THE HISTORICAL CHANGES OF AQUATIC HABITAT STRUCTURE
IN THE KIZU RIVER
Mikyoung Choi1*, Yasuhiro Takemon2 and Tetsuya Sumi 3
1

Ph. D. Student, Water Resources Research Center, Disaster Prevention Research Institute, Kyoto
University, Gokasho, Uji 611-0011, Japan(Tel: +81-774-38-4317, Fax: +81-774-38-4036, e-mail: choi.mk1981@gmail.com)
2
Associate professor, Water Resources Research Center, Disaster Prevention Research Institute, Kyoto
University, Gokasho, Uji 611-0011, Japan(Tel: +81-774-38-4253, Fax: +81-774-38-4036, e-mail: yasuhiro.takemon.5e@ kyoto-u.ac.jp)
3
Professor, Water Resources Research Center, Disaster Prevention Research Institute, Kyoto
University, Gokasho, Uji 611-0011, Japan(Tel: +81-774-38-4307, Fax: +81-774-38-4036, e-mail: sumi.tetsuya.2s@kyoto-u.ac.jp)

Abstract: Hierarchical structure of aquatic habitats in the lower reaches of the Kizu River, a tributary of
the Yodo River, central Japan, was investigated using images of aerial photographs taken in 1948, mid1970s and 2009. The channel landscapes into water surface, island bar and lateral bar as channel scalecharacteristics. Bar scale landscapes into bareland, bushland, woodland and cleared-land for artificial
land use. And then, aquatic habitats were classified into riffle, run and deep slow, active pool, terrace
pool, bar-head backwater and bar-tail backwater. Historical changes in the habitat structure wereanalyzed quantitatively using the DEM data and the aerial photographs. Results of the landscape changes
showed that bar area and shoreline index in the channel scale increased with decreasing water surface,and at the same time, bareland decreased with increasing bushland and woodland. The significant
increase of habitat richness during the period indicated that the increase of vegetation area contributed toraising habitat richness to some extent. Therefore, the stability of flow regimes and reduction in sediment
dynamics fascinated the environmental heterogenety in there 60 years in the Kizu River.
Keywords: Fluvial geomorphology, landscape, habitat richness, sandy bar, historical change, Kizu River.

1. INTRODUCTION
Habitat diversity is closely related to high biodiversity in terms of most stream animals needed a
set of different habitats with stages of their life cycle (Yuma and Hori 1990; Holomuzki and Messier
1993; Takemon 1997). For example, different geomorphic habitat may act as feeding (runs), resting(backwater), and spawning (gravel bars) sites for fish, such that the reach-scale assemblage of
geomorphic units may influence the composition of fish assemblages (Brierley and Fryirs, 2005).
Since geomorphic units constitute relatively distinct habitats for aquatic fauna and flora, they provide
a sound basis with which to link geomorphological structure and ecological habitat (Thomson, 2001).
In general, habitat diversity evaluated spatial patch or mosaic in terms of Landscape ecology(Nathan et al., 2012; Hohensinner et al., 2011). Traditional methods in landscape ecology are based on
the assumption that such patches exhibit high levels of within-patch homogeneity, so that measures
such as patch size, patch density, and the broader spatial arrangement of patches can be used to assessoverall landscape structure and connectivity (Riitters et al.,1995; Gustanfson, 1998).The type number,and connectivity among patch types in these systems is a function of large scale and long-term*

Correspondence: Mikyoung Choi, Water Resources Research Center, Disaster Prevention ResearchInstitute, Kyoto University, Gokasho, Uji 611-0011, Japan E-mail: choi.mk1981@gmail.com

feedbacks among hydrology, geomorphology, ecology, and human land and water use (Ward et al.,1999) and strongly influence biodiversity patterns (Ward et al., 1999; Koel,2004; Thorp et al., 2006).
Several studies have classified the habitats based on geomorphic influence (Brierley and Fryirs, 2005;
Ro Charlton, 2008; Church, 1992; Schumm, 1977), e.g. pools, riffles, cascades, bar, benches, levees,
and cutoff channels, levees, crevasse splays, backswamps, flood channels, floodouts, meander scroll
bars, cut-offs, palaeochannels,; fish community (John and Edwin., 2008), e.g. bars, benches, rifflepool sequences, steps and pools, rapids and cascades, potholes, bedrock bars or matrix type of poolfront, pool-mid, pool-rear, pool-scour, gride, riffle-simple, riffle-complex, submerged point bar,
marginal deadwater ; aquatic area (Wilcox 1993; Nathan, 2012) e.g. main navigation channel, main
channel border, secondary channel, tertiary channel, tributary channel, contiguous floodplain lake,
contiguous floodplain shallow aquatic area, contiguous impounded area, isolated floodplain lake,
isolated floodplain.
Prediction of future changes, and understanding how best to return degraded reaches to a goodcondition will require a functional understanding of how large-scale geomorphic processes operate
under various catchment conditions to shape local habitat (Thomson et al., 2001). Within floodplain
landscapes, habitat patches can be delineated using standard geomorphologic techniques along withaerial photography (Thoms, 2003; Thorp et al., 2006). The present study investigated the long-term
habitat composition and the spatially and temporally varying habitats during a time period by fromwhich generally no detailed data are available.
The intermediate disturbance hypothesis (Connell, 1978) relates biotic community diversity to
disturbance frequency and intensity. This hypothesis suggests that maximum diversity is found atintermediate levels of natural disturbance. At high rates of disturbance, only early successional species,
which are generally good colonizers but poor competitors, are able to survive. In contrast, themaximum species diversity can be also expected when the habitat diversity becomes the maximum
under intermediate disturbance condition (Takemon, 1997). In fact, rivers that migrate across theirfloodplains form complex channel patterns and contain high diversity of habitat riparian and aquatic
habitat types (e.g. Kondolf et al., 2003; Beechie et al., 2006). Thus diversity of aquatic habitat types
will be a good indicator for testing the latter hypothesis. This paper aims at showing the relationshipamong historical changes of landscape characteristic, habitat richness and habitat abundance in the
Kizu River.

2. METHOD
2.1. Study Site
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). Because it is strongly influenced by grantite in upper stream of
Kizu River basin, it had been so called as a typical sand river. A mean of river slope in study area was
1/1180 and mean diameter of bed material was 2 mm ~3 mm.
Channels of the Kizu River had changed dynamically with a huge amount of sediment as a flowfrom tributaries. However, the riverbed has been degraded and the bars have been fixed due to sandexcavation in 1960’s and construction of 5 dams; Takayama Dam (1969), Syourenzi Dam (1970),
Murou Dam (1974), Nunome Dam (1992), Hinachi Dam (1999). The flood exceeding 4000 m3/s indischarge decreased and the mean annual maximum discharge become less frequant from 2500 m3/s
to 1800 m3/s by Takayama Dam (Kizu River research Group, 2009). Although the Kizu River isunder the influence of the excavation and dam construction, the study reaches have various habitat
structures in the channel. After started to shows the alternative bars in 1970’s, riverbed of this section
has been changed from braided to double row bar.

Fig.1. Study area

2.2. Data sources
In other to analysis how to be changed the number or area of aquatic habitat during period, therectified aerial photographs that comprise information on terrain topography, x-y coordinate have beencollected among usable data from the Yodogawa River Bureau. The selected 3 aerial photo of 1948,
1974~1978 (mid70s), 2009 were used for the study.

2.3. Landscape and habitat classification
In order to minimize errors of survey, recent aerial photograph compared with DEM data and themap of plants altitude in 2009 at first. All data overlaid according to coordinate and quantitatively
calculated the number or area of habitats by Acrgis (ESRI). And then, these works were conducted
step by step in recent years order with considering color type of each aerial photo with considering
photo flight season. Within study area (0~26km), Area and number of habitats classified per 1km unit.

2.3.1. Landscape parameter
Landscape parameter classified channel scale characteristics and bar scale characteristics. Channel
scale landscapes were classified into water surface, island bar and lateral bar. The island bar defined as
bar area larger than 200m2. Bar scale landscapes were classified into bareland, bushland, woodland,
cleared-land. Cleared-land defined as farm or empty space by tree cutting (Fig. 2).
Additionally, shoreline index and sinuosity ratio considered as landscape parameter. Shoreline
index have important value in terms of landscape ecology. Water along the shoreline provides shallow,
low velocity habitats (Emily et al., 2011; Bowen et al., 2003) that are used by many riverine species
including softshell turtles (Plummer, 1997; Moll and Moll, 2004), riverine fishes (Scheidegger andBain, 1995; Johnson and Jennings, 1998). Shoreline index is calculated as follows:

Where L is the length of the shore, and A is the surface area.
Sinousity ratio was possible to check a tendency of thalweg or degree of curve in channel.
Sinousity defined as ratio of channel length to valley length (Charlton, 2008). In this study, sinuosity
calculated length of flow channel to straight length per 1km unit.

2.3.2. Aquatic habitat parameter
Habitat parameter classified based on the spatial classification of Habitatology introduced by
Takemon (2007). Habitatology is a specialized field of science for analyzing habitat structure andelucidating mechanism of habitat creation and maintenance. This is classified into lotic and lentic
ecosystem depending on spatial size of animals and their home rages.

Fig. 2 An example of classification of landscape and habitats in reaches at 18km-19km in the
KizuRiver
Table. 1. Definitions of classification of aquatic habitat using aerial photographs in the Kizu River
habitat typedefinition
lotic
area of high current flow with rough water surface rowing locating
rifflepoint of bars
area of slow current flow with smooth water surface locating
lotic
run and deep-slow
between riffles
lenticactive pool

lenticterrace pool

lenticBar-head backwater

lenticBar-tail backwaterside pool in active channel
permanent or temporary standing stagnant water on bare landside pool on terrace at abandoned channel
permanent or temporary standing stagnant water on wood/
grasslandchannel blocked by bare/vegetation deposits with upstream
connection
channel blocked by bare/ vegetation deposits with downstream
connection

As guided by the classification criteria in Table. 1, habitat classified within the study area. Aquatic
habitat composed riffle, active pool, terrace pool, bar-head backwater, bar-tail backwater (Fig. 2).

3. DATA ANALYSIS
3.1. Landscape characteristic
Area of total habitats was summarized in each year. A one-way ANOVA and paired-sample t-test
tested for differences in mean and sum of area, as well as index of shoreline and sinuosity per each year.

3.2. Aquatic habitat characteristic
Total area and number of aquatic habitat was also summarized in each year. Habitat richness
defined as total number of aquatic habitats was classified 5 type; riffle, active pool, terrace pool, barhead backwater, bar-tail backwater. According to definition of habitat richness, it has value fromminimum 0 to maximum 5.
Aquatic habitat also was ascertained by analyzing of a one-way ANOVA and t-test.

3.3. Relations of habitat richness and landscape characteristic
To examine relations of habitat richness to landscape characteristic, regression analysis was used.
Channel ratio and Lateral bar ratio, shoreline index and sinuosity index selected measured variables
among channel scale characteristic and bareland ratio and vegetation-land (bushland + woodland) ratio
selected among bar scale characteristic. Correlation between all measured variables and habitatrichness showed each relation that they have. Graph showed coefficients of regression withprobability line, if they have the relation each other.

4. RESULTS
4.1. Landscape characteristics
4.1.1 channel scale characteristics
The Kizu River landscape scale was comprised of channels and bars of 2types, island bar andlateral bar. The mean area of the lateral bar differed discernibly among the years from 61.3 in S23, to74.8 in mid-70s and 85.3 in 2009 (P<0.00001, one-way ANOVA)(Fig. 3). The area of lateral bar
increased continually during period (P<0.005, t-test). The mean island bar area showed 8.0, 7.5 and2.4 in 1948, mid-70s and 2009, respectively (P=0.024, one-way ANOVA). The island bar area were
not different between 1948 and 1970 (P=0.85, t-test), whereas the value in 2009 was smaller than 1948
and mid-1970s significantly (P<0.05, t-test).
The mean channel area was 30.7, 17.7 and 12.3 in 1948, mid-70s and 2009, respectively(P<0.00001, one-way ANOVA). The channel area decreased continually (p<0.00001, t-test) withincreasing the lateral bar area. Shoreline index was 2.92, 3.55 and 3.77 on average in 1948, mid-70s
and 2009, respectively (P=0.01, one-way ANOVA)(Fig. 4). Value in 1948 was significantly lower
than mid-70s, 2009 (p=0.009, t-test). Sinousity ratio was 1.07, 1.08 and 1.09 on average in 1948, mid70s and 2009, respectively (P=0.5, one-way ANOVA)(Fig. 5). Sinuosity ratio increased slightly(p>0.3, t-test).

4.1.2 Bar scale characteristics
The bars consisted of bareland, bushland, woodland and cleared-land (Fig. 6). Total area of thebareland in bars in 0~26km reaches of the Kizu River was 4.8, 3.8 and 2.3 in 1948, mid-70s,
2009,respectively (P<0.00001, one-way ANOVA). The bareland area showed continuous reduction
significantly (p<0.005, t-test). In contrast to bareland, the area of bushland significantly increased from1948 to 2009 (P<0.0001, t-test). The bushland area was 0.58, 2.38 and 3.96 in 1948, mid-1970s and 2009,
respectively (P<0.00001 one-way ANOVA).The area of woodland was the smallest in 1948(p<0.00001,
t-test). It differed from 0.12 in 1948 to 1.39 in mid-1970s and 1.95 in 2009 (P<0.00001, one-way
ANOVA). The cleared-land was 0.11, 0.09 and 0.087 in 1948, mid-1970s and 2009, respectively(P=0.44, one-way ANOVA). The cleared-land did not differed significantly (p>0.01, t-test).

14.0
12.0
area (km²)

10.0
8.0

Lateral bar

6.0
4.0

Island bar

2.0

water
surface0.0
1948

mid-70s
Year

2009

6

Shoreline index

5

b

b

mid-70s
year

2009

a

4
3
2
1
0

1948

Fig 3. Changes in landscapes if channel scale charateristic

Fig 4. Changes in mean values of the shoreline index.
Error bars indicated ±SD. The maen values with different
symbols differ sigficantlly (P<0.001, t-test)

1.2
bSinousity

1.16

c

a
1.12
1.08
1.04

1
1948

mid-70s
year

2009

12.0

bar area (km²)

10.0Bareland

8.0
Bushland

6.0
4.0

Woodland

2.0
usingland
0.0

1948

mid-70s
Year

2009

Fig 5. Changes in values of the sunousity. Error bars indicated ±SD. The
maen values with different symbols differ sigficantlly (P<0.001, t-test)Fig 6. Changes in landscapes of scale characteristic

4.2. Aquatic habitat characteristics
4.2.1 lotic habitats
The mean of riffle area was the highest in 1948 (p<0.0005, t-test). It decreased continuously from1948 into it’s one-fourth in 2009. However, the number of riffles showed an increase in mid-70s andthen decreased dramatically into a half number in 2009 (Table 2).

4.2.2 lentic habitats
Lentic habitat was comprised of active pool, terrace pool, bar head backwater, bar tail backwater.
(Table 2) The mean of active pool area decreased (P=0.01, t-test) and the number also decreased from1948 to mid-70s significantly. And then, area increased from mid-70s to 2009 (P=0.08, t-test).
The mean of terrace pool area showed a increases from 1948 to 2009 (p=0.03, t-test). The mean of
bar-head backwater area increased (p=0.1, t-test) from 1948 to 2009 gradually. The mean of bar-tailbackwater area also increased (p=0.7, t-test) with similar difference.
Table 2. Historical changes in the mean area of each aquatic habitat
within a unit reach(1 km) in the Kizu River
Lotic

LenticPool

Backwater

RiffleYear

ActiveMean area±SD(m²)nMean area±SD(m²)

TerracenMean area±SD(m²)bar-headn

Mean area±SD(m²)

bar-tail
Mean arean±SD(m²)n

1948

33,209 ± 21,503

105

2,423 ± 3,82272

372 ± 73738

107 ± 3872853 ± 1,611

9

mid-70s

13,992 ± 7,847

124

480 ± 75646

657 ± 124640

301 ± 564

7

1,053 ± 2,508

13

2009

7,691 ± 4,88564

906 ± 1,097

86

1,429 ± 1,964120

482 ± 75717

1,213 ± 1,897

39

SD= standard deviation

Habitat richness was 2.5, 2.7and 3.8 on average in 1948, mid-1970s and 2009, respectively and theone-way ANOVA analysis resulted in significant difference among the years (P<0.0001, one-way

ANOVA)(Fig. 7). Although habitat richness in 2009 was significantly higher than 1948 and mid1970s, those in 1948 and mid-70s were not (ns, t-test).
5bHabitat richness

4

a

a

3
2
1

0
1948

mid-70syear

2009

Fig 7. Historical changes in habitat richness in the Kizu River. Error
bars indicated ±SD.

(a)

(b)
5

5

y = -0.0449x2 + 1.197x - 3.8197
R² = 0.1674 P<0.05

4

Habitat richness

4

3

3

2

2

1

1

0

0
0

20

40

y = -0.0067x2 + 1.0383x - 35.72
R² = 0.1259 P>0.05

060

mid-70s

2009

probability line (2009)

1948

(c)

60

80

100

mid-70s

2009

(d)
5

5

4

4
y = -0.4001x2 + 3.8754x - 4.7645
R² = 0.4563 P<0.01

3

3

2

2

1

1

0

y = 46.544x2 - 107.76x + 65.776
R² = 0.1235 P>0.05

0
0.0

2.0

4.0

6.0

8.0

1.0

1948

mid-70s

2009

1.1

1.2

1.3

Sinousity ratiox

Shoreline index

(e)

40

lateral bar ratio (lateral bar area/ landscape scale area)channel ratio (channel area/ landscape scale area)
1948

20

probability line (2009)

1948

(f)

mid-70s

2009

1.4

5

5

4

4
y = -1.8076x2 - 0.5853x + 3.6287
R² = 0.1664 P<0.05

3

3

2

2

1

1

0

y = -1.0889x2 + 2.7136x + 2.2549
R² = 0.1558 P<0.05

0
0.0

0.2

0.4

0.6

0.8

1.0

1.2

0.0

Bareland ratio (bare B. area/ bar area)
1948

mid-70s

2009

0.2

0.4

0.6

0.8

1.0

Vegetation land ratio (woodland B. + bushland B. area/ bar area)

probability line (total)

1948

mid-70s

2009

probability line

Fig 8. Relations habitat richness to each landscape characteristic. Measured variables: channel scale characteristic (a~d), bar scalecharacteristic (e,f)

4.3. Relations of aquatic habitats to landscape characteristics
4.3.1 Habitat richness & channel scale characteristics
Relationship between habitat richness and channel ratio, lateral bar ratio did not have relation
definitely (Fig. 8a; 8b). However, analysis of habitat richness to channel ratio related in slightly in2009. In 2009, maximum of habitat diversity had from 13 to 14 into channel ratio. Because lateral bar
ratio distributed high value all years, it was difficult to analyze correlation between lateral bar rationand habitat richness.
Regression analysis of habitat richness to shoreline index related significant in 2009 (Fig. 8c). In
2009, Habitat richness shows the maximum value between 4.5 and 5.0 of shoreline index. In contrast
to shoreline index, the habitat richness did not show correlation with sinouisty (Fig. 8d).

4.3.2 Habitat richness & bar scale characteristics
Relationship between habitat richness and bar scale characteristics also did not show relation
significantly (Fig. 8e; 8f). However, habitat richness showed week probability with bareland ratio
negatively, whereas that correlated with vegetation-land bar ratio positively.

5. DISCUSSION
The classification categorizes aquatic habitat structures into detailed types depending on spatial
scale of habitat used by fishes, birds and macro-invertebrates such as aquatic insects and crustaceans.
The classification considers the spatial distribution of riffles, pools, and backwater for a habitat spatial
scale and shoreline for a microhabitat special scale. Although the classification of habitat have toconsider not only landscape characteristics but hydraulic conditions such as water velocity, slope, andsediment size, etc., we intend to make the habitat classification based on only aerial photographs at
first and then interpret the relationship among these factors, because the simple method of the present
study enable habitat assessment for past years in terms of Landscape ecology.
The dam construction has great impacts on landscape and hydrology, so it is of scientificimportance to investigate and evaluate the landscape changes induced by dam construction. (Qinghe,

2011). Because discharge and sediment was controlled due to artificial impact such as construction of
dam and levee, excavation, area of lateral bar and vegetation land ratio increased by small frequency
of disturbance. In this perspective, according to decreasing the area of water surface and increasing thearea of lateral bar, it was natural result that area of riffle decreased. It was necessary to examine
relation between changes of landscape and habitat diversity constantly for improvement of
biodiversity and restoration of endemic species. Habitat richness in The Kizu River increased
significantly (Fig. 7) with increasing the area and number of terrace pool, backwater from 1948 to2009. Number and area of active pool decreased from 1948 to mid-70s and then increased frommid70s to 2009. In contrast, area of riffle decreased and number of riffle increased from 1948 to mid70s. We suggest correlation between active pool and riffle with inverse proportion slightly (Fig. 9). Tochange between water surface and bareland occurred continuous due to changing of flow and sedimenttransport. In many cases, active pool increased with sediment deposits instead of water surface andriffle increased with division of lateral bar.
Most studies emphasise the scale-depedant nature (spatially and temporally) of equilibrium
concepts (DeAngelis and Waterhouse, 1987; Wiens, 1989; Turner et al., 1993). Wien(1984) argues
that an equilibrium state generally cannot be reached due to the high frequency of natural disturbances(Hohensinner et al., 2011). This study considered the relations of habitat richness to landscape scalecharacteristics. Among various variable, channel ratio and shoreline index, bareland ratio andvegetation land ratio were related to habitat richness. The result proved hypothesis reviewed slightly.
In case of channel ratio and shoreline index, had maximum value for the highest habitat richness. In
the Kizu River, as increasing the vegetation ratio, habitat diversity increased compare with period wascomprised most of bareland and water surface. In the reason, we suggest that habitat diversity will
decrease in the case that bareland ratio reaches to 0 or vegetation ratio reaches to 1.

Active pool abundance

According recent report of Kizu River (Kizu River research Group, 2009), biodiversity increased
gradually, whereas endemic species have disappeared and exotic species have increased in Kizu River.
Because biodiversity was influenced not only habitat characteristics but environmental factor andhydraulic conditions such as water temperature, water quality, sediment size, etc., biodiversity should
consider habitat diversity and each hydrogeomorphic habitat characteristics.
16
14
12
10
8
6
4
2
0

0

5

10

15

Riffle abundance1948

mid-70s20

2009

Fig 9. Relations between active pool abundance and riffle abundance in the Kizu River.

6. CONCLUSION
The Kizu River had increased habitat richness with increasing area of vegetation-land (Fig. 8f).
Results of the landscape changes showed that bar area and shoreline index in the channel scale
increased with decreasing water surface, and at the same time, bareland decreased with increasing
bushland and woodland. The significant increase of habitat richness during the period indicated thatthe increase of vegetation area contributed to raising habitat richness to some extent. Therefore, thestability of flow regimes and reduction in sediment dynamics fascinated the environmental
heterogenety in there 60 years in the Kizu River.
To examine a hypothesis of the optimal landscape characteristics to maximize habitat richness, it isrequired to increase data plots.
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