Influence of prey variables, food supply, and river restoration on the foraging activity of Daubenton’s bat (Myotis daubentonii) in the Shibetsu River, a large lowland river in Japan

Biological Conservation 142 (2009) 1302–1310

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Influence of prey variables, food supply, and river restoration on the foraging activity of Daubenton’s bat (Myotis daubentonii) in the Shibetsu River, a large lowland river in Japan Takumi Akasaka *, Daisuke Nakano 1, Futoshi Nakamura Department of Forest Science, Graduate School of Agriculture, Hokkaido University, Kita 9 Nishi 9 Kitaku, Sapporo 060-8589, Japan

a r t i c l e

i n f o

Article history: Received 14 April 2008 Received in revised form 29 December 2008 Accepted 9 January 2009 Available online 12 March 2009 Keywords: Microchiroptera Channel morphology Riparian habitat Ecosystem management Prey selection Anthropogenic disturbance

a b s t r a c t To conserve the foraging habitat of Daubenton’s bat (Myotis daubentonii) in a large lowland river, we investigated the influence on this bat of prey variables (number or biomass) and insect origin (aquatic or terrestrial). We tested the hypothesis that river restoration (re-meandering) conducted in the Shibetsu River, northern Japan, enhances foraging habitat quality by increasing the abundance of aquatic insects. From June to September 2004, flying insects were collected using Malaise traps in restored and channelised reaches in the Shibetsu River. Bat activity was recorded by bat detectors placed near the Malaise traps in each of the two reaches. Foraging activity of Daubenton’s bat was more strongly related to the number of insects than to biomass, and to adult aquatic insects than to terrestrial insects. The high dependence of Daubenton’s bat on aquatic prey was attributed to the fact that aquatic insect numbers were always higher than those of terrestrial insects. Contrary to the hypothesis, Daubenton’s bat was more active in the channelised reach than the restored reach in all months except June, and it synchronized its foraging activity with the seasonal distribution of adult aquatic insects. However, the study was undertaken just two years after restoration and the riparian vegetation had not yet established itself. Our results demonstrate the importance of aquatic insect abundance for Daubenton’s bat throughout the seasons in large lowland rivers. A further decrease in aquatic insects, associated with progressive anthropogenic alteration of river environments, undoubtedly exerts a harmful influence on the conservation of this species. Ó 2009 Elsevier Ltd. All rights reserved.

1. Introduction Human activities can result in habitat modification and loss of the habitats of various animals worldwide (Fukami and Wardle, 2005; Bulling et al., 2006; Ives and Carpenter, 2007; Maron and Fitzsimons, 2007; Young et al., 2007). These anthropogenic disturbances reduce bat populations by altering or destroying not only roosting habitats but also foraging habitats. Thus, conserving these habitats is critical to prevent further declines in bat populations (Racey and Entwistle, 2003). The habitat use of foraging bats has been studied recently on a landscape level and has focused on the influence of habitat fragmentation and land cover variation on bat species diversity (Gorresen and Willig, 2004; Lumsden and Bennett, 2005; Kusch and Schotte, 2007). However, in order to use this knowledge for local conservation plans, detailed information is also required on a smaller scale (Hobbs, 2003). Numerous

* Corresponding author. Tel.: +81 11 706 3842; fax: +81 11 706 3842. E-mail addresses: [email protected] (T. Akasaka), [email protected] (D. Nakano), [email protected] (F. Nakamura). 1 Present address: Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry, Abiko 270-1194, Japan. 0006-3207/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2009.01.028

foraging habitat selection studies have been conducted on a small scale with respect to spatial heterogeneity of land cover (Brooks and Ford, 2005), prey distribution (Rydell, 1992; Wickramasinghe et al., 2004), edge effects (Delaval and Charles-Dominique, 2006), and water quality (Kalcounis-Rueppell et al., 2007). However, the habitat requirements of foraging bats in different land covers have not been thoroughly examined. Rivers and riparian zones are important foraging habitats for a broad range of bat species throughout the world (Racey et al., 1998; Holloway and Barclay, 2000; Warren et al., 2000; Ciechanowski, 2002; Whitaker, 2004; Lloyd et al., 2006); therefore, protection of these aquatic ecosystems is a high priority for bat management and conservation (Fukui et al., 2006). Around the world, recent intensive alteration of rivers associated with land use development has resulted in deteriorated lotic environments, homogenised heterogeneous structures of instream habitats (Brookes, 1994; Rosenberg et al., 2000), and the reduction, or even destruction, of riparian habitats (Fennessy and Cronk, 1997; Grossinger et al., 2007). River channelisation is one of the most serious anthropogenic disturbances. This process directly alters the physical structure of rivers and riparian habitats and results in species loss and the decline of populations for long periods of time

T. Akasaka et al. / Biological Conservation 142 (2009) 1302–1310

(Brookes, 1988). These perturbations greatly influence aquatic biota such as macroinvertebrates, fish (Moyle, 1976; Brookes, 1988), and other terrestrial animals such as bats that feed on insects (Holloway and Barclay, 2000; Warren et al., 2000; Iwata et al., 2003; Bank et al., 2006; Kalcounis-Rueppell et al., 2007). The conservation of instream and riparian habitats is of critical importance for foraging bats in large lowland rivers because these rivers are severely impacted by channelisation (Malmqvist and Rundle, 2002; Tockner and Stanford, 2002; Anderson et al., 2006). Bat foraging activity should vary with biomass and the number of insects (Kusch et al., 2004). Moreover, the importance of different prey variables may vary with species because there is a wide variation in the prey preferences and foraging strategies of different bat species (Fenton, 1990). Nevertheless, either the biomass or the number of insects have been used as metrics to estimate prey abundance in previous studies of bat foraging habitat selection (e.g., Warren et al., 2000; Wickramasinghe et al., 2004; Fukui et al., 2006). In order to provide effective conservation plans, it is necessary to examine which prey variable best explains the foraging activity of bats. Furthermore, both adult aquatic insects and terrestrial insects fly over rivers and riparian zones (Nakano and Murakami, 2001), and the abundance ratio of the two origins (aquatic and terrestrial) of insects in these habitats varies among seasons (Nakano and Murakami, 2001). However, with the exception of Fukui et al. (2006), no studies have examined the relative importance of terrestrial versus aquatic insects on the foraging activity of bats. Numerous rivers have been channelised since the 1960s in Hokkaido, northern Japan, in association with the extensive development of crop and pasture fields over the floodplains (Nakamura and Yamada, 2005). In March 2002, an experiment to re-meander the straightened channel in a lowland reach of the Shibetsu River, eastern Hokkaido, was conducted as a pilot restoration project in order to promote the recovery of biological communities in the river and floodplains. The results of this experiment indicated that the formation of shallow marginal habitats created by the meandering channel increased the density and taxon richness of aquatic larvae (Nakano and Nakamura, 2006). Thus, an increase of aquatic insects due to channel re-meandering may greatly improve the quality of foraging habitat for bats in the short term and it may also contribute to the conservation of entire bat communities in the long term. Daubenton’s bat (Myotis daubentonii) is widely distributed throughout Europe and Asia (Bogdanowicz, 1994). According to previous studies conducted in various regions, this species feeds on a variety of insects such as Diptera, Trichoptera, Hemiptera, Lepidoptera, and Coleoptera (Vaughan, 1997; Boonman et al., 1998; Flavin et al., 2001). Although the diet of Daubenton’s bat differed among sites, Diptera, especially adults and larvae of Chironomidae, was a common and critical component of their diet across all sites. Given that the foraging habits of this species depend on aquatic habitats because of its special foraging technique known as trawling (gaffing prey from the water surface; Ciechanowski, 2002), Daubenton’s bat may be sensitive to river alterations. Daubenton’s bat populations are greatly increasing with the eutrophication of rivers and lakes throughout mainland Europe (Racey et al., 1998). Contrastingly, Daubenton’s bats are on the verge of extinction in Japan and still need to be protected with suitable conservation and management plans (Environment Agency of Japan, 2002). In order to restore the foraging habitat of Daubenton’s bat in a large lowland river, we examined which prey variable, biomass or number of insects, is more strongly related to the foraging activity of Daubenton’s bat; clarified the relative importance of aquatic and terrestrial insects in determining foraging activity; and tested the hypothesis that re-meandering of the Shibetsu River enhances the quality of foraging habitat by increasing the abundance of aquatic insects.

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2. Materials and methods 2.1. Study site The study site was situated in the lower segment of the Shibetsu River in eastern Hokkaido. The mean temperature was 6.8 °C (maximum and minimum temperatures were 33.5 °C and – 19.6 °C, respectively), and the total precipitation was 1,410 mm in 2004. During the research period, the mean daily temperature was 15.0 °C (maximum and minimum temperatures were 33.5 °C and –1.1 °C, respectively). In the 1940s, the Shibetsu River showed its original meandering pattern, and wetland floodplains consisting of alluvial soil and low moor peat extended over more than 3,000 ha in the lower segment of this river. Since the 1950s, the lower segment of the Shibetsu River has been straightened and channelised for flood control and farmland reclamation, and the meandering channel was completely channelised by the 1970s. The re-meandering experiment was conducted 8.5 km upstream from the river mouth. The oxbow lake, once isolated by channelisation, was reconnected to the main channel, which restored the historic meander (Fig. 1). In order to connect the oxbow lake with the channelised reach, approximately 250 m of the river was excavated using heavy machinery and was left with disturbed banks lacking original vegetation cover (Nagayama et al., 2008). The length of the restored reach was 470 m. Consequently, heterogeneous microhabitats were created, including point bars with shallow marginal habitats, and fish and macroinvertebrate populations increased in the re-meandered reach (Kawaguchi et al., 2005; Nakano and Nakamura, 2006; Nakano et al., 2008). However, the banks in the excavated portion of the re-meandered reach, which lacked its original vegetation cover, have been scoured repeatedly by floods (Watanabe et al., 2005), and seedlings and saplings on the point bars have been washed away frequently by floods (original observation data). Thus, the channel morphology and riverline vegetation in the re-meandered reach have not reached a stable phase and are still adjusting to the restored flow and sediment regime. The whole of the restored reach was designated as the restoration treatment in our study, and a 200 m long channelised reach, upstream of the restored reach, was designated as a control. The mean low-flow widths of the channelised and restored channels are 32 m and 28 m, respectively, and the riverbed gradients are 1/458 and 1/578, respectively. The young overhanging riparian forests (approximately 15 m high) are dominated by Salix spp. and are distributed along the edges of the channelised reach, while the seedling and sapling willow trees are colonised on sand bars and are occasionally scoured by the floods in the restored reach. The original riparian vegetation is distributed sporadically at distances greater than 10 m from the channel course of the restored reach. There are almost no aquatic plants in either of the studied reaches. We identified almost all water surfaces in the study area as ‘smooth’ with few ‘rapid’ currents (sensu Warren et al., 2000). Therefore, Daubenton’s bat could use nearly the entire length of the water way in our study area. 2.2. Methods We collected flying insects using Malaise traps (100 cm high, 190 cm long, and 190 cm wide, made of 1.0 mm mesh with a 500 ml jar on top with 70% ethanol for sample preservation) to estimate the abundance of adult aquatic and flying terrestrial insects near the water surface. Because Daubenton’s bat forages near the water surface (usually within 30 cm), we placed these traps 15 cm above the water surface on the river banks, facing vertically towards the direction of flow. These traps can catch insects flying between 15 cm to 75 cm above the water surface. Four traps were

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Fig. 1. Map of Japan and schematic diagram of the study site.

placed in each of the channelised and restored (re-meandering) reaches. We collected flying insects from June to September 2004, for one week per month. All traps were installed simultaneously with more than 50 m between them. Samples collected by Malaise trap were preserved in 70% ethanol until they were sorted and identified. We identified flying insect samples to their respective orders using a binocular microscope and sorted them into aquatic and terrestrial insects. All collected orders were either aquatic or terrestrial in origin, except the Diptera, which were further sorted into aquatic and terrestrial taxa. We counted the number of individuals in each insect group and recorded the wet mass to the nearest 0.01 mg. The weights were transformed to dry mass using orderspecific conversion formulae (Kawaguchi, 2000). We investigated foraging activity of bats using bat detectors (Mini-3, Ultrasound Advice, London, UK) from June to September 2004, for three days per month during the insect survey periods. Four bat detectors were placed near each Malaise trap in both of the two reaches. Bat detectors were placed at least 50 m apart. Although this distance may not ensure complete independence of each bat detector, it was the longest distance that allowed for enough replications within the limited re-meandered length. Thus, we conducted a Moran’s test to check correlations of bat foraging activities among the sites. The results showed no significant correlations among sites throughout the study period (p < 0.01); thus, we may assume that the bat detectors were independently distributed in the study site. We put the bat detectors into shelters and placed them level with the river banks, with Mini-Disk recorders (MZ-N920, Sony Corporation, Tokyo, Japan) aimed in the direction of river flow. We placed all bat detectors 30 cm above the water

surface, where Daubenton’s bat usually forages. We set the detectors to monitor at a frequency of 50 kHz, the normal call frequency of Daubenton’s bat (Parsons and Jones, 2000). It is difficult to identify bat species by this sampling method. However, from a fauna survey using mist nets at the study site, only Daubenton’s bat was captured above the river surface. Furthermore, although Ikonnikov’s whiskered bat (Myotis ikonnikovi) and the long-eared bat (Plecotus auritus) were captured near the river, their numbers were very small. Daubenton’s bat made up more than 85% of the total catch, while Ikonnikov’s whiskered bat accounted for only 5%. Thus, we assumed that bats detected at 50 kHz above the river were Daubenton’s bats. We recorded echolocation calls of bats for 4 hours after sunset because random sampling throughout the night showed that Daubenton’s bat forages very actively at this time. All bat detectors were installed simultaneously to investigate foraging activities, except on rainy nights. We counted the number of search phase sequences and feeding buzz sequences (classified according to Griffin, 2002) by listening to the sounds recorded by each MiniDisk. A sequence was defined as the interval from the beginning to the end of sequential pulses, followed by a silent interval. Buzz sequences were defined as those that ended with a burst of pulses of short duration with short interpulse intervals (Griffin, 2002). 2.3. Statistical analysis Monthly variations in the abundance of adult aquatic and flying terrestrial insects were analysed using generalised linear mixed models (GLMM; Crawley, 2002) in which the detector site was incorporated as a random effect. The explanatory variables were

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month, insect origin (aquatic or terrestrial), and the interaction between the two. The response variables were the number or biomass of total flying insects in each month. When the number of insects was used as a response variable, a Poisson error structure and a log link function were used, and when biomass was used as a response variable, a Gaussian error structure and an identity link function were used. Model selection was performed using the Akaike’s Information Criterion (AIC) and a best-subset selection procedure (Burnham and Anderson, 1998). The effect of insect origin on the foraging activity of Daubenton’s bat was examined using a GLMM with a Poisson error structure and log link function, in which study site was incorporated as a random effect. Two models were built based on different hypotheses. One hypothesis was that the foraging activity of Daubenton’s bat can be explained by a combination of both adult aquatic insects and flying terrestrial insects, and the other was that activity can be explained by the two types of insects independently. Thus, the explanatory variables were either adult aquatic insects and flying terrestrial insects, or total flying insects. The best combination of the selected variables was determined by AIC in all cases of model selection (Burnham and Anderson, 1998). Two indicators of insect abundance, the number and biomass in each month, were used to establish which insect variable was suitable to assess the foraging activity of Daubenton’s bat. The effects of each insect group on the foraging activity of Daubenton’s bat were examined in each month using generalised linear models (Crawley, 2002) with a Poisson error structure and a log link function. The explanatory variable of each model was composed of one insect group (e.g., foraging activity = aquatic Diptera). The best model was determined by AIC in all cases of model selection. Monthly variation in the abundance of adult aquatic and flying terrestrial insects between the restored and channelised reaches was analysed using a GLMM, in which study site was incorporated as a random effect. The explanatory variables were month, reach, and the interaction between the two. The more effective variable of prey abundance, either number or biomass, for foraging bats from the previous analyses was used as a response variable. When the number of insects was selected as a response variable, a Poisson error structure and a log link function were used, and when biomass was selected, a Gaussian error structure and an identity link function were used. Model selection was performed using the AIC in a best-subset selection procedure. To assess the effect of foraging activity of Daubenton’s bat between the two reaches, a GLMM with a Poisson error structure and log link function, in

which study site was incorporated as a random effect, was used. The explanatory variables were month, reach, and the interaction between the two. Model selection was performed using the AIC in a best-subset selection procedure. Month was used as a categorical variable in all models throughout this study. We also used the percentage of deviance explained [100  (null deviance – residual deviance) / null deviance] for all best models as an index of goodness of fit. All statistical analyses were conducted using the statistical program R (R Foundation for Statistical Computing, Vienna, Austria).

3. Results The flying insects sampled consisted of various insect orders, mainly Diptera, Trichoptera, Ephemeroptera, Hymenoptera, and Lepidoptera (Table 1). Aquatic Diptera were dominated by Chironomidae, whereas terrestrial Diptera consisted mainly of Dolichopodidae and Cecidomyiidae. Parameter selection using AIC in the GLMM revealed that the origin of insects (aquatic or terrestrial insects), month, and interaction of the two were the best predictors explaining the number of flying insects (deviance explained = 56.6%, Table 2). The number of adult aquatic and flying terrestrial insects varied among the four months (Fig. 2a). Despite a decrease in June and August, the number of adult aquatic insects was higher than that of terrestrial insects. Adult aquatic insects dominated the number of total flying insects caught, contributing to more than 70% of the catch. Among the aquatic insects, aquatic Diptera contributed to more than 90% of insects caught throughout the months (Table 1). In contrast to number of insects, the biomass of flying insects could be best predicted by month and insect origin (deviance explained = 13.6%, Table 2). The biomass of both adult aquatic and flying terrestrial insects showed similar variations among the four months, and flying terrestrial insects dominated (55 - 66%) in all months (Fig. 2b). In total, we recorded 6,039 echolocation calls of bats. The best model to predict the foraging activity of Daubenton’s bat was built using the numbers of adult aquatic and flying terrestrial insects separately, rather than combination of the two (deviance explained = 58.6%, Table 2). Of the two origins of insects, however, the number of adult aquatic insects was a better predictor of foraging activity than the number of flying terrestrial insects Fig. 3a, Table 2. Furthermore, the number of insects was a better predictor of foraging activity than biomass in all models (Fig. 3a, b, Table 2).

Table 1 Seasonal compositions of each insect group (%) and DAIC of each fitting model. Poisson regression model is ‘‘Foraging frequency of M. daubentonii = each insect group”. The difference between the AIC values for the minimum AIC model and each of the other models in the set is termed DAIC. Order

Percentage (%) June

Adult aquatic insects Aquatic Diptera Ephemeroptera Trichoptera Plecoptera Other adult aquatic insects Flying terrestrial insects Terrestrial Diptera Hemiptera Hymenoptera Lepidoptera Coleoptera Other flying terrestrial insects Null

DAIC July

August

September

June

July

Num.

Mass

Num.

Mass

Num.

Mass

Num.

Mass

Num.

Mass

Num.

72.5 0.5 1.9 1.7 0.0

20.9 0.2 16.1 1.9 0.2

77.4 5.4 1.7 0.9 0.0

10.1 13.8 10.1 2.1 0.0

57.7 0.9 10.7 0.3 0.0

5.8 0.6 26.3 0.2 0.9

88.1 0.4 5.8 0.3 0.0

3.9 1.4 38.9 0.6 0.3

0.0 210.4 60.4 134.8 147.1

44.3 181.2 54.1 130.8 147.1

0.0 565.9 219.6 502.2 930.9

20.7 0.6 1.3 0.5 0.2 0.0

44.8 0.2 4.9 8.9 1.7 0.0

11.4 1.4 1.0 0.6 0.2 0.0

39.7 4.7 4.1 11.7 3.8 0.0

23.0 2.2 2.7 2.1 0.3 0.0

29.1 7.3 4.5 23.1 2.2 0.0

4.2 0.5 0.4 0.3 0.0 0.0

21.2 3.8 5.7 22.5 1.9 0.0

71.0 129.2 209.8 199.9 167.2 183.2 209.0

52.6 148.0 194.5 168.0 139.0 163.5

840.9 391.0 794.9 523.4 120.7 1142.9 1142.9

August Mass

September

Num.

Mass

Num.

Mass

101.4 558.9 781.9 482.5 930.9

0.0 710.1 676.1 684.1 682.1

651.1 667.1 608.1 681.1 682.1

0.0 67.8 511.2 184.7 678.2

312.7 159.4 462.2 249.7 678.2

1132.9 712.9 933.9 456.7 713.9 1142.9

703.1 701.1 673.1 661.1 585.1 289.1 712.1

197.3 472.9 629.1 703.1 494.9 382.8

682.2 599.2 388.2 188.8 14.2 680.2 680.2

361.2 440.2 681.2 257.3 579.2 680.2

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Table 2 Selected results of GLMM in all model selections. The difference between the AIC values for the minimum AIC model and each of the other models in the set is termed DAIC. Models

DAIC

Abundance of adult aquatic and flying terrestrial insects Number of insects All flying insects = insect origin + month + insect origin: month All flying insects = insect origin + month All flying insects = insect origin All flying insects = month All flying insects = Null

0.0 2400.0 29130.0 96730.0 123530.0

Biomass of insects All flying insects = insect origin + month + insect origin: month All flying insects = insect origin + month All flying insects = insect origin All flying insects = month All flying insects = null

5.0 0.0 2.7 2.4 4.1

Influence of flying insects abundance on M. daubentonii Foraging frequency = number of total flying insects Foraging frequency = number of adult aquatic insects + number of flying terrestrial insects Foraging frequency = number of adult aquatic insects Foraging frequency = number of adult aquatic insects + number of flying terrestrial insects Foraging frequency = biomass of all flying insects Foraging frequency = biomass of adult aquatic insects + biomass of flying terrestrial insects Foraging frequency = biomass of adult aquatic insects Foraging frequency = biomass of adult aquatic insects + biomass of flying terrestrial insects Foraging frequency = Null

2.0 0.0 12.0 1356.0 883.0 806.0 874.0 1074.0 1720.0

Distribution of number of adult aquatic insects in channelised and restored reaches Adult aquatic insects = reach + month + reach: month Adult aquatic insects = reach + month Adult aquatic insects = reach Adult aquatic insects = month Adult aquatic insects = null

0.0 7470.0 95170.0 7470.0 95170.0

Distribution of number of flying terrestrial insects in channelised and restored reaches Flying terrestrial insects = reach + month + reach: month Flying terrestrial insects = reach + month Flying terrestrial insects = reach Flying terrestrial insects = month Flying terrestrial insects = null

0.0 2977.0 10931.0 2977.0 10881.0

Distribution of foraging M. daubentonii in channelised and restored reaches Foraging frequency = reach + month + reach: month Foraging frequency = reach + month Foraging frequency = reach Foraging frequency = month Foraging frequency = null

Aquatic Diptera comprised a greater proportion of the total number of insects caught than any other insect group for all four months (deviances explained for each month > 50%, Table 1). Although the insect group with the most influence on foraging activity in terms of biomass varied among the months, these groups showed a higher AIC (weak prediction) than the number of aquatic Diptera overall (Table 1). The number of adult aquatic and flying terrestrial insects in the restored and channelised reaches varied with month, reach, and the interaction of the two (deviances explained: adult aquatic insects, 89.6%; flying terrestrial insects, 78.3%; Table 2). The number of adult aquatic insects in the channelised reach was greater than in the restored reach in all of the months except June (Fig. 4a), whereas the number of flying terrestrial insects in the channelised reach was greater than that in the restored reach in July and September (Fig. 4b). The Poisson GLMM indicated that the foraging activity of Daubenton’s bat was influenced by month, reach, and the interaction of the two (deviance explained = 83.5%, Table 2). In all months but June, Daubenton’s bat foraged more actively in the channelised reach than in the restored reach, and the foraging frequency was several times greater in the channelised reach throughout the months (Fig. 5).

0.0 870.9 2444.9 876.9 2440.9

4. Discussion The foraging activity of Daubenton’s bat had a stronger relationship with the number of insects than with biomass in this study. In contrast, Houston and Jonea (2003) demonstrated in their laboratory and field experiments that Daubenton’s bat chooses large prey over small. However, as they suggested, their experimental design, which provided the same number of large and small prey at fixed locations, differed greatly from natural conditions. In the natural environment, prey of variable size and shape are clumped or sparsely distributed in space and time, and each bat species uses their individual echolocation calls to capture them (Barclay, 1985; Jones, 1990; Agosta et al., 2003). Average detection and reaction distances of Daubenton’s bat are only 128 cm and 112 cm, respectively (Kalko and Schnitzler, 1989). Additionally, Daubenton’s bat requires at least 500 insects per hour during foraging times, which means that one insect is caught every seven seconds on average, in order to maintain their energy balance (Kalko and Braun, 1991). Although large insects are highly valuable, the chance of capturing these insects is low because of their low densities. These may suggest that the density of individual insects is an important factor to evaluate when studying the foraging habitats of Daubenton’s bat under natural conditions.

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a Foraging frequency (time hour -1)

1500

1000

500

0

Biomass of insects (mg trap -1 day -1)

b

July

August

September

b Foraging frequency (time hour -1)

June

250

200

150

100

50 40 30 20 10 0

0

500

June

July

August

September

Fig. 2. (a) Number and (b) biomass of adult aquatic and flying terrestrial insects (mean ± SE) in each month. Open circles denote adult aquatic insects and filled circles denote flying terrestrial insects.

Although the foraging activity of Daubenton’s bat was influenced by the number of both adult aquatic and flying terrestrial insects, the number of adult aquatic insects was more influential. The high dependence of Daubenton’s bat on aquatic prey can be attributed to the greater number of aquatic insects than terrestrial insects during the study period as a whole (Fig. 2). Moreover, the number of aquatic Diptera had the highest influence of all aquatic insects caught throughout the research period. Our results are in agreement with previous studies on the diet of Daubenton’s bat conducted by faecal analyses across various field sites (Vaughan, 1997; Boonman et al., 1998; Flavin et al., 2001) and also emphasise the role of aquatic Diptera in a large lowland river throughout the seasons. However, in our study, the most important insect groups in terms of biomass were different from these previous studies, and we underestimated the importance of aquatic Diptera throughout the season, except in June and July. In particular, we found that the Ephemeroptera group was the strongest group in term of biomass in September, but this group accounted for only a few percent of their diet in previous studies. This finding suggests that both prey variables should be examined simultaneously to evaluate foraging habitats for bats to avoid a misunderstanding of the factors contributing to their foraging habitats.

2500

200 300 400 500 Biomass of insects (day -1)

600

40 30 20 10 0

0

0

1000 1500 2000 Number of insects (day -1)

50

100

50

Fig. 3. Differences in relationship between foraging activity of M. daubentonii and two prey variables [(a) number of prey and (b) biomass of prey]. Crossbars denote total flying insects, open circles denote adult aquatic insects, and filled circles denote flying terrestrial insects.

-1 -1 Number of flying insects (trap day )

Number of insects (trap -1 day -1)

a

2000

1500

1000

500

0 June

July

August

September

Fig. 4. Abundance (mean ± SE) of number of adult aquatic insects and flying terrestrial insects in the restored (adult aquatic insects: filled squares, flying terrestrial insects: filled triangles) and channelised (adult aquatic insects: open squares, flying terrestrial insects: open triangles) reaches in each month.

Many aquatic insects (most aquatic Diptera, Torichoptera, Ephemeroptera, and Plecoptera) drift on the water surface in both the aquatic and emerged phases (Todd and Waters, 2007). In addition, aquatic Diptera, Torichoptera, and Ephemeroptera swarm above the water surface after they emerge (e.g., Ogawa, 1992;

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Foraging frequency (time hour -1)

50 40 30 20 10 0 June

July

August

September

Fig. 5. Foraging activity of M. daubentonii (mean ± SE) in the restored (filled squares) and channelised (open squares) reaches in each month.

Gullefors and Petersson, 1993; Wishart and Hughes, 2001; Kriska et al., 2007) and are easier to capture than terrestrial insects because of their reduced flying ability (Fukui et al., 2006). In this study, the abundance of aquatic insects was the strongest predictor of the foraging activities of Daubenton’s bat throughout the study season in the Shibetsu River. This result differs from the foraging pattern of bats, including the trawling species, observed in a spring-fed, forested small stream (Fukui et al., 2006). In the forested small stream, the ratio of adult aquatic and flying terrestrial insect abundance varied with season because of changes in foliage and insolation (Nakano and Murakami, 2001). Emergence of aquatic insects peaks in the spring when trees are leafless and when periphyton becomes abundant because of higher insolation, whereas terrestrial insects increase in the summer when leaves are present and the productivity of terrestrial plants rises (Nakano and Murakami, 2001). Therefore, aquatic insects dominate in spring, while terrestrial insects dominate in summer months (Nakano and Murakami, 2001). Bats change their diet between seasons in response to the change in the abundance of insects from the two origins (Fukui et al., 2006). Conversely, in large lowland rivers, the proportion of canopy cover of riparian forests above the water surface is very limited, and a large proportion of the river remains open, resulting in significant periphyton production with ample sunlight reaching the riverbed bottom throughout the seasons (Allan, 1995). The constant production of periphyton supports a high abundance of aquatic insects in all seasons. In addition, the availability of terrestrial insects above the river is very low in large lowland rivers because the abundance of terrestrial insects is greater in forests than in open spaces (Peng et al., 1993; Hradetzky and Kromp, 1997; Grubler et al., 2008). In this study, the number of adult aquatic insects was greater than that of flying terrestrial insects throughout all months examined. Although the biomass of flying terrestrial insects was greater than that of adult aquatic insects, adult aquatic insects showed stable abundances, and there was no seasonal switch between insects from the two origins. Thus, the emergence of aquatic insects in large lowland rivers may continue at a high level under high insolation regardless of the season. Hence, from our finding regarding the foraging activity of Daubenton’s bat and the number of aquatic insects, we conclude that adult aquatic insects play a critical role in the diet of Daubenton’s bat in a large lowland river ecosystem throughout the months of June through September. Daubenton’s bat foraged more actively in the channelised reach than in the restored reach in all of the months of the study except June (Fig. 5). In addition, Daubenton’s bat synchronised its foraging

activity with the seasonal distribution of adult aquatic insects (Fig. 4a). These findings suggest that frequent foraging activities of Daubenton’s bat in the channelised reach can be attributed to the elevated number of adult aquatic insects in this reach. However, as opposed to adult aquatic insects, aquatic larvae in this study area were more abundant in the restored reach than in the channelised reach (Nakano and Nakamura, 2006, 2008). Changes in the abundance of aquatic insects between the two reaches in their two life stages (adult and larva) suggest that the different life stages of these insects may use the habitat differently. Flying insects are more likely to be found above rivers with trees on their banks compared with rivers without trees (Warren et al., 2000). Additionally, the abundance and species richness of Chironomidae, which dominated aquatic Diptera in this study and are an important component of the diet of Daubenton’s bats (Vaughan, 1997), are dependent on the quality of terrestrial environments, such as vegetation structure (Fowler et al., 1993; Delettre and Morvan, 2000). Young riparian forests hanging over the river had been established in the channelised reach since the 1970s. In the restored reach, however, very few or only seedling and sapling trees were found in proximity to the river channel, and these trees were repeatedly washed away in association with frequent movement of the thalweg. Although we cannot demonstrate where larvae move after emergence with the present data, emerged insects in the restored reach may preferentially move to overhanging riparian forests in the channelised reach. Furthermore, the absence of welldeveloped riparian vegetation may directly reduce the foraging activity of Daubenton’s bat in the restored reach because some bat species prefer forested riparian edges as foraging sites (LaVal et al., 1977; Biscardi et al., 2007). The re-meandering experiment in the Shibetsu River did not appear to enhance the quality of foraging habitat for Daubenton’s bat. However, increases in aquatic larvae arising from the river restoration might indirectly contribute to the maintenance of Daubenton’s bat populations because a constant supply of adult aquatic insects throughout the seasons is important for their foraging activity in large lowland rivers. A further decrease in aquatic insects associated with progressive anthropogenic alteration of river environments could become a serious problem for animals, including bats, that forage for insects in lowland rivers and floodplains. In order to conserve and increase foraging habitats for these predators, it is necessary to consider not only instream environments but also riparian environments, such as floodplain forests, that attract aquatic insects after emergence. In doing so, the spatial distribution and quality of the riparian forests, such as distance from the river channel and the presence of overhanging vegetation, may be important characteristics that influence bat foraging habitats. However, the results of this study were obtained at the initial stage of the experimental restoration, during which river and riparian environments were unstable and were still adjusting to the restored flow regime. Thus, the riparian vegetation was made up of trees in seedling and sapling stages in the restored reach. The continuous follow-up research is required to provide strong general indication of the worth of river re-meandering restoration. Acknowledgements We are grateful to D. Fukui and M. Akasaka for helpful advice on this paper. We are also sincerely grateful to T. Kagaya for advice on data analyses. This manuscript was significantly improved by many critical and helpful comments from the two anonymous reviewers. This study was supported by funds provided by the River Ecology Research Group of Japan for the Shibetsu River, and by Grants in Aid for Scientific Research (numbers 18201008, 19208013) from the Ministry of Education, Science and Culture, Japan.

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