salmonid.1016/j.geomorph.2016.03.029
http://dx.doi.org/10.1016/j.geomorph.2016.03.029
-
Fig. 1. Slope maps based on LiDAR-derived topography for the
basin above Kentucky Falls on the North Fork Smith River and nearby
Harvey Creek, which contains nomajor knickpoints.
3C. May et al. / Geomorphology xxx (2016) xxx–xxx
2.2. Slope-area relation
Geomorphologists have long recognized the relationship
betweenchannel slope (S) and drainage area (A) as an important
predictor ofriver profile characteristics (Hack, 1957). Empirical
observations fromriver systems around the world reveal a consistent
power-law scalingof the slope-area relation (e.g., Hack, 1973;
Flint, 1974; Howard andKerby, 1983). Reach-scale slope-area
datawere obtained from syntheticchannel networks developed by
Clarke et al. (2008). The resulting linearrelation was restricted
to stream reaches with drainage areas N1 km2 tolimit observations
to the fluvial process domain, based on the scalingbreak observed
in previous studies (Stock and Dietrich, 2003). Differ-ences in the
regression coefficients between the two basinswere exam-ined using
multiple linear regression of the log-transformed variable.The
difference in intercepts of the regression lines was tested by
addinga variable that identified the basin; a difference in slope
of the regres-sion lines was tested by adding an interaction term
to the regression(basin ∗ drainage area). Effect size of the
waterfall on upstream channelslope was calculated from the
difference between Kentucky Falls andHarvey Creek and dividing by
the value from Harvey Creek as a refer-ence point. These values
were calculated over a range of drainageareas using the regression
equations for the width-area relations. Weused a steepest descent
algorithm to generate longitudinal profiles foreach mainstem
channel. We hypothesized that the above-waterfallbasin would have a
lower channel slope for a given drainage area com-pared to the
basin adjusting to a fluctuating base level, as representedby
Harvey Creek.
Please cite this article as: May, C., et al., The waterfall
paradox: How knickpopulations in ideal habita..., Geomorphology
(2016), http://dx.doi.org/10
2.3. Hillslope angles and shallow landslide potential
Because the propensity for hillslopes to produce shallow
landslidesdepends on the topography of headwall regions, including
colluvial hol-lows and sideslopes, we analyzed the average angle of
hillslopes. In ad-dition, we employed a commonly-used coupled slope
stability-hydrology algorithm to identify sites of potential
shallow landslidingin the paired basins and used the resulting data
as a proxy for landslidedisturbance potential (Montgomery and
Dietrich, 1994). The actuallikelihood of channel disturbance
depends on the details of predictedlandslide runout pathways (e.g.,
May and Gresswell, 2004), but suchan analysis is beyond the scope
of this contribution. Instead, the long-term persistence of
knickpoints at our study site implies that hillslopesabove and
below have adjusted to the pace of local base-level loweringsuch
that sediment production processes can be inferred frommorphol-ogy
all else equal.
We calculated values of q/T, where q is effective rainfall and T
is soiltransmissivity according to Montgomery and Dietrich (1994)
using pa-rameters characteristic of the Oregon Coast Range. The
topographic vari-ables required for this computation include local
hillslope gradient, whichwegeneratedusing the LiDAR smoothing
procedure described above, anddrainage area per unit contour width,
which we generated using the Dinfalgorithm as implemented in Matlab
by Perron et al. (2008). Followingthe procedures described in
Montgomery and Dietrich (1994), we de-fined unconditionally stable
terrain as having slopes less than the criticalvalue for full soil
saturation (in this case 0.38 or 38%). Slopes greater than1.0 (or
100%) were deemed unconditionally unstable and these areas
points disconnect hillslope and channel processes, isolating
salmonid.1016/j.geomorph.2016.03.029
http://dx.doi.org/10.1016/j.geomorph.2016.03.029
-
Table 1Knickpoint effect size on valley width (m), calculated
from the regression equations inFig. 2 for a range of drainage
areas.
Drainage area (km2) Harvey Creek Kentucky Falls Effect size
0.1 4.8 7.8 63%1 18.1 32.5 80%10 67.8 134.4 98%
4 C. May et al. / Geomorphology xxx (2016) xxx–xxx
commonly have thin or absent soil mantle based on our field
observa-tions. As such, the q/T values define the relative
propensity for shallowlandslide failure for slopes between 0.38 and
1.0. Low values of q/T reflectfailure-prone siteswith a high
propensity for failure because low effectiveprecipitation is
required to induce landsliding.
2.4. Fish habitat modeling
We modeled juvenile trout habitat potential using a
reach-scaleintrinsic potential (IP) value:
IP ¼ IMAD � IBFW � IGRADIENTð Þ1=3
where IMAD is an index of mean annual discharge, reflecting the
need forchannels large enough to supply adequate perennial
streamflow for sal-monid persistence (Burnett et al., 2007).
Suitability curves developedfor coastal cutthroat trout indicate
that habitat suitability is maximizedin mid-sized streams (0.05–0.6
m3/s). The second parameter, IBFW, is anestimate of the bank-full
channel width from local hydraulic geometryrelations (based on
field data from the Oregon Department of Fish andWildlife and the
U.S. Environmental Protection Agency, as cited byClarke et al.,
2008). Suitability curves suggest that habitat is maximizedfor
coastal cutthroat trout in channel reaches with an estimated
bank-full width between 1and 8 m. The third parameter, IGRADIENT,
is anindex of reach-scale channel gradient estimated from synthetic
streamnetwork routed through 10-m DEMs using elevations
interpolatedfrom contour lines (Clarke et al., 2008). The habitat
suitability curvefor coastal cutthroat trout developed by Griswold
and Reeves (2014)originated from below-barrier streams where
cutthroat are in competi-tion with other salmonids, most notably
Coho Salmon (Oncorhynchuskisutch). Competition leads to habitat
segregationwith coastal cutthroattrout occupying riffles and coho
salmon occupying pools, resulting inthe competitively inferior
trout occupying less favorable habitatwhen dominated by salmon
(Glova, 1987). Similarly, Sabo andPauley (1997) concluded that the
advantages of size and experienceallow salmon to dominate and that
trout populations that haveevolved with salmon are less competitive
than those that haveevolved in isolation. Therefore, we compared
the coastal cutthroatsuitability curve developed by Griswold and
Reeves (2014), wherehabitat suitability is maximized in channel
reaches with 4–8%channel gradient with a revised curve where
habitat suitability ismaximized in all reaches with b8% channel
gradient to reflect thelack of competitive exclusion from low
gradient habitats in above-barrier populations.
Fig. 2. The power-law relation between valley floor width and
drainage area for the abovewaterfall basin (Kentucky Falls)
compared to the ambient landscape (Harvey Creek) forthe full extent
of the channel network.
Please cite this article as: May, C., et al., The waterfall
paradox: How knickpopulations in ideal habita..., Geomorphology
(2016), http://dx.doi.org/10
The IP value is based on reach-scale habitat suitability scores,
whichconvert the value of each variable to a score between 0 and 1.
The com-ponent indices are equally weighted and IP value is
calculated at thegeometric mean of each of the three parameters.
The IP values close toone indicate great potential for high-quality
habitat; whereas, IP valuesclose to zero indicate almost no
potential for habitat. The proportion ofthe channel network length
in each of four IP categories (negligiblehabitat b0.25, low quality
habitat 0.25–0.49, moderate quality habitat0.5–0.74, and high
quality habitat N0.75) was calculated for each basinand compared
using a Chi-square (χ2) test.
In addition to determining the overall quality of habitat using
theIP value, the quantity of habitat can be calculated as the
proportionof the drainage network that is accessible to fish. This
calculation isbased on a slope-induced limit for coastal cutthroat
trout of ~10% for thereach-scale channel gradient (unpublished data
by R. Gresswell). Paststudies have shown that slope-induced limits
to fish distributioncan be a strong predictor for trout occurrence
and their presencetends to decrease linearly with increasing
channel slope up to the10% limit (Kruse et al., 1997).
3. Results and discussion
3.1. Valley width
Regression analysis revealed a significant difference in the
rela-tion between drainage area and valley floor width in the two
basins(Fig. 2). The intercept of the regression lines was greater
for KentuckyFalls (p b 0.001); however, the slope of the regression
lines did not differ(p = 0.142). Because the regression lines
diverged at larger drainageareas, the effect size increased with
drainage area and ranged from 63to 98% (Table 1). These results
indicate that valley floorwidthwas consis-tently broader than
anticipated in the above-waterfall basin, suggestingthat lateral
river erosion that broadens valleys is playing a larger rolethan in
actively incising valleys that are keeping pacewith base-level
low-ering. This in turn can lead to lower hillslope angles
(Penserini, 2015),
Fig. 3. Comparison of the slope-area relation for stream reaches
in the fluvial processdomain (N1 km2) in the above waterfall basin
(Kentucky Falls) and the ambientlandscape (Harvey Creek).
points disconnect hillslope and channel processes, isolating
salmonid.1016/j.geomorph.2016.03.029
http://dx.doi.org/10.1016/j.geomorph.2016.03.029
-
Fig. 4. Comparison of hillslope steepness in the
above-knickpoint basin (Kentucky Falls)and the basin devoid of
knickpoints (Harvey Creek).
Table 2Knickpoint effect on channel slope (m/m), calculated from
the regression equations inFig. 3 for a range of drainage
areas.
Drainage area (km2) Harvey Creek Kentucky Falls Effect size
1 0.07 0.03 −57%5 0.02 0.01 −32%10 0.01 0.01 −18%
Fig. 5.Maps of q/T values (Montgomery and Dietrich, 1994) for
Harvey Creek and the basin aboindicate highpropensity for shallow
landsliding;whereas highvalues (slightlynegative, cool colstable
and deep red colors show terrain that is unconditionally unstable
(or too steep to retain
5C. May et al. / Geomorphology xxx (2016) xxx–xxx
Please cite this article as: May, C., et al., The waterfall
paradox: How knickpopulations in ideal habita..., Geomorphology
(2016), http://dx.doi.org/10
longer residence times for soils (Sweeney et al., 2012), reduced
erosionrates (Hurst et al., 2012), and is consistent with the
effect of knickpointsformed by resistant rock layers in the study
by Marshall and Roering(2014).
Exponents for the power-function relation of drainage area
andvalley floor width ranged from 0.57 for Harvey Creek to 0.62
aboveKentucky Falls, which are both within the range reported by
Snyderet al. (2000) of 0.50–0.67but notably higher than the value
of 0.4 reportedby Snyder et al. (2003). Surprisingly, no scaling
breakwas observed in thewidth-area relation for the North Fork
Smith River above Kentucky Falls.A previous study by Snyder et al.
(2003) and our research inHarvey Creekdocumented a scaling break at
a drainage area of 0.1 km2 (May et al.,2013), below which no
corresponding decrease in valley width withdrainage areawas
observed. This constant width is likely the signal of de-bris flows
carving valleys of small drainage areas, with downstream areasbeing
carved by fluvial incision (Montgomery and Foufoula-Georgiou,1993;
Stock and Dietrich, 2003). The lack of a robust scaling breakabove
Kentucky Falls suggests that some headwater channels may betoo
broad and low gradient to transport debris flows.
Broad valley floors are a critical driver of fish habitat
because theyallow for floodplain development (e.g., Naiman et al.,
2010), increasedcarbon storage (Wohl et al., 2012), enhanced
hyporheic exchange(e.g., Baxter and Hauer, 2000), and provide
off-channel habitats duringfloods that increase juvenile salmonid
survival (e.g., Solazzi et al., 2000;Bell et al., 2001). A previous
study by Belmont (2011) observed a similarpattern of relatively
wide and mostly unconfined floodplains above asteep incising
knickpoint. Broad valley floors also intercept debris flows
ve Kentucky Falls on the N.F. Smith River. Low values of q/T
(highly negative, warm colors)ors) reflect lowpropensity for
failure.Darkblue pixels reflect terrain that is unconditionallya
persistent soil mantle).
points disconnect hillslope and channel processes, isolating
salmonid.1016/j.geomorph.2016.03.029
http://dx.doi.org/10.1016/j.geomorph.2016.03.029
-
Fig. 6. The distribution of IP values from habitat suitability
curves developedwhere coastalcutthroat trout are in competition
with coho salmon and habitat utilization is maximizedin reaches
with 4–10% gradient (A), and the distribution of IP values from
habitatsuitability curves where cutthroat are expected to use lower
gradient channels (allreaches b8%) in the absence of competition
(B).
6 C. May et al. / Geomorphology xxx (2016) xxx–xxx
and thus dampen episodic inputs of sediment (May andGresswell,
2004),rendering fish populations more resilient to disturbance.
3.2. Channel slope
Reach-scale channel slopewas lower for a given drainage area in
theabove-barrier catchment (Fig. 3). Regression analysis revealed a
differ-ence in the slope-area relation between basins, where the
intercept(p b 0.001) and slope (p b 0.001) of the regression was
lower in theabove-waterfall basin compared to the ambient
landscape. Becausethe regression lines converged at larger drainage
areas, the effect sizedecreased with drainage area and ranged from
57 to 18% reduction inslope with increasing drainage area (Table
2). With lower channelslopes extending farther up into the drainage
network, the potentialfor pool-riffle morphologies was greatly
expanded. Pool-riffle morphol-ogies typically occur in reaches ≤2%
slope (Montgomery and Buffington,1997;Wohl andMerritt, 2005), which
extend as high up in the networkas 1.8 km2 inNorth Fork Smith River
above Kentucky Falls,whereas theyare limited to drainage areas N4.0
km2 in Harvey Creek.
3.3. Hillslope angles and shallow landslide potential
While some subcatchments above Kentucky Falls are as steep
asthose observed in Harvey Creek many are systematically gentler
im-plying decreased rates of sediment production through soil
creepprocesses and shallow soil slips. The mean hillslope gradient
forHarvey Creek is 0.74±0.20, whereas the mean value above
KentuckyFalls is 0.53±0.25 (Fig. 4). The coupled hydrology-slope
stability modelresults demonstrate that a substantial fraction of
the basin upstream ofKentucky Falls is unconditionally stable
(slopes b 0.38) in contrast toHarvey Creek where only the valley
floor and debris fan deposits exhibitsuch low slope angles (Fig.
5). The origin of the numerous and contiguousgentle hillsides in
the basin above Kentucky Falls is unclear, although itmay result
from decreased steepness owing to reduced base-level lower-ing. The
proportion of unconditionally unstable slopes (slope N 1.0) ismuch
higher in Harvey Creek than above Kentucky Falls, where steepslopes
are scattered throughout the catchment. The q/T values
aresystematically lower in Harvey Creek than above Kentucky Falls
aswell, suggesting that the frequency of shallow landsliding and
de-bris flows may be higher in Harvey given that lower values of
effectiveprecipitation are required for failure. Taken together,
the topographic dif-ferences between Harvey Creek and the
hillslopes above Kentucky Fallsare profound despite their
proximity, implying a substantial knickpointcontrol on the rate and
pattern of sediment production in the basinabove Kentucky
Falls.
3.4. Habitat quality and quantity
Because broad valleys and low-gradient channels extend higher
inthe network in the above-waterfall basin, a greater proportion of
thenetwork exhibits high IP values compared to the reference
landscapeof Harvey Creek (Fig. 6). This finding is consistent with
the original IPvalues developed for coastal cutthroat trout where
habitat use wasmaximized in channels with 4–8% gradient because of
competitiveexclusion (p-value b 0.01; Fig. 6A), and the revised IP
value for coastalcutthroat trout residing in the absence of
competition (habitat utiliza-tion maximized in all reaches b8%)
provided similar results (p b 0.01;Fig. 6B). Correspondingly, we
observed an increase in habitat quantity,with 59% of the total
channel length above Kentucky Falls occurring inreaches that were
less than the slope-induced limit for cutthroat trout(b10% slope);
whereas Harvey Creek had only 27% of the network pro-viding habitat
(Fig. 7). This is a direct result of the less steep river
profileaboveKentucky Falls (Fig. 8). However, the areawhere there
is potentialfor direct overlap between debris flows and fish
habitat (S = 3–10%:May and Lisle, 2012) is greater in the
above-barrier stream network(Table 3).
Please cite this article as: May, C., et al., The waterfall
paradox: How knickpopulations in ideal habita..., Geomorphology
(2016), http://dx.doi.org/10
The resulting effect of the differences in river profiles is an
increasein potential habitat of 2.3 times in the above-barrier
basin, with morelongitudinally and latitudinally connected habitat.
This high connectiv-ity of habitat and consistently lower gradient
reaches in the above-barrier network can increase gene flow and
reduce genetic differen-tiation (Wofford et al., 2005; Guy et al.,
2008; Kanno et al., 2011).Greater expansion of the fish-bearing
channel network also createsan opportunity for a broader spatial
distribution of fish, thus reduc-ing competition for limited
resources and enhancing the opportuni-ty for the spatial spreading
of risk. Previous studies have also foundthat isolated populations
occurring in larger stream networkshave retained substantial
genetic variation, which suggests thatthe amount of habitat in
headwater streams is an important consid-eration for maintaining
the evolutionary potential of isolated popu-lations (Whiteley et
al., 2010).
4. Conclusions
Ecogeomorphology is emerging as an interdisciplinary field that
ex-plores the concept of connectivity and places particular
importance ondescribing the structural and functional linkages
between the flow ofwater, landforms, and the dispersal of organisms
(e.g., With and Crist,1995; Pringle, 2003; Wainwright et al.,
2011). The opposing conceptof disconnectivity in landscape
processes is also being recognized asplaying some important
functional roles in riverine systems (e.g., Laneet al., 2004;
Jackson and Pringle, 2010). One of the drivers on land-scape
connectivity is the geomorphic response of hillslopes andchannels
to base-level lowering (e.g., Faulkner, 2008). By exploringhow
knickpoints disconnect small watersheds from base-level
lowering,and thereby the surrounding landscape, we can reveal
previously unrec-ognized patterns. This is particularly insightful
when investigating head-water streams, which compose a large
portion of the total channelnetwork length and directly connect the
upland and riparian landscapeto the rest of the stream ecosystem
(Freeman et al., 2007).
points disconnect hillslope and channel processes, isolating
salmonid.1016/j.geomorph.2016.03.029
http://dx.doi.org/10.1016/j.geomorph.2016.03.029
-
Fig. 7. The spatial distribution and quantity of habitat in the
above-barrier catchment (Kentucky Falls) and the ambient landscape
(Harvey Creek).
7C. May et al. / Geomorphology xxx (2016) xxx–xxx
Results of our study explicitly linked the unique geomorphic
settingof headwater streams in above-knickpoint basins with the
unanticipat-ed ecological outcome of barrier-isolated populations
inhabiting themost resilient and ideal habitat in mountainous
landscapes. Althoughthe geomorphic setting is unique, it is not an
isolated incidence asknickpoints are common features in otherwise
steady state landscapes.Specifically, this study posed a
fundamental question about landscapeconnectivity and the role of
knickpoints in channel development,while also addressing a pressing
conservation question in aquatic ecol-ogy about disconnected fish
populations. We hypothesize that limited
Fig. 8. Longitudinal profiles for the mainstem of the North Fork
Smith River aboveKentucky Falls (which corresponds with the steep
reach at ~12,500 m) and themainstem of Harvey Creek.
Please cite this article as: May, C., et al., The waterfall
paradox: How knickpopulations in ideal habita..., Geomorphology
(2016), http://dx.doi.org/10
incision imposed by a relatively stationary knickpoint has led
to lateralexpansion of the valley and less steep river profile that
provides for agreater expansion of low-gradient stream reaches
throughout the fluvi-al network and reduced sediment flux owing to
lower gradienthillslopes. From an ecological perspective, the
novelty of our findingsis quantifying the geomorphic controls on
the habitat template thatleads to the long-term persistence of
small disconnected populations,whereas the majority of past studies
have focused on factors leadingto extirpation. Future studies are
needed to test the generality ofthese results as the availability
of LiDAR-derived topography becomesmore spatially extensive and
provides the opportunity for replication.Our current paired
watershed approach is limited, but our novel hy-pothesis warrants
testing. Qualitative examination of other small wa-tersheds
situated above knickpoints in western Oregon revealssimilar
topographic characteristics. Because our analysis derivesfrom a
process-based perspective on how channel incision regulatesvalley
morphology, hillslope form, and sediment production; ourapproach
should have application in other mountainous settings.
Table 3Proportion of the channel network in low gradient fish
habitat (b3%), habitats wheredebrisflows andfish habitat directly
overlap (3–10%), and nonfish bearing stream reachesin the debris
flow process domain (N10%).
Stream gradient Harvey Cr. Kentucky Falls
b3% 0.08 0.273–10% 0.18 0.32N10% 0.73 0.41
points disconnect hillslope and channel processes, isolating
salmonid.1016/j.geomorph.2016.03.029
http://dx.doi.org/10.1016/j.geomorph.2016.03.029
-
8 C. May et al. / Geomorphology xxx (2016) xxx–xxx
The combination of broader than anticipated valley floors and
thegreater extent of low gradient stream reaches interact to
develop agreater abundance of high quality fish habitat in
above-barrier catch-ments. Our results indicate that the effect of
knickpoints on valley widthincreases with drainage area, with a
near doubling of valley width at adrainage area of 101 km2.
Concomitantly, the effect of knickpoints onchannel slope decreases
with drainage area, resulting in low gradientstream reaches with
favorable fish habitat extending further up in thechannel network.
In addition to differences in physical habitat that can in-crease
fish production, these disconnected above-barrier catchments
arealso protected from invasion by nonnative fish,
hybridizationwith hatch-ery fish, and spread of disease (Rahel,
2013). These populations also havereduced competition from other
species (Ross, 1991), which can increaseproductivity.
Channel networks above barriers experience relatively
constantbase-level, and thus, hillslope and channel processes that
are drivenby incision are effectively disconnected. These
disconnected hillslopeshave less potential for debris flows
(Penserini, 2015), longer residencetimes for soils (Sweeney et al.,
2012), and more rounded hillslopeswith reduced erosion rates (Hurst
et al., 2012). With less potential forepisodic disturbance, fish
populations may undergo fewer populationbottlenecks andmaymaintain
consistently more abundant populationsthan their downstream
counterparts. A primary focus in conservationgenetics is to
understand factors that influence small populations, andas the rate
of population fragmentation and isolation increases, it be-comes
increasingly important to examine factors that influence
themaintenance of genetic diversity and therefore the likelihood of
persis-tence (e.g., Letcher et al., 2007; Whiteley et al., 2010;
Toterotot et al.,2014). From this topographically based analysis of
fish habitat we hy-pothesize that above-barrier fish populations
reside inmore temporallystable and productive habitat and that
populations will be consistentlylarger and more stable through
time. Future research can use populationgenetics to test this
hypothesis, with the prediction that above-barrierpopulations have
fewer population bottlenecks and larger effective popu-lation size.
In contrast, populations isolated by anthropogenic factors,such as
dams and culverts, may be at greatest risk of extirpation
becausethe co-evolved geomorphic template for habitat formation and
reduceddisturbance is not present.
Acknowledgements
The authors would like to thank NCALM (National Center
forAirborne Laser Mapping) and the Oregon LiDAR Consortium
(operatedby the Oregon Department of Geology and Mineral
Industries) for pro-viding topographic data. We also wish to thank
the CLAMS project andBrett Holycross with Pacific States Marine
Fisheries Commission forsharing stream layers and IP parameters.
Statistician Lihua Chen gener-ously assisted on the analyses. We
thank the Binghamton symposiumorganizers for the opportunity to
present this study. We are grateful totwo anonymous reviewers and
Frank Magilligan, who provided thor-ough reviews that improved the
manuscript. Any use of trade, firm, orproduct names is for
descriptive purposes only and does not imply en-dorsement by the
U.S. Government.
References
Agrawal, A., Schick, R.S., Bjorkstedt, E.P., Szerlong, R.G.,
Goslin, M.N., Spence, B.C.,Williams, T.H., Burnett, K.M., 2005.
Predicting the potential for historical coho,Chinook and steelhead
habitat in Northern California. NOAA Technical
MemorandumNOAA-TM-NMFS-SWFSC-379, Santa Cruz, Calif.
Baxter, C.V., Hauer, R.F., 2000. Geomorphology, hyporheic
exchange, and selection ofspawning habitat by bull trout
(Salvelinus confluentus). Can. J. Fish. Aquat. Sci. 57(7),
1470–1481.
Bell, E., Duffy, W.G., Roelofs, T.D., 2001. Fidelity and
survival of juvenile coho salmon in re-sponse to a flood. Trans.
Am. Fish. Soc. 130 (3), 450–458.
Belmont, P., 2011. Floodplain width adjustments in response to
rapid base level fall andknickpoint migration. Geomorphology 128,
92–102. http://dx.doi.org/10.1016/j.geomorph.2010.12.026.
Please cite this article as: May, C., et al., The waterfall
paradox: How knickpopulations in ideal habita..., Geomorphology
(2016), http://dx.doi.org/10
Benda, L., Dunne, T., 1997. Stochastic forcing of sediment
supply to channel networksfrom landsliding and debris flow. Water
Resour. Res. 33 (12), 2849–2863.
Burnett, K.M., Reeves, G.H., Miller, D.J., Clarke, S.,
Vance-Borland, K., Christiansen, K., 2007.Distribution of
salmon-habitat potential relative to landscape characteristics and
im-plications for conservation. Ecol. Appl. 17, 66–80.
http://dx.doi.org/10.1890/1051-0761(2007)017[0066:DOSPRT]2.0.CO;2.
Clarke, S.E., Burnett, K.M., Miller, D.J., 2008.Modeling streams
and hydrogeomorphic attri-butes in Oregon from digital and field
data. J. Am. Water Resour. Assoc. 44 (2),459–477.
http://dx.doi.org/10.1111/j.1752-1688.2008.00175.x.
Crosby, B.T., Whipple, K.X., 2006. Knickpoint initiation and
distribution within fluvial net-works: 236waterfalls in theWaipaoa
River, North Island, New Zealand. Geomorphol-ogy 82 (1), 16–38.
Faulkner, H., 2008. Connectivity as a crucial determinant of
badlandmorphology and evo-lution. Geomorphology 100, 91–103.
Fausch, K.D., Torgerson, C.E., Baxter, C.V., Li, H.W., 2002.
Landscapes to riverscapes: bridg-ing the gap between research and
conservation of stream fishes. Bioscience 52 (6),483–498.
http://dx.doi.org/10.1641/0006-3568.
Flint, J.J., 1974. Stream gradient as a function of order,
magnitude, and discharge. WaterResour. Res. 10 (5), 969–973.
Freeman, M.C., Pringle, C.M., Jackson, C.R., 2007. Hydrological
connectivity and the contri-bution of stream headwaters to
ecological integrity at regional scales. J. Am. WaterResour. Assoc.
43 (1), 5–14.
Frissell, C.A., Liss, W.J., Warren, C.E., Hurley, M.D., 1986. A
hierarchical framework forstream habitat classification: viewing
streams in a watershed context. Environ.Manag. 10, 199–214.
Glova, G.J., 1987. Comparison of allopatric cutthroat trout
stocks with those sympatricwith coho salmon and sculpins in small
streams. Environ. Biol. Fish 20 (4), 275–284.
Gresswell, R.E., 1999. Fire and aquatic ecosystems in forested
biomes of North America.Trans. Am. Fish. Soc. 128 (2), 193–221.
Gresswell, R.E., Bateman, D.S., Lienkamper, G.W., Guy, T.J.,
2004. Geospatial TechniquesFor Developing A Sampling Frame Of
Watersheds Across A Region. In: Nishida, T.,Kailola, P.J.,
Hollingworth, C.E. (Eds.), GIS/Spatial Analyses In Fishery And
Aquatic Sci-ences vol. 2. Fishery-Aquatic GIS Research Group,
Saitama, Japan, pp. 517–530.
Gresswell, R.E., Torgersen, C.E., Bateman, D.S., Guy, T.J.,
Hendricks, S.R., Wofford, J.E.B.,2006. A spatially explicit
approach for evaluating relationships among coastal cut-throat
trout, habitat, and disturbance in small Oregon streams. Am. Fish.
Soc. Symp.48, 457–471.
Griswold, K., Reeves, G., 2014. Coastal Cutthroat Trout
Assessment, Final Report to Nation-al Fish and Wildlife Foundation
(NFWF grant #2010-0055-022).
Guy, T.J., Gresswell, R.E., Banks, M.A., 2008. Landscape-scale
evaluation of genetic struc-ture among barrier-isolated populations
of coastal cutthroat trout (Oncorhynchusclarkii clarkii). Can. J.
Fish. Aquat. Sci. 65 (8), 1749–1762.
http://dx.doi.org/10.1139/F08-090.
Hack, J.T., 1957. Studies of longitudinal stream profiles in
Virginia andMaryland. U.S. Geo-logical Survey Professional Paper
294-B.
Hack, J.T., 1973. Streamprofile analysis and stream-gradient
index. U.S. Geol. Surv. J. Res. 1(4), 421–429.
Heimsath, A.M., Dietrich, W.E., Nishiizumi, K., Finkel, R.C.,
2001. Stochastic processes ofsoil production and transport: erosion
rates, topographic variation and cosmogenicnuclides in the Oregon
Coast Range. Earth Surf. Process. Landf. 26 (5), 531–552.
Howard, A.D., Kerby, G., 1983. Channel changes in badlands.
Geol. Soc. Am. Bull. 94,739–752.
Hurst, M.D., Mudd, S.M., Walcott, R., Attal, M., Yoo, K., 2012.
Using hilltop curvature to de-rive the spatial distribution of
erosion rates. J. Geophys. Res. Earth Surf. 117,2003–2012.
http://dx.doi.org/10.1029/2011JF002057.
Jackson, C.R., Pringle, C.M., 2010. Ecological benefits of
reduced hydrologic connectivity inintensively developed landscapes.
Bioscience 60 (1), 37–46.
Jackson, M., Roering, J.J., 2009. Post-fire geomorphic response
in steep, forested land-scapes: Oregon Coast Range, USA. Quat. Sci.
Rev. 28 (11), 1131–1146.
http://dx.doi.org/10.1016/j.quascirev.2008.05.003.
Kanno, Y., Vokoun, J.C., Letcher, B.H., 2011. Fine-scale
population structure and riverscapegenetics of brook trout
(Salvelinus fontinalis) distributed continuously along
headwaterchannel networks. Mol. Ecol. 20 (18), 3711–3729.
Kobor, J.S., Roering, J.J., 2004. Systematic variation of
bedrock channel gradients in thecentral Oregon Coast Range:
implications for rock uplift and shallow landsliding.Geomorphology
62 (3), 239–256.
Kruse, C.G., Hubert, W.A., Rahel, F.J., 1997. Geomorphic
influences on the distribution ofYellowstone Cutthroat Trout in the
Absaroka Mountains, Wyoming. Trans. Am. Fish.Soc. 126, 418–427.
Kruse, C.G., Hubert, W.A., Rahel, F.J., 2001. An assessment of
headwater isolation as aconservation strategy for cutthroat trout
in the Absaroka Mountains of Wyoming.Northwest Sci. 75, 1–11.
Lamberti, G.A., Gregory, S.V., Ashkenas, L.R., Wildman, R.C.,
Moore, K., 1991. Streamecosystem recovery following a catastrophic
debris flow. Can. J. Fish. Aquat. Sci. 48,196–208.
Lande, R., 1988. Genetics and demography in biological
conservation. Science 241,1455–1460.
Lane, S.N., Brookes, C.J., Kirkby, A.J., Holden, J., 2004. A
network-index based version ofTOPMODEL for use with high-resolution
digital topographic data. Hydrol. Process.18 (1), 191–201.
Letcher, B.H., Nislow, K.H., Coombs, J.A., O'Donnell, M.J.,
Dubreuil, T.L., 2007. Populationsresponse to habitat fragmentation
in a stream-dwelling brook trout population.PLoS One 2 (11), e1139.
http://dx.doi.org/10.1371/journal.pone.0001139.
Marshall, J.A., Roering, J.J., 2014. Diagenetic variation in the
Oregon Coast Range: implica-tions for rock strength, soil
production, hillslope form, and landscape evolution.J. Geophys.
Res. Earth Surf. 119, 1395–1417.
http://dx.doi.org/10.1002/2013JF003004.
points disconnect hillslope and channel processes, isolating
salmonid.1016/j.geomorph.2016.03.029
http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0005http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0005http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0005http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0010http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0010http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0010http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0015http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0015http://dx.doi.org/10.1016/j.geomorph.2010.12.026http://dx.doi.org/10.1016/j.geomorph.2010.12.026http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0025http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0025http://dx.doi.org/10.1890/1051-0761(2007)017[0066:DOSPRT]2.0.CO;2http://dx.doi.org/10.1890/1051-0761(2007)017[0066:DOSPRT]2.0.CO;2http://dx.doi.org/10.1111/j.1752-1688.2008.00175.xhttp://refhub.elsevier.com/S0169-555X(16)30124-6/rf0040http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0040http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0040http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0045http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0045http://dx.doi.org/10.1641/0006-3568http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0055http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0055http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0060http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0060http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0060http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0065http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0065http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0065http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0070http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0070http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0075http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0075http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0080http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0080http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0080http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0080http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0085http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0085http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0085http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0090http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0090http://dx.doi.org/10.1139/F08-090http://dx.doi.org/10.1139/F08-090http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0100http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0100http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0105http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0105http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0110http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0110http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0110http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0115http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0115http://dx.doi.org/10.1029/2011JF002057http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0125http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0125http://dx.doi.org/10.1016/j.quascirev.2008.05.003http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0135http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0135http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0135http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0140http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0140http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0140http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0145http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0145http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0145http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0150http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0150http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0150http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0155http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0155http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0155http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0160http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0160http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0165http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0165http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0165http://dx.doi.org/10.1371/journal.pone.0001139http://dx.doi.org/10.1002/2013JF003004http://dx.doi.org/10.1016/j.geomorph.2016.03.029
-
9C. May et al. / Geomorphology xxx (2016) xxx–xxx
May, C.L., Gresswell, R.E., 2004. Spatial and temporal patterns
of debris-flow deposition inthe Oregon Coast Range, USA.
Geomorphology 57, 135–149.
May, C.L., Lisle, T.E., 2012. River profile controls on channel
morphology, debris flow dis-turbance, and the spatial extent of
salmonids in steep mountain streams. J. Geophys.Res. 117, F00A03.
http://dx.doi.org/10.1029/2011JF002324.
May, C.L., Roering, J., Eaton, L.S., Burnett, K.M., 2013.
Controls on valleywidth inmountainouslandscapes: the role of
landsliding and implications for salmonid habitat. Geology 41(4),
503–506. http://dx.doi.org/10.1130/G33979.1.
Montgomery, D.R., 2000. Coevolution of the Pacific salmon and
Pacific Rim topography.Geology 28, 1107–1110.
http://dx.doi.org/10.1130/0091-7613(2000)28b1107:COTPSAN2.0.CO;2.
Montgomery, D.R., 2001. Slope distributions, threshold
hillslopes, and steady-state topog-raphy. Am. J. Sci. 301 (4-5),
432–454.
Montgomery, D.R., Buffington, J.M., 1997. Channel-reach
morphology in mountain drain-age basins. Geol. Soc. Am. Bull. 109
(5), 596–611.
Montgomery, D.R., Dietrich, W.E., 1994. A physically based model
for the topographiccontrol. Water Resour. Res. 30 (4),
1153–1171.
Montgomery, D.R., Foufoula-Georgiou, E., 1993. Channel network
source representationusing digital elevation models. Water Resour.
Res. 29, 3925–3934. http://dx.doi.org/10.1029/93WR02463.
Naiman, R.J., Bechtold, J.S., Beechie, T.J., Latterell, J.J.,
Pelt, R.V., 2010. A process-based viewof floodplain forest patterns
in coastal river valleys of the Pacific Northwest. Ecosys-tems 13,
1–31. http://dx.doi.org/10.1007/s10021-009-9298-5.
Northcote, T.G., 1997. Potamodromy in Salmonidae – living and
moving in the fast lane.N. Am. J. Fish Manag. 17, 1029–1045.
Ouimet,W.B.,Whipple, K.X., Granger, D.E., 2009. Beyond threshold
hillslopes: channel ad-justment to base-level fall in tectonically
active mountain ranges. Geology 37 (7),579–582.
Oxford, J., 2006. Early Oligocene Intrusions In The Central
Coast Range of Oregon M.S.thesis Oregon State University (237
pp.).
Penserini, B., 2015. Debris Flow Networks And The Role Of
Baselevel In Steep HeadlandLandscapes M.S. thesis University of
Oregon (89 pp.).
Perron, J.T., Dietrich, W.E., Kirchner, J.W., 2008. Controls on
the spacing of first-ordervalleys. J. Geophys. Res. Earth Surf.
http://dx.doi.org/10.1029/2007JF000977.
Pringle, C., 2003. What is hydrologic connectivity and why is it
ecologically important?Hydrol. Process. 17 (13), 2685–2689.
Purvis, A., Gittleman, J.L., Cowlishaw, G., Mace, G.M., 2000.
Predicting extinction risk in de-clining species. Proc. R. Soc.
Biol. Sci. 267, 1947–1952.
http://dx.doi.org/10.1098/rspb.2000.1234.
Rahel, F.J., 2013. Intentional fragmentation as a management
strategy in aquatic systems.Bioscience 63 (5), 362–372.
http://dx.doi.org/10.1525/bio.2013.63.5.9.
Reeves, G.H., Benda, L.E., Burnett, K.M., Bisson, P.A., Sedell,
J.R., 1995. A disturbance-basedecosystem approach to maintaining
and restoring freshwater habitats of evolution-arily significant
units of anadromous salmonids in the Pacific Northwest. Am.
Fish.Soc. Symp. 17, 334–349.
Reneau, S.L., Dietrich, W.E., 1991. Erosion rates in the
southern Oregon Coast Range:evidence for an equilibrium between
hillslope erosion and sediment yield. EarthSurf. Process. Landf. 16
(4), 307–322.
Roering, J.J., Kirchner, J.W., Dietrich, W.E., 1999. Evidence
for nonlinear diffusive sedimenttransport on hillslopes and
implications for landscape morphology. Water Resour.Res. 35 (3),
853–870.
Roghair, C.N., Dollof, C.A., Underwood, M.K., 2002. Response of
a brook trout populationand instream habitat to a catastrophic
flood and debris flow. Trans. Am. Fish. Soc.131, 718–730.
Please cite this article as: May, C., et al., The waterfall
paradox: How knickpopulations in ideal habita..., Geomorphology
(2016), http://dx.doi.org/10
Ross, S.T., 1991. Mechanisms structuring stream fish
assemblages: are there lessons fromintroduced species? Environ.
Biol. Fish 30 (4), 359–368.
Sabo, J.L., Pauley, G.B., 1997. Competition between
stream-dwelling cutthroat trout(Oncorhynchus clarki) and coho
salmon (Oncorhynchus kisutch): effects of relativesize and
population origin. Can. J. Fish. Aquat. Sci. 54, 2609–2617.
Schlosser, I.J., 1991. Stream fish ecology: a landscape
perspective. Bioscience 41, 704–712.Seidl, M.A., Dietrich, W.E.,
1992. The problem of channel erosion into bedrock. Catena
Suppl. 23, 101–124.Snyder, N.P., Whipple, K.X., Tucker, G.E.,
Merritts, D.J., 2000. Landscape response to
tectonic forcing: DEM analysis of stream profiles in the
Mendocino triple junction re-gion, northern California. Geol. Soc.
Am. Bull. 112 (8), 1250–1263.
Snyder, N.P., Whipple, K.X., Tucker, G.E., Merritts, D.J., 2003.
Channel response to tectonicforcing: field analysis of stream
morphology and hydrology in the Mendocino triplejunction region,
northern California. Geomorphology 53, 97–127.
Solazzi, M.F., Nickelson, T.E., Johnson, S.L., Rodgers, J.D.,
2000. Effects of increasing winterrearing habitat on abundance of
salmonids in two coastal Oregon streams. Can. J. Fish.Aquat. Sci.
57, 906–914.
Stock, J., Dietrich, W.E., 2003. Valley incision by debris
flows: evidence of a topographic sig-nature. Water Resour. Res. 39
(4), 1089. http://dx.doi.org/10.1029/2001WR001057.
Stock, J., Dietrich, W.E., 2006. Erosion of steepland valleys by
debris flows. Geol. Soc. Am.Bull. 118 (9), 1125–1148.
Sweeney, K.E., Roering, J.J., Almond, P., Reckling, T., 2012.
How steady are ‘steady-state’landscapes? Using soil spectroscopy to
quantify erosional variability. Geology 40,807–810.
http://dx.doi.org/10.1130/G33167.1.
Toterotot, J.B., Perrier, C., Bergeron, N.E., Bernatchez, L.,
2014. Influence of forest road cul-verts and waterfalls on the
fine-scale distribution of Brook Trout genetic diversity in aboreal
watershed. Trans. Am. Fish. Soc. 143 (6), 1577–1591.
Turner, M.G., Dale, V.H., 1998. Comparing large, infrequent
disturbances: what have welearned? Ecosystems 1, 493–496.
Wainwright, J., Turnbull, L., Ibrahim, T.G., Lexartza-Artza, I.,
Thornton, S.F., Brazier, R.E.,2011. Linking environmental regimes,
space and time: interpretations of structuraland functional
connectivity. Geomorphology 126 (3), 387–404.
Waples, R.S., Pess, G.R., Beechie, T., 2008. Evolutionary
history of Pacific salmon in dynam-ic environments. Evol. Appl. 1,
189–206. http://dx.doi.org/10.1111/j.1752-4571.2008.00023.x.
White, P.S., Pickett, S.T.A., 1985. Natural Disturbance And
Patch Dynamics: An Introduc-tion. In: Pickett, S.T.A., White, P.S.
(Eds.), The Ecology of Natural Disturbance andPatch Dynamics.
Academic, New York, pp. 3–13.
Whiteley, A.R., Hastings, K., Wenburg, J.K., Frissell, C.A.,
Martin, J.C., Allendorf, F.W., 2010.Genetic variation and effective
population size in isolated populations of coastal cut-throat
trout. Conserv. Genet. 11, 1929–1943.
With, K.A., Crist, T.O., 1995. Critical thresholds in species'
responses to landscape struc-ture. Ecology 76, 2446–2459.
Wofford, J.E.B., Gresswell, R.E., Banks, M.A., 2005. Influence
of barriers to movementon within-watershed genetic variation of
coastal cutthroat trout. Ecol. Appl. 15,628–637.
Wohl, E., Merritt, D., 2005. Prediction of mountain stream
morphology. Water Resour.Res. 41, W08419.
http://dx.doi.org/10.1029/2004WR003779.
Wohl, E., Dwire, K., Sutfin, N., Polvi, L., Bazan, R., 2012.
Mechanisms of carbon storage inmountainous headwater rivers. Nat.
Commun. 3, 1263.
Wood, J., 1996. The Geomorphological Characterization Of Digital
Elevation Models Ph.D.dissertation University of Leicester,
Leicester, UK.
points disconnect hillslope and channel processes, isolating
salmonid.1016/j.geomorph.2016.03.029
http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0180http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0180http://dx.doi.org/10.1029/2011JF002324http://dx.doi.org/10.1130/G33979.1http://dx.doi.org/10.1130/0091-7613(2000)282.0.CO;2http://dx.doi.org/10.1130/0091-7613(2000)282.0.CO;2http://dx.doi.org/10.1130/0091-7613(2000)282.0.CO;2http://dx.doi.org/10.1130/0091-7613(2000)282.0.CO;2http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0200http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0200http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0205http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0205http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0210http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0210http://dx.doi.org/10.1029/93WR02463http://dx.doi.org/10.1007/s10021-009-9298-5http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0225http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0225http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0230http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0230http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0230http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0235http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0235http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0240http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0240http://dx.doi.org/10.1029/2007JF000977http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0250http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0250http://dx.doi.org/10.1098/rspb.2000.1234http://dx.doi.org/10.1098/rspb.2000.1234http://dx.doi.org/10.1525/bio.2013.63.5.9http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0265http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0265http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0265http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0265http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0270http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0270http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0270http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0280http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0280http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0280http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0285http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0285http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0285http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0290http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0290http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0295http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0295http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0295http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0300http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0305http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0305http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0310http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0310http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0310http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0315http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0315http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0315http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0320http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0320http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0320http://dx.doi.org/10.1029/2001WR001057http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0330http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0330http://dx.doi.org/10.1130/G33167.1http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0340http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0340http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0340http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0345http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0345http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0350http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0350http://dx.doi.org/10.1111/j.1752-4571.2008.00023.xhttp://dx.doi.org/10.1111/j.1752-4571.2008.00023.xhttp://refhub.elsevier.com/S0169-555X(16)30124-6/rf0360http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0360http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0360http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0365http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0365http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0370http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0370http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0375http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0375http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0375http://dx.doi.org/10.1029/2004WR003779http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0385http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0385http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0390http://refhub.elsevier.com/S0169-555X(16)30124-6/rf0390http://dx.doi.org/10.1016/j.geomorph.2016.03.029
The waterfall paradox: How knickpoints disconnect hillslope and
channel processes, isolating salmonid populations in ideal ...1.
Introduction2. Methods2.1. Measuring valley width2.2. Slope-area
relation2.3. Hillslope angles and shallow landslide potential2.4.
Fish habitat modeling
3. Results and discussion3.1. Valley width3.2. Channel slope3.3.
Hillslope angles and shallow landslide potential3.4. Habitat
quality and quantity
4. ConclusionsAcknowledgementsReferences