Springer 2005
Hydrobiologia (2005) 539:121–130
DOI 10.1007/s10750-004-3914-3
Primary Research Paper
Characterizing macroinvertebrate assemblage structure in relation to stream
size and tributary position
Jani Heino1,*, Juha Parviainen2, Riku Paavola3, Michael Jehle2, Pauliina Louhi4
& Timo Muotka2,5
1
Finnish Environment Institute, Research Programme for Biodiversity, P.O. Box 413, FIN-90014 University of Oulu,
Finland
2
Department of Biology, P.O. Box 3000, FIN-90014 University of Oulu, Finland
3
Department of Zoology, University of Toronto, Toronto, ON M5S 3G5, Canada
4
Finnish Game and Fisheries Research Institute, Tutkijantie 2 A, FIN-90570 Oulu, Finland
5
Finnish Environment Institute, Research Department, P.O. Box 140, 00251 Helsinki, Finland
(*Author for correspondence: E-mail: jani.heino@ymparisto.fi)
Received 25 September 2003; in revised form 27 August 2004; accepted 28 September 2004
Key words: assemblage structure, benthic macroinvertebrates, biodiversity conservation, functional feeding groups, lotic
communities, streams
Abstract
We examined the variability of macroinvertebrate assemblage structure, species identities, and functional
feeding group composition in relation to stream size, tributary position, and in-stream factors in a boreal
watershed in Finland. Our study included three riffle sites in each of three stream sections in each of three
stream size classes. Multi-response permutation procedure, indicator value method, and canonical correspondence analysis revealed clear differences in assemblage structure among the stream size classes, with a
gradual increase of species richness as the stream size increased. Significant differences in assemblage
structure were also found among the tributary river systems. The functional feeding group composition
broadly followed the river continuum concept, i.e., headwaters were dominated by shredders, gatherers, or
filterers, whereas scrapers increased in relative abundance with stream size. There was, however, considerable variation in the functional feeding group composition both among and within the headwater stream
sections. Our findings refer to a strong influence of stream size on macroinvertebrate assemblages, but also
factors prevailing at the scale of individual riffles should be considered in biodiversity conservation of lotic
ecosystems.
Introduction
Successful conservation of biodiversity requires
the identification of regionally representative sets
of key habitats and associated biological communities, thereby creating a need for extensive biodiversity inventories. Extensive inventories of
biological communities in several regions are,
however, costly in terms of money and effort.
A cost-effective alternative for extensive surveys
is to develop predictive models of community–
environment relationships in a few well-examined
regions, and to apply such information for conservation planning in more poorly-known regions
(Angermeier & Winston, 1999). Such predictive
models should incorporate information on both
taxonomic and functional components of biodiversity. In this regard, streams are particularly
challenging, given that their biodiversity is affected
by (i) longitudinal processes along the stream size
gradient, (ii) lateral interactions with the surrounding landscape, and (iii) within-stream vari-
122
ability at the scale of stream sections and microhabitats (Allan, 1995; Ward, 1998).
Viewing stream communities in the holistic
context of drainage systems has been a major research approach in stream ecology, and it has led
to the generation of many influential hypotheses
about the organization of stream communities.
The river continuum concept (RCC) (Vannote
et al., 1980; Minshall et al., 1985) in particular has
attained a central position in stream ecology, although its global applicability has also been
questioned (Winterbourn et al., 1981; Statzner &
Higler, 1985). The RCC predicts, for example, that
the functional feeding group composition of
macroinvertebrate assemblages should shift from
the shredder-dominated headwaters via scraperdominated middle reaches to the collector-dominated lower reaches of large rivers (Vannote et al.,
1980; Minshall et al., 1983). Furthermore, species
richness should peak in the middle reaches of large
rivers, where high environmental heterogeneity
enables the co-occurrence of species with widely
differing niche requirements (Minshall et al., 1985;
Grubaugh et al., 1996; Vinson & Hawkins, 1998).
While the RCC mainly relates biotic changes to
parallelling variation in the productivity base,
other conceptual approaches associate such changes to stream hydraulics (e.g., Statzner & Borchardt, 1994), or stress the effects of stream position
in terms of downstream confluences on biotic
patterns along the river continuum (e.g., Osborne
& Wiley, 1992).
The spatial position and in-stream/riparian
characteristics of a riffle site may also have considerable effects on macroinvertebrate assemblage
structure. For instance, sites in different tributaries
within a drainage system may differ sharply in
water chemistry and physical habitat characteristics, leading to corresponding differences in stream
biota (Townsend et al., 1983; Ormerod &
Edwards, 1987; Carter et al., 1996; Paavola et al.,
2000). Furthermore, even neighbouring riffles
within a stream may differ considerably in habitat
conditions and benthic assemblage structure (e.g.,
Downes et al., 1993). However, although several
studies have reported predictable patterns in the
distribution of biota along the river continuum,
the degree to which variation in macroinvertebrate
assemblage structure among and within streams
confounds longitudinal patterns within a drainage
system has gained little attention (Li et al., 2001;
Wright & Li, 2002; Parsons et al., 2003; Heino
et al., 2004).
Our objective was to examine the degree to
which macroinvertebrate assemblages in a boreal
drainage system correspond to predictions of the
RCC, and whether different stream size classes and
tributary river systems differ in faunal attributes,
i.e., assemblage structure, species identities, and
functional feeding group composition. Furthermore, we examined the relationships between
assemblage structure and riffle-scale environmental variables to determine whether local riffle
characteristics could confound longitudinal patterns along the river continuum.
Materials and methods
Study area and study design
The study was conducted in the River Kiiminkijoki
drainage system (65 N, 26 E) in Finland (Fig. 1).
Bedrock in the study area mainly consists of greywacke, mica schist, and quartzite. The forests are
dominated by coniferous trees, mainly Scotch pine
(Pinus sylvestris L.) and Norwegian spruce (Picea
abies L.). Typical deciduous vegetation along river
courses consists of birch (Betula pubescens Ehrh.
and Betula pendula Roth), buckthorn (Rhamnus
frangula L.), alder (Alnus incana L.), willows (Salix
spp.), birdcherry (Prunus padus L.), and aspen
(Populus tremula L.). Due to the extensive occurrence of peatlands in the watershed, stream water is
slightly acidic, with high concentrations of humic
substances and nutrients (Table 1).
Our study incorporated samples from 27 riffle
sites (Fig. 1). The sites were divided into three size
classes: we thus sampled three riffles from each of
three headwater streams (1st and 2nd orders),
three riffles in each of the three mid-sized rivers
(3rd order), and three riffles in each of three main
channel sections (5th order). The 18 riffles in the
headwater streams and mid-sized rivers represented three separate tributaries (Fig. 1).
Field and laboratory procedures
Sampling was conducted in late September 1999.
We randomized the order in which the streams
123
Figure 1. Location of the study sites in the Kiiminkijoki drainage system. MCa, MCb, and MCc refer to main channel sections. Riffles
of different size classes are denoted by different colours: black squares ¼ large (5th order); dark grey squares ¼ mid-sized (3rd order);
light grey squares ¼ small (1st and 2nd orders).
were sampled. At each riffle site, we quantified
habitat variables at 40 plots. Each plot had a
surface area of 0.04 m2 (20 · 20 cm). We measured depth and current velocity (0.4 · depth),
and estimated the cover of macrophytes and
mosses in each plot. Furthermore, the sizes of two
randomly selected stones were recorded for each
plot. Substratum size was determined by measuring three perpendicular dimensions of each stone,
and stone surface area was subsequently calculated
following Graham et al. (1988).
Ten benthic invertebrate samples were taken at
each riffle site. Samples were taken using a stratified random sampling protocol: transects were
placed regularly across the riffle, and two to five
plots were placed randomly in each transect,
depending on stream width. Sampling was conducted using a Surber sampler (20 · 20 cm, net
mesh size 0.3 mm). All samples from a riffle site
were pooled, and thus variability at smaller,
within-riffle scales will not be considered here. The
invertebrates sampled were identified to the lowest
possible taxonomic level, mainly species or genus
level, and invertebrates were subsequently classified into functional feeding groups according to
Merritt & Cummins (1996) and our own observations of invertebrate gut contents (J. Heino
et al., unpublished data).
Data analysis
Overall differences in assemblage structure among
riffles of different stream size classes and among
different tributaries were examined using multiresponse permutation procedure (MRPP). MRPP
is a non-parametric alternative to discriminant
function analysis, aiming to reveal whether a priori
determined groups [in this case, (i) size classes and
(ii) tributaries when the main channel sites were
omitted] differ in assemblage structure (McCune &
Mefford, 1997). The null hypothesis of no difference among groups was tested by a Monte Carlo
randomization test. Following MRPPs, we used
the indicator value method (IndVal) of Dufrene &
Legendre (1997) to identify species discriminating
among the a priori groups. The indicator value
varies from 0 to 100, attaining its maximum value
when all individuals of a species occur at all sites of
a single group (Dufrene & Legendre, 1997). The
significance of the indicator values for each species
was tested by the Monte Carlo randomization test.
For both MRPP and IndVal, 1000 Monte Carlo
permutations were run using PC-Ord (McCune &
Mefford, 1997).
Canonical correspondence analysis (CCA) was
used to examine which environmental factors best
accounted for variation in assemblage structure
among the riffles. CCA is one of the most commonly used constrained ordination methods that
analyses both species and environmental data by
combining ordination and multiple regression
(Ter Braak & Prentice, 1988; Legendre & Legendre, 1998). Stepwise selection of environmental
variables was used to obtain a reduced set of
significant explanatory variables, and the significance of the relationship between environmental
124
Table 1. Average chemical and physical characteristics of the stream sections studied in the River Kiiminkijoki drainage system. R1,
R2, and R3 refer to different tributary river systems. MCa, MCb, and MCc refer to different main channel sections (Fig. 1)
Size
Small
Section
Näsiäoja Haaraoja Loukonoja
Juuanjoki
Jolosjoki
Onkamonoja
Tributary
(R1)
(R1)
(R2)
(R3)
Stream order
Shading (%)
Stream width (m)
2
44
2.0
Mid-sized
(R2)
(R3)
Large
MCa
MCb
1
2
3
3
3
5
5
61
2.3
73
1.0
22
4.3
24
6.8
42
5.0
0
52.0
0
67.0
0
83.0
12.0
Discharge (m3 s)1)
0.03
0.11
0.06
0.12
0.42
0.22
11.9
11.9
pH
6.5
5.7
6.1
6.6
6.2
5.9
6.5
6.5
Total N (lg L)1)
600
Total P (lg L)1)
Colour (mg Pt L)1)
750
610
820
790
13
26
20
15
32
200
280
240
160
280
3.4
6.4
Conductivity (mS m)1)
5.0
MCc
3.2
variables and species data was tested at each step
using the Monte Carlo randomization test with
1000 permutations. Separate analyses were performed for the size class (27 sites) and tributary (18
sites, main channel sites omitted) comparisons.
Species occurring only at a single site were omitted
from both analyses. CCAs were run using CANOCO version 4.0 (Ter Braak, 1998). PC-ORD
was used to plot the abundance variation of significant indicator species found by IndVal on the
CCA ordination biplots.
4.3
520
460
17
200
2.8
5
6.6
460
450
26
26
24
150
150
160
3.1
3.1
3.7
Results
A total of 101 operational macroinvertebrate taxa
(hereafter called species) were found from the riffle
sites sampled. MRPP revealed significant differences in assemblage structure among the size
classes (R ¼ 0.233, p < 0.001). Pairwise tests
indicated significant differences between riffles in
smalll and mid-sized (R ¼ 0.141, p < 0.001),
small and large (R ¼ 0.220, p < 0.001), and midsized and large streams (R ¼ 0.204, p < 0.001).
Table 2. Summary of indicator value analysis for the stream size class comparison. Shown are the 14 species with highest indicator
values. Indicator values were calculated based on the relative abundance and frequency of occurrence of each species among the a
priori groups. All indicator values were significant at p < 0.001
Species
Small
Mid-sized
Large
Baetis niger (Linnaeus)
6
71
0
Baetis digitatus Bengtsson
0
6
80
Leptophlebia marginata (Linnaeus)
74
0
2
Ephemerella mucronata Bengtsson
0
3
82
Caenis rivulorum Eaton
Leuctra hippopus Kempny
0
0
0
81
67
5
Capnopsis schilleri (Rostock)
0
66
0
Hydropsyche siltalai Döhler
0
2
95
Arctopsyche ladogensis (Kolenati)
0
0
77
Cheumatopsyche lepida (Pictet)
0
0
100
Psychomyia pusilla (Fabricius)
0
0
97
Agapetus ochripes Curtis
0
13
79
Lepidostoma hirtum (Fabricius)
Ancylus fluviatilis (Linnaeus)
0
0
7
0
90
100
125
Figure 2. Biplot of CCA for the relationship between environmental variables and assemblage structure of the riffle sites: size-class
comparison. Riffles of different size classes are represented by different colours: black squares ¼ large (5th order); dark grey squares ¼ mid-sized (3rd order); light grey squares ¼ small (1st and 2nd orders). Abbreviations: PS ¼ particle size, MC ¼ moss cover,
MP ¼ macrophyte cover, W ¼ riffle width. Also shown are selected indicator species found by IndVal analysis for each size class, and
their relative abundance variation among the riffles. The smallest squares denote the absence of a species at a site.
Similarly, macroinvertebrate assemblage structure
exhibited significant, albeit weaker, differences
among the three tributaries (R ¼ 0.126,
p ¼ 0.002). Pairwise tests showed that tributary 1
differed significantly from tributary 2 (R ¼ 0.109,
p ¼ 0.019) and from tributary 3 (R ¼ 0.129,
p ¼ 0.007), whereas tributary 2 did not differ significantly from tributary 3 (R ¼ 0.059, p ¼ 0.068).
IndVal yielded further insight into the differences among the a priori groups. No species appeared confined to small streams, whereas several
species discriminated the riffles of the mid-sized
and the large rivers from the others (Table 2,
Fig. 2). For instance, the mayfly Baetis niger and
the stoneflies Leuctra hippopus and Capnopsis
schilleri had high indicator values for the mid-sized
rivers. The mayflies Baetis digitatus, Ephemerella
mucronata, and Caenis rivulorum, the caddisflies
Hydropsyche siltalai, Arctopsyche ladogensis,
Cheumatopsyche lepida, Psychomyia pusilla, Agapetus ochripes, Lepidostoma hirtum, and the snail
Ancylus fluviatilis had high indicator values and
126
Table 3. Summary of indicator value analysis for the tributary
comparison. Shown are the eight species with the highest
indicator values. All indicator values were significant at
p < 0.05. R1, R2, and R3 refer to different tributary river
systems (Fig. 1)
Species
R1
R2
R3
Baetis vernus group
0
3
56
Heptagenia sulphurea (Müller)
0
21
69
Ephemerella mucronata Bengtsson
Nemoura cinerea (Retzius)
0
6
0
92
67
0
Isoperla difformis (Klapalek)
3
9
84
Rhyacophila nubila (Zetterstedt)
14
54
33
Lepidostoma hirtum (Fabricius)
3
66
8
Atherix ibis (Fabricius)
2
16
79
showed strong preference for the large river riffles.
Only the mayfly Leptophlebia marginata had a
high indicator value for small streams, but this
species also occurred in some large river riffles
(Table 2). By contrast, only eight species had significant indicator values in the tributary river
system comparison. Most of these species were
either absent from or had low abundances in
tributary 1. Only the mayfly Ephemerella mucronata was restricted to a single tributary, whereas
all other indicator species also occurred in low
abundance/low frequency in the other two tributaries (Table 3, Fig. 3).
CCA with all 27 sites included had eigenvalues
of 0.257, 0.076, and 0.074 for the first three axes,
respectively (Table 4). Four environmental variables were selected by the forward selection procedure. Thus, variation in species composition
along axis 1 was strongly related to riffle width,
mirroring the overriding influence of stream size.
The second axis was related to particle size and
macrophyte cover (Fig. 2), and the third axis to
particle size and moss cover. The relationship between assemblage structure and environmental
variables was significant for both the first CCA
axis and the overall analysis (Monte Carlo test
with 1000 permutations, p ¼ 0.005). When the
riffles of the largest size class (main channel, 5th
order sites) were omitted from the analysis, the
eigenvalues were 0.262, 0.094 and 0.059 for the
first three axes, respectively (Table 5). Three variables were significantly related to the assemblage
structure in this analysis. The first axis was
strongly related to riffle width, the second one to
moss cover (Fig. 3), and the third one to particle
size and moss cover. Both the first axis and the
overall analysis were significant (Monte Carlo test,
1000 permutations, p ¼ 0.005). In the CCA biplot,
riffles in mid-sized rivers (3rd order streams) were
clearly separated from riffles in small stream (1st
and 2nd order stream) (Fig. 3).
Relative abundances of functional feeding
groups showed considerable variation within and
among size classes and tributaries (Fig. 4). Along
the size gradient, the clearest pattern was the increase in the proportion of scrapers from headwaters to large river riffles. Headwater assemblages
were generally variable, being dominated by either
shredders, filterers, or gatherers. No clear differences were observed among the tributaries, mainly
due to the inclusion of two size classes from each
tributary and the variation among riffles within
each section (Fig. 4).
Discussion
The river continuum concept (RCC) predicts
that macroinvertebrate assemblages change
gradually from headwaters to large rivers
downstream (Vannote et al., 1980). For instance,
the relative proportions of functional feeding
groups should change from the shredder-dominated headwaters to the collector-dominated
lower reaches of large rivers. Furthermore,
scrapers should attain highest abundances in the
middle reaches of large rivers. These connotations broadly applied to our study system, considering that our largest sites were in a 5th order
river. Headwater streams were either dominated
by shredders, gatherers, or filterers, while scrapers occurred in only low abundance. By contrast,
our 3rd to 5th order riffles were characterized by
an increase of scraper abundance, likely following the decrease in canopy cover (see Vannote
et al., 1980; Hawkins et al., 1982). Furthermore,
in the large river sites (5th order), macroinvertebrate abundances were more evenly distributed
among different functional feeding groups. Nevertheless, considerable variation in functional
feeding group composition was found among
riffles within a stream, especially in headwater
streams, suggesting that the characteristics of a
riffle site exert a strong control over functional
127
Figure 3. Biplot of CCA for the relationship between environmental variables and assemblage structure of the riffle sites: tributary
comparison where the main channel sites were excluded. Riffles in different tributaries are represented by different colours as follows:
black squares ¼ tributary 1; dark grey squares ¼ tributary 2; light grey squares ¼ tributary 3. Mid-sized riffles (3rd order) are encircled
by a dashed line, others are headwater riffles (1st and 2nd orders). Also shown are the indicator species found by IndVal analysis for
each river system, and their relative abundance variation among the riffles.
feeding group composition. The riffle sites varied
with regard to the distance to upstream lakes,
the retention capacity, and the amount of
riparian inputs, thereby likely influencing filterer
and shredder abundances. Furthermore, riffles
differed greatly in moss cover, which also directly relate to the retention capacity of the
streambed (Muotka & Laasonen, 2002). Such
local effects may lead to deviations from the
expectations of the RCC for streams of a certain
order (Naiman et al., 1987; Grubaugh et al.,
1996).
Stream size was the major factor influencing the
taxonomic structure of macroinvertebrate assemblages in our study, concurring to earlier findings
from both temperate and boreal streams (e.g.,
Hildrew & Giller, 1994; Malmqvist & Mäki, 1994;
Malmqvist & Hoffsten, 2000). In general, more
taxa were added as stream size increased, and no
species appeared to be restricted to the headwa-
128
Table 4. Results of CCA for the relationship between assemblage structure and riffle-scale environmental variables, with all
27 sites included. Total inertia was 1.320, and the sum of all
canonical eigenvalues was 0.458. Coefficients of the intraset
correlations among the environmental variables and the CCA
axes are also shown
Axis 1
Axis 2
Axis 3
Eigen value
Variation explained %
0.257
19.5
0.076
5.7
0.074
5.6
Particle size
)0.139
0.686
)0.699
Riffle width
0.997
0.073
0.023
Moss cover
0.009
0.262
)0.887
Macrophyte cover
)0.099
)0.564
)0.374
ters. By contrast, mid-sized riffles had several
mayfly species absent from the headwaters, a
pattern likely related to the fact that most mayflies
in our system were scrapers. Similarly, the large
river sites harboured several species of filtering
caddisflies and grazing snails that were absent
from the headwaters and occurring only sporadically in mid-sized streams. A similar continual
change in the species distributions for filtering
caddisflies has been reported elsewhere, being related to the interaction of current velocity, food
supply, and the mesh size of the filtering nets (e.g.,
Ross & Wallace, 1983).
Based on the spatial proximity, one would
easily envisage that macroinvertebrate assemblages in riffles from the same tributary river system or stream should resemble each other more
than riffles in other systems (see Parsons et al.,
2003). In our study, there was wide variation in
benthic assemblages among the headwaters and
the mid-sized sections within each tributary river
system, and especially among riffles within the
headwater streams (Fig. 3). These findings suggest
that even riffles separated by a distance of only a
few hundred metres may harbour macroinvertebrate assemblages with highly variable structure,
thus cautioning against generalizations based on
samples from a single riffle (see also Downes et al.,
1993; Heino et al. 2004). Although neighbouring
riffles within a stream are unlikely to exhibit considerable differences in species identities, the relative and absolute abundances of species may vary
Figure 4. Relative abundances of macroinvertebrate functional feeding groups in the three riffle sites of each stream section.
129
Table 5. Results of CCA for the relationship between assemblage structure and riffle-scale environmental variables, with the
main channel sites excluded. Total inertia was 1.079, and the
sum of all canonical eigenvalues was 0.416
Axis 1
Axis 2
Axis 3
Eigen value
0.262
0.094
0.059
Variation explained %
24.3
8.8
5.5
Particle size
0.560
)0.082
)0.825
Riffle width
)0.954
0.284
0.094
Moss cover
0.292
)0.736
)0.611
drastically according to local conditions. Thus,
environmental filters (sensu Poff, 1997) prevailing
at the reach-scale (e.g., stream size) may largely
determine species distributions within a drainage
system, while their ultimate success in terms of
local abundance is determined at the among- and
within-riffle scales.
The gradual change in assemblage structure
along the stream size gradient suggest that a
satisfactory conservation of benthic fauna might
be achieved by preserving large river riffles.
Nevertheless, other factors should also be considered when planning for conservation programs
at the level of whole drainage systems. For instance, headwater streams may act as source
habitats for some species occurring also in large
rivers (e.g., Angermeier & Winston, 1997). Thus,
if headwaters remain unprotected from habitat
degradation, several species may be threatened or
even lost from the drainage system. Furthermore,
although we found very few indicator species for
the headwater streams in our study system, small
streams often contain regionally rare species, and
rare assemblage types not typically found in larger rivers (Wright et al., 1998; Furse, 2000;
Malmqvist & Hoffsten, 2000). For example, chironomid midges are by far the most diverse
group of benthic macroinvertebrates in boreal
headwaters (Heino et al., 2003), yet little is
known about their habitat requirements. Several
chironomids and other ‘cryptic’ taxa may well be
restricted to headwater streams, thereby increasing their potential conservation value. Furthermore, because headwaters contribute importantly
to the ecological integrity of whole drainage systems, it has been suggested that headwaters
should be regarded as key zones for focusing
conservation efforts in freshwater ecosystems
(Saunders et al., 2002). In any case, it appears
that stream conservation planning should be
based on size-class stratification, because stream
size is clearly a key environmental gradient
determining the functional and taxonomic biodiversity of lotic macroinvertebrate assemblages.
Acknowledgements
We thank P. Tikkanen for originally suggesting
the study idea to us. The efforts of A. Huhta, J.
Kurppa, T. Lahdenperä, and P. Tikkanen during
the demanding field work are also greatly appreciated. J. Ylönen organized the sorting of the
invertebrate samples. This paper is part of the
Finnish Biodiversity Research Programme (FIBRE). Financial support was also provided by
Maj and Tor Nessling Foundation, North Ostrobothnia Fund of the Finnish Cultural Foundation,
Oulun Luonnonystäväin Yhdistys, and Entomological Society of Helsinki.
References
Allan, J. D., 1995. Stream Ecology. Structure and Function of
Running Waters. Chapman and Hall, New York.
Angermeier, P. L. & M. R. Winston, 1997. Assessing conservation value of stream communities: a comparison of approaches based on centres of density and species richness.
Freshwater Biology 37: 699–710.
Angermeier, P. L. & M. R. Winston, 1999. Characterizing fish
community diversity across Virginia landscapes: prerequisite
for conservation. Ecological Applications. 9: 335–349.
Carter, J. L., S. V. Fend & S. S. Kennelly, 1996. The relationships
among three habitat scales and stream benthic invertebrate
community structure. Freshwater Biology 35: 109–124.
Downes, B. J., P. S. Lake & E. S. G. Schreiber, 1993. Spatial
variation in the distribution of stream invertebrates: implications of patchiness for models of community organization.
Freshwater Biology 30: 119–132.
Dufrene, M. & P. Legendre, 1997. Species assemblages and
indicator species: the need for a flexible asymmetrical approach. Ecological Monographs 67: 345–366.
Furse, M. T., 2000. The application of RIVPACS procedures in
headwater streams – an extensive and important national
resource. In Wright, J. F., D. W. Sutcliffe & M. T. Furse
(eds), Assessing the Biological Quality of Fresh Waters.
Freshwater Biological Association, Ambleside: 79–92.
Graham, A. A., D. J. McCaughan & F. S. McKee, 1988.
Measurement of surface area of stones. Hydrobiologia 157:
85–87.
130
Grubaugh, J. W., J. B. Wallace & E. S. Houston, 1996. Longitudinal changes of macroinvertebrate communities along
an Appalachian stream continuum. Canadian Journal of
Fisheries and Aquatic Sciences 53: 896–909.
Hawkins, C. P., M. L. Murphy & N. H. Anderson, 1982.
Effects of canopy, substrate composition, and gradient on
the structure of macroinvertebrate communities in Cascade
Range streams of Oregon. Ecology 63: 1840–1856.
Heino, J., T. Muotka, R. Paavola & L. Paasivirta, 2003.
Among-taxon congruence in biodiversity patterns: can
stream insect diversity be predicted using single taxonomic
groups? Canadian Journal of Fisheries and Aquatic Sciences
60: 1039–1049.
Heino, J., P. Louhi & T. Muotka, 2004. Identifying the scales of
variability in stream macroinvertebrate abundance, functional composition and assemblage structure. Freshwater
Biology 49: 1230–1239.
Hildrew, A. G. & P. S. Giller, 1994. Patchiness, species
interactions and disturbance in the stream benthos. In
Giller, P. S., A. G. Hildrew & D. Raffaelli (eds), Aquatic
Ecology. Scale, Pattern and Process. Blackwell Science,
Oxford: 21–62.
Legendre, P. & L. Legendre, 1998. Numerical Ecology. 2nd
edn. Elsevier, Amsterdam.
Li, J., A. Herlihy, W. Gerth, P. Kaufmann, S. Gregory,
S. Urquhart & D. P. Larsen, 2001. Variability of stream
macroinvertebrates at multiple spatial scales. Freshwater
Biology 46: 87–97.
Malmqvist, B. & P. O. Hoffsten, 2000. Macroinvertebrate
taxonomic richness, community structure and nestedness in
Swedish streams. Archiv für Hydrobiologie 150: 29–54.
Malmqvist, B. & M. Mäki, 1994. Benthic macroinvertebrate
assemblages in north Swedish streams: environmental relationships. Ecography 17: 9–16.
Merritt, R. W. & K. W. Cummins, 1996. An Introduction to the
Aquatic Insects of North America. 3rd edn. Kendall/Hunt,
Dubuque.
McCune, B. & M. J. Mefford, 1997. PC-ORD. Multivariate
Analysis of Ecological Data, Version 3.0. MJM Software
Design, Gleneden Beach, Oregon.
Minshall, G. W., R. W. Petersen, K. W. Cummins, T. L. Bott,
J. R. Sedell, C. E. Cushing, & R. L. Vannote, 1983. Interbiome comparison of stream ecosystem dynamics. Ecological Monographs 53: 1–25.
Minshall, G. W., K. W. Cummins, R. C. Petersen, C. E.
Cushing, D. A. Bruns, J. R. Sedell & R. L. Vannote, 1985.
Developments in stream ecosystem theory. Canadian Journal of Fisheries and Aquatic Sciences 42: 1045–1055.
Muotka, T. & P. Laasonen, 2002. Ecosystem recovery in restored headwater streams: the role of enhanced leaf retention. Journal of Applied Ecology 39: 145–156.
Naiman, R. J., J. M. Melillo, M. A. Lock, T. E. Ford & S.
Reice, 1987. Longitudinal patterns of ecosystem processes
and community structure in a subarctic river continuum.
Ecology 68: 1139–1156.
Ormerod, S. J. & R. W. Edwards, 1987. The ordination and
classification of macroinvertebrate assemblages in the
catchment of the River Wye in relation to environmental
factors. Freshwater Biology 17: 533–546.
Osborne, L. L. & M. J. Wiley, 1992. Influence of tributary
spatial position on the structure of warmwater fish communities. Canadian Journal of Fisheries and Aquatic Sciences 49: 671–681.
Paavola, R., T. Muotka & P. Tikkanen, 2000. Macroinvertebrate community structure and species diversity in humic
streams of Finnish Lapland. Verhandlungen der internationalen Vereinigung für theoretische und angewandte
Limnologie 27: 2550–2555.
Parsons, M., M. C. Thoms & R. H. Norris, 2003. Scales of
macroinvertebrate distribution in relation to the hierarchical
organization of river systems. Journal of the North American Benthological Society 22: 105–122.
Poff, N. L., 1997. Landscape filters and species traits: towards
mechanistic understanding and prediction in stream ecology.
Journal of the North American Benthological Society 16:
391–409.
Ross, D. H. & J. B. Wallace, 1983. Longitudinal patterns of
production, food consumption, and seston utilization by netspinning caddisflies (Trichoptera) in a southern Appalachian
stream. Holarctic Ecology 6: 270–284.
Saunders, D. L., J. J. Meeuwig & C. J. Vincent, 2002. Freshwater protected areas: strategies for conservation. Conservation Biology 16: 30–41.
Statzner, B. & B. Higler, 1985. Questions and comments on the
river continuum concept. Canadian Journal of Fisheries and
Aquatic Sciences 42: 1038–1044.
Statzner, B. & D. Borchardt, 1994. Longitudinal patterns and
processes along streams: modelling ecological responses to
hydrological gradients. In Giller, P. S., A. G. Hildrew & D.
Raffaelli (eds), Aquatic Ecology. Scale, Pattern and Process.
Blackwell Science, Oxford: 113–140.
Ter Braak, C. J. F., 1998. Program CANOCO, version 4.0.
Centre for Biometry, Wageningen.
Ter Braak C. J. F. & I. C. Prentice, 1988. A theory of gradient
analysis. Advances in Ecological Research 18: 273–317.
Townsend, C. R., A. G. Hildrew & J. Francis, 1983. Community
structure in some southern English streams: the influence of
physicochemical factors. Freshwater Biology 13: 521–544.
Vannote, R. L., G. W. Minshall, K. W. Cummins, J. R. Sedell
& C. E. Cushin, 1980. The river continuum concept. Canadian Journal of Fisheries and Aquatic Sciences 37: 130–137.
Vinson, M. R. & C. P. Hawkins, 1998. Biodiversity of stream
insects: variation at local, basin, and regional scales. Annual
Review of Entomology 43: 271–293.
Ward, J. V., 1998. Riverine landscapes: biodiversity patterns,
disturbance regimes and aquatic conservation. Biological
Conservation 83: 269–278.
Winterbourn, M. J., J. S. Rounick & B. Cowie, 1981. Are
New Zealand stream ecosystems really different? New Zealand
Journal of Marine and Freshwater Research 15: 321–328.
Wright, K. K. & J. L. Li, 2002. From continua to patches:
examining stream community structure over large environmental gradients. Canadian Journal of Fisheries and Aquatic
Sciences 59: 1404–1417.
Wright, J. F., M. T. Furse & D. Moss, 1998. River classification using invertebrates: RIVPACS applications. Aquatic
Conservation – Marine and Freshwater Ecosystems 8:
617–631.