BENTHIC COMMUNITY STRUCTURE RESPONSE TO FLOW DYNAMICS IN
TROPICAL ISLAND AND TEMPERATE CONTINENTAL STREAMS
Dissertation
Submitted to
The College of Arts and Sciences of the
UNIVERSITY OF DAYTON
In Partial Fulfillment of the Requirements for
The Degree
Doctor of Philosophy in Biology
By
Kathleen R. Gorbach, M.S.
UNIVERSITY OF DAYTON
Dayton, Ohio
December, 2012
BENTHIC COMMUNITY STRUCTURE RESPONSE TO FLOW DYNAMICS IN
TROPICAL ISLAND AND TEMPERATE CONTINENTAL STREAMS
Name: Gorbach, Kathleen R.
APPROVED BY:
__________________________
Albert J. Burky, Ph.D.
Faculty Advisor
__________________________
M. Eric Benbow, Ph.D.
Faculty Advisor
__________________________
Karolyn Hansen, Ph.D.
Graduate Committee Member
__________________________
Mollie D. McIntosh, Ph.D.
Graduate Committee Member
__________________________
Mark Nielsen, Ph.D.
Graduate Committee Member
__________________________
P. Kelly Williams, Ph.D.
Graduate Committee Member
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© Copyright by
Kathleen R. Gorbach
All rights reserved
2012
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ABSTRACT
BENTHIC COMMUNITY STRUCTURE RESPONSE TO FLOW DYNAMICS IN
TROPICAL ISLAND AND TEMPERATE CONTINENTAL STREAMS
Name: Gorbach, Kathleen R.
University of Dayton
Advisors: Drs. Albert J. Burky & M. Eric Benbow
Hydraulic characteristics in lotic ecosystems are influential in the structure and
function of aquatic benthic communities. Human activities and the increased demand for
freshwater have caused the modification of natural flow regimes worldwide.
Hydrological alterations, such as dams, diversions, and channelizations, are associated
with ecological change and known to have detrimental effects on benthic communities.
As a whole, this dissertation investigated the effects of hydraulic variables on the spatial
distribution of macroinvertebrates and habitat template characteristics in tropical and
temperate freshwater streams of the West Maui Mountains, Maui, Hawaii, and in Dayton,
Ohio.
The first two studies took place in Hawaiian mountain streams that have been
diverted, often removing >95% of base flow, for development, agriculture and tourism,
thus modifying the natural flow and altering habitat and species composition. A
transplant study investigated the effects of water removal and increased density on
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dispersal and upstream migration of N. granosa. Initial mean upstream migration rate
was 0.25, 0.66 and 1.16 m/d under reduced flow, natural flow and natural flow with
increased snail density, respectively. Through calculations using rates from published
studies of neritids migrating en masse or in long lines, we generated realistic time frames
for N. granosa to migrate above diversions, ranging from 72 days to 2.5 years (aggregate)
and 29 days to 1.1 years (long narrow line). By understanding upstream migration,
recommendations for migratory pathway and population restoration can be applied
globally for tropical amphidromous species.
Secondly, habitat template, discharge, habitat flow, and macroinvertebrate insect
indices were evaluated within riffle and cascade microhabitats upstream and downstream
of the highest elevation diversion in four streams of the West Maui Mountains. A
significant 44% reduction in macroinvertebrate density downstream of diversions was
found when streams and sites were pooled (p = 0.0009, df = 1, F = 11.49). Microhabitat
had a significant effect on the ratio of native to introduced taxa densities, with the
amphibious splash zone home to significantly more endemic taxa compared to riffles.
Non-native taxa were dominant (> 95% by density) and ubiquitous in riffle habitats. Our
findings contribute to ongoing water management and restoration efforts focused on the
conservation of native species and habitat integrity in tropical streams worldwide.
Finally, in the Little Miami River, Ohio, the physical template and
macroinvertebrate community were compared between riffle and run habitats. Mean
flow velocity and macroinvertebrate densities were significantly greater in riffle (Flow:
mean ± SE = 0.74 ± 0.04 m/s; Density: 1892 ± 200.2) than run (Flow: 0.32 ± 0.01 m/s;
Density: 540.3 ± 76.8) habitats. Linear regression found a positive and significant
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relationship (y = 4097x – 115.1, p < 0.0001) where 49% of variation in macroinvertebrate
density was explained by mid-column velocity. Our results call for the need of future
analyses using simple and complex hydraulic variables to accurately predict the
distribution of invertebrate communities.
In conclusion, comprehensive understanding of how flow variation affects stream
ecosystems is necessary for the development of future management practices that
promote balance between economic and environmental benefits.
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Dedicated to my parents, Fred and Anne Jennings,
who have encouraged me to seize every opportunity, supporting me with excitement and
enthusiasm, and showering me with unconditional love.
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ACKNOWLEDGMENTS
I have had the pleasure of interacting with wonderful people throughout this
doctoral graduate program, each impacting my life in a profound way. It’s amazing
where life takes you, and I’m fortunate to have had this wonderful experience. Family,
friends and colleagues have made it all possible, contributing immensely to this final
product. Whether it was support at home, another warm body in the field, hours spent
picking bugs at the microscope, or good laughs to ease the frustration; my relationships
with others have made this achievable.
I am deeply grateful to my two advisors, Drs. Albert Burky and Eric Benbow.
They have shown me the world, taught me invaluable life lessons, dedicated hours and
hours to me – talking, teaching and helping me better my critical thinking and writing
skills, all the while developing a friendship that will always be true. You are two of the
most outstanding and important men in my life. Thank you to my Graduate Advisory
Committee – Drs. Carl Friese, Karolyn Hansen, Mark Nielson, Mollie McIntosh, and
Kelly Williams. I appreciate the continued guidance and time they gave to developing
me as a contributing scientist. I would also like to express thanks to the University of
Dayton Graduate School and Biology Department for their financial assistance, providing
teaching and travel opportunities, and maintaining a successful graduate program.
Going through it together, I’d like to thank my fellow graduate students who
provided much camaraderie – especially Casey Hanley, Andy Lewis, Rachel Barker, Jen
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Lang, Tracy Collins, and Elizabeth Rhodes. A special and sincere thanks to my sidekick,
partner in crime and friend through it all, Megan Shoda. Her positivity, intellectual
insights, brute strength, and smiles made all the difference. The endless hours together –
in the stream, at home, driving the stream mobile, and of course in the lab sitting around
our microscopes, were more than enjoyable. Fortunate for me, she saved me from wild
dogs and bioluminescent algae scam artists, and the GIS expertise she provided has
always been top notch.
My fieldwork and the laboratory aftermath would not have been humanly possible
without the help of numerous undergraduates. Thank you to Doug Vonderhaar, Tiffany
Blair, Jon White, Carolyn Teter, Maggie Ernst, Ryan Lemier, Ryan Andrews, Allison
Gansel, Ian Barron, Gustavo Diaz, Elise Grotehouse, Jack Farrely, Jessica Teater,
Charlotte Perko, John Kurzawa, Liz Grazdick, and Melanie Aldaharian. I am grateful for
the time and effort they put into my work. Their extra hands and eyes, and more
importantly their companionship, made the cold mornings in the stream, long sampling
days, and crowded lab benches in 226, quite memorable. It was a pleasure working with
each one of them and I wish them all a wonderful future.
Finally, my family has given me the strength to always keep going. Thank you to
my husband, John, because while he doesn’t always ‘get it’, he loves and supports me
everyday, gently pushing me to get it done! My mom, sister, two brothers and their
families have been by my side every step of the way – showing interest in my passion,
trusting in my travels, helping with Charlie and around the house so I could get work
done, and loving me no matter what. I am truly grateful.
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TABLE OF CONTENTS
ABSTRACT……………………………………………………………………….... iv
DEDICATION……………………………………………………………………... vii
ACKNOWLEDGMENTS…………………………………………………………. viii
LIST OF FIGURES………………………………………………………………. xiii
LIST OF TABLES………………………………………………………………... xv
CHAPTERS
I.
INTRODUCTION & LITERATURE REVIEW……………………….1
Introduction………………………………………………………… 1
Literature Review………………………………………………….. 3
References………………………………………………………….. 15
II.
DISPERSAL AND UPSTREAM MIGRATION OF AN AMPHIDROMOUS
NERITID SNAIL: IMPLICATIONS FOR RESTORING MIGRATORY
PATHWAYS IN TROPICAL STREAMS……………………………..20
Summary…………………………………………………………… 20
Introduction…………………………………………………………22
Methods……………………………………………………………. 25
Results……………………………………………………………… 31
Discussion ………………………………………………………….33
Acknowledgments ………………………………………………….39
Tables………………………………………………………………. 41
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Figures………………………………………………………………50
Appendices………………………………………………………….54
References………………………………………………………….. 63
III.
VARIABILITY IN HABITAT TEMPLATE AND BENTHIC COMMUNITY
RESPONSE TO ANTHROPOGENIC WATER REMOVAL IN TROPICAL
MOUNTAIN STREAMS.……………………………………………...69
Abstract……………………………………………………………..69
Introduction ………………………………………………………...70
Methods …………………………………………………………….74
Results ……………………………………………………………...79
Discussion ………………………………………………………….85
Acknowledgments ………………………………………………….91
Tables………………………………………………………………. 92
Figures……………………………………………………………... 97
References………………………………………………………….. 106
IV.
BENTHIC COMMUNITY STRUCTURE UNDER DIFFERENT FLOW
AND SUBSTRATE CONDITIONS IN THE LITTLE MIAMI RIVER,
OHIO…………………………………………………………………...112
Abstract……………………………………………………………..112
Introduction…………………………………………………………113
Methods……………………………………………………………..115
Results………………………………………………………………118
Discussion…………………………………………………………..121
Figures………………………………………………………………124
References………………………………………………………….. 131
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FUTURE DIRECTIONS………………………………………..…………………. 135
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LIST OF FIGURES
Note: Titles have been abbreviated.
CHAPTER II
Figure 1: Map of the Hawaiian Islands with Maui and study streams identified ........50
Figure 2: Individual snail captures made during each treatment ! 16 days after
release plotted on an x, y coordinate system (release point = 0,0)................................51
Figure 3: Mean (SE) Euclidean migration rates (EMR; black bar) and Upstream
migration rates (UMR; white bar) between treatment conditions. ...............................52
Figure 4: a) Mean upstream migration rate (UMR) over all initial (! 6 days)
search days for each treatment. b) Mean (SE) upstream migration rates for RF, NF
and NF+D treatments with captured snails that traveled ! 8m in ! 6 days, pooled
longer-term captures made 16, 33 and 63 post-release, and ‘rapid’ snail captures
that traveled " 8m in ! 6 days.......................................................................................53
CHAPTER III
Figure 1: Map of West Maui, Hawaii, with study watersheds highlighted and
corresponding study locations as black dots.................................................................97
Figure 2: Mean (SE) measured discharge in all streams, upstream and downstream
of the highest elevation diversion. ................................................................................98
Figure 3: Mean relative percent of available habitat within the upstream and
downstream 100 m study reaches. ................................................................................99
Figure 4: a) Mean (SE) riffle macroinvertebrate non-corrected density and b)
mean (SE) habitat-corrected density for upstream and downstream reaches within
each stream....................................................................................................................100
Figure 5: Mean (SE) macroinvertebrate density between riffle habitat and
amphibious and torrenticolous microhabitats of cascades upstream and
downstream of diversions, with all streams pooled. .....................................................101
Figure 6: Community composition of riffle, torrenticolous and amphibious
habitats for all streams and sites pooled. ......................................................................102
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Figure 7: Mean (SE) macroinvertebrate density for habitat and location upstream
and downstream of the highest elevation diversions of all streams (data pooled)........103
Figure 8: Index of Nativity (ratio of native taxa density to introduced taxa density)
for each habitat and location upstream and downstream of the highest elevation
diversion in each stream (data pooled). ........................................................................104
Figure 9: NMDS ordination with habitat overlay. ........................................................105
CHAPTER IV
Figure 1: Hydrograph depicting mean daily discharge (m3/s) for the Little Miami
River (USGS gage 03240000), near Oldtown, Ohio from May through September
2008...............................................................................................................................124
Figure 2: Riffle and run habitat substrate particle size frequency distribution............125
Figure 3: Mean (SE) flow velocity measured at each benthic sample in the riffle
and run habitats. ............................................................................................................126
Figure 4: Mean (SE) macroinvertebrate density for habitat and sampling time..........127
Figure 5: Linear regression relationship between mid-column velocity (m/s) and
macroinvertebrate density.............................................................................................128
Figure 6: Community composition of riffle and run habitats for all sites pooled........129
Figure 7: NMDS ordination with habitat overlay. .......................................................130
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LIST OF TABLES
Note: Titles have been abbreviated.
CHAPTER II
Table 1: Shell length, width and height of Neritina granosa collected from
Honomanu Stream, Maui, Hawaii. ...............................................................................41
Table 2: Habitat and hydraulic variables for each treatment during Neritina
granosa migration in Iao Stream, Maui, Hawaii. .........................................................42
Table 3: Three types of snail capture data. ..................................................................44
Table 4: Snail Upstream Migration Rate (UMR as m d-1), under historic
discharge quantiles, Q50, Q70, Q90, and minimum discharge needed to reach the
ocean ............................................................................................................................46
Table 5: Migration as described in previous published studies compared to results
of the current study. ......................................................................................................47
CHAPTER III
Table I: Two-way ANOVA statistics for physical habitat template characteristics
and macroinvertebrate density and diversity for the riffle habitat. ..............................92
Table II: Mean (± SD) density of represented macroinvertebrate taxa in the riffle
habitats among the study streams and between upstream and downstream of
diversion........................................................................................................................94
Table III: Two-way ANOVA statistics for the Index of Nativity for each
microhabitat and site within each stream......................................................................96
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CHAPTER I
INTRODUCTION & LITERATURE REVIEW
INTRODUCTION
The importance of flow to the ecology of aquatic benthos is unquestionable in
lotic ecosystems (Nowell & Jumars 1984). The integrity of these freshwater habitats
depends on how various benthic species assemble into structural communities, provide
ecosystem functions and contribute to complex food webs (Covich et al. 1999). Benthic
organisms, also known as macroinvertebrates, include crustaceans, gastropods and
aquatic larval and pupal forms of terrestrial insects that reside on and within the stream
substrate. Through the use of macroinvertebrates, physical-biological coupling can aid
our understanding of the dynamic organization of the ecological structure of streams and
rivers.
The literature review and experimental work presented throughout the following
chapters indicate the importance of riverine hydraulic variables in governing habitat
template characteristics and spatial distribution of benthic organisms. Developing a more
complete understanding of how spatial and temporal flow variation affects the structure
and function of stream ecosystems will provide deeper insight into ecological
organization, improve our ability to predict how flow alterations caused by human
activities affect these vital ecosystems, and guide water management practices that would
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achieve a better balance between economic and environmental benefits (Hart & Finelli,
1999).
Although the dissertation work was completed in two different locations –
tropical island and temperate continental freshwater streams – unifying ecological themes
permeate throughout such as Community Ecology, Disturbance Ecology, Hydraulic
Stream Ecology, and the potential application of Conservation and Restoration Ecology.
The tropical island stream studies, presented in Chapters II and III, were carried out in
four streams of the West Maui Mountains on Maui, Hawaii. They investigated the effects
of anthropogenic stream flow removal on macroinvertebrate community composition and
upstream migration rate of a native neritid snail. Our findings are of timely importance
due to a recent legal battle regarding the return of water to the streams under study.
Experimental efforts in the temperate continental stream, the Little Miami River, in
Dayton, Ohio, presented in Chapter IV, examined the spatial distribution of
macroinvertebrate communities between habitats of differing flow conditions and habitat
template characteristics. The current conclusions and those gathered through the
completion of future analyses can contribute substantially to fundamental knowledge of
Stream Ecology.
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LITERATURE REVIEW
Part 1: Review of flow effects on benthic organisms
The role of macroinvertebrates in stream ecosystems
Benthic invertebrates (i.e. macroinvertebrates) are abundant and typically diverse
in freshwater sediments. While macroinvertebrates are ideal biological indicators of
overall stream health and integrity (Rosenberg 1993), their functional importance
generally goes unnoticed until unexpected changes occur in ecosystems (Covich et al.
1999). They play a fundamental role in the biological community and food web of
aquatic ecosystems, serving as food for fish and facilitating ecosystem functions such as
sediment mixing, nutrient cycling and energy flow. Each species is uniquely important,
adapted to functioning under variable conditions and performing distinct ecosystem
services; the addition or loss of a single species can dramatically alter food web dynamics
(Covich et al. 1999).
Effects of flow
Flow is recognized in running water ecology as the fundamental abiotic factor
controlling ecological processes and patterns in stream ecosystems (Hart & Finelli 1999).
The natural flow regime is the range and variation of flows over recent historical time,
and sets the template for contemporary ecological processes (Resh et al. 1988, Doyle et
al. 2005), evolutionary adaptations (Lytle & Poff 2004), and native biodiversity
maintenance (Bunn & Arthington 2002, Poff & Zimmerman 2010). Streams are known
to provide patchy landscape where hydraulic and structural heterogeneity have been
proposed to be major determinants of macroinvertebrate community organization.
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Small-scale differences in hydraulic conditions created by combinations of
velocity, depth and substrate roughness play an important role in the spatial distribution
of macroinvertebrates in riffle habitats (Brooks et al. 2005). As summarized by Hart &
Finelli (1999), flow affects the ecological processes of benthic organisms directly or
indirectly through multiple causal pathways. Processes affected include dispersal, habitat
use, resource acquisition, competition, and predator-prey interactions (Hart & Finelli
1999). Not only are organisms influenced individually, but also hydraulic characteristics
affect entire assemblages (Statzner et al. 1988).
Many of the flow forces and processes affecting benthic organisms (i.e. drag, lift,
diffusivity, and mass transfer) vary as a function of velocity (Denny 1993, Vogel 1994,
Hart & Finelli 1999) and thus, flow characteristics related to velocity are often considered
as having the greatest relevance. The problem with “mean velocity” is that it is only one
characteristic of moving water and can hardly be used to comprehensively explain the
physical environment experienced by the organism (Statzner et al. 1988). Flow in a
natural channel is three-dimensional which means that each fluid particle may travel in
the upstream—downstream direction, from bank to bank and from bottom to surface
(Statzner et al. 1988).
Not only is flow multi-dimensional, but flow conditions experienced by benthic
organisms differ from those experienced farther above the stream bed due to the presence
of a velocity gradient, or the “boundary layer,” which is created by friction between the
moving water and the stationary bed (Nowell & Jumars 1984, Statzner et al. 1988, Hart
& Finelli 1999). Many invertebrate taxa are constrained by these near-bed flow
conditions, living within this layer where turbulent flows are highly irregular,
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unpredictable and uniquely dependent on the shape, size and arrangement of roughness
elements (Dolédec et al. 2007). Unfortunately, such complex topography makes it
extremely difficult and currently impossible to predict near-bed velocities using simple
formulae such as the log-linear relationship between velocity and height above the bed
(Nowell & Jumars 1984, Hart & Finelli 1999).
Habitat preferences of benthic organisms
Hydraulic preferences of lotic invertebrates can be explained by tradeoffs between
energy costs and oxygen consumption, biotic interactions and the ability to colonize
habitats (Phillipson 1956, Edington 1968, Peckarsky et al. 1990, Doledec et al. 2007,
Fonseca & Hart 2001). While previous studies have shown that habitat preferences are
influenced by flow conditions (Merigoux & Dolédec 2004), specific relationships have
not been addressed that could be used to confidently predict habitat preferences (Benbow
et al. 1997). Benbow et al. (1997) found a significant relationship between water microflow parameters in torrential benthic habitats where chironomid larval density was
inversely correlated with depth and positively correlated with bottom velocity. In this
study, the heterogeneity of the substrate and the near bottom water flow were found to
interact to produce areas of flow refugia affecting species abundance, distribution, and
habitat availability. A similar study of blackfly larvae determined that the current speeds
measured 10 mm above the bed were poor predictors of speeds measured at 2 mm,
limiting our understanding of the quantitative and qualitative importance of flow to
benthic stream organisms (Hart et al. 1996). Further, blackfly larvae have been observed
positioning their body below the boundary layer, while extending their filter feeding
structures in the high velocity flow (Hart et al. 1996).
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Hydraulic preferences may also be identified and explained through
morphological and behavioral observations of these organisms. Many benthic organisms
lower the risk of dislodgement by reducing the drag force experienced with a streamlined
body shape or a smaller size, which allows them to inhabit zones of greatly reduced
velocities. They may also have specialized structures or modify their position with the
flow to avoid dislodgement. In contrast, some benthic organisms actively expose
themselves to flow for dispersal. This has been documented where the rate at which
black fly larvae enter the water column decreases with increasing water velocity (Hart,
1999). It has also been shown that larval simuliids (Chance & Craig 1986), various
pulmonate snails (Dussart 1987), dorsoventrally flattened insects and streamlined limpets
(Smith & Darnall 1980, Statzner & Holm 1982, McShaffrey & McCafferty 1987)
negotiate rather complicated flow and consequently endure the forces of flows (Statzner
et al. 1988).
Exploring these linkages between the organism and the abiotic environment,
specifically hydraulic preferences, is required prior to developing predictive models
regarding the structure and function of ecosystems. Such information will allow
quantification of flow regimes necessary for maintaining biotic and abiotic processes
within stream ecosystems (Dolédec 2007, Hart & Finelli 1999).
Part 2: Anthropogenic disturbances in stream ecosystems
Modification of the flow regime
Disturbance of river communities has been a central focus in the growth of lotic
science, with much thought given to defining and quantifying disturbance in systems that
are inherently dynamic (Resh et al. 1988, Poff 1992, Kinzie et al. 2006). Disturbance can
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arise from many sources, but most attention has been devoted to disturbances resulting in
changing the flow conditions of a river (Kinzie et al. 2006). These hydrological
modifications include any anthropogenic disruption of flow in terms of magnitude,
frequency, duration, timing or rate of change of timing; thus changing the natural flow
regime (Standford et al. 1996, Hart & Finelli 1999, Rosenberg 2000, Poff & Zimmerman
2010) and impacting the physical, chemical and biological structure and function of
rivers and streams (Ward & Standford 1983, Allan 1995).
Ecosystems worldwide are threatened by demands on freshwater resources due to
increased population growth and consumption (Postel 1997, Benstead et al. 1999, March
et al. 2003). To account for these demands, many streams and rivers have undergone
hydrological alterations such as dams and surface-water diversions, stream
channelization, and intercatchment water transfer (Rosenberg et al. 2000, Dudgeon 2000,
Baker et al. 2011). Alterations can occur simultaneously at different scales, such as
landscape (watershed), stream reach and microhabitat. For example, urbanization (a
landscape scale process) is typically accompanied by channelization and the removal of
riparian canopy cover (a reach scale process), resulting in higher water temperatures,
increased daily temperature fluctuations, increased siltation, and decreased substrate size
(microhabitat scale processes) (Brasher 2003).
In a review by Poff & Zimmerman (2010) of 165 studies that reported either
aquatic or riparian responses to flow regime alteration, 92% of the studies found negative
ecological changes in response to a variety of types of flow alteration. These
modifications can include decreased flow and changes in the riffle – run sequence of
streams, thus altering available habitats and species composition. Such consequences
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include changes in species distribution, abundance, composition and diversity of aquatic
communities, recruitment failure and loss of native species, isolation of populations and
local extinction, and the invasion and success of exotic and introduced species (Bunn &
Arthington 2002).
Knowledge of how organisms colonize and persist in a habitat after such
disturbance can provide insight into the impact of human processes on natural systems
(Dolédec et al. 2007). Thus, a better understanding of physical-biological coupling in
streams will enhance our ability to predict how flow alterations caused by various human
activities affect these vital system, advance efforts to restore structure and function, and
enable solutions to some of our most pressing environmental problems (Hart & Finelli
1999).
Stream diversions in the Hawaiian Islands
While freshwater ecosystems worldwide are threatened by increased demands on
freshwater resources, tropical stream habitats are undergoing substantial alteration as
human population increases and watersheds become far different from those that once
sustained native stream communities (Brasher 2003). Streams throughout the tropics
have been altered by water diversion, channel modification, introduced species and water
quality degradation (Brasher 2003). The impact of water removal and subsequent changes
within the aquatic ecosystem have been extensively studied in temperate regions;
whereas, relatively little research has been conducted in tropical regions leaving these
ecosystems and human impacts poorly understood (Benke et al. 1988, Flowers 1991,
Jackson & Sweeney 1995).
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This is especially true of tropical islands, such as Hawaii, where freshwater
resources are naturally limited to surface streams and groundwater supplied by heavy
tropical rains (Fitzsimons et al. 1997, Brasher 2003, March et al. 2003). To original
Hawaiian civilizations, water resources were culturally important and used in native
practices of taro cultivation and habitat to native stream macrofauna, such as fish, shrimp,
snails and prawns that were harvested as a food source. However, through Western
colonization and associated development of large-scale commercial sugarcane plantations
in the mid-1800s, stream diversions and extensive tunnel transport systems were built to
translocate water from the wet, windward watersheds to the dry leeward areas of growth
and development. At least 58% of the estimated 366 perennial streams had experienced
some type of streamflow alteration by 1978, with water being exploited for
anthropogenic uses, such as agriculture, development and tourism (Parrish et al. 1978,
HCPSU 1990).
Many of these diversions remove 90 – 100% of base flow volume, altering the
natural flow regime which is important for sustaining native biodiversity and ecosystem
integrity (Wilcox 1996, Poff et al. 1997, Benbow 1999, McIntosh et al. 2002, Brasher
2003, McIntosh et al. 2008). During major precipitation events, water may breech some
diversions; however, the quantity and magnitude of the flood events are reduced
compared to natural conditions. Diversions can have serious impact on native,
amphidromous organisms by disrupting larval drift to the ocean and obstructing
postlarval recruitment (return migration) by reducing or eliminating flow downstream
(Timbol & Maciolek 1978, Kinzie 1990). Disruption of this lifecycle could significantly
lower the number of breeding populations of these native Hawaiian species. Removal of
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stream flow can also result in alterations in downstream habitat subsequently altering the
physical and chemical conditions that regulate biological communities; thus, limitations
in habitat availability may shift species interactions, eliminate native and introduced
aquatic species, potentially increase the number of invasive species, and alter the entire
food web (Cowx et al. 1984, Poff et al. 1997, Brasher 2003). This is of particular concern
in Hawaii because of several native and endemic species that are sensitive to changing
environmental conditions and introduced species (Shoda et al. 2010).
Na Wai Eha Watershed
The ecosystems under study are of great interest and have been the topic of a
heated debate. In 2004, on the island of Maui, an initiative by local interest groups, in
cooperation with government agencies began efforts to determine interim stream flow
levels for the N! Wai ‘Eh!. The N! Wai ‘Eh! is considered the four major watersheds of
the West Maui Mountains (Waikapu Stream, Iao Stream, Waiehu Stream and Waihe’e
River). One of the major objectives of this effort was to determine adequate flow
volumes necessary to support healthy stream biological communities. It is understood
that water must be returned to these streams to again provide a continuum of stream flow
and habitat for aquatic organisms; however, it is the minimum amount of stream flow
needed to maintain reproductive populations that remains unknown. Tentative
restoration plans include controlled releases for a final restoration level equal to the
estimated long-term minimum daily mean flow. However, in order to understand
biological responses of these aquatic communities, baseline data on these amphidromous
and non-amphidromous invertebrate communities under historic diverted conditions is
needed.
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Water Management Initiatives
Increasing demands for water in the state of Hawaii have put tremendous pressure
on water managers who require a sound basis for making water allocation decisions
(DAR 1996, Kinzie et al. 2006). Of particular interest is the importance of naturally
occurring flow variability which influences channel maintenance, clearing of debris
dams, promotion of migration and movement of amphidromous species, cues for
reproductive cycles of stream organisms, enhancement of primary or secondary
production, control of alien species, provision of habitat heterogeneity, and maintenance
of benthic communities (March et al. 2003, Brasher 2003, Kinzie et al. 2006). Because
flow in many Hawaiian streams is presently diverted (Timbol & Maciolek 1978, Wilcox
1996), understanding human impacts on flow in stream systems is critical for
management and mitigation (HCPSU 1990, March et al. 2003, Kinzie et al. 2006).
The task of determining minimum flows necessary to prevent detrimental effects,
while fulfilling freshwater needs, has become a popular, yet difficult task for water
resource managers (Bunn & Arthington 2002, Dewson et al. 2007). Total elimination of
dams and water diversions in tropical streams is not an appropriate solution, instead,
impacts can potentially be reduced through various structural and operational changes
such as increased minimum flow, installation or improvement of fish and shrimp ladders
and periodic releases of flushing flows (March et al. 2003, see Bednarek & Hart 2005). If
ecological structure and function is to be restored and maintained to stream networks,
water-conservation strategies and a strong commitment to sustainable use of water
resources must be implemented, especially on tropical islands where freshwater resources
are already limited and endemism is high (Smith et al. 2003). In the last decade, it has
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become increasingly evident that conserving aquatic ecosystems while balancing the
anthropogenic need for freshwater is a pressing issue around the world – urging a deeper
understanding of the direct and indirect impacts of flow modifications on aquatic
communities and overall ecosystem services, for the development of effective
management strategies (Power et al. 1996, Jackson et al. 2001, Baron et al. 2002, Brasher
2003).
Part 3: Tropical vs. temperate streams
The ecology of insular tropical stream and river drainages are not well
understood. Most tropical streams differ significantly from those found on continents by
having relatively short, straight and steep channels in comparatively small, narrow
watersheds (Smith et al. 2003). Temperate streams are more seasonally driven whereas
tropical stream networks tend to be more event-driven, which may be relatively
unpredictable (Smith et al. 2003). Although extensive research has documented the
impacts of hydrologic alterations on biotic communities in temperate systems, far less is
known about biotic responses to hydrologic modifications in tropical systems (Pringle et
al. 2000, Smith et al. 2003).
It is not yet clear how the concepts derived from studies of continental stream
ecosystems in the temperate zone can be effectively applied to understand and manage
streams and rivers on islands in tropical areas (Smith et al. 2003). There is a growing
recognition, from studies of both temperate continental and tropical insular ecosystems,
of the importance of conserving the biological resources of watersheds as well as the
other “ecosystem services” they provide such as a clean water supply, fishery resources,
and recreation (Smith et al. 2003). The demand on the freshwater resources provided by
12!
!
these island watersheds is especially critical as this demand will continue to increase due
to fast growing populations, which may ultimately transform and irreversibly alter these
ecosystems (Brasher 2003, March et al. 2003, Smith et al. 2003).
Comparison among stream systems is necessary because the vast amount of
research undertaken on north temperate streams has given rise to ecological models (i.e.
the River Continuum Concept: Vannote et al. 1980; the Riverine Productivity Model:
Thorp & Delong, 1994) that are now being used to guide research questions and
management approaches in rivers worldwide (Boulton et al. 2008). Evaluations between
temperate and tropical streams are confounded by immense variability inherent in these
systems, and the wide range of climatic, geomorphology and hydrological conditions that
may generate a habitat template for ecological differences (Boulton et al. 2008). Further,
understanding diversity differences have been hampered by the imbalance in research
between these climatic zones. For example, lists of species are scarce for the tropics –
especially for macroinvertebrates – and the identification of tropical species has been
difficult for non-specialists (Boulton et al. 2008).
While these systems may not be routinely compared in singular studies, Boulton
et al. (2008) summarized in a review of the literature, that there were no consistent
differences in food web structure, productivity, organic-matter processing or nutrient
dynamics, and response to disturbance between tropical and temperate systems and that
the adjective ‘tropical’ has no particular significance when applied to stream ecology.
Instead, ecological processes in tropical streams tend to be driven by the same variables
that are important in temperate ones. Consequently, valid extrapolation of models and
management strategies may not be so much an issue of latitude (tropical vs. temperate)
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!
but of ensuring suitable comparability at an appropriate scale. However, this review
clearly demonstrated that whereas ecological mechanisms may be similar, the organisms
involved can and do differ (Boulton et al. 2008).
Similarly, Greathouse & Pringle (2006) investigated the application of the river
continuum concept on a tropical island stream and found that while collector-filterers
showed a trend opposite to that predicted by the model, patterns in basal resources
suggest that this was consistent with the central theme: longitudinal distributions of FFGs
follow longitudinal patterns in basal resources. Their results indicated that the river
continuum concept generally applies to tropical streams, however they concluded that
additional theoretical and field studies across a broad array of stream types was necessary
to examine whether the river continuum concept needs to be refined to reflect the
potential influence of top down trophic controls on FFG distributions (Greathouse &
Pringle 2006).
Although these studies have begun to investigate the relationship between tropical
and temperate stream systems, further comparative studies are necessary to understand
the application of ecological models in tropical systems. Further, there is a growing need
to establish more unified themes of research, management and conservation in tropical
stream ecosystems (Smith et al. 2003).
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CHAPTER II
DISPERSAL AND UPSTREAM MIGRATION OF AN AMPHIDROMOUS NERITID
SNAIL: IMPLICATIONS FOR RESTORING MIGRATORY PATHWAYS IN
TROPICAL STREAMS
With kind permission from Wiley-Blackwell publishing
K.R. Gorbach, M.E. Benbow, M.D. McIntosh, A.J. Burky (2012). Dispersal and
upstream migration of an amphidromous neritid snail: implications for restoring
migratory pathways in tropical streams. Freshwater Biology, 57, 1643-1657.
SUMMARY
1. The amphidromous lifecycle of several species of neritid snails, shrimp and gobies
throughout the tropics includes juveniles that migrate from the ocean to breed in fresh
water. In many Hawaiian streams, the decline of Neritina granosa, an endemic gastropod,
has been associated with habitat degradation and water withdrawal, which are common
factors affecting tropical rivers around the world.
2. We investigated the effects of water withdrawal and density on dispersal and upstream
migration of N. granosa using three experimental treatments: 1) reduced flow due to a
stream diversion, 2) natural flow, and 3) natural flow with artificially increased snail
density. For each treatment snails were differentially tagged and released in a stream
without a natural, extant population of N. granosa.
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3. Capture rates ranged from 17 – 65% over a 63-day period following release. Captures
on 2 – 6 days after release measured initial dispersal and migration, whereas longer-term
migration rates were calculated from snails captured 16 – 63 days after release. Snails
under natural flow displayed positive rheotactic behaviour, with only 3 – 12 %
demonstrating initial downstream movement. Under reduced flow 22 – 77 % of snails
moved downstream or showed no bias either way.
4. Initial mean upstream migration rate was 0.25, 0.66 and 1.16 m d-1 under reduced
flow, natural flow and natural flow with increased snail density, respectively. Longerterm migration rates did not differ significantly among treatments and the overall mean
was 0.62 m d-1.
5. Principal component analysis and generalized linear models were used to identify
habitat characteristics important to upstream migration rate, with habitat and reach-scale
hydraulics as the most important factors. The relationship between discharge and
upstream migration rate suggested it would take 11 – 35 years for snails to migrate past
the most upstream water diversion. However, rates from published studies of neritid snail
species migrating en masse or in long lines under natural situations, suggested that N.
granosa could migrate above stream diversions within 72 days to 2.5 years (when in an
aggregation) and 29 days to 1.1 years (when following in long lines).
6. An understanding of upstream neritid snail migration can be used for management and
conservation of this and other migratory species in tropical streams.
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INTRODUCTION
Dispersal, and often migration, is an essential component of the life history and
ecological niche of many organisms (Dingle & Drake, 2007). Migration has been
documented for gastropod snails in tropical (Paulini, 1963; Ford & Kinzie, 1982;
Schneider & Frost, 1986; Wallace, 1992; Blanco & Scatena, 2005, 2006, 2007; see Pyron
& Covich, 2003), temperate (Bovjberg, 1952; Ball, Wojtalik & Hooper, 1963; Houp,
1970; Mancini, 1978; Burris, Bamford & Stewart, 1990) and intertidal habitats (Garrity
& Levings, 1981; Crowe, 1996). Migration from the ocean into fresh water occurs in two
subclasses, three orders and 10 gastropod families (Hutchinson, 1967; Graham, 1985;
Huryn & Denny, 1997).
Many migratory taxa move between marine and fresh water to complete their
lifecycle, dominating tropical island systems in numbers and biomass (Gross, Coleman &
McDowall, 1988; Blanco & Scatena, 2007). More unusual is the amphidromous lifecycle
of several decapod crustaceans, neritid snails and gobiid fishes of Oceania, the
Neotropics, Indomalaya, Japan and New Zealand (Benbow & McIntosh, 2009;
McDowall, 2004 & 2007). This lifecycle is a type of diadromy where adults live, breed
and deposit eggs in streams; upon hatching, planktotrophic larvae drift to the ocean where
they grow and develop, after which postlarvae move back into stream mouths and begin
an upstream migration to the adult habitat where they mature and breed (McDowall,
1998, 2004, 2007; Hodges & Allendorf, 1998; Crandall et al., 2010). Migration has been
described as movement that is regular in terms of season, direction and life stage, and
where the organisms occupy two distinct and well-separated habitats (see McDowall,
2007).
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Neritina granosa (Sowerby) is an amphidromous endemic Hawaiian gastropod
found on bedrock, boulders and large gravel in clear, cool, well oxygenated, and fast
flowing perennial streams (Ford, 1979). After the pelagic larval stage, spat (snail
postlarvae ! 5 mm in shell length) settle at a stream mouth and begin an upstream
migration until finding adult habitat (Ford, 1979; Way et al., 1993; Hau, 2007). During
the upstream migration, spat (! 5 mm) and juveniles (" 6 mm) grow to about 9 mm over
several months; growth then continues at a rate of 1 – 3 mm y-1, slowing until they reach
a mean maximum adult length of 29 mm (Brasher, 1997). Ford (1979) suggested a 10year life span, while studies undertaken by Brasher (1997) implied a 6 – 10 year life span.
However, we recovered tagged snails in Kinihapai Stream, Maui in 2009 that were
released in 1994, confirming a potential life span > 10 years (Benbow, unpublished).
Migrating spat, juveniles and other pre-adults of N. granosa remain on the underside of
rocks by day, feed nocturnally, and usually inhabit areas of strong flow. However, adults
can be found in pools mating and grazing during the day (Maciolek, 1978). Brasher
(1997) proposed that smaller snails (! 9 mm) are the migrating stage, while adults lose
the rheotactic response.
Upstream migration of neritid snails has attracted much research attention
(Schneider & Frost, 1986; Schneider & Lyons, 1993; Blanco & Scatena, 2005 & 2007). It
has been suggested that migration relates to the search for food and space (Paulini, 1963),
predator avoidance (Gross et al., 1988; Schneider & Lyons, 1993; Blanco-Libreros &
Arroyave-Rincón, 2009), a response to accidental downstream drift (Carpenter, 1928;
Schneider & Frost, 1986), constraints imposed by body architecture and hydrodynamics
(Haynes et al., 1985; Way et al., 1993; Huryn & Denny, 1997), the availability of
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23
breeding sites (Söderström, 1987) and variation among adults and juveniles in tolerance
of physical factors such as salinity and temperature (Pyron & Covich, 2003). Further,
seasonal change, channel substratum, distance from the ocean, flow hydraulics and water
depth may affect migration at different spatial scales (Way et al., 1993; Pyron & Covich,
2003; Blanco & Scatena, 2005). Massive upstream snail migration has been hypothesized
to be density and body size dependent; spat and juvenile forms (generally ! 9 mm in
length) have been observed to move together in long lines and/or dense aggregations
(Schneider & Frost, 1986; Schneider & Lyons, 1993; Brasher, 1997; Pyron & Covich,
2003; Blanco & Scatena, 2005; Hau, 2007). In Puerto Rico, Blanco & Scatena (2006 &
2007) concluded that younger snails prefer fast, turbulent and erosive habitats, and that
densities were greater in deep habitats with heterogeneous substrata thus indicating that
migration might ultimately be influenced by stream discharge and channel hydraulics.
Diversions and dams are responsible for modified flow regimes, fragmented
populations, obstructed breeding migrations and the loss of navigational cues and
endemic species in tropical streams (Drinkwater & Frank, 1994; Benstead et al., 1999;
Pringle et al., 2000; Dudgeon, 2003). Further, natural amphidromous populations are
important components of tropical stream communities but are profoundly affected by
altered flow regimes (McIntosh et al., 2002; Brasher, 2003). To our knowledge, this is
the first experimental field study using a transplant and monitoring approach to evaluate
the effects of stream diversions on the upstream migration of an amphidromous, neritid
snail, with application for stream management and conservation in other regions of the
world. Our objectives were to determine patterns of N. granosa spat initial dispersal and
upstream migration rates under reduced flow conditions and increased spat density. We
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24
hypothesized that reduced stream flow would negatively affect rheotaxis and initial
dispersal with ultimate consequences for migration rate and distance, while increased
snail density would have opposite effects. We also sought to understand the relationship
between amphidromous snail upstream migration rates and hydraulic habitat
characteristics and, further, to use published stream discharge data and neritid migration
rates to predict the time taken to migrate by tropical amphidromous neritid snails, for
application in catchment management and conservation.
METHODS
Snail collection & tagging
Neritina granosa were collected from Honomanu Stream, East Maui (Fig. 1).
While a diversion on this stream ~2.5 km upstream of the ocean usually results in a dry
streambed, a natural spring ~250 m upstream of the tidal influence maintains a wetted
channel at the stream mouth. A large number of N. granosa accumulate below this
spring, where we collected them for the transplant study.
On 11 June 2001, rocks were carefully lifted and N. granosa ranging from 2.6 –
7.0 mm in shell length, including spat (! 5mm) and young juveniles (6 – 7 mm), were
collected and placed in a cooler of stream water. Immediately following length and width
(±0.1 mm) measurements using an electronic caliper (Mitutoyo 700-103), 3.0 mm
coloured and numbered bee tags (The Bee Works, US; Canada) were applied with Super
Glue ® to 396 snails and allowed to air dry. Snails were returned to aerated buckets of
stream water at low densities resulting in little mortality (< 0.5%) and resumed a
nocturnal movement pattern (crawling in circles) for at least six hours before being
transplanted to the study stream. On 5 July 2001, an additional 2,600 snails were
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25
measured of which 198 were tagged using different colours from the previous release,
while 2,157 were left untagged (Table 1). In previous research, snails with these tags
have been recovered after >10 years; the tag numbers are often not legible, but are in
place and sometimes covered by nacreal shell formation that, when removed, reveals
number and colour (Benbow, unpublished). We monitored initial snail dispersal and
migration rates under three experimental treatments: 1) reduced flow conditions (RF) due
to a stream diversion, 2) natural flow conditions (NF) upstream of the diversion, and 3)
natural flow conditions with increased spat density (NF+D).
Release sites and treatments
The release sites were in Iao Stream, a 13.4 km second order stream, located in
the Wailuku catchment on the northeastern side of the West Maui Mountains, Hawaii
(Fig. 1). Iao Stream is diverted at three locations, withdrawing ~0.8 m s-1 for agricultural
and developmental purposes (Shade, 1997; Benbow, 1999). Stream flow breaches all
three diversions and flows to the ocean only after high rainfall (Oki, 2007; Oki et al.,
2010). Because of these diversions, constructed in the mid-1800’s, natural populations of
N. granosa were not found in the study reaches; this was tested in hundreds of personhours doing snorkel searches during the weeks before snail releases and for nearly six
years of prior routine surveys (Benbow, unpublished). The absence of natural populations
facilitated snail release and capture and also ensured no pre-existing slime trails could
affect movement and migration (Pyron & Covich, 2003; Hau, 2007). The NF and NF+D
release site was ~1.0 km above the highest altitude diversion while the RF site was
located ~100 m downstream of this diversion, where flow was reduced by 92 – 98% of
daily base flow (Fig. 1; McIntosh et al., 2002).
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26
On 12 June 2001, 198 tagged snails were released at both the NF and RF sites.
The NF study reach was on average 8 m wide and characterized by deep, fast and
turbulent flow, numerous riffles and cascade habitats, while the RF study reach was on
average 4 m wide and characterized by shallow and slow flow, infrequent riffles and
small shallow pools. On 13 July 2001 an additional group of 198 tagged plus 2,157
untagged snails was released under natural flow (NF+D) at the NF site. The release sites
in each study reach appeared similar – small pools along the bank in a 0.06 m2 area of no
flow, ~0.25 m in depth and protected from the thalweg. When standardized for benthic
area, the density of released snails was 3,168 m-2 for RF and NF treatments, and 37,680
m-2 for NF+D. Immediately after release, snails were observed for 15 minutes and then
the small pool was covered with a large, flat rock suspended above the water to provide
cover against birds.
Snail capture
We searched for snails on days 2, 3, 5, 6, 16, 33 and 63 after they were released.
Two to three trained researchers, adjacent to each other across the stream, worked
upstream searching under and around all substrata using facemasks and snorkels. When
large, immovable boulders were encountered, effort was made to feel in and around all
accessible surfaces and interstitial spaces to locate spat. Each observed snail was
considered a capture with its location marked by an x-y coordinate system, where the
origin (0,0) was the point of release, x the perpendicular distance to the bank of origin,
and y the parallel distance up- or downstream along the bank of origin; measurements
were made to the nearest 0.1 m using a tape measure stretched between a depth rod at the
capture point and a person on the adjacent bank. At each point, snail tag number and
!
27
colour, x-y coordinate, depth and water velocity using an Ohio Professional electronic
impeller flow meter (The Great Atlantic Trading Co. Ltd.) were recorded; measurements
were subsequently used to calculate Froude and Reynolds numbers (Statzner, Gore &
Resh, 1988). Unsafe stream conditions prevented search efforts on day 2 of the NF and
day 6 of the NF+D study periods. Captures made on days 2 – 6 after release were used to
determine initial dispersal and migration whereas longer-term migration rates were
calculated from captures made on days 16, 33 and 63 after release. Capture rates were
calculated as the percentage of the total number of snails released on the original date that
were found on a subsequent search day.
Discharge and water temperature were measured on each search day and the
volume of diversion flow removal was estimated by measuring discharge above and
below it using the velocity-area method (Gordon, McMahnon & Finlayson, 1992). In
addition, stream discharge data were retrieved from a U.S. Geological Survey gauge
(16604500) immediately upstream of the diversion. Because attempts to normalise data
were unsuccessful, Kruskal-Wallis non-parametric one-way analysis of variance
(GraphPad Prism 5.0 Software) was used to test habitat differences among treatments,
while Mann-Whitney tests were used when only two treatments could be compared (i.e.
unsafe stream conditions).
Initial snail dispersal and upstream migration
Snails could move in any direction from the release location, so for the purposes
of this study any upstream movement was considered migration. Initial snail dispersal
during days 2 – 6 after release was described as downstream, upstream or neutral
(remaining at release site) from the release location. Snails that moved up- or downstream
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28
not only moved parallel (y-coordinate) to the flow but also perpendicular to it (xcoordinate) as they dispersed. To represent the degree of snail aggregation, the coefficient
of variation (CV) of the total captured snail population movement along the x-axis was
compared among days and treatments: a low CV represented aggregation, while a larger
CV represented more independent movements. Further, over the six days after release,
the Euclidean distance between the re-captures of any particular snail was used to
calculate a Euclidean Migration Rate (EMR as m d-1). Movement parallel to stream flow
between re-captures defined an Upstream Migration Rate (UMR as m d-1). KruskalWallis non-parametric one-way analysis of variance with Dunn’s post-hoc tests and nonparametric two-way ANOVA with Bonferroni post-hoc tests for pairwise comparisons
were used (GraphPad Prism 5.0 Software) to test for differences in EMR and UMRs
among treatments and days. Mann-Whitney tests were used when data for all three
treatments were unavailable.
Snail movement that demonstrated rapid migration (" 8 m in ! 6 d, ‘rapid’ snails)
was estimated to provide a maximum upstream migratory potential not weighted by a few
individuals that affected initial movement and migration dynamics. To assess migration
beyond our initial 6 day period, mean longer-term UMRs were calculated from fewer
(N=31) captures made 16, 33 and 63 d after release. Differences in UMR among snails
that migrated ! 8 m in ! 6 days, the ‘rapid’ snails and the longer-term estimates were
tested using Kruskal-Wallis non-parametric one-way analysis of variance.
Migration – habitat relationship
The same habitat variables measured or calculated on each search date were also
used to evaluate the possible effect of previous habitat conditions encountered the day
!
29
before a re-capture. Several analytical steps were employed to test for relationships
between habitat variables and upstream migration rates to represent a gradient of
migratory conditions (Supporting Information, Appendix S1).
Application to restoration ecology of amphidromous migration
Although microhabitat characteristics may be more specific, overall stream
discharge is often readily available from gauging stations and may be a practical tool for
predicting upstream migration rates of amphidromous species. Measured mean daily
discharge was used to predict mean daily UMRs using simple linear regression. These
regression models were then used to predict migration rates under different quantiles of
published stream discharge conditions from 1985-2005 (Oki, 2007). The Q50, Q70, and
Q90 were determined using duration curves for three diverted West Maui Streams (Oki,
2007): Iao Stream, Waiehu Stream north and south branches, and Waihee River. For
these streams, Oki (2007) also provided the minimum discharge necessary to maintain
stream flow to the ocean (Qmin). We used these quantiles and regression models for each
stream to estimate the time (in days and years) necessary for N. granosa to migrate from
the ocean to the reach upstream of the highest altitude diversion. Further, in order to
provide estimates that would include the effect of aggregate migration, we compared our
upstream migration rates to published studies of other neritid snails under natural
conditions.
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30
RESULTS
Habitat characteristics & snail capture
There was a 98% reduction in stream discharge below the diversion that
corresponded to a 49% reduction in available habitat and warmer water temperatures
(Mann-Whitney U = 1316, P < 0.0001) (Table 2). Snails in the NF+D treatment
population used habitats with greater hydraulic intensity; mean velocity, Froude and
Reynolds numbers followed the trend of RF < NF < NF+D (Table 2). Interestingly, the
CV for the hydraulic variables was greater in the NF population compared to both RF and
NF+D (Table 2), suggesting that microhabitat conditions of NF snails were more variable
than the other populations. Capture rates over the first 6 d ranged from 17 – 65%, with
the highest from the NF+D population (Table 3). The mean capture rate among all snails
was 39%.
Initial snail dispersal and upstream migration
Over the first 6 d, mean initial dispersal patterns revealed substantially more
downstream/neutral snail movement in the RF (43.3%) compared to NF (5.7%) or NF+D
(5.3%) populations (Fig. 2; Table 3). Snails moved upstream, downstream and also
perpendicular to the flow. As a measure of aggregation, the CV for lateral movement
across the channel decreased from 1.01 on 2 d to 0.53 on 6 d, from 0.62 on 3 d to 0.27 on
6 d, and from 0.65 on 2 d to 0.29 on 5 d, for the RF, NF and NF+D populations,
respectively, inferring increased movement in aggregation with higher discharge and
snail density. The mean 6 d EMR for NF+D snails was significantly higher than the NF
snails, while the latter were almost 5x faster than RF snails (Fig. 3). Similarly, mean
UMR more than doubled from RF to NF and from NF to NF+D (Fig. 3). There were
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31
significant treatment (F = 17.93, P < 0.0001, df = 2), day (F = 12.67, P = 0.0004, df = 1)
and interaction (F = 5.94, P = 0.0028, df = 2) effects on UMR between days 3 and 5 (Fig.
4a). The mean UMR of the RF population differed over all days, driven by an increase in
upstream migration on day five, whereas it was consistent across days for the other
populations (Fig. 4a).
Four, three and 31 snails exhibited ‘rapid’ migration (" 8 m in ! 6 days) under
RF, NF and NF+D conditions (Fig. 2); however, upstream migration rate was not
different among the populations (Kruskal-Wallis, H = 1.19, P = 0.55). Thus, these data
were pooled for a mean ± SE maximum potential UMR of 2.18 ± 0.14 m d-1 (N = 38)
(Fig. 4b). Similarly, upstream migration rates from 16, 33 and 63 days after release did
not differ among populations (Kruskal-Wallis, H = 3.99, P = 0.14) and the mean longerterm UMR from pooled data was 0.62 ± 0.06 m d-1 (N = 31) (Fig. 4b).
Migration – habitat relationship
The cumulative variation in upstream migration rate explained by retained habitat
variables in PCA ordinations (Appendix S2) was 77%, 83% and 80% for RF, NF, and
NF+D populations, respectively. Using generalized linear models, habitat-scale
hydraulics, including velocity, Froude and Reynolds number, were positively related with
upstream migration rate across all populations (Appendices S3 & S4). Snail spatial
configuration (aggregation) explained 3 – 31% of the residual variation, and position in
the thalweg influenced migration rates.
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32
Application to restoration ecology of amphidromous migration
We found a positive linear relationship between mean daily discharge and UMR
(y = 0.43x + 0.45, R2 = 0.23, P = 0.16). Using this model to predict UMRs under Qmin,
Q50, Q70, Q90 discharge quantiles it would take N. granosa spat from 11 years at Q50 to 35
years under Qmin conditions to migrate beyond the highest altitude abstraction point
(Table 4). Because our migration rates are from a transplant experiment in higher altitude
reaches, and do not represent natural aggregate conditions reported elsewhere to be much
faster, we used published studies of N. granosa and related Neritina spp. to provide a
range of time estimates needed to restore naturally migrating neritid populations in West
Maui streams (Tables 4 & 5). In general, non-aggregate migration < aggregate migration
< migration in long lines.
DISCUSSION
Water flow alterations by dams and diversions change downstream habitat for
aquatic organisms (Dewson, James & Death, 2007). In Iao Stream, discharge was
significantly lower downstream of the diversion, negatively affecting water depth and the
wetted substratum available for benthic movement, and water temperature was higher.
Depth did not differ between NF and NF+D, because these treatment conditions were in
the same reach during different study periods. However, habitat hydraulic variables
associated with snail capture locations were significantly higher in the NF+D population,
which may indicate snail preference for faster flowing microhabitats, or that the overall
channel reach had been modified. Further, the coefficient of variation for these variables
was less than those of the NF population, illustrating the use of more similar hydraulic
habitats for snails under the increased density treatment.
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33
Mean capture rate over all treatments was 39% and greatest at 65% for the NF+D
population. Other studies have documented higher capture rates, such as 95% by Pyron
& Covich (2003); however, 40-60% of these snails remained at the release site. Such
variation may be due to stream habitat differences, organism size, tagging and search
techniques or season (Covich, Crowl & Scatena, 2003; Pyron & Covich, 2003). In our
reduced flow treatment there was a greater new capture rate, which may have been due to
restricted depth and a narrow channel that reduced the overall search area.
Under reduced flows, initial snail movement appeared disoriented, displaying
non-rheotaxis and nearly random movement from the release location. On day 2, 77% of
these snails did not move, or if they did, moved downstream. This may be related to the
pool-like habitat ~4 m up- and downstream of the release location, characterized by
shallow water, very slow flow and back eddy currents; a current which could result in
downstream dispersal, as the snails would have moved against the flow, displaying
rheotaxic behaviour (Vermeij, 1969; Ford, 1979; Schneider & Frost, 1986). Thus, largescale discharge removal changes smaller-scale hydraulic conditions that could be
disorienting to migrating spat, mediating dispersal patterns and upstream migration. A
small cascade (0.25 m vertical drop), about 4 – 5 m upstream of the release point did
generate increased flow, possibly providing a migratory cue not initially detected by the
released snails, but later in migration. Although cascades may act as a migration barrier,
N. granosa can overcome cascades as long as there is some flow and wetted substratum
(Ford, 1979). The few RF snails that reached the cascade and beyond moved 14 m in 6 d,
similar to migration rates and distances of both natural flow snail populations. This may
indicate that, once snails detect flow, they display a more natural upstream migration.
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34
The two populations under natural flow exhibited very little (<10%) downstream/neutral
movement, with a pronounced pattern moving upstream and toward the thalweg. These
pattern differences may be due to increased density of migrating snails, the use of more
similar and hydraulically intense microhabitats, or both. Ford (1979) suggested that N.
granosa spat migration may not be density dependent; however, our results indicate that
increased numbers enhance upstream migration.
According to Michel, McIntyre & Chan (2007), snail movement rates have been
calculated for surprisingly few species. To contribute to this knowledge base, we have
described neritid migration under altered flow and density conditions. Under reduced
flow, upstream migration rate was half that under natural flow, and this rate increased by
two-fold with increased spat density. The initial release density was high; however, visual
observations suggested that such conditions did not persist as the snails moved within the
available habitat. Even though our daily densities did not remain as high as some
recorded neritid mass migrations, where >5,000 m-2 have been documented (Blanco &
Scatena, 2007), our experimentally increased density did have a significant positive
effect, indicating that naturally occurring en masse aggregative migration is probably
much faster than in our transplanted snails. Further, upstream migration rate was
consistent over all recovery days under natural flow conditions, whereas the rates of
reduced flow snails significantly increased 5 d after release. This could have been due to
the small cascade upstream of the release location. Our results demonstrate that N.
granosa spat potentially have accelerated migration rates under natural flow and
aggregative conditions.
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35
The migratory behaviour of natural populations of Neritidae has been documented
in several studies. Long lines of snails moving over a few centimetres have been
measured and, when extrapolated, range impressively from 15 – 250 m d-1 (Ford, 1979;
Schneider & Frost, 1986; Schneider & Lyons, 1993; Pyron & Covich, 2003). Although it
is unlikely this rate of travel would continue throughout the day and over seasons, snails
are capable of large-scale coordinated upstream migration (Schneider & Frost, 1986).
Notably, upstream migration rate estimates calculated from Brasher (1997), where young
snails 11 mm in shell length had a mean upstream movement of 21 m in one month, or
about 0.7 m d-1, are very similar to our mean upstream migration rate of 0.66 m d-1 under
natural flow conditions (Table 5).
Gastropoda are widely known to produce adhesive mucus trails as they move,
generating a trail-following phenomenon (Bretz & Dimock, 1983; Denny, 1989; Smith &
Morin, 2002). A possible, yet untested, explanation for the higher migration rate and
movement pattern in the increased density population could be from active mucus trailfollowing – directional information from chemical cues within the mucus or energy
conservation by moving over previously laid trails (Shaheen et al., 2005; Stafford &
Davies, 2005; Alfaro, 2007; Davies & Blackwell, 2007). Although mucus decay is not
fully understood in lotic systems, conclusions drawn from marine intertidal studies
(Connor, 1986; Calow, 1979; Herndl & Peduzzi, 1989; Davies & Beckwith, 1999; Davies
& Blackwell, 2007) indicate that trails laid by snails under natural flow conditions would
not have affected snails under increased density because of degradation between study
periods (four weeks). Further research is needed to understand more of the effects of
mucus trails on aggregate migration of freshwater snails.
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36
The importance of flow velocity in the ecology, behaviour and physiology of
stream organisms is well established for many temperate stream organisms (Statzner et
al., 1988). Our results identified habitat- and reach-scale hydraulic variables as
significant predictors of upstream migration rate of an amphidromous tropical snail. The
remaining variation may be attributed to variable periphyton productivity, microhabitat
hydraulic conditions, substratum variability, and the use of more dense aggregate
movement, slime trails or hitch hiking behaviours (Schneider & Lyons, 1993; Pyron &
Covich, 2003; Blanco & Scatena, 2005 and 2007; Hau, 2007; Kano, 2009). While other
environmental characteristics may influence movement and upstream migration, our
results concur with Way et al. (1993), who proposed that micro-scale habitat flows
directly influence paths of grazing, refugia from predators, migratory pathways and
spawning areas of N. granosa. Additional studies have noted that large numbers of
smaller snails (<8 mm) tend to be found in, and move against, fast and turbulent flow
(Vermeij, 1969; Ford, 1979; Schneider & Frost, 1986; Way et al., 1993; Brasher, 1997;
Huryn & Denny, 1997; Blanco & Scatena, 2005, 2006 & 2007). Huryn & Denny (1997)
proposed that hydrodynamic drag on the shell generates torque on the foot and causes the
snail to rotate until its anterior end faces upstream, essentially steering snails upstream.
Without sufficient velocity to produce such torque, movement may not occur in an
upstream direction. In high-flow events, common to Hawaiian streams (Moore, 1964), N.
granosa are usually found on the underside of boulders or in crevices (Brasher, 1997),
and are well adapted to maintain position on the substratum (Ford, 1979); again
illustrating the role of flow in determining snail movement and placement.
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37
Across Hawaii and other tropical islands, water withdrawal from streams
continues to occur (Hawaii Cooperative Park Service Unit, 1990). Our results indicate
that 98% of base flow was removed from Iao Stream, which can lead to the decline of
native and endemic fauna (Oki et al., 2010; Shoda et al., 2010). While this threat is
understood and acknowledged, migration time and habitat requirements have not been
fully investigated. This study demonstrates that N. granosa can successfully be
transplanted to dewatered streams; however, given the current diverted conditions,
sustained recruitment for long-term restoration of resident populations is not possible.
Using our regression models, we estimated that it would take N. granosa from 11 – 35
years to migrate above the highest altitude abstraction points in the West Maui
catchments. These are overly conservative and unrealistic estimates, considering a
potential 6 – 15+ year life span (Ford, 1979; Brasher, 1997; Benbow, unpublished). Such
unrealistic estimates could be because spat were transplanted from a lower to higher
altitude and under relatively low densities compared to other studies of N. granosa
aggregations (Ford, 1979; Hau, 2007), thus, creating experimental conditions that were
not representative of natural high density spat aggregations at stream mouths. Because of
such limitations, it was necessary to use other Neritidae migratory studies to estimate
time frames that may be broadly applied to other regions. Snails reportedly moving en
masse allow us to consider that N. granosa would have the ability to migrate above
stream diversions in realistic time frames under natural stream flow conditions within 72
days to 2.5 years, when moving as an aggregate, and 29 days to 1.1 years, when traveling
in long lines. Perennially restored flow could have effects on N. granosa migration,
where large densities would probably entrain at stream mouths to form natural
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38
aggregations, like those reported by Ford (1979), and be capable of migrating to altitudes
of at least 400 m (Maciolek, 1978), ultimately enabling natural populations to re-establish
at higher altitudes.
Dudgeon (2000) drew attention to the need for tropical research with international
relevance. In this context, our study contributes to the growing literature on tropical
stream organisms and, more specifically, on the factors affecting the upstream migration
of ubiquitous but understudied, amphidromous neritid snails. As the threat of decline of
native populations continues, discussions of restoration and the development of
management plans are becoming increasingly important. If restoration efforts use this
migratory information on the slowest amphidromous species, surely it is possible for
faster species to be restored concurrently (Benbow et al., 2002). Therefore, understanding
time frames necessary for these species to reach natural habitats and adult breeding
grounds may facilitate mitigation practices that would restore pathways for all
amphidromous organisms and could be applied in other tropical regions experiencing
similar disturbances and population decline.
ACKNOWLEDGMENTS
Support for this study was provided by the University of Dayton Graduate School, Learn,
Lead and Serve Program and Department of Biology, the Earthwatch Institute and Center
For Field Studies, and the Office of Hawaiian Affairs. We would like to acknowledge T.
Fernandes, L. Orzetti, M. Shoda and Earthwatch Institute volunteers that assisted during
the 2001 season. We would also like to thank the Hawaii Department of Natural
Resources, Division of Aquatic Resources for granting research permits, S. Hau for
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39
continued support of our research, and two referees and Alan Hildrew for improving
earlier drafts.
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40
Table 1: Shell length, width and height of Neritina granosa collected from Honomanu Stream, Maui, Hawaii. Height was measured
for only the tagged snails of the Natural flow + increased density (NF+D) treatment. Snail density was determined from snail counts in
nine, 1m2 quadrats, where water depth was also measured.
Measurement
Tagged snails
Length
Width
Height
Untagged snails
Length
Width
Height
Quadrat measurements
Density (snails m-2)
Depth (m)
N
Range (mm)
Mean (mm) ± SE
C.V. (%)
594
594
198
2.6 - 7.0
2.1 - 6.9
1.3 - 2.7
5.2 ± 0.05
3.9 ± 0.04
1.9 ± 0.02
23.7
23.8
13.3
2402
2402
2402
2.2 - 22.3
1.6 - 20.1
0.4 - 8.0
6.8 ± 0.05
5.2 ± 0.04
2.6 ± 0.01
35.7
38.9
27.5
9
9
17 - 1192
0.04 - 0.54
309 ± 130.10
0.32 ± 0.06
126.3
52.9
41
Table 2: Habitat and hydraulic variables for each treatment during Neritina granosa migration in Iao Stream, Maui, Hawaii. The three
treatments were Reduced Flow (RF), Natural Flow (NF) and Natural Flow + Increased Density (NF+D). The Range, Mean (SE),
Coefficient of Variation (CV%), Kruskal-Wallis analysis of variance test statistics, and the results of Dunn’s post-hoc tests are
provided.
Environmental Variable
Treatment
Water Temperature (°C)
Stream Width (m)
Depth (m)
Surface Velocity (m s-1)
Froude
Range
Mean ± SE
C.V. (%)
N
RF
NF
NF+D
19.5 - 21.0
18.5 - 19.0
20.5 - 21.5
20.3 ± 0.44
18.7 ± 0.17
20.8 ± 0.33
3.8
1.6
2.8
3
3
3
RF
NF
NF+D
1.0 - 7.4
4.0 - 12.5
4.0 - 12.5
4.3 ± 0.61
8.4 ± 0.90
8.4 ± 0.90
50.6
36.7
36.7
RF
NF
NF+D
0.12 - 0.67
0.08 - 0.81
0.03 - 0.88
0.39 ± 0.01
0.48 ± 0.01
0.51 ± 0.01
RF
NF
NF+D
0.0 - 0.71
0.0 - 1.95
0.0 - 1.50
RF
NF
NF+D
0.0 - 0.34
0.0 - 0.77
0.0 - 0.61
KruskalWallis test
statistic
P Value
0.0538
5.84
13
12
12
0.0008
*t=3.84,
df=23
30.6
40.7
38.9
132
263
294
<0.0001
48.88
0.19 ± 0.02
0.37 ± 0.02
0.43 ± 0.02
78.7
100.1
74
40
252
294
<0.0001
27.63
0.10 ± 0.01
0.11 ± 0.01
0.19 ± 0.01
74
122.1
69.7
39
293
294
<0.0001
67.51
42
Table 2 continued.
Reynolds number
Reach Discharge (m3 s-1)
USGS Discharge (m3 s-1)
RF
NF
NF+D
0.0 - 317
0.0 – 1380
0.0 – 952
79 ± 10.59
174 ± 14.12
294 ± 12.61
84
138.2
86.7
40
293
294
<0.0001
36.56
RF
NF
NF+D
0.002 - 0.12
0.94 - 1.22
0.56 - 1.53
0.03 ± 0.02
1.09 ± 0.06
0.92 ± 0.31
188.3
10.9
58.9
5
4
3
0.016
8.27
RF
NF
NF+D
n/a
0.91 - 2.52
0.68 - 1.84
n/a
1.64 ± 0.23
1.08 ± 0.15
n/a
36.5
37.5
n/a
7
7
0.06
*U=9.5
Note: When only two groups were compared a Student’s t-test was used between upstream and downstream study sites, and Mann
Whitney U-test between NF and NF+D treatments.
43
Table 3: Three types of snail capture data: a) Number of new captures, identified as snails that had not previously been captured, and
the corresponding percentage of the total number of snails released on the original release date, b) Total number of captures for each
treatment and capture rates calculated as the percentage of the total number of snails released on the original release date found on
each search date and c) Total number of captured snails found downstream or at the release site (neutral) and its percentage of the
overall total captured. n/a indicates no data. See Table 2 for explanation of treatments.
Capture type
a.) New captures
Percentage
b.) Total captures
Percentage
Treatment
RF
2
75
100
3
46
57
Days After Release
5
50
56
NF
n/a
115
100
81
32
65
20
28
21
NF+D
117
100
84
39
67
28
n/a
n/a
RF
78
39
46
23
54
27
33
17
n/a
NF
n/a
116
59
81
41
66
33
28
14
NF+D
128
65
89
45
77
39
n/a
n/a
44
6
33
30
16
n/a
Table 3: continued.
c.) Downstream/Neutral
total captures
Percentage
RF
60
77
23
50
12
22
8
24
n/a
NF
n/a
12
10
3
4
2
3
n/a
NF+D
15
12
0
0
3
4
n/a
n/a
45
Table 4: Snail Upstream Migration Rate (UMR as m d-1), under historic discharge quantiles, Q50, Q70, Q90, and minimum discharge
needed to reach the ocean (Qmin) (based on Oki [2007]) in three West Maui streams, were calculated using the discharge – migration
rate regression equation (y = 0.43x + 0.45, R2 = 0.23, P = 0.16). The “Individual Snail UMR Maximum” and “Mean UMR Maximum
Potential” calculated from ‘rapid’ snails are provided. The approximate distance from the ocean to the highest altitude diversion in
each stream are as follows: Iao = 6900 m, Waihee = 4500 m, N. Waiehu = 3600 m, S. Waiehu = 4000 m. Based on these distances,
the time necessary to migrate beyond these diversions was estimated, in days and years, for all upstream migration rates.
Discharge - Migration Regression Equation
NF
Treatment
NF+D
Treatment
Mean
UMR
Maximum
Potential
Rapid
Snails
Individual Snail UMR Maximum
Q50
Q70
Q90
Qmin
RF
Treatment
UMR
Days
Years
0.92
7492
20.5
0.79
8744
23.9
0.69
9929
27.2
0.55
12592
34.5
5.6
1232
3.4
4.9
1408
3.9
3.77
1830
5
2.18
3165
8.7
Waihee
UMR
Days
Years
1.09
4126
11.3
1
4517
12.4
0.9
4988
13.7
0.47
9598
26.3
5.6
804
2.2
4.9
918
2.5
3.77
1194
3.3
2.18
2064
5.7
Waiehu N.
UMR
Days
Years
0.51
7016
19.2
0.5
7242
19.8
0.49
7368
20.2
0.47
7587
20.8
5.6
643
1.8
4.9
735
2
3.77
955
2.6
2.18
1651
4.5
Waiehu S.
UMR
Days
Years
0.51
7810
21.4
0.49
8093
22.2
0.48
8315
22.8
0.47
8498
23.3
5.6
714
1.9
4.9
816
2.2
3.77
1061
2.9
2.18
1835
5
Stream
Measure
Iao
46
Table 5: Migration as described in previous published studies compared to results of the current study. The organism of interest, study
location and a brief explanation of study observations are provided. All non-aggregate and aggregate mean rates were calculated using
details within authors’ observations. Results in cm min-1 were extrapolated to m d-1 and assuming migration takes place 8-12 hours
day-1 (Benbow et al., 2002). Migration time frames, in days, were estimated using stream distance to highest diversion (in
parentheses) and calculated migration rates.
Calculated Migration
(m d-1)
Migration Author
Type
Organism,
location
Observation
Nonaggregate
N.
granosa,
Maui,
Hawaii
three
treatments,
800
observations
of 590 tagged
snails over 6
days
following
release; 3 – 7
mm in shell
length
Gorbach
et al.
(2012)
Current
Study
Mean
Migration
Rate
(m d-1)
0.25 under
reduced
flow
0.66 under
natural
flow
1.16 under
natural
flow +
density
47
Days to migrate beyond highest
diversion
8 hrs of 12 hrs of
Iao
Waihee
migration migration 6900m 4500m
N.
S.
Waiehu Waiehu
(3600m) (4000m)
--
--
27600
18000
14400
16000
--
--
10455
6818
5455
6061
--
--
5948
3879
3103
3448
Table 5: continued.
NonPyron &
aggregate Covich,
(2003)
NonBrasher,
aggregate (1997)
Neritina
punctulata,
Puerto
Rico
N.
granosa,
Hawaii
1140
observations of
274 tagged
snails over 15
weeks; 24 mm
in shell length
769 tagged
snails
recaptured after
1 month; 11-13
mm in shell
length
762 tagged
snails
recaptured after
2 months, 16-33
mm in shell
length
0.153 mean
upstream
rate
0.81
greatest
mean rate
2.38
maximum
upstream
rate
--
--
45098 29412
23529
26144
--
--
8519
5556
4444
4938
--
--
2899
1891
1513
1681
0.7
--
--
20909 13636
10909
12121
0.17
--
--
40588 26471
21176
23529
48
Table 5: continued.
Aggregate Pyron &
Covich,
(2003)
N.
punctulata,
Puerto Rico
~307 snails,
~12 mm in
shell length
Aggregate Schneider
& Lyons,
(1994)
Neritina
latissima,
Costa Rica
Following Ford,
in narrow (1979)
line
7.4
--
--
932
608
486
541
>500,000
snails, <7 mm
in shell length
50 (ranged
30 -110)
--
--
138
90
72
80
N. granosa,
Hawaii
80 snails in a
chain,
!5 mm in shell
length
50.4
16.8
25.2
274 411
179 268
143 214
159 238
Following Schneider
in narrow & Frost,
line
(1986)
N. latissima,
Costa Rica
140 snails/m,
trail 32m long,
2-6 mm in shell
length
181.44
60.48
90.72
76 114
50 74
40 - 60
44 66
Following Schneider
in narrow & Lyons,
line
(1993)
N. latissima,
Costa Rica
20 snails in a
chain moving 2
cm, <7 mm in
shell length
250.56
83.52
125.28
55 83
36 54
29 - 43
32 48
Following Pyron &
in narrow Covich,
line
(2003)
N.punctulata, 20 snails in a
Puerto
chain, ~12 mm
Rico
in shell length
120.96
40.32
60.48
114 171
74 112
60 - 89
66 99
49
!
!
Figure 1: Map of the Hawaiian Islands with Maui and study streams identified. a) Iao Stream in the West Maui Mountains and b)
Honomanu Stream of East Maui. Insets highlight study reaches (black dots) and stream diversions (black rectangle).
!
50
!
Figure 2: Individual snail captures made during each treatment ! 16 days after release plotted on an x, y coordinate system (release
point = 0,0): a) Reduced flow (RF), b) Natural flow (NF), and c) Natural flow + increased density (NF+D). The number (N) of snails
captured on each day is provided in Table 3. Similar symbols represent captures across treatments: 2d = ‫܆‬, 3d = !, 5d = !, 6d = ",
and 16d = # and the $ in NF+D treatment represent captured untagged snails of the density effect. !
!
51
!
!
Figure 3: Mean (SE) Euclidean migration rates (EMR; black bar) and Upstream
migration rates (UMR; white bar) between treatment conditions. UMR and EMR in the
RF treatment were not significantly different, ns (P>0.05). EMR and UMR were
significantly different within the NF and NF+D treatments, and when each migration rate
was compared among treatments (Kruskal-Wallis H =203.0, P < 0.0001; H = 122.0, P <
0.0001; respectively). Different letters indicate significant differences between columns
(P < 0.05). The number of observations (N) for the RF, NF and NF+D treatments were
204, 260 and 268, respectively.
!
!
!
!
!
!
52
Figure 4: a) Mean upstream migration rate (UMR) over all initial (! 6 days) search days
for each treatment – RF (black), NF (grey) and NF+D (white). Negative UMR represents
downstream movement. RF and NF+D UMR were significantly different on 2 d (Mann
Whitney U = 642.5, P < 0.0001), and likewise, RF and NF were significantly different on
6 d (U = 776.0, P = 0.02). Mean UMR of the RF treatment differed over all days (H =
50.73, P < 0.0001), whereas in the other treatments, UMR was consistent (NF: H = 0.02,
P = 0.99; NF+D: H = 3.87, P = 0.14). b) Mean (SE) upstream migration rates for RF, NF
and NF+D treatments with captured snails that traveled ! 8m in ! 6 days (H = 131.1,
P<0.0001), pooled longer-term captures made 16, 33 and 63 post-release, and ‘rapid’
snail captures that traveled " 8m in ! 6 days. Rapid mean UMR was significantly greater
than snails that traveled ! 8m in ! 6 days (H = 165.2, P <0.0001) and the pooled longerterm mean UMR (U = 33.0, P <0.0001). Different letters indicate significant differences
between columns (P <0.05). !
!
53
APPENDICES
METHODS
Habitat variables measured (or calculated) on each search day for each snail
capture and included the following: discharge (Q), water column depth (D), surface flow
velocity (SV), mid-column velocity (MCV), Froude (F), Reynolds number (R), and
distance to nearest neighbour (NN). Additional covariates included each of these
measured variables on the previous recapture day of a particular snail (denoted with p).
For example, pDischarge (pD) is the discharge measured on the previous recapture day.
These variable codes were used in subsequent multivariate analyses and corresponding
tables.
A series of analytical steps, using JMP Version 4.0 (SAS Institute Inc., Cary, NC,
U.S.A.), was employed to test for significant relationships between habitat variables and
upstream migration rates for each treatment and when treatments were pooled,
representing a gradient of stream and migratory conditions. First, correlation matrices
tested for multicollinearity and correlation coefficients summarized the strength of the
linear relationship between each pair of response variables for each treatment, over all
recovery days. Mahalanobis and Jackknife distances identified snail capture data that
violated the correlation structure. These data were considered outliers and removed from
further analyses (Jolliffe, 2002; Bayley & Prather, 2003; Venturelli & Tonn, 2005). For
each treatment and when pooling all treatments, Principal Component Analysis (PCA)
was performed on the correlated habitat variables to summarize the structure of
intercorrelation and reduce the number of environmental variables (Graham, 2003; Roy et
al., 2003; Lehman et al., 2005). The number of components retained was decided using
!
54
the strategy of Lehman et al. (2005). Varimax factor rotation was performed on the
retained principal components and the new rotated factor loadings identified variables
that loaded heavily on each component, which were then used to determine the construct
measured by each component (Lehman et al., 2005). Standard least square linear
regression models tested the relationship between the factor-rotated components and the
four possible calculated response variables – EMR from the release point, EMR from the
point of previous capture, UMR from the release point, and UMR from the point of the
previous capture. The response variable best explained by the factor-rotated components
was determined by comparing the adjusted R2 among the four models. Using the PCA
factor-rotated components as explanatory covariates, and interactions among them, we
developed a set of candidate models to relate upstream migration rate to habitat template
covariates. We used generalized linear modeling (GLM) with an identity link function
and maximum likelihood techniques to determine the best-fit model, explaining a
significant portion of deviance between the response and explanatory covariates (Guisan,
Edwards & Hastie, 2002). Candidate models, differing in combinations of explanatory
covariates, were compared using the Akaike Information Criteria adjusted for small
sample size (AICc). The model with the lowest AICc value was accepted as the best-fit
model of the candidate models considered (Akaike, 1973; Burnham & Anderson, 2002).
To account for any remaining variation not explained by the factor-rotated components, a
standard least squares regression was used to examine the relationship between the
studentized deviance residuals and the distance recaptured snails moved perpendicular to
flow (x-coordinate), as a measure indicating usage of the thalweg and spatial aggregation
!
55
relative to the stream bank (i.e., how spread across the channel snails were as they
migrated upstream).
RESULTS
For each treatment and when treatments were pooled, relationships between instream habitat template covariates and upstream migration rates were tested using a series
of analytical steps. Individual captures that were identified as outliers, using Jackknife
and Mahalanobis distances, were removed from each treatment (14 from RF, 10 from NF,
7 from NF+D treatment, and 23 from the pooled treatments). Correlation matrices
determined strong multicollinearity among covariates and therefore Principal Component
Analysis (PCA) was used to summarize the structure of intercorrelation and reduce the
number of environmental variables (Graham, 2003; Roy et al., 2003; Lehman et al.,
2005). The number of components retained in each PCA was determined and
cumulatively the amount of variation in the response variable explained by the retained
components in the PCA ordination was 77% in the RF treatment, 86% in NF, 83% in
NF+D and 80% when treatments were pooled (Appendix S2). Factor rotation was
performed on the retained principal components and the new rotated factor loadings
identified covariates that loaded heavily on each component. Based on the nature of these
covariates, a construct was named for each component, depicting the biological measure
described by the covariates (Lehman et al., 2005). The construct, “habitat-scale
hydraulics (HH),” was used to define the biological nature of covariates including SV,
MCV, F, and R; the construct, “reach-scale hydraulics (RH),” described the discharge
covariate; and the construct, “aggregation (A),” was used to define the distance to the
nearest neighbor calculated from the spatial distribution of captures. Water column depth
!
56
did not load heavily on any retained component and was not described by a construct.
Not only were these constructs used to describe the covariates measured on each day of
capture, but they also indicated the covariates measured on the previous day of capture.
Accordingly, we also evaluated habitat-scale hydraulics and reach-scale hydraulics
measured on the previous day of capture (pHH and pRH) as constructs (Appendix S2).
The rotated factor component scores, identified by their construct names, were used as
covariates. The adjusted coefficients of determination (R2) of linear regressions between
the rotated factor component scores and the four possible response variables identified
EMR measured from the origin as the response variable that was used in subsequent
analyses in all treatments except in the RF, where UMR from the origin was used.
Generalized linear modeling (GLM) tested candidate models by comparing AICc
values (Appendix S3). Of the candidate models, AICc ranged from 313.6 to 304.3 in the
RF treatment, 377.5 to 366.3 in the NF treatment, 581.2 to 577.2 in the NF+D treatment,
and 1797.2 to 1795.2 when treatments were pooled (Appendix S3). Although a general
trend was not seen across all treatments, the models with the lowest AICc contained the
constructs HH, pHH, RH and pRH and their interactions for NF and NF+D, while those
for RF only included HH and RH (Appendix S4). As predicted, habitat-scale hydraulics
was positively correlated with migration rate across all treatments. Further, HH and RH
had the highest weight (parameter estimates = 0.596 and 0.510, respectively) for
predicting migration rate when the treatments were pooled. From 3 – 31% of the residual
variation in upstream migration was further explained by snail spatial configuration
relative to the stream bank (x-coordinates). Even though these values are relatively small,
usage of the thalweg appeared to influence upstream migration rate.
!
57
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Submersed aquatic vegetation and chlorophyll in western boreal shallow lakes.
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!
!
!
58
Appendix S2: Principal component analysis results for each treatment and when pooled. Eigenvalues, the percent variance explained
by each component, and the cumulative percent variance captured by the retained components are provided. Each component was
identified by a construct that captured the biological significance of the covariates that loaded heavily on the component. These are
habitat-scale hydraulics (HH), reach-scale hydraulics (RH) and aggregation (A). The letter “p” is added for that construct measured
on the day previous to capture. See Table 2 for explanation of Treatments.
4.35
4.05
1.61
% of
variance
33.5
31.1
12.4
Cumulative
%
33.5
64.6
76.9
Component
construct
HH
pHH
RH
1
2
3
4
5.67
3.24
1.30
1.08
43.7
24.9
9.9
8.3
43.7
68.6
78.5
86.9
pHH
HH
pRH
A
NF+D
1
2
3
5.67
3.77
1.30
43.6
29.0
10.0
43.6
72.6
82.7
pHH
HH
pRH
Pooled
1
2
3
5.88
3.31
1.16
45.2
25.5
8.9
45.2
70.7
79.6
pHH
HH
RH
Treatment
Component
Eigenvalue
RF
1
2
3
NF
59
Appendix S3: Generalized linear model results examining the effect of habitat template covariates on upstream migration rate. Chisquare test statistic (!2), K as the number of covariates in each model, the probability of significance, and overdispersion for each
candidate model are provided. Corrected AIC values were used to compare candidate models; model with the lowest AICc was
considered the best-fit model for each treatment. See Table 2 for explanation of Treatments. Candidate models were arbitrarily given
letter identification a – h.
Model !2
K
Prob>!2
overdispersion
AICc
a
b
c
d
e
f
68.03
68.21
68.49
68.53
69.94
69.55
2
3
4
5
6
7
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.29
0.29
0.29
0.29
0.29
0.29
304.31
306.14
308.10
310.22
311.99
313.59
NF
a
b
c
d
e
f
g
h
120.06
121.75
122.70
123.31
124.16
124.64
124.75
124.90
8
9
10
11
12
13
14
15
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.29
0.29
0.29
0.29
0.28
0.28
0.28
0.28
366.30
366.83
368.13
369.78
371.21
373.05
375.27
377.48
NF+D
a
b
c
178.30
178.40
178.55
5
6
7
<0.0001
<0.0001
<0.0001
0.56
0.56
0.56
577.19
579.22
581.23
Pooled
a
b
385.39
385.46
6
7
<0.0001
<0.0001
0.87
0.87
1795.17
1797.16
Treatment
Candidate Model
RF
60
Appendix S4: Best-fit generalized linear model results for each treatment and when treatments were pooled – !2 test statistic (!2), K
as the number of covariates in each model, the probability of significance, overdispersion, and AICc for each best-fit model. Each
covariate included in the best-fit model along with their corresponding parameter estimates, standard error (SE) and probability of
significance are provided. See Table 2 for explanation of Treatments. Note: Habitat-scale hydraulic covariate (HH), reach-scale
hydraulic covariate (RH), aggregation covariate (A) and the letter “p” is added when referring to that covariate measured on the
previous day of capture.
Treatment
RF
NF
Model !2
68.03
K
2
OverProb>!2 dispersion
<0.0001
0.29
120.06
8
<0.0001
0.29
AICc
304
366
Parameter
Estimate
0.18
0.31
-0.19
SE
0.04
0.04
0.04
Prob>!2
<.0001
<.0001
<.0001
Intercept
pHH
HH
pRH
A
(HH-0.009)*(A-0.024)
1.05
-0.08
0.08
0.14
-0.38
-0.19
0.04
0.04
0.04
0.04
0.04
0.05
<.0001
0.067
0.027
0
<.0001
0
(pHH+0.050)*(HH0.009)*(A-0.024)
0.13
0.08
0.096
(HH0.009)*(pRH+0.030)*(A0.024)
(pHH+0.050)*(HH0.009)*
(pRH+0.030)*(A-0.024)
0.23
0.07
0.001
0.27
0.12
0.024
Model Covariates
Intercept
HH
RH
61
Appendix S4: continued.
NF+D
178.3
5
<0.0001
0.56
577
Intercept
HH
pHH*HH
pRH
pHH*pRH
pHH*HH*pRH
2
0.67
-0.29
-0.09
0.17
0.29
0.05
0.05
0.06
0.06
0.07
0.06
<.0001
<.0001
<.0001
0.1
0.013
<.0001
Pooled
385.39
6
<0.0001
0.87
1795
Intercept
pHH
HH
(pHH+0.021)*(HH0.006)
RH
(pHH+0.021)*(RH0.001)
(HH-0.006)*(RH0.001)
1.15
0.22
0.6
-0.13
0.04
0.04
0.04
0.04
<.0001
<.0001
<.0001
0
0.51
-0.24
0.05
0.07
<.0001
0
0.25
0.07
0
62
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CHAPTER III
VARIABILITY IN HABITAT TEMPLATE AND BENTHIC COMMUNITY
RESPONSE TO ANTHROPOGENIC WATER REMOVAL IN TROPICAL
MOUNTAIN STREAMS
ABSTRACT
Mountain streams that originally supported Hawaiian cultural practices have been
diverted for development, agriculture and tourism for over 150 years. Habitat
characteristics and benthic macroinvertebrate community responses to water withdrawal
were studied in four West Maui Mountain watersheds. We compared riffle and cascade
habitats upstream and downstream of the highest elevation diversion in each watershed.
Riffles were shallow areas with moderate flow; while cascades were identified as high
velocity water flowing over boulders, and separated into torrenticolous and amphibious
microhabitats. Among streams, downstream discharge was reduced by 84 – 99%. Flow
velocity was 4x greater upstream and depth was 50% lower downstream, corresponding
to reductions in both downstream habitats. There was a significant 44% reduction in
macroinvertebrate density downstream of diversions (t = 3.261, df = 136, p = 0.0014);
however, density was not significant different among streams (F = 1.95, df = 3, p =
0.125). When density was corrected for habitat availability we found significantly greater
proportions of native taxa in amphibious microhabitats compared to riffle and
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torrenticolous habitats. Non-native Chironomidae and Trichoptera (Cheumatopsyche sp.
and Hydroptila sp.) were dominant (> 95%) and ubiquitous in riffle habitats, whereas
native Limonia sp. dominated (30%) amphibious microhabitats. Macroinvertebrate
community structure varied among streams, sites and microhabitats indicating
inconsistency in response to water withdrawal, dependent upon watershed size and
microhabitat conditions. Our findings contribute to ongoing water management and
restoration efforts focused on conservation of native species and habitat integrity in
tropical streams worldwide.
INTRODUCTION
Ecosystems worldwide are threatened by increased demands on freshwater
resources due to growing populations and associated consumption (Postel, 1997;
Benstead et al., 1999; March et al., 2003). To account for these demands, many streams
and rivers have undergone hydrologic alterations such as dams, surface water diversions,
stream channelization, and inter-catchment water transfer (Rosenberg et al., 2000;
Dudgeon, 2000; Baker et al., 2011). These hydrologic modifications include any
anthropogenic disruption in the magnitude or timing of river discharge; thus changing the
natural flow regime (Standford et al., 1996; Hart & Finelli, 1999; Rosenberg et al., 2000)
and impacting the physical, chemical and biological structure and function of rivers and
streams (Ward & Standford, 1983; Allan, 1995).
The reduction or elimination of flow downstream of diversions has been shown to
have significant impacts on native and amphidromous (a form of diadromous
reproduction) stream organisms of many tropical regions by disrupting the connection
between upstream habitats and the ocean, therefore preventing larval drift to the ocean
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and obstructing postlarval return migration (Timbol & Maciolek, 1978; Ford & Kinzie,
1982; Kinzie & Ford, 1982; Maciolek & Ford, 1987; Kinzie, 1990; Resh et al., 1992;
Benstead et al., 1999). Removal of streamflow can also alter downstream habitat which
affects physical and chemical conditions that regulate macroinvertebrate insect
communities; thus, limitations in habitat availability and/or quality may shift species
interactions, threaten native and endemic aquatic populations and potentially increase the
number of invasive species (Cowx et al., 1984; Poff et al., 1997; Brasher, 2003). This is
of particular concern in Hawaii because several native and endemic species are sensitive
to changing environmental conditions and community impacts of introduced species
(Shoda et al., 2010).
Much of previous flow alteration research has focused on the direct downstream
effects of dam construction and flow diversion on habitat conditions, invertebrate
community structure, and biotic interactions (Rosenberg et al., 2000; Brasher, 2003;
Dewson et al., 2007; Miller et al., 2007); however, there are also upstream effects on
migratory fauna and related basal food resources and invertebrate assemblages (for full
review see Benstead et al., 1999 and Greathouse et al., 2006). While the impacts of dams
have received some attention, few studies have assessed the direct physical and hydraulic
effects of flow diversion on stream communities (Baker et al., 2011) even though the
construction of small low head dams have undergone substantial proliferation in tropical
watersheds (Benstead et al., 1999). Further, hydrologic alterations and subsequent
ecosystem changes have been extensively studied in temperate regions; whereas, far less
is known about these impacts in tropical regions, especially islands, leaving these
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ecosystems poorly understood (Benke et al., 1988; Benstead et al., 1999; Pringle et al.,
2000; March et al., 2003; McIntosh et al., 2008; Shoda et al., 2010).
The increasing development and urbanization of tropical island nations will
continue to strain freshwater resources (Jackson & Sweeney, 1995; Benstead et al., 1999;
Smith et al., 2003). Hydrologic changes do not occur in isolation but interact with other
threats to biodiversity, such as introduced species and water quality degradation
(Dudgeon, 2000; Brasher, 2003). Although the study of tropical streams has grown,
further studies of biodiversity are necessary for continued and improved conservation
efforts (Jackson & Sweeney, 1995; Smith et al., 2003; Kinzie et al., 2006). Further, it is
not yet clear how ecological theory derived from studies in temperate continental stream
ecosystems can be effectively applied to understand and manage tropical stream systems
(Smith et al., 2003).
As the most isolated island archipelago in the world, freshwater in the Hawaiian
Islands is naturally limited to surface streams and groundwater supplied by heavy tropical
rains (Fitzsimons et al., 1997; Brasher, 2003; March et al., 2003). To original Hawaiian
civilizations, water resources were culturally important and used in the native practice of
taro cultivation. Flowing water was also important to the habitat of native stream
macrofauna, such as fish, shrimp, snails and prawns that were harvested as a food source.
However, through Western colonization and associated development of large-scale
commercial sugarcane plantations in the mid-1800s, stream diversions and extensive
tunnel systems were built, transporting freshwater from the wet, windward watersheds to
the dry leeward areas for agricultural production and population growth and
development. At least 58% of the estimated 366 Hawaiian perennial streams had
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experienced some type of streamflow alteration by 1978, with water being exploited for
anthropogenic uses, such as agriculture, development and tourism (Parrish et al., 1978;
Hawaii Cooperative Park Service, 1990). Depending on diversion structure and capacity,
water removal varies substantially across watersheds. Many of these diversions remove
from 90 – 100% of base flow volume, altering the natural flow regime which is important
for sustaining native biodiversity and ecosystem integrity (Wilcox, 1996; Poff et al.,
1997; Benbow, 1999; McIntosh et al., 2002; Brasher, 2003; McIntosh et al., 2008).
The native fauna of Hawaiian freshwater streams is represented by relatively few
species (Brasher, 2003; Font, 2003). Only 100 – 150 of the 795 species of Hawaiian
aquatic insects and mites inhabit freshwater streams, of which more than 85% are
endemic (Resh & Szalay, 1995). The native macroinvertebrate species richness that
represents island streams is lower than continental streams. The native Hawaiian stream
fauna composition is remarkably different than typical continental streams, with no native
species of Ephemeroptera, Megaloptera, Plecoptera, or Trichoptera (Resh et al., 1990;
Howarth & Polhemus, 1991; Larned et al., 2003). Further, these streams have been
invaded by introduced species, which now far outnumber populations of native fauna
(Devick, 1991; Cowie, 1997; Brasher, 2003; Shoda et al., 2010). Unfortunately, extensive
stream alterations throughout the Hawaiian Islands have created degraded conditions that
are more suitable for introduced species than the original native species (Maciolek, 1978;
Brown et al., 1999; Brasher, 2003). These introduced species have broad environmental
tolerances, whereas, native species evolved in watershed conditions with natural flow
regimes that are remarkably stochastic (Norton et al., 1978; Timbol & Maciolek, 1978).
Not only can introduced species prey on, and often outcompete native species (Brasher,
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2003), but these effects are exacerbated by disrupted flow regimes that have differentially
more negative effects on at least some native macroinvertebrates (Brown et al., 1999;
McIntosh et al., 2003; Shoda et al., 2010; Gorbach et al., 2012).
This study identified the effects of water removal on habitat template
characteristics and biological communities in four streams of the West Maui Mountains,
Hawaii, USA. We hypothesized that streamflow removal would negatively affect riffle
habitat template characteristics with negative effects on macroinvertebrate community
structure. Further, we compared our results from riffle habitats to a companion study of
cascade habitats and amphibious and torrenticolous microhabitats (Shoda et al., 2010) to
identify native and introduced species response differences among habitats. We predicted
that stream diversion effects on the habitat template would be associated with shifts in
macroinvertebrate density and community composition and that these effects would vary
by watershed size and extent of water withdrawal.
METHODS
Study sites
This investigation took place in the four watersheds of the West Maui Mountains,
collectively known in Hawaiian as the N! Wai ‘Eh!: Waikapu Stream, Iao Stream,
Waiehu Stream (North Branch) and Waihe’e River (Fig. 1; Oki et al., 2010). These
naturally perennial, 3rd order, windward streams have a large proportion of high velocity
turbulent flow habitats under natural conditions, but have been extensively diverted to
transport water to the dry, more arid leeward side of Maui where agriculture,
development and tourism dominate land use. The existing diversions on these streams
have the combined capacity to remove 75 million gallons of water per day (3.29 m3/s);
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often removing all, or nearly all, of base flow (Oki et al., 2010). The summit of the West
Maui Mountains receives > 8.89 m of annual rainfall, and supplies the headwaters of Iao
Stream and Waihe’e River, two of the largest streams on Maui based on flow volume
(Oki et al., 2010). Oki (2007) described mean base flow discharge (Q70) for each of these
streams during climate years 1984 – 2005. Q70 discharge represents the daily streamflow
volume that is equaled to or exceeded 70% of the time in historical records, and was
defined as base flow conditions for Hawaiian streams (Oki et al., 2010). For the study
watersheds, the Q70 discharge was as follows: 1.27 m3/s (Waihe’e River), 0.101 – 0.118
m3/s (N. Waiehu Stream), 0.788 m3/s (Iao Stream), 0.171 – 0.227 m3/s (Waikapu
Stream). Thus, to evaluate watershed size differences, reflected by base flow, the four
streams were divided into ‘small’ – Waiehu Stream and Waikapu Stream – and ‘large’ –
Iao Stream and Waihe’e River.
To study the effects of water removal in each watershed, study sites were
established as stream reaches 500 m upstream (US) and downstream (DS) of the highest
elevation diversion in each stream, and identified through collaboration with the U.S.
Geological Survey (USGS) who conducted hydrologic surveys of these watersheds
during the same study period. Habitat template characteristics (e.g. flow velocity, water
depth, channel width, and substrate size) associated with randomly sampled biological
samples (e.g., macroinvertebrates, chlorophyll a, etc. see below) were taken from a
defined 100 m study reach at each site, which was further divided into 10 transects
perpendicular to flow and representative of all habitat types (i.e. riffle, pool, run,
cascade). For a further detailed description of these watersheds and hydrological
conditions refer to Oki et al. (2010) and Shoda et al. (2010). Based on funding, logistical
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and accessibility constraints, all sites were sampled twice in August 2007 and once in
May 2008, which was similar to sampling frequency for other published bioassessment
studies of Hawaiian streams (McIntosh et al., 2002, 2003, 2008; Brasher et al., 2004;
Wolff, 2005; Shoda et al., 2010). !
Physical habitat template
The physical habitat of each reach was characterized and described in detail by
Shoda et al. (2010) and included reach discharge, wetted channel width, percent canopy
cover, substrate size, reach gradient, habitat extent, water temperature and dissolved
oxygen. In addition to discharge measurements made in the field, undiverted discharge
data were obtained from USGS streamgages upstream of the highest diversions in Iao
Stream (station #16604500) and Waihe’e River (station #16614000); there were no
functional gages on the other streams. Water column depth and flow velocity (at 0.6
depth) were measured every 0.5 m along each transect. Discharge and flow velocity were
measured using a SonTek Doppler Flowtracker (SonTek/YSI, 2005). We measured
Seston fine particulate organic matter (FPOM), chlorophyll a and the ratio of epilithic
biomass to chlorophyll a, or the Autotrophic Index (Kinzie et al., 2006; Hauer &
Lamberti, 2006). We quantified habitat availability by measuring the area of all
geomorphic channel units within the 100 m study reach using a range finder and
measuring tape.
Macroinvertebrate sampling
Six benthic samples were randomly collected from riffles at each site using a
modified Surber sampler (0.0625 m2) and methods described by McIntosh et al. (2002,
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2003, 2008). Prior to each benthic sample, we measured water column depth and flow
velocity profiles (at 0.2, 0.6 and 0.8 depth) at four equidistant points within the sampled
area. In a companion study (Shoda et al., 2010), we identified six cascade habitats, in
which two microhabitats were randomly sampled from each – torrenticolous (submerged
habitat) and amphibious (wetted splash zones on adjacent exposed rock) – using methods
of Benbow et al. (1997, 2003, 2005) and Shoda et al. (2010). We preserved all
macroinvertebrate samples in 70-90% ethanol for laboratory sorting and identification.
Macroinvertebrates were counted and identified to genus level; however, order
and family resolution was used when genus was not practical because of damaged
specimens or if keys were unavailable (Terry, 1913; Denning & Beardsley, 1967;
Denning & Blickle, 1971; Beardsley et al., 1998; Zimmerman, 2001; Merritt et al., 2008;
Shoda et al., 2010). We pooled members of Chironomidae, excluding Telmatogeton sp.,
which was easily identifiable as an endemic midge (Benbow, 2008; Shoda et al., 2010)
and verified identifications using voucher specimens identified by EcoAnyalyst Inc.
Based on the findings of previous studies (Williams, 1983; Polhemus, 1995; Englund et
al., 2007), and similar to Shoda et al. (2010) we classified all members of Procanace,
Limonia, Ephydridae, Telmatogeton sp., Hyposmocoma sp., Megalagrion sp. and Atyoida
bisulcata as endemic to the Hawaiian Islands.
Statistical analysis
Total macroinvertebrate density and habitat-corrected reach densities, determined
by multiplying the macroinvertebrate density by the total area of available riffle habitat
within each reach, were used to describe macroinvertebrate abundance, whereas
Simpson’s Diversity Index expressed the extent of biodiversity at each site. Cascade
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habitats and their corresponding microhabitats were analyzed in full detail in Shoda et al.
(2010). For purposes of this paper, cascade data from Shoda et al. (2010) were included
to investigate density and taxa response differences between cascade and riffle habitats,
which was not previously done. We calculated an Index of Nativity (I.N.), described as
the ratio of native to introduced taxa densities, to describe differential responses of native
and introduced taxa to reduced discharge. All data were appropriately transformed to
meet assumptions of normality and homogeneity of variances when possible; however,
when transformations were not effective, we used nonparametric analyses. A student’s ttest evaluated the effect of diversion between upstream and downstream sites when total
densities and habitat-corrected reach densities were pooled among streams. We
performed two-way ANOVA with Bonferroni post-tests using GraphPad Prism 5.0
(GraphPad Software) to test differences among streams, between upstream and
downstream sites and the interaction for mean macroinvertebrate densities, habitatcorrected reach densities, Simpson’s Diversity Index, I.N., microhabitat-specific densities
and habitat template variables, including FPOM, chlorophyll a, reach discharge, and
transect flow velocities and depths. Because similar hypotheses were tested for each of
these response variables, a Bonferroni adjusted p-value = 0.005 was used to interpret
statistically significant main effects. Similar analyses of additional habitat template
variables, including wetted channel width, percent canopy cover, substrate size, and reach
gradient were presented in Shoda et al. (2010, Table 1).
Macroinvertebrate community composition differences among streams, between
sites and between riffle and cascade microhabitats were evaluated using Non-metric
multidimensional scaling (NMDS) followed by multi-response permutation procedures
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(MRPP) using PC-Ord (McCune & Mefford, 1999). The Sørensen distance measure was
used with a random starting configuration and 250 runs with real data (McCune & Grace,
2002). We identified indicator taxa for each habitat or microhabitat and between sites
using Indicator Species Analysis as described by in McCune & Grace (2002), and results
from Monte Carlo tests with 4999 randomizations were used to determine significant
differences in community structure similar to the multivariate approach by Shoda et al.
(2010).
RESULTS
Physical habitat template
Water removal significantly altered the physical habitat template of the
downstream sites. Mean daily discharge recorded during the study by USGS streamgages
in Iao Stream and Waihe’e River was 1.23 m3/s and 0.97 m3/s, respectively. When we
measured instantaneous discharge, there were significant differences among streams and
sites (Table I). Discharge was reduced by 84 – 99% downstream of the diversions and did
not statistically differ among downstream reaches of the streams. Upstream discharge
significantly varied among streams: Iao Stream and Waihe’e River was significantly
greater than both small streams, with Waihe’e River significantly greater than Iao Stream
(t = 5.087, p < 0.001), while the two small streams did not significantly differ (t = 0.088,
p > 0.05). When the two large streams were pooled, lower discharge below the diversions
was associated with significantly reduced riffle and cascade habitat, (US to DS, riffle:
29.0% to 6.0% of total reach area and cascade: 20.6% to 3.5% of total reach area). For
the two small streams, cascade habitat decreased (17.0% to 14.6%) but riffle habitat
increased (14.6% to 22.6%) downstream of the diversion (Fig. 3).
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Streamflow ranged from 0.004 m3/s downstream in Waikapu Stream and Waiehu
Stream to 1.33 m3/s upstream in Waihe’e River (Fig. 2). Mean flow velocity and depth
measured along reach transects were also significantly different among streams and sites
with velocity following trends of measured discharge and depth significantly reduced
downstream in all streams (Table I). Nonparametric correlation analysis found a
significant positive relationship between percent cascade habitat and depth (Spearman r =
0.833, p = 0.015). However, there were no other significant relationships between percent
habitat (riffle and cascade) and depth and velocity.
There was a significant stream effect (F = 7.297, df = 3, p = 0.0007; Table I) on
FPOM (mg/L); however, the effect of diversion on FPOM varied among watersheds.
There were no significant differences among the upstream sites, while downstream
FPOM in Waihe’e River was significantly greater than all other downstream sites.
Further, upstream FPOM in Iao Stream was significantly greater than downstream (t =
2.97, p < 0.05). There were significant main effects of stream and site (Table I) on
chlorophyll a (!g/L), with upstream significantly greater than downstream in Iao Stream
(t = 2.94, p < 0.05). The Autotrophic Index was greater downstream in all streams (Table
I); among all downstream sites, the Autotrophic Index in Waikapu Stream was
significantly greater than Waihe’e River (t = 2.45, p < 0.05).
Macroinvertebrate density and diversity
There was a significant 44% reduction in macroinvertebrate density in riffle
habitats downstream of diversions when streams and sampling dates were pooled (t =
3.261, df = 136, p = 0.0014). When the effects of water removal on macroinvertebrate
density were analyzed for individual streams, there was a significant effect of site (F =
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11.49, df = 1, p = 0.0009; Table I, Figure 4a); however, this was not the case among
streams (F = 1.95, df = 3, p = 0.125). Within Waihe’e River, there was a significant
reduction in mean macroinvertebrate density downstream of the diversion (t = 4.92, p <
0.0001). Further, there were significantly greater densities in the upstream site in Waihe’e
River compared to the two smaller streams: Waikapu Stream (t = 2.95, p < 0.01) and
Waiehu Stream (t = 4.12, p < 0.001); but the upstream densities in Iao Stream were not
significantly different from the other upstream sites. There was no significant difference
in macroinvertebrate density among downstream sites.
When densities were corrected for available riffle habitat within each reach, there
were significant stream (F = 24.43, df = 3, p < 0.0001; Table I, Figure 4b), site (F =
89.81, df = 1, p < 0.0001) and interaction effects (F = 33.08, df = 3, p < 0.0001).
Habitat-corrected macroinvertebrate density was significantly greater upstream than
downstream in both Iao Stream and Waihe’e River (t = 10.55, p < 0.001; t = 9.462, p <
0.001; respectively). However, this was not the case for Waikapu Stream and Waiehu
Stream (t = 0.3134, p > 0.05; t = 0.7006, p > 0.05; respectively). When comparing
habitat-corrected densities between streams, Waikapu Stream had significantly greater
density than Waiehu Stream, both upstream and downstream. Conversely, Waiehu
Stream downstream density was similar to downstream sites of the larger streams.
Further, habitat-corrected density did not significantly differ between the downstream
sites in Waikapu Stream and Waihe’e River (t = 1.580, p > 0.05), whereas upstream
densities significantly differed among all streams following the trend of Waiehu Stream <
Waikapu Stream < Iao Stream < Waihe’e River (Fig. 4b). Finally, Simpson’s
Biodiversity Index was not different among streams or between sites (Tables I and II).
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To understand the differential effects of water removal on the macroinvertebrate
communities occupying different habitats, we pooled data from all streams and compared
macroinvertebrate density in riffles versus cascades (pooled torrenticolous and
amphibious microhabitats, as given in Shoda et al., 2010). There was significantly greater
macroinvertebrate density in upstream habitats (F = 25.77, df = 1, p < 0.0001), but this
depended on habitat (F = 138.9, df = 1, p < 0.0001) (interaction: F = 17.99, df = 1, p <
0.0001). The cascade habitat was then separated into amphibious and torrenticolous
microhabitats, and similarly, there were significant site (F = 15.02, df = 1, p = 0.0001),
microhabitat (F = 76.69, df = 2, p < 0.0001) and interaction (F = 9.308, df = 2, p =
0.0001) effects on macroinvertebrate densities (Fig. 5). However, macroinvertebrate
density was not significantly different between upstream and downstream sites within
amphibious (t = 0.3112, p > 0.05) or torrenticolous (t = 0.6425, p > 0.05) microhabitats;
further, habitat-corrected density calculations were not possible for these microhabitats.
Community composition
Riffle macroinvertebrate communities were primarily composed of three
introduced taxa, including Chironomidae (excluding Telmatogeton sp.) and two
Trichoptera, Cheumatopsyche sp., and Hydroptila sp. (Fig. 6, Table II). When all streams
and sites were pooled, introduced Chironomidae dominated the riffle communities at
58.6%, followed by Cheumatopsyche, 27.9%, and Hydroptila, 8.6%. Similarly,
introduced Chironomidae dominated the torrenticolous (64.9%) and amphibious (46.5%)
communities. Cheumatopsyche, 21.1%, and Hydroptila, 7.0%, also composed the
torrenticolous community, however, these introduced Trichoptera contributed much less
to the amphibious community, 2.2% and 2.3%, respectively. Instead, amphibious
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communities included native taxa, Limonia (30.4%) and Ephyridae (10.7%). Finally,
Telmatogeton sp. made up 3.0% and 1.8% of the torrenticolous and amphibious
communities, respectively. In all habitats, other taxa, including native, endemic and
introduced taxa, were present but no other taxa represented more than 3% of the total
community. When streams and sites were considered independently, the only additional
taxa that made up greater than 3% were introduced Physa sp. (Waikapu US: 4.7%) and
Oligochaeta (Waiehu DS: 3.5%; Waihe’e US: 4.0%).
To evaluate the general impact of water removal on non-native versus native
taxa, streams were pooled to compare native and introduced taxa density differences
related to stream diversions (Fig. 7). There was only a significant main effect of site on
native taxa density (F = 18.40, df = 1, p < 0.0001), whereas there were significant effects
of habitat (riffle vs. cascade; F = 39.42, df = 1, p < 0.0001), site (F = 13.21, df = 1, p =
0.0004), and their interaction (F = 9.911, df = 1, p = 0.0019) on introduced taxa density.
In the riffle habitat, the density of both native and introduced taxa was significantly
greater upstream than downstream (t = 3.998, p < 0.001; t = 4.796, p < 0.001;
respectively). Further, introduced taxa density was significantly greater upstream in the
riffle than the cascade habitat (t = 6.665, p < 0.001; Fig. 7).
The cascade habitat was further separated into microhabitats where we found a
significant main effect of microhabitat on the Index of Nativity in each stream; however,
a significant main effect of site was only evident in the larger streams – Iao Stream (F =
7.385, df = 1, p = 0.0079) and Waihe’e River (F = 4.503, df = 1, p = 0.0365). Further, the
I.N. was significantly greater in the upstream compared to the downstream amphibious
microhabitat in Iao Stream (t = 4.309, p < 0.001) and Waihe’e River (t = 3.309, p < 0.01).
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The index was not a different between sites in the two smaller streams – Waikapu and
Waiehu Streams (F = 1.785, df = 1, p = 0.1847; F = 0.3997, df = 1, p = 0.5293;
respectively). Additionally, when streams were pooled, the amphibious I.N. was
significantly greater than both riffle and torrenticolous habitats, between downstream
sites (t = 4.417, p < 0.001; t = 4.205, p < 0.001; respectively) and between upstream sites
(t = 4.821, p < 0.001; t = 4.728, p < 0.001; respectively) (Fig. 8). Conversely, I.N. did not
differ between riffle and torrenticolous habitats in any stream or between downstream (t
= 0.207, p > 0.05) or upstream sites (t = 0.092, p > 0.05).
Using NMDS with MRPP we found a significant difference in macroinvertebrate
community structure among habitats (Euclidean distance measure, A = 0.185, p =
0.00000; Figure 9). There also was a significantly different community composition
between upstream and downstream sites (A = 0.0086, p = 0.0029) and among streams (A
= 0.0092, p = 0.011). Specifically, this was evident between Waikapu and Iao Streams (p
= 0.01) and between Waikapu Stream and Waihe’e River (p = 0.003). We found that
Chironomidae, Cheumatopsyche and Hydroptila accounted for the highest percentage of
perfect indication of riffle habitat with 75%, 68%, and 67%, respectively (p = 0.0002, for
each). Endemic Telmatogeton sp. and Procanace were 27% and 10% indicators of the
torrenticolous microhabitat, respectively (p = 0.0002 & 0.0086), whereas, native
Tipulidae (i.e. Limonia) and Ephydridae were significant indicators of the amphibious
microhabitat (61% and 29%, respectively; p = 0.0002 for both).
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DISCUSSION
Physical habitat template
The consequences of reduced streamflow on physical habitat are consistent and
well documented (see Fig. 1 in Dewson et al., 2007 for full review). Comparisons
between upstream and downstream wetted width, percent canopy cover, substrate size
and gradient for each of these West Maui watersheds were presented in Shoda et al.
(2010). Trends of lower discharge, FPOM and chlorophyll a due to stream diversions
were evident across the four watersheds. The two larger watersheds, Iao Stream and
Waihe’e River, experienced significant water reduction downstream of the diversions;
although discharge downstream of diversions in the smaller streams was substantially
lower, it was not statistically different from upstream conditions. While the large and
small streams differed in stream size and upstream discharge volumes, strikingly,
downstream discharge and flow velocity were similar across the four streams, indicating
the diversions varied in capacity and efficiency, yet created relatively similar downstream
flow environments. Therefore, the extent to which the diversions affected physical habitat
and biological communities was dependent upon stream size and diversion capacity.
Such conclusions could impact restoration and conservation efforts of the N! Wai ‘Eh!,
especially during recent legal proceedings (Case no. CCH-MA06-01) concerning
freshwater resources and the return of flow back into diverted streams (Eagar, 2008;
Hamilton, 2008).
Similarly, in a study comparing two streams on the island of Molokai, Brasher
(1997) found that as discharge decreased below a diversion, flow velocities, water depth
and wetted channel width were reduced. We found similar effects of significantly
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reduced wetted width and depth downstream of the diversions in Iao Stream and Waihe’e
River; and depth was significantly lower downstream in the smaller streams. The similar
levels of fine particulate organic matter among upstream sites of the four watersheds
suggest comparable allochthonous input and breakdown; however, the transfer of FPOM
to downstream sites varied considerably among streams. Further, chlorophyll a was
significantly lower downstream of diversions, which was expected as primary production
would decrease with increased canopy cover (Hauer & Lamberti, 2006) from encroaching
riparian plants in the dry stream sides, which is what we found in this study. Kinzie et al.
(2006) found a similar trend of reduced benthic chlorophyll a at dewatered sites on the
island of Kauai. Although our results indicate variability in chlorophyll a among streams,
unfortunately our study only included one isolated sampling event for chlorophyll a and
FPOM from each study site, so these results should be interpreted with caution. A more
thorough systematic sampling regime would be necessary for broader conclusions (Hauer
& Lamberti, 2006).
Reduced discharge affected habitat availability for macroinvertebrate
colonization, where the relative percent of riffle, cascade, and pool habitats were lower
downstream in the larger watersheds, while the relative percent of run habitat doubled. In
the smaller streams, riffle and pool habitats actually increased downstream, whereas run
and cascade habitats decreased. This is important when sampling macroinvertebrate
communities, especially in cascade habitats, where it may be necessary to expand the size
of a study reach during conditions of low flow (Benbow et al., 2003, 2005). In addition,
overall habitat quality may be affected by reduced discharge (Miller et al., 2007) and
impact the macroinvertebrate community composition and biomass as a result of altered
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habitat suitability for certain species (Gore et al., 2001; McIntosh et al., 2003, 2008;
Dewson et al., 2007; Benbow, 2008).
Macroinvertebrate density and diversity
Our results revealed that total riffle macroinvertebrate density in these West Maui
watersheds responded negatively to reduced flows downstream of diversions, with a
statistically significant difference found in Waihe’e River. Such a high density in the
Waihe’e River upstream site could be attributed to overall habitat quality or timing of
sampling events. These results in Waihe’e River differ from a similar study by McIntosh
et al., (2003) where macroinvertebrate densities were found to be similar between
upstream and downstream reaches. Changes in hydrology and frequency of spate events
may account for such variation in communities downstream of diversions that might
mask the effect of diversions, perhaps because of low statistical power (McIntosh et al.,
2003). However, when a similar study was conducted in Iao Stream during the same
summer (McIntosh et al., 2002), macroinvertebrate densities were significantly lower
downstream of the diversion. It is important to note that habitat availability was not
accounted for in either of these studies (McIntosh et al., 2002, 2003). Further, Kinzie et
al. (2006) found that invertebrate abundance, diversity and biomass were reduced
downstream of a Wainiha River diversion on Kaua’i, Hawaii.
When habitat availability was taken into account there were profound and
significant reductions in macroinvertebrate density downstream of the diversions in the
larger streams. Interestingly, total habitat-corrected macroinvertebrate density was greater
downstream than upstream in the two smaller streams, attributable to greater riffle habitat
availability (and thus associated reduced cascades). Further, downstream habitat-
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corrected macroinvertebrate densities were generally similar among streams, likely due to
diversion differences in capacity and efficiency, creating comparable habitats. These data
demonstrate that accounting for available habitat is important to evaluating ecological
change as a response to reduced streamflow (Shoda et al., 2010).
Community composition
Similar to other Hawaiian habitats, non-native organisms have invaded the
freshwater streams. Our findings suggest that more than 95% of riffle community
composition in these West Maui watersheds was dominated by introduced taxa, whereas
native taxa only comprised approximately 1% of the overall community structure, similar
to the torrenticolous microhabitats reported by Shoda et al. (2010). Exotic Trichoptera
and Chironomidae are common in continental streams and have successfully established
themselves in the Hawaiian Islands (Howarth & Polhemus, 1991). Our findings are
comparable to other recent Hawaiian studies, where alien species have been found to
dominate riffle macroinvertebrate communities (McIntosh et al., 2002, 2003, 2008;
Brasher et al., 2004; Wolff, 2005; Kinzie et al., 2006).
When all data were pooled, the Index of Nativity identified the amphibious
habitat as having the greatest proportion of native taxa (43.9%) compared to
torrenticolous (4.7%) and riffle (1.0%) habitats. Interestingly, the Index of Nativity was
not statistically different between the torrenticolous and riffle habitats; both compositions
were dominated by introduced taxa. In all study sites upstream of diversions, the Index of
Nativity was greater in the amphibious habitat than in either of the other two habitats,
suggesting this microhabitat under natural flow conditions is crucial for the persistence of
native aquatic species in these tropical mountain streams. To our knowledge,
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macroinvertebrate community comparisons among Hawaiian stream microhabitats have
not been addressed other than by Shoda et al. (2010). However, the value of native
insects is widely acknowledged (Kido & Smith, 1997; Brasher et al., 2004; see Wolff,
2005) and they are considered potential indicators of Hawaiian stream habitat quality
(Kido & Smith, 1997; Shoda et al., 2010). Kido and Smith (1997) found that endemic
genera such as Telmatogeton and Procanace were sensitive to reduced flow and could
potentially act as indicators of moderate to excellent stream habitat quality. Our data from
four Maui watersheds support this recommendation.
The native taxa Limonia, Ephydridae, Telmatogeton sp., and Procanace
accounted for the highest percentage of perfect indication of cascade habitats. Non-native
taxa dominated the riffle habitats and included the introduced Chironomidae,
Cheumatopsyche and Hydroptila as the indicator taxa. Similarly, Brasher et al. (2004)
found that Cheumatopsyche pettiti dominated riffle communities in 9 streams on Oahu
and Shoda et al. (2010) reported that native species represented amphibious communities.
Significant community composition separation was found between upstream and
downstream sites suggesting that water withdrawal influenced overall macroinvertebrate
community structure. Separation was further found between streams of different sizes,
implying community structure similarity between streams of similar size and diversion
efficiency.
Through years of continental watershed research, riffle habitats are widely
accepted and recommended for biomonitoring (Hauer & Lamberti, 2006; Merritt et al.,
2008). However, our results here support a growing literature base of tropical island
streams suggesting that riffles are dominated by introduced taxa (Kido & Smith, 1997;
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Kinzie et al., 1997; Brasher et al., 2004; Wolff, 2005); thus, biomonitoring programs in
these tropical regions target non-native organisms. Our investigation of cascade habitats
clearly indicates their importance in high gradient, flashy, tropical streams, for
understanding macroinvertebrate community responses to anthropogenic disturbance.
Where water conservation and management are of concern in regions of high endemicity,
we propose that biomonitoring programs include habitats where native and endemic
organisms are most abundant and sensitive to appropriate anthropogenic stressors.
Identifying habitats, such as cascades, where native organisms can thrive, despite an
overall community structure overrun by introduced taxa, may be necessary in establishing
effective biomonitoring programs.
In the last decade, it has become increasingly evident that conserving aquatic
ecosystems while balancing freshwater needs is a pressing global issue, with researchers
in tropical regions urging a better understanding of the direct and indirect impacts of flow
modifications on aquatic communities and overall ecosystem services for the
development of effective management strategies (Power et al., 1996; Jackson et al., 2001;
Baron et al., 2002; Brasher, 2003). However, the task of determining minimum flows is a
difficult and politically sensitive task for water resource managers (Bunn & Arthington,
2002; Dewson et al., 2007). If ecosystem structure and function is to be restored and
maintained in stream networks, water-conservation strategies and a strong commitment to
sustainable water is necessary, especially on tropical islands with high endemism and
where freshwater resources are already limited (Smith et al., 2003).
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ACKNOWLEDGMENTS
The authors would like to acknowledge C. Hanley, A. Jennings and D. Vonderhaar for
their invaluable assistance during field sampling. K. Sproat, I. Moriwake, D. Oki, J.
Duey, J. Verel, and the Pellegrino and Duberstein families provided logistical support,
stream access and hospitality while conducting this research. This project was made
possible through the financial support of the US Geological Survey, Earthjustice, the
Office of Hawaiian Affairs and the University of Dayton Graduate School and
Department of Biology.
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Table I: Two-way ANOVA statistics for physical habitat template characteristics and
macroinvertebrate density and diversity for the riffle habitat. Site refers to upstream or
downstream of water diversions among the study streams. Bonferroni corrected p-value
= 0.005 was used to interpret statistical significance.
Parameter
Source of
variation
Percent of
variation
F
value
df
P value
Discharge (m3/s)
Stream
Site
Stream x Site
24
30.2
22.2
49.98
188.6
46.16
3
1
3
<0.0001
<0.0001
<0.0001
Depth (m)
Stream
Site
Stream x Site
7.6
10.1
1.3
63.56
254.5
10.96
3
1
3
<0.0001
<0.0001
<0.0001
Flow Velocity (m/s)
Stream
Site
Stream x Site
0.7
9.9
0.8
5.28
211
5.63
3
1
3
0.0013
<0.0001
0.0008
FPOM (mg/L)
Stream
Site
Stream x Site
30.3
3.1
22.5
7.3
2.21
5.43
3
1
3
0.0007
0.1473
0.0039
Chlorophyll a (µg/L)
Stream
Site
Stream x Site
34.6
19.3
3.2
8.58
14.32
0.78
3
1
3
0.0003
0.0006
0.5124
Autotrophic Index
Stream
Site
Stream x Site
16.9
19.6
5.1
2.8
9.7
0.85
3
1
3
0.0579
0.0041
0.4797
!
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Table I: continued.
!
Total macroinvertebrate
Density (# m-2)
Stream
Site
Stream x Site
3.6
7.1
8.5
1.95
11.49
4.59
3
1
3
0.1256
0.0009
0.0043
Total Riffle-Corrected Density
(# m-2 per 100m)
Stream
Site
Stream x Site
18
22
24.3
24.43
89.81
33.08
3
1
3
< 0.0001
< 0.0001
< 0.0001
Diversity
Stream
Site
Stream x Site
0.8
1.2
3.8
0.38
1.58
1.75
3
1
3
0.7704
0.2104
0.1601
93!
Table II: Mean (± SD) density of represented macroinvertebrate taxa in the riffle habitats among the study streams and between
upstream and downstream of diversion.
!
Riffle taxa
!
Waikapu Stream
US
DS
Waiehu Stream
US
DS
Iao Stream
US
DS
Waihe'e River
US
DS
Megalagrion sp.
2±2
1±1
8 ± 10
4±4
0±0
0±0
0±0
0±0
Dytiscidae
0±0
0±0
0±0
0±0
0±0
0±0
0±0
0±0
Chironomidae sp.
185 ± 137
155 ± 134
272 ± 141
157 ± 147
215 ± 270
253 ± 316
430 ± 336
168 ± 214
Telmatogeton sp.
2±1
1±1
3±1
1±0
2±1
1±1
4±1
2±2
Procanace sp.
0±0
0±0
0±0
0±0
0±0
0±0
0±1
0±0
Ephydridae
0±0
0±0
0±1
0±0
1±1
0±1
1±2
0±1
Limonia sp.
0±0
0±0
1±3
0±0
1±2
0±1
1±1
0±0
Cheumatopsyche analis
79 ± 78
47 ± 37
126 ± 129
48 ± 73
125 ± 183
53 ± 70
194 ± 152
53 ± 64
Hydroptila sp.
10 ± 15
1±2
36 ± 50
18 ± 54
79 ± 101
44 ± 72
306 ± 471
28 ± 50
Hyposmocoma sp.
0±0
0±0
0±0
0±0
0±0
0±0
0±0
0±0
Ferrissia sharpi
0±0
0±0
1±1
2±4
0±0
0±0
0±0
0±0
94!
Table II: continued.
Lymnaeidae
2±6
0±1
0±0
0±1
0±0
0±1
0±0
0±0
11 ± 12
4±7
1±4
0±0
1±1
0±0
2±8
0±0
Oligochaeta
2±3
1±2
9 ± 14
23 ± 75
6±8
2±3
56 ± 100
6 ± 14
Oribatei
0±0
0±0
2±3
1±3
0±0
0±0
1±2
0±1
Atyoida bisulcata
0±0
0±0
1±3
0±0
0±0
0±0
0±0
0±1
Prostoma sp.
0±1
0±0
0±1
0±0
0±0
0±0
0±0
0±0
Turbellaria
0±0
0±0
0±0
0±0
1±2
2±3
0±0
0±0
Erpobdellidae
1±3
0±1
1±2
0±0
0±0
0±0
0±0
0±0
Glossiphoniidae
0±0
0±1
0±0
0±0
0±1
0±0
0±0
0±0
Physa sp.
!
95!
Table III: Two-way ANOVA statistics for the Index of Nativity for each microhabitat and site within each stream. Site refers to
upstream (US) or downstream (DS) of water diversion among the study streams. Bolded p-values indicate statistical significance (! =
0.05) and are followed by Bonferroni pairwise comparisons between US and DS reaches for each microhabitat are presented (ns = not
significantly different).
!
F-value
df
p-value
Bonferroni post-test
comparisons between US &
DS sites for each habitat
ns
Stream
Source of variation
Percent
of
variation
Waikapu
Stream
Site
Microhabitat
Site x Microhabitat
1.4
19.8
2.8
1.79
12.58
1.76
1
2
2
0.1847
< 0.0001
0.1774
Iao Stream
Site
Microhabitat
Site x Microhabitat
5.5
12.5
10.2
7.39
8.39
6.85
1
2
2
0.0079
0.0005
0.0017
Waiehu Stream
Site
Microhabitat
Site x Microhabitat
0.4
19.1
0.6
0.4
9.58
0.28
1
2
2
0.5293
0.0002
0.7558
Site
Microhabitat
Site x Microhabitat
3.7
17.2
6.2
4.5
10.39
3.77
1
2
2
0.0365
< 0.0001
0.0266
Waihe'e River
!
!
!
!
96!
Amphibious microhabitat:
t = 4.309, p < 0.001
ns
Amphibious microhabitat:
t = 3.309, p < 0.01
Figure 1: Map of West Maui, Hawaii, with study watersheds highlighted and corresponding study locations as black dots – A)
Waikapu Stream, B) Iao Stream, C) Waiehu Stream and D) Waihee River. At each location, an upstream (US) and downstream
(DS) site was sampled above and below the highest elevation diversion in each stream.
!
97!
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2
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2
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Figure 2: Mean (SE) measured discharge in all streams, upstream (black bar) and
downstream (white bar) of the highest elevation diversion. The * represents a significant
difference between upstream and downstream sites at p < 0.001 (Bonferroni post-tests).
!
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56
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100 m study reaches, where the large (Iao Stream and Waihee River) and small streams
(Waikapu and Waiehu Streams) were pooled. The habitats were Run (Black), Riffle
(Diagonal Stripe), Cascade (Grey), and Pool (White).
!
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Figure 4: a) Mean (SE) riffle macroinvertebrate non-corrected density and b) mean (SE)
habitat-corrected density for upstream (Black) and downstream (White) reaches within
each stream. The * represents a significant difference between upstream and downstream
pairs at p < 0.001 (Bonferroni post-tests).
!
100!
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,-./(0(123 4155+67(81*123
Figure 5: Mean (SE) macroinvertebrate density between riffle habitat and amphibious
and torrenticolous microhabitats of cascades upstream (Black) and downstream (White)
of diversions, with all streams pooled. The * represents a significant difference between
upstream and downstream pairs at p < 0.001 (Bonferroni post-tests).
!
101!
544
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Figure 6: Community composition of riffle, torrenticolous and amphibious habitats for all
streams and sites pooled. Taxa comprising less than 3% of the total community were
pooled and defined as rare. Native taxa are denoted with an * and represented as solid
bars whereas introduced species are represented by hashed lines.
!
102!
=,(8->?@A-B,84*)C-:178)9:6;5,6-.(/(->:9D(8*4E4FE&A
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0*112, 3(45(6,
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Figure 7: Mean (SE) macroinvertebrate density for habitat and location upstream (Black)
and downstream (White) of the highest elevation diversions of all streams (data pooled).
Introduced taxa density references the left y-axis and native density references the right
y-axis. The * represents a significant difference at p < 0.001(Bonferroni post-tests).
There was also a significant difference in introduced taxa density between riffle and
cascade habitats, upstream of diversions (t = 6.665, df = 1, p < 0.001).
!
!
!
!
!
!
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Figure 8: Index of Nativity (ratio of native taxa density to introduced taxa density) for
each habitat (Riffle – Black, Torrenticolous – Grey, Amphibious – White) and location
upstream and downstream of the highest elevation diversion in each stream (data pooled).
Different letters indicate significant differences between columns (p < 0.001, Bonferroni
post-tests).
!
104!
Figure 9: NMDS ordination with habitat overlay. Total stress = 15.71. Axis 1 explained
52.1% and axis 2 explained 18.7% of the variation in macroinvertebrate community
structure. MRPP analysis demonstrated significant separation in community composition
among habitats (A = 0.185, p < 0.0001).
!
!
!
!
105!
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CHAPTER IV
BENTHIC COMMUNITY STRUCTURE UNDER DIFFERENT FLOW AND
SUBSTRATE CONDITIONS IN THE LITTLE MIAMI RIVER, OHIO
ABSTRACT
Streams and rivers are made up of a continuum of distinct habitats composed of
macroinvertebrate and fish communities. Many studies have investigated the differences
between these geomorphic units, but often focus on riffle and pool habitats. This study
compares the physical template and the macroinvertebrate community, in June and
September 2008, between riffle and run habitats of a 1 km reach in the Little Miami
River, Greene County, Ohio. Mean flow velocity was significantly greater in riffle (mean
± SE = 0.74 ± 0.04 m/s) than run (0.32 ± 0.01 m/s) habitat units (p < 0.0001, MannWhitney U = 28.0). Similarly, macroinvertebrate density was significantly greater in
riffle habitats (mean ± SE; 1892 ± 200.2, 4018 ± 493.6) than in run habitats (540.3 ±
76.8, 930.1 ± 139.6), in both June and September, respectively. Further, linear regression
found a positive and significant relationship (y = 4097x – 115.1, p < 0.0001) where 49%
of variation in macroinvertebrate density was explained by mid-column velocity. Our
results call for the need of future analyses and studies that focus on the relationship
between flow and community dynamics, using simple and complex hydraulic variables in
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an attempt to determine which more accurately predict the distribution of invertebrate
communities.
INTRODUCTION
Streams are generally acknowledged as having a patchy landscape (Hildrew &
Giller 1994). Geomorphic units such as pools, riffles and runs are distinct habitats for
specific assemblages of aquatic flora and fauna such as macroinvertebrates (e.g. Lium,
1974; Logan & Brooker, 1983; Pridmore & Roper, 1985; Brown & Brussock, 1991),
macrophytes, and algae (e.g. Korte & Blinn, 1983), and represent distinct habitats for fish
(e.g. Saffel & Scarnecchia, 1995; Braaten & Berry, 1997). Ecologists use these various
habitats as sampling units or for describing habitat use (Allen 1951, Pridmore & Roper
1985, Glova & Duncan 1985, Jowett 1993). However, these sampling units are often
used to reduce or to demonstrate the variability caused by the physical differences in
these habitat types, and thus further efforts are usually limited to one habitat type (i.e.
riffle habitats) (Allen 1951, Lium 1974, Logan & Brooker 1983, Pridmore & Roper 1985,
Brown & Brussock 1991, Jowett 1993).
While many studies have compared the faunas of different stream habitats, most
comparisons are concerned mainly with riffle and pool habitats (Dolling 1968, Lium
1974, Armitage 1976, Minshall & Minshall 1977, Scullion et al. 1982, Logan & Brooker
1983, O’Neill & Abrahams 1984, Brown & Brussock 1991, Jowett 1993). These habitats
are known to differ significantly in flow velocity, depth and substratum (O’Neill &
Abrahams 1984) and therefore, differences in faunal abundance and diversity may be
expected. However, variation among riffle and run habitats may not be as apparent, and
thus, are not typically the focus of biological studies.
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A riffle habitat is a geomorphic unit that can be defined as a “place where there is
an obstruction in the stream, producing a ripple, or a stretch of shallow, rapid or choppy
water, typically providing a well-oxygenated habitat” (Brown & Shoemake 1964). A
riffle habitat is hydraulically rough and a complex patchwork of microhabitats (Pringle et
al. 1988). Within a riffle habitat, sufficient microhabitat heterogeneity may exist within a
quadrat to enable several species to coexist and minimize intra- and interspecific
competition (Sites & Willig 1991). On the other hand, run habitats are hydraulically
smooth, of increased depth and made up of fine sediments, homogeneous in nature. Run
habitats often represent the “average” current velocity and depth in a lotic system
(Mosely 1982) and therefore are more similar in physical characteristics to riffles than
pools (Pridmore & Roper 1985).
Accurate identification of distinct habitats in the aquatic environment has been
encouraged as an important tool in monitoring programs (i.e National River Authority
1993 in Buffagni et al. 2000, Moore et al. 1997). However, pools, runs and riffles are not
discrete units and instead form a continuum for which classification is arbitrary and
consequently there will be some overlap in any subjective method of assessment (Jowett
1993). The functional habitat concept, proposed by Harper et al. 1992 and 1995, is a
habitat-based approach that identifies distinct habitat units based on physical and
biological attributes, using the distribution of macroinvertebrate assemblages (Buffagni et
al. 2000). Effectiveness of the functional habitat approach strongly depends upon the
existence of separate physical habitats that support different assemblages with distinct
functional roles in the river environment (Buffagni et al. 2000).
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Characterizing the hydrology, substrate and biological communities of river
systems can be done at various scales that provide different ecological information
regarding the structure and function of the stream ecosystem. In this study, our objective
was to compare the physical habitat template and biological communities between riffle
and run habitats in a 1 km reach of the Little Miami River. We hypothesized that
macroinvertebrate density and diversity would be greater in riffle habitats with a positive
relationship between flow velocity and density.
METHODS
Study site
The study took place in a 1 km reach of the Little Miami River, Ohio in Greene
County, directly upstream of the Jacoby Rd. canoe launch park, which was fully
accessible throughout the study period. Here, the river is dominated by a natural
sequence of riffle and run habitats, with very few pools. The Little Miami River flows
107 miles from its headwaters in southeastern Clark County to its confluence with the
Ohio River in Hamilton County east of Cincinnati, with a total drainage area of 1,757
square miles. The topography of the Little Miami River Watershed has been influenced
by glacial activity, which left distinctive landforms and thick deposits of silt, sand, and
gravel. Aquatic life use designations for the streams in the watershed reflect the generally
good conditions in the watershed. The stream is designated as an Exceptional
Warmwater Habitat (EWH) and has a State and National Scenic River status. Land uses
in the watershed are principally agricultural in the northern and eastern portions with
relatively limited development near cities. Beginning with the Dayton-Xenia corridor
there is an increasing impact from population and development. While most developing
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areas in the Little Miami River watershed are not immediately adjacent to the river, the
impacts of development are still a potential problem. Numerous residential, industrial,
and commercial developments are recently completed, underway, or proposed within the
watershed (OEPA 2000).
A USGS gauge station (03240000) on the Little Miami River near Oldtown, Ohio
(39°44’54” and 83°55’53”) was used to obtain discharge data throughout the 2008 study
period and data was compared to field measurements made according to Gordon et al.
(1992).
Field collections
At the Jacoby Rd. canoe launch site within the Little Miami River, a 1 km reach
was measured and five sequential riffle and five sequential run sites that ranged from
39°45.837, 83°54.137 to 39°45.998, 83°53.937 were identified based on substrate and
flow characteristics. These were identified as Riffles 1 – 5 and Runs 1 – 5. A 100 square
meter grid was placed within each riffle and run site and a random number generator
provided six 1 x 1 m cell locations from which benthic samples were collected. Prior to
each sampling, water depth and velocities were measured above the benthic habitat at
four equidistant points within the modified Surber sampler area (0.0625 m2). Flow
velocity measurements were taken at 0.2, 0.6 and 0.8x total depth to generate a flow
profile within the water column. The benthic area was then scrubbed for 30s with a
coarse brush and dislodged material was collected in a D-frame net placed directly
downstream of the sample area. All samples are stored in 70% ethanol for laboratory
sorting and identification. Sampling events took place once a month from June –
September in 2008, collecting six samples from each site each month. Samples were
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sorted and organisms were identified to genus or lowest possible taxonomic resolution for
the June and September sampling events.
Substrate size and canopy cover was described for each site once during the study
period. The composition of substrate has been identified as being an important parameter
affecting the spatial arrangement of benthic communities. Using a gravelometer and the
Wolman Pebble Count procedure, substrate size was measured by walking heel-toe
across the wetted width of the channel, representing the most downstream transect of
each habitat unit, and measuring the rock touching the toe after each step. If there are
less than ten measurements along the transect, the recorder moved 1m upstream and
continued the process. Therefore, at least 100 measurements were made to generate a
substrate size frequency distribution for each habitat unit. These measurements were
then plotted and a frequency distribution produced. Describing the amount of light
infiltrating to the streambed is important for in-stream primary production, thus a
potential food resource for the benthic organisms. This was accomplished by
determining the percent canopy cover using a convex densiometer. Four estimates (one
facing downstream, toward the left descending bank, upstream and toward the right
descending bank) were taken in the middle of the wetted width at the most downstream
transect of each habitat. From the four estimates, canopy cover was calculated for each
site.
Statistical analyses
Total macroinvertebrate density described macroinvertebrate abundance, whereas
Simpson’s Diversity Index expressed extent of biodiversity at each site and was used to
compare between riffle and run habitat units. To determine macroinvertebrate density
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117!
differences among riffle sites and among run sites, one-way ANOVA with Bonferroni
post-tests were performed using GraphPad Prism 5.0 (GraphPad Software). After
pooling all riffle sites and all run sites, two-way ANOVA with Bonferroni post-tests
determined differences in these macroinvertebrate metrics between habitat units (riffle vs.
run) and sampling events (June vs. September). All data were appropriately transformed
to meet assumptions of normality and homogeneity of variances; however, when
transformations did not produce normal distributions, nonparametric analyses were used.
A two-tailed Mann-Whitney U t-test was used to determine flow velocity differences
between riffle and run habitats. Linear regression identified the relationship between
macroinvertebrate density and flow velocity. Nonmetric multidimensional scaling
(NMDS) followed by multi-response permutation procedures (MRPP) using PC-Ord
(McCune & Mefford 1999), investigated overall macroinvertebrate community
composition between habitats, and between sampling events. Prior to the NMDS
ordinations, data were log (x + 1) transformed and Sorensen distance measure was used
with a random starting configuration and 250 runs with real data (McCune & Grace
2002). As described by in McCune & Grace (2002), results from Monte Carlo tests with
4999 randomizations determined significant differences in community structure.
RESULTS
USGS mean daily discharge data was used to generate a hydrograph during the
study period (Figure 1). On the two sampling dates, June 20 and September 13, 2008, the
Little Miami River average daily discharge was 3.34 m3/s and 0.71 m3/s, respectively.
When sampling dates and sites were pooled, average flow velocity was significantly
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greater in riffle (mean ± SE = 0.74 ± 0.04 m/s) than run (0.32 ± 0.01 m/s) habitat units
(Figure 2; p < 0.0001, Mann-Whitney U = 28.0).
Substrate size was measured at each site and pooled for each habitat. Following
the Wolman Pebble Count and distribution procedure, it was determined that 50% of the
samples were equal to or smaller than 25 mm in the run habitat and 60 mm in the riffle
habitat (Figure 2). Canopy cover was also measured at each site, facing four different
directions and averaged. Riffle habitats had 77.9% canopy cover, whereas run habitats
were slightly less at 72.5%.
Total macroinvertebrate density varied among riffle sites and among run sites.
One-way ANOVA results indicated that in June, macroinvertebrate density did not
significantly differ among riffle sites (p = 0.0642, Kruskal-Wallis KW = 8.88), whereas
density was significantly different among run sites (p = 0.004, KW = 15.53), with Dunn’s
multiple comparison test identifying differences between Run 2 and 4, and between Run
3 and 4. In September, conversely, macroinvertebrate density among riffle sites
significantly varied (p = 0.01, KW = 12.43) with a difference between Riffle 1 and 5;
however density did not significantly differ among run sites (p = 0.49, KW = 4.42).
While a general trend was not seen among sites and between sampling times, total
macroinvertebrate density from all riffle sites and from all run sites were pooled for
comparisons between habitat units. There were significant main effects of habitat (p <
0.0001, F = 63.75, df = 1) and sampling time (p < 0.0001, F = 20.46, df = 1) on
macroinvertebrate density when biological data from riffle sites and run sites were
pooled. Macroinvertebrate density was significantly greater in riffle habitats (mean ± SE;
1892 ± 200.2, 4018 ± 493.6) than in run habitats (540.3 ± 76.8, 930.1 ± 139.6), in both
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June and September, respectively (Figure 3). Bonferroni post-tests found
macroinvertebrate densities were significantly greater in the riffle habitat in September
than June (p < 0.01 t = 5.41), whereas density in the run habitat did not differ between the
two months (p > 0.01, t = 0.99). Similarly, there were significant main effects of habitat
(p = 0.02, F = 6.055, df = 1) and sampling time (p = 0.03, F = 4.7, df = 1) on Simpson’s
Diversity Index. Diversity was greater in the riffle than run habitat in June (mean ± SE;
0.88 ± 0.03, 0.79 ± 0.06) and by September, diversity increased in both habitats,
respectively (1.03 ± 0.05, 0.87 ± 0.06). Further, linear regression found a positive and
significant relationship (y = 4097x – 115.1, p < 0.0001) where 49% of variation in
macroinvertebrate density was explained by mid-column velocity (Figure 4).
While the relative percent composition of taxa varied between habitat units, seven
taxonomic groups comprised 90% of riffle and 89% of run habitats, including
Chironomidae, Heptageniidae, Optioservus sp., Hydropsyche sp., Baetis sp., Caenis sp.,
and Tricorythodes sp. (Figure 5). The remaining 10 – 11% was made up of rare taxa (<
3% each) including Ephemera sp., Isonychia sp., Plauditus sp., Dubiraphia sp.,
Psephenus sp., Berosus sp., Antocha sp., Simullidae, Cheumatopsyche sp., Hydroptila
sp., Goniobasis sp., Corbicula sp., Sphaeriidae sp., Lebertia sp., Sperchon sp.,
Torrenticola sp., Ceratopogenidae, Corydalidae, and Nematoda. Although rare, there
were two species, Isonychia sp. and Plauditus sp., which were only found in riffle
samples, while Corydalidae were only found in run samples. All other taxa were present
in both riffle and run habitats.
Community composition differences between riffle and run habitats were
investigated through multivariate analyses, however, a 3-dimensional NMDS ordination
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with high stress (32.41) explained only 0.1% of the variation among communities (Figure
6). Although clear partitioning was not visually obtained on the ordination, significant
community composition separation was found between riffle and run habitat communities
(A = 0.069, p = 0.00000) and between June and September sampling times (A = 0.061, p
= 0.00000) through MRPP analysis.
DISCUSSION
As depicted in the hydrograph, mean daily discharge decreased throughout the
summer season, which was expected as later summer months are drier and typically
experience less precipitation in continental mid-western streams. While total discharge
did decrease, the streambed remained wetted at all sites and allowed for sampling. Also
expected were the differences in flow velocity and substrate size between riffle and run
habitats. Riffle habitats are known to be more hydraulically rough with greater substrate
heterogeneity (Pringle et al. 1988), whereas run habitats are hydraulically smooth with
smaller, homogeneous sediments.
Higher total densities were found on the cobbled beds of riffles than in the
predominantly sand/gravel beds of runs, which were comparable to results found by
Pridmore & Roper (1985). This would be expected because riffle habitats are naturally
more oxygenated, readily provide food resources, and are comprised of diverse
microhabitats for an array of macroinvertebrate assemblages. Many have observed that
benthic invertebrates increase in numbers with increasing particle size from sand through
large boulders (Percival & Whitehead 1929, Tarzwell 1936, Pennak & Van Gerpen 1947,
Sprules 1947, Bell 1969, Pridmore & Roper 1985). Hynes (1970) suggested that an
increase in mean particle size may be related to an increase in the complexity of the
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substratum, which in turn in essential for an abundant and diverse fauna. Further, the
relationship between hydraulic variables and invertebrate densities and community
structure has been the topic of many investigations, especially in the development of
habitat suitability curves for benthic invertebrates (Quinn & Hickey 1994, Lloyd & Sites
2000, Jowett 2003, Mérigoux & Dolédec 2004, Brooks et al. 2005). Specifically, Froude
number has been shown to be closely related to the distribution of some stream insects
(Statzner 1981, Orth & Maughan 1983, Jowett et al. 1991, Jowett 1993).
In this investigation, community composition was qualitatively similar between
riffle and run habitats. Only two taxa groups, Isonychia sp. and Plauditus sp., were found
exclusively in riffle habitats. Most Ephemeroptera nymphs are collectors or scrapers that
feed on a variety of detritus and algae (Merritt, et al. 2008), therefore these findings
would be expected. Our results were consistent with Pridmore & Roper (1985) who
concluded that a qualitative description of the riffle fauna would likely describe the run
fauna as well. However, quantitative differences did exist between riffle and run habitats.
Therefore, when quantitative information is required, as in productivity studies or
resource assessment surveys, the two habitats should be sampled separately (Pridmore &
Roper 1985).
Hydrodynamic variables may be the most important, yet least understood
environmental factors affecting the ecology of benthic organisms (Hart et al. 1996). This
may be supported by our positive and significant relationship obtained between midcolumn velocity and invertebrate density. The hydraulic stream ecology approach
suggested by Statzner et al. (1988) links the metabolism, feeding and behavior of lotic
organisms to the physical environment through the consideration of hydraulic
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characteristics. Such an approach, utilizing simple and more complex hydraulic
variables, would better our understanding of the distribution of macroinvertebrate
communities.
In conclusion, our hypotheses were supported and basic knowledge of riffle and
run habitats was further gained. Our results call for the need of future analyses and
studies that focus on the relationship between flow and community dynamics, using
simple and complex hydraulic variables in an attempt to determine which more
accurately predict the distribution of invertebrate communities. Other field studies have
obtained mixed results and it is still unclear which are better predictors of benthic
invertebrate abundance and habitat suitability (Jowett et al. 1991, Quinn & Hickey 1994,
Gore 1996, Jowett 2003, Mérigoux & Dolédec 2004).
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100
80
Discharge (m3/s)
60
40
20
15
10
5
0
May
June
July
August
September
October
Figure 1: Hydrograph depicting mean daily discharge (m3/s) for the Little Miami River
(USGS gage 03240000), near Oldtown, Ohio from May through September 2008.
Vertical dotted lines indicate sampling events. Data were retrieved from www.usgs.gov.
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Cumulative Sediment
Distribution (%)
100
75
50
25
32
64
12
8
25
6
51
2
10
24
20
48
8
16
4
2
1
0
Particle Size Category (mm Log2)
Figure 2: Riffle and run habitat substrate particle size frequency distribution. Horizontal
dashed line indicates the particle size at which 50% of the substrate was equal to or
smaller than for each habitat. Square data points represent the run habitat and circle data
points represent the riffle habitat.
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Mid-column Velocity (SE) m/s
1.0
*
0.8
0.6
0.4
0.2
0.0
Run
Riffle
Figure 3: Mean (SE) flow velocity measured at each benthic sample in the riffle and run
habitats. The * represents a significant difference at p < 0.0001 level.
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Macroinvertebrate Density
(organisms/m2)
5000
c
4000
3000
b
2000
1000
a
a
0
Run
Riffle
June
Run
Riffle
September
Figure 4: Mean (SE) macroinvertebrate density for habitat and sampling time. Different
letters indicate significant differences between comparisons (p < 0.05).
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Macroinvertebrate Density
(organisms/m2)
8000
6000
4000
2000
0
0.0
0.5
1.0
1.5
Mid-Column Flow Velocity
(m/s)
Figure 5: Linear regression relationship between mid-column velocity (m/s) and
macroinvertebrate density. Data obtained from riffle and run habitats were pooled.
y = 4097x - 115.1
p < 0.0001
R2 = 0.49
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100
Percent taxa composition
80
60
40
Hydropsyche sp.
Optioservus sp.
Tricorythodes sp.
Heptageniidae
Caenis sp.
Baetis sp.
Chironomidae
20
0
Rare (taxa<3%)
Run
Riffle
Figure 6: Community composition of riffle and run habitats for all sites pooled. Taxa
comprising less than 3% of the total community were pooled and defined as rare.
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Figure 7: NMDS ordination with habitat overlay. Total stress = 32.41. Only 0.1% of the
variation among samples was explained by the 3-dimensional solution. However, MRPP
analysis demonstrated significant separation in community composition among habitats
(A = 0.0691, p = 0.00000) and among sampling times (A = 0.2461, p = 0.00000).
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FUTURE DIRECTIONS
In summary, the projects involved in this dissertation investigated the effects of
hydrology on habitat template and macroinvertebrate communities within lotic
ecosystems. The completion of these projects has provided deeper insight into the
ecological organization of streams and rivers, generated information that can be used to
predict how flow alterations caused by human activities affect these vital ecosystems, and
has the potential to guide management and restoration efforts.
While the conclusions drawn from each project will contribute substantially to
fundamental knowledge of Stream Ecology, further analyses can provide a more
comprehensive understanding of the relationship between hydrology and
macoinvertebrate communities. Advanced hydraulic modeling, along with the
calculation of simple and complex hydraulic variables could assist in predicting the
spatial and temporal distribution of invertebrate communities. Data gathered from these
investigations could be utilized for such purposes at a later time, and insight gained has
generated additional questions and future project plans.
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