Application of a bioenergetics model to estimate the ...

Application of a bioenergetics model to estimate the influence of habitat degradation by check dams and potential recovery of masu salmon populations Hirokazu Urabe, Miyuki Nakajima, Mitsuru Torao & Tomoya Aoyama

Environmental Biology of Fishes ISSN 0378-1909 Environ Biol Fish DOI 10.1007/s10641-014-0218-y

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Author's personal copy Environ Biol Fish DOI 10.1007/s10641-014-0218-y

Application of a bioenergetics model to estimate the influence of habitat degradation by check dams and potential recovery of masu salmon populations Hirokazu Urabe & Miyuki Nakajima & Mitsuru Torao & Tomoya Aoyama

Received: 22 February 2013 / Accepted: 2 January 2014 # Springer Science+Business Media Dordrecht 2014

Abstract Using a bioenergetics model, we examined how check dams negatively effect masu salmon (Oncorhynchus masou) populations by causing habitat loss in upstream areas and habitat degradation in downstream areas. The potential recovery of masu salmon populations in the upstream area was estimated based on the expected biomass and potential recovery area. We also determined if and how fish carrying capacity is affected by degradation of substrate conditions (armoring and compaction) in the downstream area. Recovery of upstream areas was considered to be effective in enhancing and conserving masu salmon populations. We demonstrated that the dam-induced altered substrate conditions and habitat degradation in the downstream area resulted in a considerable reduction of drifting prey. Simulation analysis revealed that a 40 % increase in the abundance of masu salmon juveniles in the downstream area could be expected if substrate conditions were restored. We concluded that both improvement of migration barriers and restoring the sediment regime would be important in enhancing and conserving wild masu salmon populations. H. Urabe (*) : M. Nakajima : T. Aoyama Salmon and Freshwater Fisheries Research Institute, Hokkaido Research Organization, 373-3 Kita-kashiwagi, Eniwa, Hokkaido 061-1433, Japan e-mail: [email protected] M. Torao Salmon and Freshwater Fisheries Research Institute, Eastern Research Branch, Hokkaido Research Organization, 3-1-10 Maruyama, Nakashibetsu, Hokkaido 086-1164, Japan

Keywords Check dam . Habitat degradation . Substrate condition . Potential recovery . Masu salmon . Bioenergetics model

Introduction The impacts of damming structures, which inhibit the migration of organisms and cause fragmentation of habitats and populations, on stream ecosystems have been globally reported (Dynesius and Nilsson 1994; Holmquist et al. 1998; Benstead et al. 1999; Joy and Death 2001; Marchant and Hehir 2002). The negative effects of dams on salmonids populations have also been well documented (Kareiva et al. 2000; Morita and Yamamoto 2001; Sheer and Steel 2006; Fukushima et al. 2007). These include reduction in stability and viability of fragmented populations (Fagan et al. 2002; Morita and Yokota 2002; Einum et al. 2003; Morita et al. 2009), which will in turn increase their vulnerability to environmental changes such as those resulting from human activities and global warming. In particular, habitat fragmentation (i.e., prevention of spawning migration to breeding areas) would significantly and rapidly affect populations of anadromous salmonids. In addition to these direct effects, dams also indirectly affect stream biota in downstream areas by changing sediment regimes (Poff et al. 1997). The lack of bed load materials supplied from upstream areas promotes armoring and compaction of the streambed (Kondolf 1997; Baker et al. 2011). Although the supply of bed load materials restarts when the dam has been filled up

Author's personal copy Environ Biol Fish

by sediment, there is a reduction in particle size supplied to downstream areas because the decreased bed slope reduces upstream tractive force (i.e. sediment sorting). It has also been reported that substrate particle size affects the abundance and community structure of benthic invertebrates (Flecker and Allan 1984; Rampel et al. 2000; Tiemann et al. 2004), which are a major food source for stream salmonids (Rader 1997). The drifting density of some benthic invertebrates is correlated with benthic density (Hildebrand 1974; Alan 1987, but see Elliott 1967 for counterview). Changes in substrate condition could therefore reduce drifting invertebrates by affecting abundance and community structure of benthic fauna. Any reduction in prey abundance of downstream areas would consequently suppress fish population growth. This combination of direct and indirect effects of dams, in prohibiting spawning migration and degrading food conditions in downstream areas, would severely impact stream salmonids populations. In Hokkaido in northern Japan, masu salmon (Oncorhynchus masou (Brevoort)) stocks have continuously declined since the 1970s, and the species has consequently been listed in the Red Data Book of Hokkaido (Hokkaido Government 2001). One of the major causes of this stock reduction is considered to be habitat loss and degradation due to check dams, which have been intensively constructed since 1960 (Tamate and Hayajiri 2008). Masu salmon in Hokkaido is generally anadromous and all females migrate to the ocean after more than 1 year in stream life stage (Kato 1991). Therefore, if an impassable dam is constructed, upstream populations will immediately become extinct (Fukushima and Kameyama 2006; Fukushima et al. 2007). For this reason, recovery of masu salmon populations will require promotion of their spawning migration to upstream areas as well as conservation of habitat in the downstream areas. Issues relating to damming structures have been reported in every part of the world where anadromous salmonids are found (e.g., National Research Council NRC 1996; Kareiva et al. 2000; Gregory et al. 2002), and many habitat restoration practices have been implemented (Bash and Ryan 2002; Bernhardt et al. 2005; Roni et al. 2008). Before effective restoration is possible, accurate tools are still required for evaluating the degree of habitat degradation and/or abundance of suitable habitat. Physical habitat models based on fish habitat preference are currently the most widely used tools for estimating the amounts of suitable habitat, and they

are relatively effective in certain situations (e.g., Jowett 1992; Urabe and Nakano 1999; Guay et al. 2003). However, problems with this approach have also been noted (e.g., Beecher et al. 2010; Bradford et al. 2011). In particular, failing to consider prey abundance could prevent accurate evaluation of fish habitat quality (Rosenfeld and Ptolemy 2012). Recent studies on habitat evaluation based on a bioenergetics model, which represents both physical factors and prey abundance, demonstrated that the energetic potential of habitats could be a direct predictor of salmonid capacity (Nislow et al. 1999; Nislow et al. 2000; Hayes et al. 2007; Jenkins and Keeley 2010; Urabe et al. 2010), and thus the bioenergetic approach could be a more effective tool for evaluation of habitat conditions. Hence, the objectives of the present study are to estimate the potential recovery of masu salmon populations in upstream and downstream areas by evaluating the potential capacity of salmonids using a bioenergetics model. Further, we examine how alteration of substrate particle size, generated by changes in sediment regime, affects energetic profitability for masu salmon in downstream areas by focusing on the response of benthic invertebrates. Study area Field surveys were conducted in the Ken-ichi and Sukki Rivers in Hokkaido, northern Japan (Fig. 1). These rivers are small, typical mountain streams with welldeveloped broad-leaved forests in their riparian zones (Table 1). Both watersheds were inhabited by masu salmon, white-spotted char (Salvelinus leucomaenis (Pallas)), freshwater sculpin (Cottus nozawae (Snyder)), and stone roach (Noemacheilus barbatulus toni (Dybowski)). In the mainstem and major tributaries of the Ken-ichi River, at least 13 check dams (hereafter dams) exist, in which fish ways have been established at only five. The entire upstream migration is prevented by dam K2 (23 m high, Lat. 42.168647°, Long. 140.056694°; Fig. 1), above which the masu salmon population has been lost. In the downstream area of the Ken-ichi River, masu salmon and anadromous white-spotted char populations are still maintained, but their habitat has been severely degraded due to drastic changes in substrate condition (armoring and compaction by fine particles). A single dam in the Sukki River watersheds, SK1 (8 m in height, Lat. 42. 602886°, Long. 139. 847769°),


Sea of Japan

Fig. 1 Map of the study area. Open circles indicate the study reaches. Solid and open rectangular symbols represent impassable and passable dams, respectively. Dam SK1 has a fishway but we regarded it as impassible because it constantly clogs and malfunctions (see text for further details). Larger rectangular symbols indicate dams whose height is greater than 10 m. Thick lines and shaded areas indicate that potential recovery and sedimentation areas, respectively

St.1 St.2

SK1

Sukki River Ken-ichi River 2km

St.1 St.2 St.3 St.4 K2 St.1 St.2 St.3 St.4 K1

Futamata Stream

Sukki River

Ken-ichi River

Sea of Japan

Table 1 General descriptions of the study sites. The characteristics of the study reaches were shown as mean and standard deviations (in parentheses)

Characteristics

Upstream

Downstream

Upstream

15.4

15.4

12.8

Number of reaches

4

4

2

Mean reach length (m)

44.5 (11.2)

39.3 (11.9)

64.0 (0)

Mean wetted width (m) Mean depth (cm) The River length indicates the total length of mainstem

Sukki River

River length (km) a

Mean gradient (%)

a

Ken-ichi River

1.1 (0.003)

0.9 (0.02)

0.7(0.003)

7.9 (2.7)

9.9 (2.7)

5.6 (1.1)

41.5 (4.4)

42.9(4.8)

34.8 (9.5)

Mean water column velocity (cm s−1)

61.3 (2.2)

43.4(6.3)

45.2 (11.5)

Mean bottom velocity (cm s−1)

34.5 (4.7)

25.1 (2.7)

25.1 (6.3)


possesses a fish way at the lower mainstem (Fig. 1). However, this is easily clogged by woody debris, brushes and sediment, and scarcely functions throughout the year. In fact, only a few masu salmon fry were captured in a 200 m reach established above the dam in the Sukki River in 2005 (Urabe unpubl. data), which suggests that masu salmon populations above the dam are virtually extinct. Armoring was also found in downstream area of the Sukki River, but was less serious than in the Ken-ichi River.

Methods Outline We estimated the potential recovery of masu salmon populations in upstream areas in both the Ken-ichi and the Sukki Rivers using a bioenergetics model described by Urabe et al. (2010). Four reaches were set above dams in the Ken-ichi, and two above dam in the Sukki Rivers so as to represent an environment of the potential recovery area (hereafter upstream sections; Fig. 1 and Table 1). In the Ken-ichi River, we also estimated the potential carrying capacity in four reaches of the downstream area (hereafter downstream section) and compared it with the capacity in the upstream area to examine whether changes in substrate condition caused by alteration of sediment regime can affect habitat capacity. Substrate condition was quite different between the upstream and the downstream areas of dam K2, and more serious degradation was found in downstream area of dam K1. Although the degraded area extended to around the confluence of the main stem and the Futamata Stream, it was difficult to precisely identify the extent of the degradation induced by dam K2. Further, geomorphological properties, such as gradient and stream size, below dam K1 were significantly different from those in the upstream area of dam K2 (i.e., control section). Hence, study reaches in downstream section were set between dam K2 and K1. Further, we attempted to identify the mechanism of the decline in habitat capacity in the downstream section by comparing the substrate condition, periphyton abundance, abundance and community structure of benthic invertebrates, and abundance and species composition of drifting invertebrates between upstream and downstream sections, regarding upstream section as a reference. The four parameters essential to the bioenergetics

model–velocities at focal and foraging points, depth, and drifting density–were measured in the field, and all other parameters were derived from Urabe et al. (2010). All field surveys were carried out during August 3–4, 2004 in the Ken-ichi River, and September 3, 2003 in the Sukki River, when the stream flow was at an approximate summer base level. Physical environment In each reach we established 30 or 40 equally spaced transects that included five equally spaced measuring points. The number of transects was determined by the following rules: 30 transects placed in reaches less than 50 m long, and 40 transects placed in those 50–100 m long. As a consequence, measuring grids of approximately 1.5 m (long)×1 m (wide) were set. At each measuring point, the depth, current velocity at 3 cm above the bottom (hereafter bottom velocity) and current velocity at 60 % depth (hereafter water column velocity) were measured, and these were used as velocities at focal and foraging points in the bioenergetics model (Urabe et al. 2010). In addition to these parameters, we concurrently determined the substrate types at measuring points in the Ken-ichi River. The degree of substrate compaction (loose with interstices among particles or firm without) was also evaluated by touch and visual observation. Substrate types were classified as follows: fine sediment (256 mm) and bedrock. Sampling of drifting and benthic invertebrates and periphyton To evaluate drifting prey density, we collected drifting invertebrates and measured the volume of water sieved by drift nets following Urabe et al. (2010). We attempted to collect drifting prey samples at every study reach. However, in the Ken-ichi River, net setting points could be spaced apart from the neighboring reach by approximately 100 m at reach number 2 and 3 in both the upstream and downstream sections. Concurrent sampling at such proximate reaches causes significant sampling errors, and thus we collected samples at reach number 2 in the upstream section and at reach number 3 in the downstream section, and the samples were regarded as representative of the neighboring reaches. The drift sample obtained at reach number 1 of the


upstream section in the Ken-ichi River was lost by accident, and so the reach was omitted from analyses of drifting invertebrates and habitat capacity. In the Kenichi River, we collected 10 benthic invertebrate samples in the riffle of each reach using a Surber sampler (500 μm mesh, 25×25 cm mouth opening), and 10 periphyton samples were also collected to determine food availability for benthic invertebrates. For periphyton collection, we chose cobbles of approximately 15 cm diameter and scraped the surface (within a 25 mm diameter circle) using acrylic fiber. After extracting chlorophyll a by steeping in 90 % aceton for 24 h in the dark, we measured the level of chlorophyll a using spectrophotometer in a laboratory according to Lorenzen (1967). The invertebrates obtained from drift and benthic samplings were generally identified to the order level. However, orders Ephemeroptera and Diptera included families that are sensitive to substrate condition, such as Baetidae, Chironomidae and Tipulidae, and so those orders were identified into family level. We classified the aquatic insect adults obtained from drift samples into terrestrial invertebrates, because the amount in samples did not directly reflect benthic fauna in the reaches. Consequently, the aquatic invertebrates were classified

as follows: Ephemeroptera except for Baetidae, Baetidae, Plecoptera, Trichoptera, Diptera except for Chironomidae and Tipulidae, Chironomidae, Tipulidae, Coleoptera, and others. After sorting, samples were dried by each taxon at 55 °C for 24 h, and weighed to the nearest 0.1 mg. We then calculated drifting prey density per unit time. Data analyses Evaluation of potential recovery in the upstream section We estimated habitat capacity for stream salmonids in the upstream area as NEI (net energy intake) potential using data obtained from field surveys and the bioenergetics model. All the parameters used in the model, except for depth, velocity variables and drifting density, and the assumptions for calculation were the same as those described in Urabe et al. (2010). We evaluated the potential biomass of salmonids in the upstream areas based on the NEI potential, which was estimated in the present study, and the relationship between the NEI potential and salmonids biomass shown in Fig. 2 (upper-left panel) in Urabe et al. (2010). The regression equation is as below (hereafter NEI-Biomass equation).

logðbiomass of overall salmonidsÞ ¼ 0:382logðmean NEI potentialÞ−0:076; R2 ¼ 0:771; P < 0:0001

300

Mean NEI potential (J h-1)

To estimate the potential recovery of masu salmon populations in the upstream areas of the dams, the recovery area needs to be identified. According to a previous study (Hokkaido Fish Hatchery 2001) implemented near the present study area, the upper limit of habitable areas for masu salmon was found to be 200 m in elevation. Hence, we assumed that masu salmon population would recover in an area extending up to 200 m in elevation. Subsequently, we can calculate the total biomass of overall salmonids that would recover in the upstream areas from the expected biomass and potential recovery area identified above. We further estimated the abundance of juvenile masu salmon using the composition of masu salmon relative to overall salmonid biomass (0.507 and 0.211 in the Ken-ichi and the Sukki Rivers, respectively) and the mean body weight (5.6 g and 8.2 g in the Ken-ichi and the Sukki Rivers, respectively) of juvenile masu salmon, which were derived from Urabe et al. (2010).

ð1Þ

250

200

150

100

50

0

Upstream

Downstream

Fig. 2 Comparison of mean NEI potential between the upstream and downstream sections in the Ken-ichi River. Error bars indicate 1 SD


Evaluation of habitat degradation in the downstream section We compared the NEI potential between the upstream and downstream sections to examine whether the degradation of substrate conditions caused a decline in the habitat capacity for masu salmon in the Ken-ichi River. We also compared the physical characteristics, abundance and species composition of drifting and benthic invertebrates, and periphyton abundance between the upstream and downstream sections to examine if and how downstream degradation of substrate condition (due to alteration of sediment regime) affects habitat capacity. The effect of habitat restoration on masu salmon populations in the downstream area was evaluated from the expected increase of masu salmon juveniles resulting from an increase of the NEI potential using the NEI-biomass equation under the assumption that prey density attains the same level as in the upstream section. We were not able to identify the extent of the degraded area downstream (see methods), and thus the increase of masu salmon was estimated as a percentage of biomass per unit area. We examined differences in physical and biological traits between the upstream and downstream sections using one-way ANOVA. For these statistical analyses, to improve the normality and homogeneity of variance, log- or log+1- and arcsine-transformations were made to all the numerical and percentile data, respectively.

Results Potential recovery of juvenile masu salmon in the upstream areas The mean drifting density and NEI potential in the study reaches were 0.0458 mg m − 3 (SD = 0.0045, range=0.0426–0.0490) and 241.5 J h−1 (SD=15.1, range = 228.1–257.9) in the Ken-ichi River, and 0.0636 mg m−3 (SD=0.0054, range=0.0598–0.0674) and 306.6 J h−1 (SD=44.6, range=275.0–338.1) in the Sukki River, respectively. The potential recovery area in the Kenichi River was 21,686 m2 in the mainstem and 1,736 m2 in tributaries, while the equivalent figures in the Sukki River were 21,700 m2 and 2,920 m2, respectively (Table 2). The potential recovery of biomass per unit area and of the total biomass of salmonids were 7.6 g m−2 and 178,004 g in the

Ken-ichi River, and 8.3 g m−2 and 204,346 g in the Sukki River, respectively. The estimated total abundance of recovering juvenile masu salmon was 16,115 and 5,259 individuals in the Ken-ichi and Sukki River watersheds respectively (Table 2). Habitat degradation in the downstream area The mean NEI potential in the downstream section was significantly lower than in the upstream section (Fig. 2, F1,5 =15.86, P=0.0105). The drifting density of overall invertebrates, which combined aquatic and terrestrial invertebrates, in the downstream section was also significantly lower than in the upstream section (Table 3). Although the drifting density of aquatic invertebrates in the downstream section was lower than in the upstream section, the drifting density of terrestrial invertebrate was unchanged (Table 3). In both sections, Baetidae was the most dominant taxon in the drift samples, and a nearly significant difference was found in the drifting density between the sections (Table 3). In the analysis of benthic samples, the total density of benthic invertebrates did not differ between the sections, although species composition did vary considerably (Table 4). In the analysis for each taxon, density of Baetidae in the downstream section was lower than in the upstream section, whereas densities of Chironomidae and Tipulidae in the downstream section were significantly greater than in the upstream section (Table 4). The mean depth of the reaches was relatively homogeneous between the sections (Table 1, F1,6 =0.14, P=0.7264). Although the current velocities differed considerably (Table 1, water column velocity: F1,6 =13.90, P=0.0136, bottom velocity: F1,6 =12.49, P=0.0167), discharge within the prey capture area (see equation 3 in Urabe et al. (2010) for details of the calculation) did not differ between sections (F1,6 =0.18, P=0.6851). The percentages of fine sediment in the downstream section were greater than in the upstream section, whereas percentage of pebbles in the downstream section was lower than in the upstream section (Table 5). The percentage of loose substrate was also lower in the downstream section than in the upstream section (Fig. 3, F1,6 =51.23, P=0.0008). We found the abundance of periphyton to be nearly four times greater in the downstream section than in the upstream section (Fig. 4, F1,6 =185.69, P