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Movements of a macroinvertebrate (Potamophylax latipennis)
across a gravel-bed substrate: effects of local hydraulics and
micro-topography under increasing discharge
Stephen P. Rice a, Thomas Buffin-Bélanger, b, Jill Lancaster c and Ian Reida
a
Department of Geography, Loughborough University, Leicestershire LE11 3TU, United
Kingdom.
b
Module de géographie, Département de biologie, chimie et géographie, Université du
Québec à Rimouski, 300 allée des Ursulines, Rimouski (QC), G5L 3A1, Canada.
c
Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh,
Ashworth Labs, West Mains Road, Edinburgh EH9 3JT, Scotland.
Gravel Bed Rivers 6, Austria, 2005
Total words (including title, abstract, body, captions, tables & references): 9200
Main text (abstract and body): 6945
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Abstract
Flow refugia provide a mechanism that can explain the persistence of macroinvertebrate
communities
in
flood-prone,
gravel-bed
rivers.
The
movement
behaviour
of
macroinvertebrates is a key element of the flow refugia hypothesis, but surprisingly little is
known about it. In particular, little is known about how local near-bed hydraulics and bed
microtopography affect macroinvertebrate movements. We used a novel casting technique to
reproduce a natural gravel-bed substrate in a large flume where we were able to observe the
movement behaviour of the cased caddisfly, Potamophylax latipennis at different discharges.
The crawling paths and drift events of animals were analysed from video recordings and used
to classify sites on the substrate according to the type of insect movement. We used acoustic
Doppler velocimeter (ADV) measurements close to the boundary to characterise hydraulic
conditions at different sites and a detailed Digital Elevation Model (DEM) to characterise
sites topographically. Animals made shorter more disjointed crawling journeys as discharge
increased, although they tended to follow consistent paths across the substrate. As
hypothesised, crawling behaviour was locally associated with low elevations, low flow
velocities and low turbulent kinetic energies, while sites that insects avoided were
characterised by higher elevations, velocities and turbulence. Discrimination was greater at
higher discharges, indicating that movement behaviour is contingent upon flow conditions.
We suppose that these relations reflect the need of animals to reduce the risk of entrainment
and minimise energy expenditure by avoiding areas of high fluid drag. As discharge
increased, there was a general upward shift in the frequency distributions of local velocities
and turbulent kinetic energies. The animals responded to these shifts and it is clear that their
different activities were not limited to fixed ranges of velocity and turbulence. We assume
that the absolute hydraulic forces would become a limiting factor at some higher discharge.
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At the discharges examined here, which are below those required to instigate framework
particle entrainment, patterns of animal movement appear to be associated with the animals’
experiences of relative rather than absolute hydraulic forces.
Key words:
benthic macroinvertebrate movement, near-bed hydraulics, flow refugia, gravel substrate,
drift, caddisfly
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1. Introduction
How do populations of stream invertebrates persist in gravel-bed rivers subject to
hydrological disturbances (floods) where hydraulic forces and associated bed material
movement can result in mortality and/or loss of individuals? This is a problem of enduring
interest to stream ecologists and an area for fruitful collaboration between ecologists and
geomorphologists. Understanding this problem involves three linked ideas.
(1) In gravel-bed rivers, near-bed hydraulics are conditioned by the complex 3-D microtopography of the bed materials and are therefore spatially heterogeneous. This
heterogeneity persists at the highest flows and some low-stress areas are present even
at high discharges. Spatially distributed flow measurements above gravel beds are
rare (Lamarre and Roy, 2005) and the degree to which spatial heterogeneity is
maintained as discharge varies has not been widely studied or quantified.
Nevertheless, the persistence of low-stress areas across a range of discharges has been
demonstrated, both at fixed locations (Lancaster and Hildrew, 1993a) and at shifting
locations in association with changing stage (Rempel et al., 1999).
(2) The distribution of benthic invertebrates across the stream bed is also spatially and
temporally heterogeneous and this patchiness is associated with the heterogeneity in
near-bed hydraulics. Several studies have shown that during high flows, animal
densities are higher in areas of low shear stress and low velocity (Lancaster and
Hildrew, 1993b; Palmer et al., 1996; Rempel et al., 1999). Additional abiotic and
biotic factors (substrate, food availability, predation, competition) contribute to
patchy invertebrate organisation, but a wealth of evidence suggests that flow is a
primary consideration (e.g. Hart and Finelli, 1999) by direct influence on entrainment
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and by indirect effects, such as the availability of particulate organic foodstuffs
(Bouckaert and Davis, 1998).
(3) During floods, parts of the stream bed that experience low hydraulic stresses may act
as flow refugia, such that invertebrates that happen to be in, or move into, these areas
avoid entrainment. Local population loss is thereby minimised and a group of
survivors is available to re-colonise the bed. Flow refugia have been associated with
single stable stones (Matthaei et al., 2000), microform bed clusters (Biggs et al.,
1997), the hyporheos (Dole-Olivier et al., 1997), bar edges (Rempel et al., 1999),
inundated floodplains (Badri et al., 1987) and woody debris (Palmer et al., 1986), as
well as undifferentiated in-channel zones of relatively low velocity (Lancaster and
Hildrew, 1993a). The relative importance of these refugia is contested (Palmer et al.,
1992; Robertson et al., 1997; Matthaei and Townsend, 2000; Matthaei and Huber,
2002), and it seems most likely that they serve different animals at different times,
depending on their availability and the life-stage and traits of the animals.
In all cases, however, the efficiency of the flow refugia mechanism relies upon the passive or
active movement of animals into and, perhaps, out of the protected areas. Thus, important
keys to understanding the basis of how flow refugia can facilitate population persistence are:
an understanding of the movement behaviour of invertebrates across the stream bed; how this
behaviour is influenced by local hydraulic conditions; and the net effect of those movements
at the population level (Lancaster and Belyea, 1997). Surprisingly little is known about the
movement of benthic macroinvertebrates in natural settings; for example, there is almost no
information about the velocity at which insect larvae are able to move across a gravel
substrate, their preferred pathways of movement in relation to bed micro-topography and
whether movement behaviour changes in response to changes in the general flow
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characteristics. The effects of stream flow on invertebrate drift have received some attention
(e.g., recent review in Hart and Finelli, 1999), but detailed studies of movements in
association with the substrate (crawling, walking) are scarce. There is indirect empirical
evidence of the role hydraulics plays in the dynamic spatial distribution of invertebrates from
field surveys (Lancaster & Hildrew, 1993b; Palmer et al., 1996; Rempel et al., 1999;
Lancaster and Belyea, 2006) and some manipulative field experiments (Lancaster, 2000;
Winterbottom et al., 1997), but there is a lack of direct observations of invertebrate movement
in realistic environments. This is the general focus of our work.
In this paper, the interaction between insect movement, local micro-topography and
hydraulics at the stream bed are investigated. We map the paths taken by insects as they move
across a realistic facsimile of a gravel surface above which near-bed flow is spatially
heterogeneous. We then examine the differences in hydraulics and elevation at locations
where different types of movement and different levels of mobility are observed. In another
paper, we examine how these interactions might have higher order implications for
population-level processes, e.g., net displacement, spatial dispersion, etc. (Lancaster et al.,
2006).
2. Rationale, Aims and Approach
Our basic assumptions are that animals seek to minimise the energy costs of movement
(Vogel, 1981; Huryn and Denny, 1997) and minimise the risk of long-distance, downstream
displacement through entrainment and drift. Drift is often regarded as a surrogate measure of
mortality because it may result in increased predation risk, reduced feeding opportunities,
physical damage and/or transport to unsuitable habitat (Palmer et al., 1992; 1996). A few
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individuals may survive long distance drift in the order of thousands of metres, including
some vagile mayflies (Hershey et al., 1993) and cased caddis that rarely drift (Neves, 1979),
but catastrophic or unintentional drift is still likely to be a high risk activity. We therefore
expect moving animals to avoid locations that are energetically expensive or where the risk of
entrainment is high in favour of sites where energy expenditure and the risk of entrainment
are low. Sites that experience high flow velocity are likely to entail greater energy expenditure
because animals have to work harder to resist and overcome drag. Sites that experience high
turbulent kinetic energy probably exhibit a higher risk of entrainment because animals are
subject to more variable and more extreme fluid forces, increasing the probability that
entrainment thresholds are exceeded. It is therefore likely that high-risk sites are characterised
by high near-bed velocity and high turbulence intensity, whereas low risk sites exhibit low
near-bed velocity and low turbulence intensity. Notwithstanding the complex 3-D flow fields
created by a rough gravel boundary, greater elevation implies greater exposure to higher
velocities and exclusion from dead-water zones, for example at interstitial junctions. So,
differences in macroinvertebrate behaviour with local elevation are also likely.
Specifically, we hypothesise that:
1. Sites characterised according to type of movement activity will have significantly
different near-bed hydraulics, such that velocity and turbulence intensity are lower at
sites where crawling is common, but higher at sites associated with entrainment.
Places where there is little or no insect activity, to the extent that they can be regarded
as sites that are ‘avoided’ or less favourable, are expected to exhibit the highest
velocities and turbulent kinetic energies.
2. Sites characterised according to type of movement activity will have significantly
different local elevations such that crawling is common at relatively low average
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elevations and entrainment occurs at higher elevations. We assume that any effects
due to elevation reflect local hydraulic differences, and view assessment of hypothesis
2 as an extension of hypothesis 1, acknowledging that the more easily-obtained
elevation data are used as a simple surrogate for more hard-won hydraulic
information.
In another paper, we have shown how the hydraulic environment close to a natural gravel
surface changes with the general flow condition. In particular, we have demonstrated that the
increases in spatially-averaged velocity and turbulence intensity that are driven by changes in
channel discharge are associated with increased local values and greater spatial variability of
these flow parameters (Buffin-Bélanger et al., 2006). Here, we investigate whether such
changes affect the relations between macroinvertebrate movement, local hydraulics and local
topography by assessing hypotheses 1 and 2 across three discharge conditions. Higher
discharges may be associated with greater hydraulic differentiation of sites where different
activities occur, because conditions are more constraining and local environments are more
diverse, and we hypothesise that:
3. Differences in the hydraulics and/or elevation of sites where contrasting movement
activities occur will become greater as discharge increases.
We therefore consider the role of both highly local hydraulics, as controlled by the microtopography of the gravel surface, and the effects of general increases in flow.
Detailed measurements of near-bed hydraulics and macroinvertebrate movements on gravel
substrates are difficult to achieve in the field, becoming impracticable at high flows.
Conversely, controlled measurements are possible in laboratory flumes, but the reproduction
of natural gravel fabrics requires greater transport rates than can be generated artificially,
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limiting the realism and validity of the data obtained. Previous hydraulic studies have
attempted to reconstruct (Young, 1992), import (Buffin-Bélanger, 2001) or reproduce
(Lawless & Robert, 2001) natural gravel structures in the laboratory, or have developed
water-worked textures using small gravels (Kirkbride, 1993; Lane et al., 2004). Small scale
(cm) movements of individual invertebrates are extremely difficult to observe directly in the
field. Those studies which have done so have necessarily avoided natural, high flows and
worked at very small scales on individual clasts (Poff and Ward, 1992; Hart et al., 1996) or
have worked at larger scales with less detailed behavioural observations and little hydraulic
detail (Hart and Resh, 1980; Jackson et al., 1999). Most previous detailed studies of insect
movement-flow interactions have therefore used flumes with highly simplified environments
or a random arrangement of gravels (e.g., Holomuzki & Biggs, 1999; Lancaster, 1999).
Accordingly, the near-bed hydraulics of these experimental arenas are likely to be
unrepresentative of natural stream channels. To overcome these problems, a novel casting
technique (Buffin-Bélanger et al., 2003) was used to produce a precise replica of a fluvial
cobble-gravel substrate that was deployed in a large laboratory flume, where we could control
and manipulate flow, take detailed hydraulic measurements and observe invertebrate
movements.
3. Methods
3.1 Experimental arrangement
A precise replica of a natural cobble-gravel substrate, 1.0 by 2.0 m, was made using the
casting technique described by Buffin-Bélanger et al. (2003). The cast was obtained from an
exposed gravel bar in the River Manifold, UK, and reproduces the true three-dimensional
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complexity of a natural, water-worked unit. The cast retains significant small-scale detail
including the texture of mosses and sands and most of the surface interstices.
Orthophotographs and a digital elevation model (DEM) of the cast surface were generated by
close-range digital photogrammetry (Chandler et al., 2003). A grid-by-number grain size
distribution obtained by a non-invasive photographic technique (Graham et al., 2005) and
truncated at 0.008 m, yields a median diameter D50 = 0.048 m and a D95 = 0.119 m. A
representative sub-area of the cast 1.1 m long and 0.80 m wide was selected for detailed
hydraulic measurements and insect observations (Figure 1). This area is many times the area
of the individual grains that make up the bed. Elevation data for this area were examined to
characterise surface roughness. Elevations, h (n = 38,480), measured relative to the lowest
point in the sub-area, rise to 0.121 m, have a median h50 = 0.053 m, are positively skewed and
exhibit a lognormal distribution. Comparison of this elevation distribution with previously
published data indicates that the cast and the prototype gravel patch are representative of
water-lain gravel surfaces in other rivers. For example, the lognormal fit is consistent with the
field observations of Smart et al. (2004) who made detailed roughness characterizations of six
natural river gravels. Also, the skewness value hSK = 0.46 is similar to the average value
reported by Nikora et al. (1998) for 77 field profiles from eight gravel-bed rivers (hSK = 0.47,
s.d. = 0.51) and notably different from the negative skewness values reported for manually
created, ‘unworked’ flume beds (Kirchner et al., 1990).
The cast was positioned in a 9.0 m long, 0.9 m wide, and 0.8 m deep flume with a fixed slope
of 0.002. Full details of the flume set-up can be found in Buffin-Bélanger et al. (2006). Three
uniform and steady flows were established by running the flume successively at three
discharges while minimising changes in water depth (Table 1). All three flows were fully
turbulent, sub-critical, representative of flows in natural rivers and differentiated by increases
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in a variety of relevant flow characteristics (e.g., mean velocity, Reynolds number, shear
velocity). The three flows represent a distinct treatment (referred to as Flow in our analyses)
that provides a means of examining the interactive effects of local hydraulics and general,
externally-driven, flow conditions that, in some respects, mimic the rising limb of a flood
hydrograph.
Gravel-bed rivers are characterised by hydraulic stresses that rarely exceed the entrainment
thresholds of the framework particles exposed at the bed surface, so that insects are often
exposed to high flows but benefit from a stable substrate. Estimated bed shear stress for the
highest discharge was below the critical entrainment threshold of the framework particles in
the prototype gravel patch, so the flows used are consistent with the stability of this particular
substrate. The fixed nature of the substrate surface was important for our experiments because
it meant that we were able to examine the effects of flow forces only on insect movement,
without the confounding effects of substrate movement.
3.2 Hydraulic measurements
For each flow, spatially-distributed, near-bed hydraulic measurements were made using an
acoustic Doppler velocimeter (ADV). The ADV was deployed at 110 locations in an eleven
by ten x - y grid with spacings of 0.1 m and 0.05 m, respectively (Figure 1b). At each
location, velocity measurements were made at z = 0.008 m above the local bed, rather than
above an arbitrary horizontal reference plane. The full set of spatially distributed
measurements therefore describes the hydraulics in a convolute layer that follows the
topographic highs and lows of the surface. The sampling volume of the ADV is cylindrical
and less than 200 mm3. The near-bed positions, the sampling volume and the use of local
topography as the reference height ensured that our measurements describe the hydraulic
conditions experienced by macroinvertebrates moving across the gravel surface.
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At each location, instantaneous velocities were measured for the three orthogonal velocity
components (streamwise, U; cross-stream, W; vertical, V) over a period of 60 seconds at a
sampling frequency of 25 Hz. The potential sources of error in ADV data are well-understood
(Lane et al., 1998; Nikora and Goring, 1998; Finelli et al., 1999; McLelland and Nicholas,
2000; Wahl, 2000) and a rigorous validation scheme was employed to ensure maximum
quality (Buffin-Belanger et al., 2006). The mean and standard deviation for each velocity
component (e.g. <U>, URMS) were extracted from the velocity time series at each location and
turbulent kinetic energy, a surrogate for the intensity of 3-D turbulent fluctuations about the
mean flow, was computed as:
K = 0.5 ( URMS2 + VRMS2+ WRMS2 )
(1)
where  is water density (= 1000 kg m-3) and K is in J m-3.
3.3 Macroinvertebrate observations
Larvae of the cased caddisfly, Potamophylax latipennis (Curtis) were selected for use in the
experiments. At instars IV and V, these insects are relatively large, slow-moving, benthic
species that live inside a cylindrical case built from medium-coarse sand grains. The average
case had a length of 20 mm (range 17-28 mm) and an average density of approximately 1100
kg m-3. Further methodological details regarding the invertebrate observations can be found
in Lancaster et al. (2006.)
In each of six replicate trials, carried out at the three different and predetermined flow
conditions, we recorded the movement of five animals. Five points located within the ADV
measurement grid were selected as seeding or start locations (MH6 – 10; Figure 1b). Seeding
locations were relatively sheltered positions, usually in the lee of particles that projected
slightly above the general surface, where the larvae could be introduced with minimal danger
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of immediate entrainment. Using five animals per trial minimised the net duration of the
experiment and use of fixed seeding locations maximised the likelihood that animals would
settle on the cast. The periods of observation for a trial ranged between 1 and 23 minutes with
an average of approximately 9 minutes. The experiment was a split-plot design with two fully
orthogonal fixed factors (flow, seeding location) and one random factor (trial) nested within
flow treatment.
Larval movements were recorded using a digital video camera suspended above the substrate
surface. A Perspex viewing box was positioned carefully on the water surface without altering
significantly the near bed hydraulics in order to facilitate an undistorted image of the
substrate. The video imagery has dimensions of 767 by 575 pixels and covers an area of
approximately 1 m2, giving a ground resolution of 0.0015 m. From the video recordings we
obtained the x and y location of each caddis every 5 s and also the time and x and y locations
of entrainment start and stop (reattachment) positions. These time series of (x, y) coordinates
define a trace across the cast surface of the path followed by each larva. At each interrogation
(5 s intervals), the behaviour of the larva was classified as crawling, entrained, struggling or
stationary. Note that larvae never truly drifted, i.e., were never fully suspended in the water
column, but rather they tumbled close to the bed surface. Relevant metrics estimated for each
larva included proportion of time crawling, average crawling velocity and total displacement
by entrainment. A full analysis of these metrics is reported elsewhere (Lancaster et al., 2006),
but general results are used here to support our investigation.
3.4 Data analysis
A set of screws was embedded in the prototype bar, reproduced in the cast and used as
spatially distributed benchmarks. It was then possible to locate DEM postings,
orthophotographs, larval paths, and hydraulic data within a single coordinate system that
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allowed extraction of spatially explicit information. A radial correction was applied to the
larval paths to allow for distortion in the video imagery due to the camera lens. Remaining
errors in the video trace data due to camera tilt and camera rotation are small and we estimate
a maximum cumulative error in the positioning of insects of 0.0075 m.
Crawling and drift paths for all larvae were grouped by Flow and mapped onto
orthophotographs and three-dimensional renderings of the DEM. These maps provided a
means of examining general patterns and, in addition, allowed locations on the cast surface to
be classified with respect to four categories of insect activity, which we subsequently refer to
by the factor name Activity: crawling (one or two crawling paths), congested crawling (more
than two crawling paths), entrainment sites and sites of no activity (animals were never
present, so no crawling or entrainment were recorded). This classification scheme was applied
to circular areas of the bed (radius = 20 mm), which we call "sites", centred on each of the
ADV sampling positions. Some sites were excluded from analyses a priori, e.g., sites where
estimates of hydraulic conditions were impossible and seeding locations where high insect
activity simply reflected the sampling design. Differences in hydraulic characteristics at 0.008
m above the local bed elevation (<U>, K) between insect activities (Activity; Hypothesis 1)
and across the flow treatments (Flow; Hypothesis 3) were then examined using two-way
ANOVA.
The elevations at which these different activities took place were examined in a similar
manner. Crawling and entrainment elevations were obtained by extracting values of h from
the DEM along the crawl path and at points of entrainment. Crawling elevations during each
flow were compared to the mean elevation of the sampling sub-area of the cast surface using
one-sided, one-sample t-tests. Entrainment and crawling elevations were compared at each
flow using paired t-tests with the mean entrainment elevation of each individual compared
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with its own mean crawling elevation (Activity; Hypothesis 2). We tested for the effect of
Flow (Hypothesis 3) on crawling elevation using a split-plot ANOVA (fixed factors = Flow,
seeding location; random factor = trial). The design assumes that there is no significant
interaction term, Location x Trial (Flow), and the residual error cannot be estimated (MS for
the random factor is used as the error term in the F-test). In no case were any interaction terms
significant so, for brevity in the text that follows, only the main Flow effects are reported.
4. Results
4.1 Path Maps
The path maps provide a clear illustration of how insect movements were affected by flow. As
discharge increased (Figure 2, panels a to c), crawling paths became shorter and increasingly
disjointed. The average straight-line displacement resulting from individual crawling events
declined significantly, from 67 mm to 30 mm and then to 27 mm under flows 1, 2 and 3,
respectively (F2,15 = 18.1 p < 0.001, Flow effect in split-plot ANOVA). In contrast, the
frequency of entrainment events increased 23-fold from flow 1 to flow 3 and distance per
event increased similarly. Thus, as discharge increased, long crawling journeys were replaced
with shorter journeys and were broken by periods of inactivity or by entrainment (full details
in Lancaster et al., 2006.).
The path maps are also useful in revealing that there was a tendency for crawling individuals
to converge on particular locations and to travel along the same routes as one another. Spatial
concentration of crawling activity was inevitable close to the seeding sites, but beyond the
immediate vicinity of the five seeding locations, certain pathways were frequently used,
suggesting a degree of preference. The consistent use of particular corridors was apparent
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under each flow condition (Figure 2 a - c) and between flow conditions (Figure 2d). For
example, under flows 1 and 2, a corridor of activity extended downstream from the seeding
locations toward the right edge of the large cobble centred on x = 60 cm, y = 10 cm (labelled
A in Figure 1). At flow 3, activity within this corridor was restricted to two small areas.
Topographic and inferred hydraulic conditions provide possible reasons why the larvae
converged on particular paths. For example, Figures 2 and 3 show that a set of partially
imbricated gravel particles form a weak cluster that flanks the upstream edge of the corridor
highlighted above, perhaps providing a hydraulically sheltered path in its lee where larvae
could move with relative ease. In contrast, the large cobble just downstream has an exposed
stoss face where no traces were recorded. The consistent movement of animals toward its
right-hand edge at all discharges might indicate that the stoss face was unacceptable crawling
terrain or simply that the cluster-protected corridor presented an acceptable route that did not
require the animals to seek alternative paths. At flows 2 and 3, movements were also noted
along the upstream edge of the cobble, toward its left flank and, indeed, at flow 3 the outline
of the cobble’s base was essentially traced out by crawling activity of multiple individuals
(Figure 2c). Whether by design or by default, the larvae tended not to crawl on top of this or
other large exposed particles, particularly at stronger flows (Figure 3). Thus, at flows 1 and 2
several paths crossed the upper surface of the particle centred at x = 25 cm, y = 0 cm but, at
flow 3, no paths are apparent on this surface.
The path maps (Figures 2 and 3) suggest that larvae tended to crawl around large particles
rather than over higher, exposed surfaces. This is consistent with our observations which
show that, when crawling, larvae were most frequently observed on plane-bed areas (where
the upper surfaces of adjacent grains lie at approximately the same elevation) or at the
interstitial junctions between plane beds and larger, taller clasts (75-85 % of the time under
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flow 1; 61 % under flow 3) rather than on particle tops or sides (Lancaster et al., 2006).
4.2 Site hydraulics, general flow conditions and insect activity
Site hydraulics influenced insect activity and there was an interactive effect in that the
strength of this influence varied with the general flow condition (flow 1, 2 or 3), i.e., insect
movement behaviour changed with flow. Figure 4 shows the mean and the 95% confidence
limits of <U> and K for sites characterised by congested crawling, crawling, entrainment and
no activity, under the three flow treatments. At the majority of sites there was no activity (60 70 %), but the frequency of no activity sites did not vary with flow (  22 = 1.24 p > 0.05). For
both of the hydraulic variables, velocity and turbulence, the main treatments of Flow and
Activity were significant and the interaction term was significant for velocity (Table 2). An
increase in site velocity and turbulence with increasing flow is unsurprising. However,
noteworthy in terms of Activity, is that velocity and turbulence were lower in congested
crawling sites and higher in no activity sites (Figure 4). The hydraulic character of crawling
and entrainment sites generally lay between the extreme conditions, i.e. those typical of no
activity and congested crawling sites. The significant interaction between Flow and Activity
for velocity is particularly interesting (i.e., movement activity is contingent upon flow) and
attributed to an increase in the magnitude of the difference in site hydraulics for each type of
activity as discharge increases (Table 2). Thus, sites of different activity are most clearly
differentiated by velocity under flow 3. Indeed, it is apparent that the significant Activity
effect in the ANOVA results is largely due to the differences in velocity between the activity
groups at Flow 3 (Table 2). While the general trend from low velocity at congested crawling
sites to higher velocity at no activity sites is consistent at the two other discharges (Figure 4),
the differences are not statistically significant (Table 2). This suggests that animals strongly
avoided the highest velocity sites at high flow, but were less discriminating at lower flow
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(Figure 4).
These results suggest that crawling is associated with lower local velocities and lower
turbulence, but that this activity is not restricted to a narrow range of hydraulic conditions. In
particular, the results suggest that larvae are able to respond to shifts in the range of local
hydraulic characteristics driven by general changes in discharge.
4.3 Elevation, general flow conditions and insect activity
The path maps and the simple metrics, reported above, imply that larvae tended to crawl at
relatively low elevations and this was further supported by a significant difference between
the average elevation of the cast surface and the mean crawling elevation at flow 3 (t 26 = 5.39
p < 0.001) (Figure 5). For flows 1 and 2, there was a strong suggestion that crawling elevation
was less than the mean surface elevation (t30 = 1.62 p = 0.059 and t25 = 1.64 p = 0.057,
respectively). As discharge increased, however, there was no change in the mean crawling
elevation, even though it appeared to be lower at flow 3 (main flow effect in split-plot
ANOVA: F2,15 = 1.60 p = 0.23).
Comparing the elevations at which entrainment occurred with crawling elevations yielded
inconclusive results (Figure 5). Mean entrainment elevation was generally higher than mean
crawling elevation for individuals at flow 2 (paired t-test: t24 = 2.35 p = 0.034), but not at flow
3 (t21 = 0.514 p = 0.613). Similar analysis for flow 1 was not possible given the scarcity of
entrainment events. On the basis of these equivocal results it would be imprudent to conclude
that entrainment is more or less likely from higher elevations, especially since the visual
impression in Figure 2 is that entrainment occurs from a wide range of topographic positions.
This apparent indeterminacy might, in part, reflect the changing dimensions of coherent flow
structures that arise from changes in discharge. Points of shear layer detachment and
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reattachment and patterns of deflection of high speed fluid will alter as flow increases and
decreases. Elsewhere we have shown that, as discharge increases from flow 2 to 3, there is a
decrease in the average elevation of maximum turbulent kinetic energy associated with shear
layers extending downstream from the crests of protruding particles (Buffin-Belanger et al.,
2006). If entrainment probabilities are increased as turbulent kinetic energy increases, this
lowering of shear layers might help to explain why entrainment elevations decline, on
average, at flow 3.
5. Discussion
Crawling paths and entrainment maps (Figures 2 and 3) highlight the patchy distribution of
Potamophylax latipennis larvae as they crawl across a rough, gravelly substrate. Individual
paths do not criss-cross the substrate at random but exhibit a degree of co-location which
suggests that there are preferred crawling tracks. Analysis of the hydraulics and elevation at
sites where different activities occur provides some insights into these insect preferences that,
it is assumed, reflect a requirement to minimise energy expenditure and reduce the risk of
entrainment. Sites where crawling and congested crawling are common are interpreted as
those that most favour movement and we have hypothesised that such sites would be
characterised by relatively low elevations, low velocities and low turbulent kinetic energies.
We have found strong evidence to support these hypotheses (Figure 4, Figure 5, Table 2),
especially at higher discharges.
We have also hypothesised that entrainment would occur from sites with a higher average
elevation and from sites with higher velocities and more intense turbulence than crawling
sites. While velocities at entrainment sites tend to be higher than at congested crawling and
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Rice et al., FINAL SUBMISSION Nov 2006
crawling sites, turbulent kinetic energies are not, in general, any greater. Our findings
regarding the elevation of entrainment sites are equivocal and Figure 2 suggests that
entrainment occurs from a wide range of topographic positions. There is certainly no evidence
to suggest that entrainment occurs exclusively at exposed sites or only where turbulence
intensity and velocity are particularly high. Several reasons may explain why this hypothesis
has not been validated. First, the total number of entrainment events was relatively small (107
events for 39 animals) and it is likely that better characterisation of entrainment sites requires
a larger number of observations under stronger flows. Second, there is the possibility that
entrainment events are initiated by short term velocity fluctuations that are not revealed by
flow parameters such as the time-averaged streamwise velocity (<U>) and the turbulent
kinetic energy (K). The entrainment of an insect may occur following the passage of an
intense velocity event, such as a sweeping motion. These events have been linked with the
transport of bed sediments (e.g. Drake et al., 1988; Sumer et al., 2003) and could also be
associated with the entrainment of benthic insects. Concurrent data on entrainment and
velocity are needed to examine this possibility and would usefully be augmented by flow
visualisation to investigate the effect of turbulent flow structures on entrainment.
Areas without any activity are interpreted as places that animals actively avoided or places
that they were simply not carried to. Given our interest in elucidating the role of local
hydraulics and micro-topography on insect movement, the distinction between these is not
important because both imply a significant physical control on movement. Sites of no activity
might also indicate places that insects did not have the opportunity to reach because their
initial seeding location was too far away. However, we think this is relatively unimportant,
because larvae did journey across the whole of the cast surface and no restrictions on
observation time were enforced. So, areas of no activity are interpreted as areas that the
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Rice et al., FINAL SUBMISSION Nov 2006
insects avoided, though avoidance could have been active or passive. We have hypothesised
that such areas would, in general, exhibit the highest local velocities and turbulent kinetic
energies because these reflect the greatest energy costs and entrainment risk for mobile
insects. The hypothesis is supported by the significant Activity effects in our examination of
hydraulic variables and the generally higher mean velocity and turbulent kinetic energy values
at no activity sites compared with other sites (Table 2; Figure 4).
Overall these results demonstrate that the movement activity of Potamophylax latipennis is
conditioned by micro-scale hydraulic patchiness (Hypotheses 1 and 2). Animals discriminated
between sites, avoiding areas where entrainment risk and the energetic cost of fluid drag were
high and moving more frequently in low-lying areas or other places where velocity and
turbulent kinetic energy values were relatively low. Our results illustrate the importance of
hydraulic patchiness for benthic mobility and the retention of animals at particular locations.
They therefore demonstrate that rough, heterogeneous substrates which create hydraulic
patchiness, are important for the provision of in-stream refugia – at least for relatively slowmoving, crawling species such as this caddisfly. An interesting question is, then, whether
gravel texture can be used to quantify the quality of in-stream refugia. It is clear that high
quality in-stream refugia will be characterised by sufficient low-velocity sites, which in turn
implies heterogeneity in the size and arrangement of bed particles. Bed material sorting
indices and structural characteristics may then provide a reasonable means of assessing
refugia potential. This will be the subject of a forthcoming paper that compares near-bed
hydraulic variability and insect activity between substrates that have different textural
characteristics.
It is evident from Figure 4 that the distinction between no activity and other sites is most clear
at flow 3, where discharge is highest and this is reflected in the significant interaction term for
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Rice et al., FINAL SUBMISSION Nov 2006
Flow and Activity in Table 2. The effect on local hydraulics of a general increase in flow (an
increase in discharge) and the fact that macroinvertebrates change their behaviour in response
to changes in flow are fundamental to understanding animal behaviours during flood events.
For the cast used here, Figure 6 illustrates the effect of increased discharge on local mean
velocity and turbulent kinetic energy: there was an increase in the average values in response
to a general upward shift of the bulk of the frequency distribution and an increase in
variability between sites. The upward shift of the values for the bulk of the sites means that,
as discharge increased, animals were increasingly exposed to larger absolute velocities and
turbulent kinetic energies across the whole of the cast surface. Although some sites continued
to experience very low velocities and turbulent kinetic energies, these sites became
increasingly rare. It is clear from Figure 4 that the Potamophylax larvae were able to respond
to these shifts and that their activities were not limited to fixed ranges of velocity and
turbulence. Thus, at flow 3, larvae crawled at sites with significantly higher turbulent kinetic
energy and velocity than at flow 1 and were active in hydraulic conditions which, at lower
flows, characterised sites where no activity was observed. However, animals did discriminate
among the available hydraulic conditions (e.g., avoiding sites with the highest velocities) and
the strength of this discrimination increased with flow (Hypothesis 3), i.e. movement
behaviour is contingent upon flow. This might suggest that insects key into spatial variations
in relative hydraulic conditions, not absolute velocities, at least for the range of flows studied
here.
Figure 7 shows that the spatial pattern of relative velocities remained very consistent between
different discharges so that sites with above or below average velocity at one flow
experienced above or below average velocity at other flows. It is apparent in Figure 2d that
there was a degree of spatial consistency in movement patterns too, albeit that movements
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Rice et al., FINAL SUBMISSION Nov 2006
were more restricted under higher discharges. Together, these observations suggest that
patterns of animal movement are associated with particular sites, despite local changes in
hydraulics, because certain sites consistently represent the same opportunities in terms of
energy savings and risk-aversion. At discharges sufficient to mobilise the bed, these relations
are unlikely to persist and there must be an absolute limit to the hydraulic forces that animals
can withstand without being entrained. But at modest flows that do not exceed the critical
threshold for framework particle entrainment, our results suggest that patterns of
Potamophylax latipennis movement and avoidance might reflect relative opportunities rather
than absolute hydraulic forces per se.
6. Conclusion
The substrate of a gravel-bed river is a dangerous place to live, subject to large hydraulic
forces and prone to instability during large floods, yet benthic fauna are typically diverse and
abundant. Flow refugia mechanisms help to explain the persistence of macroinvertebrate
communities in gravel-bed streams. The movement of insects is central to the refugia idea,
but little is known about the nature of insect movements on rough substrates and the effect of
increases in flow or differences in substrate texture on movement patterns, pathways and
characteristics. Our observations of Potamophylax latipennis lead us to the general conclusion
that crawling journeys tend to follow low-lying paths characterised by low velocity and, to a
lesser extent, low turbulence intensity. In contrast, animals avoid sites characterised by the
highest velocities and turbulence intensities, especially at higher flows. Importantly, the
strength of this behavioural response is contingent upon flow. These observations give us an
insight into how these insects utilize the substrate to avoid entrainment and minimise energy
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Rice et al., FINAL SUBMISSION Nov 2006
expenditure and illustrate the importance of hydraulic patchiness for movement behaviour.
The degree to which animals avoid entrainment and conserve energy will depend upon the
heterogeneity of the substrate in terms of particle size and arrangement. By extension, this
suggests that high quality in-stream refugia should be characterised by heterogeneous
substrates.
Our findings add to the understanding of the basic principles which underlie the refugia
mechanism and thence the question of how invertebrate communities persist in the face of
hydraulic disturbances. In addition to rain and snow-melt flooding, such disturbances are also
associated with controlled water releases on managed gravel-bed rivers. In this respect,
insights into the successful operation of refugia mechanisms should be a consideration of
integrated river management because the survival of viable populations of macroinvertebrates
is a vital element of the biotic well-being of any gravel-bed river.
This paper has focused on linking near-bed hydraulics with the movement behaviour of a
particular cased caddisfly at discharge levels below those that would mobilize the framework
gravels. This approach, necessarily, did not consider three other sets of factors that are
important for understanding macroinvertebrate movement behaviour in the context of refugia
utilization.
First, a number of biotic factors are also likely to be important. Minimizing energy
expenditure and drift are not the only concerns of benthic insects. Biological controls might
include movement strategies that are intended to maximize food acquisition, minimize the
risk of predation or reduce competition between individuals. For example, crawling at low
elevation along interstitial junctions may in part reflect avoidance of predation. Second, our
results pertain to a single crawling species, but the morphological and behavioural traits of
different macroinvertebrate species are of fundamental importance in terms of their movement
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Rice et al., FINAL SUBMISSION Nov 2006
characteristics so that it is difficult to generalize our results to other species or to whole
communities. For example, the shape of a species partly determines its Reynolds number and
drag coefficient and thence the fluid forces that it is subjected to and its ability to resist
entrainment (Vogel, 1981; Statzner and Holm, 1989) and move around. For larvae that live in
cases there is the additional effect of the case’s weight. Waringer (1993) determined Reynolds
numbers and drag coefficients for a variety of dead, cased caddisfly and estimated critical
entrainment stresses. Potamophylax cingulatus (Steph), which is similar to the species used
here, had the highest Reynolds number and lowest drag coefficient of the macroinvertebrates
examined and required the highest tractive forces to entrain it. There is, therefore, a need to
examine the movement of animals that possess contrasting characteristics in terms of size,
weight and shape. This study indicates the experimental and analytical tools that might
facilitate such work.
Third, the role of bed stability in defining suitable refugia is not considered in our
experiments. Not surprisingly, given the difficulties of making reasonable observations, work
on insect distributions and mortality across mobile beds is scarce (Holomuzki and Biggs,
1999; Kenworthy, 2005). It is, however, an important issue, because successful refugia must
not only provide protection from hydraulic forces, but also be associated with bed elements
that do not move and crush or dislodge sheltering insects. The relations between hydraulic
conditions and bed stability are not simple and require careful consideration. For example, the
proportions of the bed that are partially and fully mobile increase with peak discharge
(Haschenburger and Wilcock, 2003) suggesting that the extent of stable refugia varies in a
fairly simple way during floods and between floods of different magnitude. However, such
relations might be complicated by the fact that the hydraulic stresses at particular places on a
partially mobile bed will respond to transformations of bed texture as a result of bed material
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deposition and entrainment. Similarly, the bed surrounding a position which offers hydraulic
shelter may be mobile so that entrained bed materials may nevertheless impinge on areas that
are offering refuge from the flow.
There is a fourth factor that is excluded from our experiments, which is likely to be
unimportant for this study but may be worthy of future experimental assessment. Animals
may migrate down into the hyporheos to avoid or bypass unfavourable hydraulic conditions,
although it is likely to be relevant to small-bodied animals and not the large, late-instars of P.
latipennis. To date, utilisation of the hyporheos by epigean (surface dwelling) insects has
been considered largely in relation to flood disturbances, but it may also be a behaviour that
facilitates movement across hydraulically patchy surfaces at more modest flows. Evidence for
insect use of the hyporheos in response to hydraulic forcing is equivocal. From observations
in a sandy-bottomed channel and experiments conducted in a flume, Palmer et al. (1992)
found only very limited evidence for vertical insect movements as water velocity was
increased. Working in a fourth-order gravel-bed channel, Olsen and Townsend (2005) found
no substantial evidence that invertebrates moved deeper into the hyporheos during flood
events. In contrast, Dole-Olivier and Marmonier (1992) found that epigean fauna in the
cobble-gravel Miribel Canal do utilise the hyporheos as a refuge during flood events,
especially in downwelling-zones (Dole-Olivier et al., 1997).
The integration of biological factors, sediment transport and the hyporheos in further
experiments on insect movement will help to elucidate their relative importance and,
ultimately, improve our understanding of flow refugia mechanisms. Continued collaboration
between aquatic ecologists and fluvial geomorphologists is central to the success of this
endeavour.
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Acknowledgments
The project was funded by NERC Grant NER/B/S/2000/00697 to Rice, Reid and Lancaster.
We are grateful to Natasha Todd-Burley, Mick Barker, David Graham and Stuart Ashby for
their help with the flume experiments, which were conducted in the Department of Civil &
Building Engineering at Loughborough University. Ian Atkins and Adam Evans helped with
video analysis of insect movements and Jim Chandler provided photogrammetric expertise.
We are grateful to two anonymous reviewers for their useful suggestions, which have
improved the clarity of the paper.
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Table 1.
Flow
Characteristics of the three experimental flows.
bed
v*
(N m-2)
(m s-1)
0.135
0.530
0.023
218622
0.240
1.467
0.038
281152
0.402
3.693
0.061
Q
C0.4
Y50
Re
(m3 s-1)
(m s-1)
(m)
1
0.153
0.310
0.536
166160
2
0.202
0.498
0.439
3
0.262
0.764
0.368
Fr
Q is discharge, C0.4 is an average representative velocity at 0.4Y50, Y50 is the median water
depth, i.e. the water depth above h50, Re is Reynolds number, Fr is Froude number, bed is the
reference bed shear stress and v* is the shear velocity. bed and v* are estimated from velocity
profiles taken upstream from the cast using the law of the wall [ v=2.5v*(ln(y/yo)) and bed =
(v*)2 ] applied to velocity measurements in the near-bed region (below 0.4Y50).
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Table 2
Summary of two-way ANOVA testing for differences in hydraulic conditions
(mean streamwise velocity and Turbulent Kinetic Energy) at sites classified
according to insect activity (Activity) and discharge (Flow).
Variable
(a) Velocity, <U>
Source
MS
F
p
Flow
2
0.0213
11.9
< 0.001
Activity
3
0.0139
7.78
< 0.001
Flow 1 Act.
3
0.0009
0.520
0.669
Flow 2 Act.
3
0.0016
0.865
0.460
Flow 3 Act.
3
0.0192
10.7
<0.001
6
0.0051
2.86
0.010
277
0.0018
Flow
2
5.38
182
< 0.001
Activity
3
0.142
4.81
0.003
Flow x Act.
6
0.013
0.428
0.860
277
0.030
Flow x Act.
Residual
(b) TKE, K
df
Residual
Given the significant interaction term in (a), we tested the effect of activity separately for each
flow, with MSresidual of the full model as the denominator. Transformation of log(x+1) for
velocity and log(x) for K was carried out to meet assumptions of normality. Unbalanced
replication is accounted for (no association between within-cell variance and sample size). To
adjust for the missing cell (entrainment was rare at flow 1), we nominally included one site in
which there was entrainment, but that had been excluded a priori (see text for explanation).
Thus the need to avoid a missing cell in the analysis out-weighed the cautious data screening.
See Figure 5 for illustration.
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List of Figures
Figure 1
Topography of the cast surface (0.8 x 1.1 m). The x-axis referred to in the text is
the long, streamwise axis, y is cross-stream and z is vertical . All axis units are
cm. (a) Oblique view of the DEM looking from the right bank, flow left to right.
Three prominent features are indicated: the large cobble located toward the
downstream end (A); the low-lying plane-bed area to its left (B) and the
upstream particle of an imbricate cluster, centre-right (C). (b) Contour map of
the DEM showing the five seeding locations (MH6 – MH10) and the 110 ADV
sampling positions (solid black dots). (c) Oblique photograph looking upstream
from the left bank (note pen - top centre at C - for scale).
Figure 2
Crawl traces (white lines) and the starting locations of entrainment events (black
dots) for flows 1, 2 and 3 (respectively a, b, c). A composite of the traces for the
three flows is shown in d (thick black is flow 1, dark grey is flow 2 and thin
black is flow 3). In each case, all replicates from each seeding location (black
circles with a cross) are shown. The background image is an orthophotograph
that is spatially consistent with the trace maps. Flow is from left to right and the
large cobble (A in Figure 1, with moss showing) is located toward the bottom
right of each image.
Figure 3
Oblique view of the DEM from the right bank with crawl traces under (a) flow 1
and (b) flow 3 showing the topography associated with favoured pathways. Flow
is from left to right and the large cobble (A in Figure 1) is located toward the
bottom right of each image.
Figure 4
Mean and 95% confidence limits of time-averaged streamwise velocity in layer
A, <U>, and turbulent kinetic energy in layer A, K, for crawling, congested
crawling, entrainment and no activity sites under each flow condition. See Table
2 for summary of statistical analyses.
Figure 5
Comparison of average crawling elevations, entrainment elevations and mean
surface elevation for three flow discharges. Mean values and 95% confidence
limits are shown. Only 1 drift event occurred under flow 1 and it is not indicated
here.
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Figure 6
Changes in local time-averaged streamwise velocity in layer A, <U> and
turbulent kinetic energy in layer A, K, with increasing discharge (flows 1 to 3;
see table 1 for details) for the 110 ADV sampling positions (see Fig. 1b). Note
the increase in both the local mean values and the spatial variability as discharge
increases.
Figure 7
Relative mean velocity in layer A (calculated as the local velocity divided by the
mean of all local velocities for a given flow) for (a) flow 1 and (b) flow 3.
Relative velocities are consistent between flows, despite significant differences
in absolute velocity and this is indicated in (c) which shows the modulus of the
difference in relative mean velocity between sites for flows 1 and 3.
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