京都大学防災研究所年報 第 57 号 B 平成 26 年 6 月
Annuals of Disas. Prev. Res. Inst., Kyoto Univ., No. 57 B, 2014

Relations of Lentic Habitat Conditions and Abundance of Bitterling and Mussels to
Reach Scale Channel Configurationin the Kizu River
Mikyoung CHOI(1), Yasuhiro TAKEMON, Sohei KOBAYASHI, Tetsuya SUMI, Kinko
IKEDA(2) and Kazuhiro NISHII(2)(1) Graduate school of Engineering, Kyoto University(2) ASIA AIR SURVEY CO., LTD.
Synopsis
The Kizu River, a branch of the Yodo River in the middle Japan, had experienced
riverbed degradation and vegetation expansion in response to peak-cut in discharge andreduction in sediment dynamism after sand excavation and dam construction in these 60
years. This paper described relations among abundance of fish and mussel communities,
habitat structures and reach-scale channel configuration (RSCC) to link between micro
habitat scales and reach scales with temporal approach. As for relations between present
species and past habitat conditions, bitterling was best explained by a model one year
ago, and mussel was best explained by a model consist of flooding frequency and depthof mud two years ago. According to relations between species and habitat conditions insame year, terrace ponds having flood frequency between 8 and 22 days/ year were themost values for bitterlings and mussels. Concave floodplain with shape index between-0.25 and -0.05 tended to have high number of habitats having frequency between 8 and
22 days/year, and Kizu River in 2000s seemed to have higher potential habitat
suitability of bitterling and mussel than before.
Keywords: bitterling and mussel, flooding frequency, floodplain vertical shape index

1.

Introduction

In the last decade, many rivers had experienced
riverbed degradation and vegetation expansion in
response to peak discharge and flood frequency(Williams and Wolman, 1984). These river channel
alternations have led to deterioration of habitat
conditions. Especially, the Kizu River was known
as many lentic ponds or wando providing habitat tobitterlings and unionid mussels. However, thediversity of bitterling and mussels decreased, andrepresentative protected bitterling ‘Acheilognathus
longipinnis’ had disappeared by reduction ofconnectivity with main channels after sandexcavation and dam construction (Kizu River
Research Group, 2003). To improve river health, it
is needed to find out habitat conditions are requiredfor diversity of bitterlings and mussels. Mussels
could be used as an indicator of fish communities
because of various symbiotic relationships (Negishi
et al., 2013; Haag and Warren, 1998). Reproductionof mussels requires gobby fish as host (Haag andWarren, 1998) and bitterlings used mussels forspawning redd (Yoshihiro and Takashi, 2010). Thus,
bitterling and mussel are useful to evaluation
habitat conditions for animal communities not only

― 570 ―

mussels but also fishes.
In other to understand the intrinsic relations ofbitterlings and mussels to habitat conditions, it isimportant to analyze effects of nor only present
habitat conditions but also past conditions. The
survival of mussels depends on the interaction ofseveral biotic and abiotic factors operating atdifferent spatial and temporal scales (Morales et al.,2006; Haag and Warren, 1998). Because successful
reproduction requires the availability of an
appropriate host fish at the appropriate time andthat juveniles find favorable habitat, mussels had
possibility that they were related with spatial
diversity as well as time lag.
Habitat conditions for bitterling and mussel
within local scale should be linked withgeomorphological conditions in larger scales.
Frothingham et al. (2002) said linkages between
geomorphologicalconditions
andaquatic
ecosystems via the influence of fluvial processes
could be helped by the management of complex
fluvial systems. Although changes in reach andlarge-scale watershed characteristics can affectcommunity composition and environmental
condition (Poole and Downing, 2004), much of thestudy of mussel-habitat relationships has been
performed on the scale of the local scale (Tiegs etal., 2009). These relations are difficult tounderstand processes and mechanisms of creationand maintenance of habitats and habitat conditions

responded to changes of disturbance. Thus, multiple
spatial scales are a critical consideration forunderstanding ecological patterns (Tiegs et al.,2009).
Purposes of this study area 1) to clarify theamount of time lag between habitat changes having
a significant influence on species abundance ofbitterling and mussel, 2) to understand habitat
parameters having a dominant role on species
abundance, 3) to link habitats and reach-scalechannel configuration (RSCC) and 4) to show
appropriate RSCC supporting habitats for bitterlingand mussels and to estimate historical changes inpotential habitat suitability.
2.

Method

2.1 Study area
The study area was established in the lower
reaches (0~26km) of the Kizu River, a tributary of
the Yodo River in central Japan (Fig. 1). The Kizu
River has been called a typical sandy river derived
from weathered granite in the upper stream. A totalof 5 dams, Takayama Dam (constructed in 1969),
Syourenji Dam (1970), Murou Dam (1974),
Nunome Dam (1992), and Hinachi Dam (1999), arelocated in the basin. The peak discharge is causedby seasonal typhoons in summer and autumn. The
largest flood event occurred in 1959 and reachedalmost 6000 ㎥ /s, whereas intensity of peakFig. 1 A map of the Kizu River― 571 ―

discharge decreased by about 3,000㎥/s after dam
construction. The annual mean bed-load transported
to the lower reach was estimated to be about
183,000㎥/y in the 1960’s, but about 23,000㎥/y in
the 2000’s (Ashida et al., 2008). Due to sediment
reduction resulting from sand excavation between
1958 and 1963 and dam construction, riverbed
degradation was accelerated and continued until
now, especially in the lower reach (0 -10 km)(Ashida et al., 2008).
2.2 Abundance of bitterlings and mussels
We used data of abundance of bitterlings andmussels were surveyed by ASIA AIR SURVEY
CO., LTD. Total number of 120 floodplain ponds
was surveyed in 2007, 2009, 2010 and 2011.
Abundance indicated number of individual ofbitterling and mussel, and they divided by surveyed
time and number of attended people for impartial
comparison. In temporal relations between present
species and past habitat conditions, just 27 ponds
having surveyed data of habitat conditions from2007 to 2011 were used. In contemporary relations
between species and habitat conditions in same year,
all 120 ponds were used. After finishing relations
between specie and habitat conditions, suitability
index (SI) of bitterling and mussel was calculated tofind out relation with suitable habitat conditions.
Based on averaged abundance per range of
explanatory values, maximum values weretransformed to 1 and minimum values were to 0.

2.3 Lentic habitat structures
A total of 9 parameters of habitat condition
were selected: area, water depth, mud depth, mean
grain size, DO, chlorophyll, wood coverage (shaded
shoreline ratio by wood), relative height and flood
frequency (Table 4). In the temporal relations,location, age and transparency were added ashabitat conditions. Relative height was calculatedby the lowest height between water level of main
channel and level of 5 m buffer around ponds using
DEM data. Flooding frequency was calculated bysimulation using DEM data and water discharge of
10 years (0: no, 1: 1 time, 2: 8 times, 3: 16 times, 4:
22 times, 5: 45 times, 6: 71 times, 7: 185 times and
8: 365 times flooding per 1 year). Lentic habitat
types were classified into bar head-active pond
(BH-AP), bar head-terrace pond (BH-TP), bar
tail-active pond (BT-AP) and bar tail-terrace pond
(BT-TP) in the just relations between species andhabitat conditions in same year.

Table 1 Historical changes of averaged habitat conditions were surveyed 27 ponds (mean ± standard
error)
Transparency (%)

Mud
depth (m)

Mean
grain
size
(mm)

DO
（mg/l）

chlorophyll (μg/l)Woodcoverage(%)

Relativeheight(m)Floodfrequency2007

36.5±26

6.21±8.5

21.3±169.9±4.0

40.1±11.5

3.1±8.5

1.1±1.2

3.8±2.32009

30.0±165.6±7.022.8±1910.1±5.3

110.0±1185.5±22.3

0.76±0.3

3.4±1.42011

36.2±1712.5±7.4

11.4±8.8

6.8±4.1

41.5±50.1

23.2±30.1

1.3±0.5

2.6±1.42012

27.2±155.9±5.1

12.7±16.
76.5±1.722.6±21.0

30.0±32

1.3±0.5

2.4±1.5― 572 ―

Table 2 Results of generalized linear model tested the relations of abundance of species in 2011 andhabitat conditions in 2007, 2009, 2010 and 2011)
Model

Abundance
Bitterling

Statistic data

Field survey data

Location + age Transparency + mean grain

n

Year

Wald χ²p-value

5

2011

1.81

.177

2010

3.83

.050

2009

1.84

.174

2007

3.15

.076

2011

0.56

.454

2010

1.99

.157

2009

12.18

.000

2007

5.90

.015

size + DO

MusselFlooding

Depth of mud

2

frequency

2.4
Parameterofreach-scalechannelconfiguration (RSCC)
Reach-scale was divided into 2 km units
according to the mean wavelength of meanderingchannels in the Kizu River. Floodplain verticalshape index (FVSI) was used as representative
parameters of RSCC, because changes of FVSI
significantly related with changes of channel
plan-form, e.g. channel width, number of channels,
ratio of vegetation, and of cross-section (Choi et al.,2013). FVSI was calculated by difference ofintegral values of relative elevation of riverbed tonormal water level and those of uniformly
distributed elevation within a 2 km unit based oncross-sectional profiles at intervals of 200 m(Takemon etl al., 2013).
FVSI shows a degree of convex or concave
shape in the altitude distribution of the floodplain.

The positive value is reflected in the convex
vertical shape, and the negative value is reflected in
the concave vertical shape. Values of FSVI were
calculated based on data of 7 years in 1961, 1971,
1979, 1990, 2002, 2006 and 2010. Only results of
two years (2006 and 2010) were connected with
habitat structures, and other yearly data were used
to estimate potential habitat suitability.
2.5 Statistical analysis
To understand relations between species
abundance and the past habitat conditions, we usedgeneralized linear model (GLM) with a Poisson
error assumption and a long link function. The bestmodel was selected based on Akaike’s Information
Criterion (AIC; Akaike, 1974), and Chi-squared (χ²)
was used to compare effect of past and recent
conditions on abundance of bitterling and mussel.

Table 3 Results of correlation analysis tested relations between abundance of species and habitat
conditions were used in model. Relations between bitterling richness in 2011 and habitat conditio ns in2010. Relations between mussel richness in 2011 and habitat conditions in 2009, and relations between
fish richness in 2011 and habitat conditions in 2011 (r values. *** p<0.001, * *p<0.01, * p<0.05)
Low

age

R.H.

locatiFloodingonfrequency

area

Veg.

DO

cove

transpa

Mean

Depth

rency

grain

mud

rage
Abundanc
e ofbitterlings
Abundanc
e ofmussels

.220

.331

size
-.203

-.454***

-.151

-.007

-.524***― 573 ―

ofsignificance for all tests. All analyses wereconducted using SPSS version 19 (SPSS 19.0, SPSSInc).

In relations between species abundance andhabitat conditions in same year, multiple and single
regression analysis were used. The best model was
selected based on Akaike’s Information Criterion.
An α value of 0.05 was used to indicate statistical

Table 4 Averaged habitat conditions across all surveyed 120 ponds and each pond type (mean ± standard
error). n= BH-AP (31), BH-TP (28), BT-AP (21), BT-TP (40)

All
ponds
BH-AP
BH-TP
BT-AP
BT-TP

Area
(m2)

Water
depth (m)

Mud
depth
(m)

Mean
grain
size
(mm)

DO
（mg/l
）

chlorophyl
l (μg/l)Woodcoverage(%)

Relativ
e height(m)Floodfrequency

507±88246.7±23.6

8.1±10.0

3.6±4.8

9.8±4.790.1±145.1

11.1±19.7

1.4±1.2

3.5±2.1

390±61148.7±22.4

5.4±6.5

3.7±4.1

10.2±3.540.6±63.1

4.3±10.9

0.9±0.5

4.5±1.8411±49442.7±25.5

7.9±8.9

4.3±5.5

10.3±4.8

54.4±81.9

10.6±21.4

2.0±1.5

2.7±1.6

678±87951.9±28.8

5.4±8.8

3.4±3.2

9.2±4.928.5±35.8

8.7±14.7

0.7±0.3

5.4±1.9575±121845.2±20.2

11.6±12.5

3.0±5.5

9.6±5.4

185.7±203.918.1±24.2

1.8±1.3

2.2±1.6

Table 5 Abundance of bitterlings and mussels across all 120 ponds and each pond type (mea n ± standard
error). n= BH-AP (31), BH-TP (28), BT-AP (21), BT-TP (40)Abundance of bitterlings

Abundance of mussels

BH-AP

7.0± 20.2
3.1± 6.7

15.7± 43.2
4.2± 17.8

BH-TP

3.6±5.6

27.6± 57.4

BT-AP

2.6± 5.0

4.9± 12.6

BT-TP

14.7±32.9

21.9± 52.6

All ponds

Table 6 Results of multiple regression analysis that examined the best models of habitat conditions forabundance of bitterlings and mussels
Area
(m2)

Water
depth
(m)

Mud
depth
(m)

Mean
grain
size
(mm)

DO
(mg/l
）

chlorophyll(μg/l)

Wood
coverage (%)

Relativ
e height(m)FloodfrequencyAbundance
0.08
-0.6
-7.8
-3.0
of
(0.26)(0.24)(0.26)(0.24)
bitterlings
Abundance
0.01
0.41
-15.8
-8.7
of mussels (0.16)(0.16)(0.18)(0.18)
Habitat parameters were included as independent variables in the best models on the basis of Akaike’s
Information Criterion. (Regression coefficients presented for each best model, parenthesis indicated levelof contribution).

― 574 ―

Fig. 2 Relations of (a) mud depth to abundance of bitterlings and (b) wood coverage to abundance ofmussels

3.

Results

3.1 Relations of abundance of bitterlings andmussels to the past habitat conditions
Table 1 showed the historical changes of habitat
conditions were analyzed of 27 ponds. Table 2
showed results of generalized linear model tested
the relations of species abundance to present andpast habitat conditions of 27 ponds. Bitterlings werebest explained by a model consist of location, age,transparency, mean grain size and DO one year ago(χ² = 3.83, P = 0.05). Mussels were best explainedby a model consist of flooding frequency and depthof mud two years ago (χ² = 12.18, P <0.001).
However, bitterlings had no significant
correlations separately (Table 3). Mussels were
negatively correlated with depth of mud (R = -0.524,
P < 0.05) and flooding frequency (R=-0.454,
p<0.05).

3.2 Relations of bitterlings and mussels tohabitat conditions
Bitterlings were observed at 63 ponds andmussels were observed at 47 ponds among 120
ponds. Values of habitat conditions per pond types
were shown in Table 4 and abundance of bitterlings
and mussels were shown in Table 4. Terrace ponds(BH-TP, BT-TP) had deeper mud depth, morechlorophyll and wood coverage, higher relative
height and lower flood frequency than active ponds(BH-AP, BT-AP). Especially, pond type of BT-TP
had the maximum values in mud depth, chlorophyll
and wood coverage (Table 4). Pond type of BT-TP
had the maximum abundance of bitterlings among
all pond types. Abundance of mussels showed morevalues in terrace ponds (BH-TP and BT-TP) thanactive ponds (BH-AP, BT-TP).
Best model for abundance of bitterlings andmussels were selected based on habitat conditionsof all pond types (Table 5). Mud depth tended tohave negative relations with abundance ofFig. 3 Relations of flood frequency to (a) relative height, (b) mud depth and (c) wood coverage― 575 ―

Fig. 4 Relations of flood frequency to (a) SI of bitterling and (b) SI o f mussel
bitterlings (Table 5, Fig. 2a) and chlorophyll had
positive relations. Habitat size and wood coverage
were positively related to abundance of mussels(Fig. 2b). Relative height and flood frequency were
important variable in explaining abundance ofbitterlings and mussels, because they were selectedin both models. These two parameters had
significant correlations each other (Fig. 3a) and hadcorrelations with abundance of bitterling andmussels. Flood frequency also tended to haverelations with mud depth and wood coverage eventhough they had low coefficients (Fig 3b, 3c).
Although flood frequency did not have relations
with habitat size, we determined flood frequency as
key parameters reflecting habitat conditions forabundance of bitterlings and mussels, because past
flood frequency also had relations with present
abundance of mussels.
Parameter of flood frequency was related withsuitability index (SI) of bitterlings and mussels (Fig4). SI of bitterling tended to have high values
between 8 and 16 days/year of flood frequency (Fig.
4a). Flood frequency between 8 and 22 days/year
had the maximum values of abundance of mussel(Fig. 4b).
3.3 Relations of habitat conditions and types to
RSCC
Floodplain vertical shape index as parameter of
RSCC was categorized into 6 groups (Fig. 5).
Number of ponds having different flood frequency
was counted by categorized values of FVSI (Fig.
5a). All ponds detected on aerial photos (n=386) as
well as surveyed ponds were used in this relation.
Number of ponds having flood frequency between
8-22 days/year showed the maximum values in
FVSI between -0.25 and -0.15, and between -0.15
and -0.05. Reach with FVSI less than -0.35 hadhigh number of ponds with frequent flood such as
45 or 71 days/year. On the other hand, number ofFig. 5 Relations of floodplain vertical shape index (FVSI) to (a) number of ponds with different flood
frequency and (b) number of pond types.

― 576 ―

ponds having 1 times/year of flood frequency
significantly increased in FVSI exceeding 0.05.
Number of pond types was also counted by valuesof FVSI (Fig. 5b). Pond types of BH-TP and
BT-TP increased on reach with FVSI exceeding-0.05 and number of ponds of BT-TP showed the
maximum values in FVSI exceeding 0.05. In
contrast, number of active ponds (BH-AP, BT-AP)
had the maximum values in FVSI less than -0.35.
Pond types tended to change from active ponds toterrace pond with increase of values of FVSI.
Although number of terrace ponds increased in
FVSI exceeding 0.05, they could not say suitable
habitats for bitterlings and mussels, because theseterrace ponds tended to have less flood frequency (0or 1 days/year). Thus, reach having FSVI between-0.25 and -0.15 tended to have a lot number ofponds with suitable flood frequency for bitterlingand mussels.
3.4 Historical changes of FVSI and habitat
suitability of bitterling and mussels
Historical values of FVSI were plotted in Fig. 6.
Mean FVSI significantly increased from -0.44 in
1961 to -0.17 in 2010. Suitable reach having FVSI
between -0.25 and -0.15 tended to have more in
2000s, and reaches with FVSI exceeding 0.05 weredetected only in 2000s. On the other hand, manyreach with FVSI less than -0.35 were seen in before
2000s. Thus, RSCC of the Kizu River before 2000’s
seemed to have higher potential SI of bitterling andmussel.

Fig. 6 Historical changes of FVSI
4.

Discussion
Many previous studies examine relations withmussel or bitterling and various habitat factors suchas current velocity, sediment size, water depth(Johnson and Brown, 2007) or shear stress (Negishi
et al., 2002). However, most of studies focused on
lotic habitats or semi-lentic habitat such as
backwaters. In case of lotic habitats depended onconnectivity with main channels, we should
consider other parameters, and we supposed flood
frequency is one of important attributes in
explaining bitterling and mussel distribution.
Parameters of flood frequency may influence
various environmental factors directly or indirectly.
Ponds having flood frequency between 8 and 16
days/year were suitable habitats for both abundanceof bitterlings and mussels, besides ponds with 22days/year of flood frequency also were suitable for
SI of mussel. Negishi et al. (2002) said flood
frequency was important for mussels, and they
compared with other potentially importantenvironmental variables (ORP, organic matter andchlorophyll) within local scale. They explained low
inundation frequency tended to results in highlevels of chlorophyll. Our results also terrace pond
having low flood frequency tended to have highchlorophyll (Table 4), and it was positively relatedwith abundance of bitterlings (Table 5). Abundance
and SI of bitterling and mussel tended to increase in
more stable ponds than unstable ponds such asactive ponds under conditions with appropriate
flood frequency. Abundance of mussels showed
more values in terrace ponds (BH-TP and BT-TP)
than active ponds (BH-AP, BT-TP), and ponds typeof BT-TP had the maximum abundance among all
pond types. Abundance of bitterling and mussel
seem to be influenced by locations as well as
environmental and geomorphological habitat
conditions. Since outside of bend occurred erosion
with fast flowing water and lots of energy,
especially flooding time, bar head terrace pond isnearly located at outside of bend may be moreunstable than bar tail terrace pond on inside of bend
within meandering channel. Specially, fish such as
bitterling may be highly influenced by flowing thanmussels.
In addition, we should consider not only present
habitat conditions but also the past conditions for
bitterlings and mussels. Our results showed species
richness of mussel was influenced by habitat― 577 ―

conditions 2years ago. It may assume that mussels
were reproduced or flowed from main channel inthe past. Because freshwater mussel was taken
about 5 years from reproduction to adulthood(Mahon and Bogan, 2001), a time lag maybe exist
between current species richness and past habitat
conditions.
Our study indicated the abundance of species or
habitat conditions were influenced by changes ofgeomorphic
channelconfiguration
wascharacterized by FVSI. Reach with concave
floodplain shape tended to flood frequently, andthen, number of ponds having high flood frequency
increased with increment of active ponds. On theother hand, reach with convex floodplain shapetended to be difficult to flood, therefore number ofponds having low flood frequency increased withterrace ponds. Frequently flooded ponds tended toexist on reach with significant concave floodplain
shape, whereas ponds having low flood frequency
tended to exist convex floodplain shape. Choi M. etal.(2013) examined the Kizu River experienced
channel narrowing and decreasing number ofchannels with significant increase in FVSI by
reduction of peak discharge and sediment supply
recent 50 years. According these changes, habitat
diversity sometimes decreased by significant
increase of terrace ponds. Therefore, riverbed
management focused on sediment supply is
proposed to prevent riverbed degradation and to
improve river ecosystems. If many case studies
carry out using multiple scale analysis like thisstudy, we could suppose proper volume of sedimentor discharge according to connection with historicalchanges of reach scale channel configuration.
5.

Conclusion

Multiple spatial and temporal scales should beconsidered in river restoration project because
ecological processes are always laid across thedifferent scales. We suggest method to link between
microhabitat scales and reach scales for abundanceof bitterlings and mussels in the Kizu River. Our
results showed suitable habitat conditions should bemaintained for bitterlings and mussel, because they
had relations with habitat conditions one year ago
or two years ago. As for relations between species

abundance and habitat conditions with structures,
terrace ponds had higher abundance of bitterlings
and mussels than active ponds. In addition, terrace
ponds having flood frequency between 8 and 22days/ year were the most suitable habitats. Numberof the suitable habitats increased on concave
floodplain with FVSI values between -0.25 and-0.05, whereas unsuitable habitats having 1
days/year of flood frequency increased on convex
floodplain with FVSI exceeding 0.05. The Kizu
River in 2000s having high number of suitable
habitats seemed to have higher potential habitat
suitability of bitterling and mussel.
Acknowledgements
This study was conducted in a research project“Development of riverbed management techniques
for river environments” supported by the Japanese
Ministry of Land, infrastructure, Transport andTourism. We would like to the Yodo River Bureau
for providing aerial photo and DEM data
References
Ashida K., Egashira S. and Nakagawa H. (2008):
River Morphodynamics for the 21st Century (inJapanese), Kyoto University Press
Choi M., Takemon Y. and Sumi T. (2013): Roles ofdisturbance in structuring geomorphology forriverine animal communities, 12th International
Symposium on River Sedimentation ISRS 2013,
pp.1701-1706
Frothingham K.M, Rhoads B.L, Herricks E.E(2002): A multiscale conceptual framework for
integrated eco-geomorphological research tosupport stream naturalization in the agricultural
Midwest, Environmental Management, Vol. 29,
pp16-23
Haag W.R. and Warren M.L., Jr. (1998): Role ofecological factors and reproductive strategies instructuring freshwater mussel communities,
Canadian Journal of Fisheries and Aquatic
Sciences, Vol. 55, pp 297-306.
Johnson P.D. and Brown K.M. (2000): The
importance of microhabitat factors and habitat
stability to the threatened Louisiana pearl shell,
Margaritifera hembeli (Conrad), Canadian Journal― 578 ―

of Zoology, Vol. 78, pp 271-277
Kizu River Research Group (2003): Integrated
research of the Kizu River II, 442pp
Negishi J.N., Nagayama S., Kume M., Sagawa. S.,
Kayaba Y. and Yamanaka Y. (2013): Unionoid
mussels as an indicator of fish communities: A
conceptual framework and empirical evidence,
Ecological Indicators, Vol. 24, pp 127-137.
Negishi J.N, Sagawa S., Kayaba Y., Sanada S.,
Kume M. and Miyashita T. (2002): Mussel
responses to flood pulse frequency: the importantof local habitat, Freshwater Biology, Vol.57, No.7,
pp.1500-1511.
MacMahon R.F. and Bogan A.E. (2001): Mollusca:
Bivalvia. pp 331-429 in H. Thorp and A.P. Covich(editors), Ecology and classification of North
American freshwater invertebrates. 2nd edition,
Academic Press, San Diego, California
Poole K.E. and Downing J.A. (2004): Relationshipof declining mussel biodiversity to stream-reachand watershed characteristics in an agriculturallandscape, Journal of the North American
Benthological Society, Vol. 23, No. 1, pp
114-125.

Takemon Y, Kobayashi S., Choi M., Terada M.,
Takebayashi H. and Sumi T. (2013): River habitat
evaluation based on cross-sectional bed profileand frequency distribution of relative elevation (inJapanese), Advances in River Engineering, JSCE
19
Takemon Y. (2010): Habitatology for Linking
Sediment Dynamism and Ecology, International
Symposium on Sediment Disasters and River
Environment in Mountainous Area, pp 25-32.
Tiegs S., Akinwole P. and Gessner M. (2009):
Litter decomposition across multiple spatial scales
in stream networks, Oecologia, Vol. 161, pp
343-351
Williams G.P. and Wolman M.G. (1984):
Downstream effects of dams on alluvial rivers,
Geological Survey Professional Paper, 1286.
Yoshihiro B.A. and Takashi M. (2010): Habitat
Characteristics Influencing Distribution of theFreshwater Mussel Pronodularia japanensis andPotential Impact on the Tokyo Bitterling, Tanakia
tanago, Zoological Science, Vol. 27, pp 912-916.

― 579 ―

(Received June 11, 2014)