Department of Physics, Chemistry and Biology
Master Thesis
Stream channelization effects on fish abundance and
species composition
Ulf Johansson
LiTH-IFM- Ex--13/2762--SE
Supervisor: Arne Fjälling, Swedish University of Agriculture Examiner: Anders Hargeby, Linköping University
Department of Physics, Chemistry and Biology Linköpings universitet
Rapporttyp Report category Examensarbete D-uppsats Språk/Language Engelska/English Titel/Title:
Stream channelization effects on fish abundance and species composition Författare/Author:
Ulf Johansson
Sammanfattning/Abstract:
Streams are important habitats, providing shelter and feeding opportunities for a wide range of organisms. The species depending on running waters includes a wide array of fish species, using these waters for their whole or parts of their lifecycle. Streams are also the subject of different anthropogenic impact, e.g. hydropower development. Hydropower development usually means lost connectivity, altered flow regimes and channelization. Channelization is one of the major factors causing stream habitat loss and degradation and thereby a threat to biodiversity of running waters. In the present study, the ecological impact of channelization on the fish fauna along a gradient of channelization severeness was examined. Besides channelization, stream velocity and depth were taken in to account. The study was carried out in two adjacent nemoboreal streams, Gavleån and Testeboån. The study was conducted between the 6th of June and the 10th of October 2012 at 15 sites. Sites were selected using historical maps and field observations and graded 0-3 depending on the degree of channelization. Fish community were sampled with, Nordic multi-mesh Stream Survey Net (NSSN). In all, 1.465 fish were captured, representing 15 species and seven families. The sites differed in species richness, abundance and proportion of individuals. Based on the results from rarefaction curves and ANOVA, channelization was found to be the main factor affecting the fish biota, both in abundance as well as species richness and composition. In general the rheophilic species declined along the gradient of increasing channelization severeness, while limnophilic species increased along the gradient.
ISBN LITH-IFM-A-EX—13/2762 SE ______________________________________________ ISRN _________________________________________________ _
Serietitel och serienummer ISSN
Title of series, numbering
Handledare/Supervisor Arne Fjälling
Ort/Location: Linköping
Nyckelord/Keyword:
Channelization, Rheophilic species, nemoboreal streams, Nordic multi-mesh Stream Survey Net, lotic, relative abundance, fish community, limnophilic
Datum/Date
2013-05-31
URL för elektronisk version
Institutionen för fysik, kemi och biologi
Department of Physics, Chemistry and Biology Avdelningen för biologi
Contents
1 Abstract ... 1
2 Introduction ... 1
3 Materials and methods... 3
3.1 Study area ... 3
3.2 Channelization ... 4
3.3 Sample method ... 4
3.4 Stream velocity and depth ... 5
3.5 Guilds ... 5
3.6 Statistical analysis ... 5
4 Results... 6
4.1 Determinants of abundance ... 8
4.2 Species richness and composition ... 10
4.3 Effect on guilds ... 11
5 Discussion ... 13
6 Conclusions ... 15
7 Acknowledgement ... 15
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1 Abstract
Streams are important habitats, providing shelter and feeding opportunities for a wide range of organisms. The species depending on running waters includes a wide array of fish species, using these waters for their whole or parts of their lifecycle. Streams are also the subject of different anthropogenic impact, e.g. hydropower development. Hydropower development usually means lost
connectivity, altered flow regimes and channelization. Channelization is one of the major factors causing stream habitat loss and degradation and thereby a threat to biodiversity of running waters. In the present study, the ecological impact of channelization on the fish fauna along a gradient of channelization severeness was examined. Besides channelization, stream velocity and depth were taken in to account. The study was carried out in two adjacent nemoboreal streams, Gavleån and Testeboån. The study was conducted between the 6th of June and the 10th of October 2012 at 15 sites. Sites were selected using
historical maps and field observations and graded 0-3 depending on the degree of channelization. Fish community were sampled with, Nordic multi-mesh Stream Survey Net (NSSN). In all, 1.465 fish were captured, representing 15 species and seven families. The sites differed in species richness, abundance and proportion of individuals. Based on the results from rarefaction curves and
ANOVA, channelization was found to be the main factor affecting the fish biota, both in abundance as well as species richness and composition. In general the rheophilic species declined along the gradient of increasing channelization severeness, while limnophilic species increased along the gradient.
Keywords
Channelization, Rheophilic species, nemoboreal streams, Nordic multi-mesh Stream Survey Net, lotic, relative abundance, fish community, limnophilic
2 Introduction
Rivers and streams are essential for the exchange of energy, organic matter and nutrients between inland and coastal areas. They drive local as well as global biochemical cycles. Minor streams are dominant interfaces between any aquatic habitat and associated land (Dodds 2002). Streams are also important habitats, providing shelter and feeding opportunities for a wide range of organisms like fish, insects, plants, mollusks, birds and mammals. There is a range of migratory fish species that use running water for foraging or as nursery areas for young stages. Among the fish species that use running waters for such purposes are salmon (Salmo salar) and trout (Salmo trutta). The list goes on with less well known species such as river lamprey (Lampetra fluviatilis), sea lamprey
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(Coregonus spp), grayling (Thymallus thymallus), ide (Leuciscus idus), vimba (Vimba vimba), sabre carp (Pelecus cultratus) and burbot (Lota lota). The biodiversity of the coast is therefore strongly dependent on intact rivers and streams discharging into coastal waters, both for nursery habitats, migration route and food resources (Degerman et al, 2005).
In addition,non-migrating species like stream-resident brown trout, grayling, perch (Perca fluviatilis), roach (Rutilus rutilus) and Northern pike (Esox lucius) form populations in rivers and streams. These populations are primarily affected by abiotic factors like flow velocity, depth, bottom quality, light conditions and temperature for their choice of habitat (Zalewski & Naiman 1985). The
stationary populations in rivers and streams play an important role in the lotic habitat food webs and are largely dependent on variations in a natural
watercourse to hold feeding, resting and spawning areas.
Globally habitat loss—due to destruction, fragmentation or degradation of
habitats is the primary threat to biodiversity(Wilcox and Murphy 1985). Streams worldwide are subject to human impacts that degrade habitat conditions
(Malmqvist & Rundle 2002) and Sweden is no exception. More than 70% of the Swedish streams are regulated and more than 33,000 km channelized (Jansson et al. 2000; Törnlund & Östlund 2002). Channelization results in loss of structural complexity, simplified flow patterns, and decreased availability of microhabitats for a wide array of lotic organisms (Karr, J. R. and Chu, E. W. 1999, Petersen et al., 1987). Therefore channelization of running waters is one of the major factors behind stream habitat loss and degradation and is a serious threat to biodiversity (Allan &Flecker 1993). Channelization has been performed for diverse
purposes, in Sweden mainly for the purpose of timber floating and land drainage which took place in the 19th century, and more recently hydropower
development.
In order to evaluate the state of aquatic organisms in running waters a range of monitoring techniques has been developed, for fish sampling, e.g. electro
fishing, traps, hook and line and none-capture methods are some of the methods used today (Sutherland 2006).
Studies on the effect of channelization on the fish fauna using electro fishing showed a significant effect on species richness and abundance (Javier et al 2005, Engman & Ramirez 2012). However no study has been found so far that
investigates the fish fauna along a gradient of increasing channelization severeness. A contributing factor for this is probably the lack of suitable
sampling methods. The present study was made possible by and conducted with a new sampling method, Nordic Multi-mesh Stream Survey Net
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Nordic Survey Net used in lakes (Kinnerbäck 2001) designed to operate in running waters.
The main aim of this study was to investigate the effects of channelization on fish biota in lotic habitats over a gradient of channelization severeness. The secondary aim was to evaluate the Nordic Multi-mesh Stream Survey Net as a tool for these kinds of investigations.
3 Materials and methods
3.1 Study area
The study was performed between the 6th of June and the 10th of October 2012 in Gävleborg County. The investigation sites were located in the two adjacent streams Gavleån (N 60° 40′ 652″, E 17° 09′700″) and Testeboån (N 60° 42′ 25.74″, E 17° 09′ 14.15″) (Fig 1) which both empty into the Bay of Gävle. The Bay of Gävle is located in the southern Bothnian Sea. At the head of the bay is the town Gävle where both of the streams have their mouths. In total 15 sites were investigated and 222 efforts were made. This gave an average of fifteen efforts per site. The distance between the investigated sites range from 50 meters to five kilometers with an average distance of 2.6 kilometers.
Gavleån has a length of 29 kilometers, 129 km when including the tributaries. Gavleån empties a drainage area of about 2,500 square kilometers. Within the drainage area 77.4% is woodland and 6.5% is farmland. The mean annual
discharge is 21 m³/s and the mean of total phosphorus is 25.8 µg/l (the mean was calculated using measurements made between 2000 and 2012, extracted from the database VISS (Water Information System Sweden)). Along the stretch there are seven hydropower plants and the channelization is in general high.
Testeboån has a length of 60 kilometers, when including the tributaries 110 km. Testeboån empties a drainage area of 1,123 square kilometers. Within the
drainage area 81.5% is woodland and 4.0% is farmland. The mean annual discharge is 11.7 m³/s and the mean of total phosphorus is 16.4 µg/l (the mean was calculated using measurements made between 1990 and 2005, extracted from the database VISS (Water Information System Sweden)). Along the stretch there are valuable wetlands, riparian forests and flowing water in a mosaic
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Figure 1. The location of Gävleborg County and the two streams Gavleån and Testeboån with the investigation sites marked with a star.
3.2 Channelization
The channelized areas were chosen and categorized using historical maps,
existing habitat mapping and field observations. The areas were categorized on a scale from 0 - 3 were “0”, is a watercourse with a natural furrow, bottom and shorelines. “1”, is a watercourse with a natural but straightened furrow and natural bottom and shorelines. “2”, is a watercourse with a straightened furrow and modified bottom, the shorelines are not all-natural. “3”, is a watercourse with a straightened furrow, flat bottom and steep smooth paved / poled shorelines.
3.3 Sample method
Fish biota was caught with Nordic multi-mesh Stream Survey Net (NSSN). The NSSN uses the same multi-mesh principle as the Nordic net; both the mesh size of the panels (12 panels with mesh size from 5 to 55 mm mesh side [ICES 2004]) and their sequential order are identical. The fishing height of the net is 700 mm (stretched height is 900 mm), the length of the 12 sections is 1.500 mm each, resulting in an efficient length of 18 m, and an efficient surface of 12.6 m². The nets were set between 6 and 8 pm and lifted between 6 and 8 am the day after. Thereby the sampling has followed the same timeframe as the
standardized method of sampling in lakes. The nets were put in to the water parallel with the water stream. For each sample site all captured fish were
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identified to species level and measured for total length (mm) and weight together (g) for total biomass.
3.4 Stream velocity and depth
The stream velocity was divided into four categories. Calm / still (from 0.0 to 0.1 m / s), low stream (0.1-0.2 m / s), streaming (0.2 to 0.7 m / s) and rushing (0.7 m / s - 2 m / s). The stream velocity was measured with a Flow meter 1 from Geopacks (Geopacks 2010) 0.3 meters below the surface in cross sections of the watercourse. The cross section consists of a measuring point in the middle of the stream and one on each side, centered between the center and land. The measurements were made in the upper, middle and lower part of the investigated site from which the average stream velocity was calculated. The depth was measured upstream and downstream each net with an echo sounder. The
measured depths were used to calculate the average depth of the sampled areas.
3.5 Guilds
To further examine the effects of channelization the species were grouped into guilds (a group of species that exploits the same kind of resources). The
classification followed the system developed within the EU project FAME (FAME CONSORTIUM, 2004). The guilds are represented by rheophilic (preferring high flow conditions, and clear water), eurytopic (having a wide tolerance of flow conditions but not considered to be rheophilic) and limnophilic species (preferring slow flowing to stagnant conditions). The categories are based upon distribution and preferences in rivers and streams rather than
considering the presence of the species in lakes. Floodplain species are classified as Limnophilic unless they exhibit tolerance of relatively high flows, in which case they are considered as Eurytopic (FAME CONSORTIUM, 2004).
3.6 Statistical analysis
A two way and a three way analysis of variance (ANOVA) was used to test for differences in fish abundance between the two streams investigated as well as areas of different channelization, stream velocity and depth. The abundance was log transformed to satisfy parametric assumptions of a normal distribution. The guilds, rheophilic, eurytopic and limnophilic species were treated with a
Kruskall Wallis test. Both ANOVA and Kruskal Wallis were carried out in IBM SPSS statistics 2.0. To compare the species richness within the different degrees of channelization, rarefaction curves with confidence interval (95%) and the expected richness were calculated, using the internet-accessible Species
Richness Estimators Eco-Tool (Colwell 2013). The calculation of the expected richness was performed since there was a difference in the number of efforts and sample sites.
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4 Results
In all, 1,465 fish were captured, representing 15 species (Fig 2) and seven
families. Overall, 222 efforts were made giving an average CPUE (catch per unit of effort, i.e. catch per net and night) of 6.6 individuals. Perch was the most common species in the catch followed by ruffe (Gymnocephalus cernuus) and roach. More species were caught in Gavleån than in Testeboån. When separating the two streams it can be seen that all 15 species sampled were found in Gavleån and eight species were found in Testeboån. In Gavleån the dominant species in the catches were perch, ruffe and roach. In Testeboån the dominant species were roach followed by perch and ruffe (Table 1). Burbot and vimba were caught in small numbers in both streams, both species are listed in the Swedish Red List as Near Threatened (NT) (Gärdenfors 2010).
Smelt Bullh ead Burb o1 Trou t Rudd Brea m S.br eam Blea k Vimba Ide Roac h Pike Zand er Ruffe Perc h 3,0 2,5 2,0 1,5 1,0 0,5 0,0 C P U E
95% CI for the Mean
Interval Plot of species captured during the study
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Table 1. CPUE and the standard deviation both to individuals and biomass for all species caught in the studied streams. The proportional catch of the total effort given in percent is also shown.
Testeboån Gavleån
Species Mean ± SD Percentage Mean ± SD Percentage
Perch Ind/net 0.29 ± 0.64 21% 2.64 ± 4.3 64% g/net 42.0 ± 119 213 ± 409 Zander Ind/net 0.036 ±0.22 3% g/net 13.5 ± 120 Roach Ind/net 0.64 ± 1.10 39% 1.7 ± 3.71 48% g/net 39.1 ± 78.9 100 ± 225 Bleak Ind/net 0.04 ± 0.19 3.90% 0.04 ± 0.22 3% g/net 0.33 ± 1.66 0.48 ± 2.75 Burbot Ind/net 0.06 ± 0.24 5.80% 0.02 ± 0.13 1.80% g/net 7.98 ± 38.9 9.87 ± 89.7 Bullhead Ind/net 0.07 ± 0.32 5.80% 0.11 ± 0.35 9.70% g/net 2.37 ± 11.6 0.57 ± 1.94 Rudd Ind/net 0.006 ±0.08 0.60% g/net 0.80 ± 10.3 Vimba Ind/net 0.02 ± 0.17 1.20% g/net 7.42 ± 67.9 Trout Ind/net 0.08 ± 0.34 5.80% 0.03 ± 0.19 1.80% g/net 2.84 ± 13.1 1.57 ± 11.6 Bream Ind/net 0.04 ± 0.18 3.60% g/net 10.5 ± 69.5 Silver bream Ind/net 0.39 ± 0.99 21% g/net 36.5 ± 129 Pike Ind/net 0.02 ± 0.14 1.90% 0.04 ± 0.2 4.20% g/net 5.56 ± 39.7 59.6 ± 332 Smelt Ind/net 0.63 ± 4.40 8.50% g/net 24.2 ± 159 Ruffe Ind/net 0.25 ± 0.63 18% 2.46 ± 7.45 40% g/net 3.00 ± 8.40 64.0 ± 210 Ide Ind/net 0.01 ± 0.11 1.20% g/net 10.7 ± 97.1
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4.1 Determinants of abundance
To evaluate the effects of channelization on fish abundance three more factors were taken into account, the stream ID, stream depth and stream velocity (Table 2). To evaluate if there was a difference in fish abundance between the two investigated streams a Two -way ANOVA was carried out (Table 3) with stream ID and channelization as given factors showing no significant difference
between the two streams. However there was a significant difference between the grades of channelization.
Table 2 Stream ID and sample areas with the measurements of stream velocity, and depths as well as the grades of channelization.
Stream ID Sample area Velocity (m/s) Channelization Depth (m)
Gavleån Islandsbron 0,79 3 2,9
Gavleån Idrottsplatsen 0,49 2 2
Gavleån Kvarnbron 0,21 3 1,6
Gavleån Gråströmmarna 0,48 2 2,4
Gavleån Gustavs bro 0,30 1 3
Gavleån Boulognerskogen 0,42 2 3,1
Gavleån Mackmyra bruk 0,44 3 1,7
Gavleån Bruksallen 0,35 0 0,75 Gavleån Kvarnåkersvägen 0,55 2 1,7 Gavleån Lundvägen 0,27 2 4,7 Gavleån Hälleh 0,30 1 3,2 Testeboån Deltat 0,15 1 2,3 Testeboån Brännssågen 0,35 0 0,65 Testeboån Åbyggeby 0,47 2 1,7 Testeboån Torsved 0,36 1 2
Table 3 Results from the two-way ANOVA were the channelization shows a significant result but the streams (Testeboån, Gavleån) do not.
Dependent Variable: Total abundance
Source ss df Ms F P
Channelization 0.727 3 0.242 4.938 0.023
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A three-way analysis of variance (ANOVA) was used to determine whether channelization, stream velocity or depth influenced the number of fish (Table 4). The results showed a highly significant result of channelization while the other factors tested showed no significant difference in variance.
Table 4 Result from the three-way ANOVA with channelization, velocity and depth as fixed factors.
Dependent Variable: Total abundance
Source Ss df Ms F P
Channelization 11.05 3 3.683 24.473 <0.001
Stream velocity 6.84E-05 1 6.84E-05 0 0.983
Depth 1.285 7 0.184 1.22 0.293
Although the channelization has a significant effect on the relative abundance, it does not follow the gradient of channelization severeness (Figure 3).
Figure 3 Relative abundance of all fish species caught during the project. The abundance is based on the CPUE.
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4.2 Species richness and composition
In order to evaluate the species richness within the different channelization rates a rarefaction curve with the expected richness was calculated (Fig 5). The curve showed considerable differences in species richness, especially between
channelization one and channelization three with almost twice as many species in channelization grade three. Also the species composition differed between the channelization rates. Trout were only caught in the 0 areas, constituting 6% of the number of fish. Smelt, zander and vimba were exclusive for channelization grade 3 and together with ide, bream and rudd they were only caught in
channelized sections of grade 2 two and 3, together constituting 10 % of the fish caught. Perch, roach, ruffe, bleak and bullhead were caught in all four grades of channelization (Table 4).
Figure 4 The species richness plotted against channelization class for sampling sites 0 2 4 6 8 10 12 1 3 5 7 9 11 13 15 17 19 21 23 25 27 R ic hn ess Samples CH_0 CH_1 CH_2 CH_3
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Table 5 The species composition, CPUE ± SD in the different areas.
Channelization0 Channelization1 Channelization2 Channelization3
Species Mean ± SD Mean ± SD Mean ± SD Mean ± SD
Perch 1.24 ± 3.02 0.32 ± 0.73 1.57 ± 1.98 4.78 ± 6.19 Roach 2.50 ± 2.69 0.41 ± 1.10 1.22± 3.29 2.14 ± 4.44 Ruffe 0.03 ± 0.19 0.39 ± 0.71 0.67 ± 1.15 6.14 ± 11.9 Bleak 0.03 ± 0.19 0.02 ±0.15 0.03 ± 0.24 0.05 ± 0.22 Bullhead 0.41 ± 0.56 0.06 ± 0.33 0.05 ± 0.27 0.03 ± 0.18 Pike 0.03 ± 0.19 0 0.04 ± 0.21 0.05 ± 0.22 Silver bream 0 0.07 ± 0.33 0.29± 0.79 0.58 ± 1.31 Ide 0 0 0.01± 0.10 0.02 ± 0.13 Bream 0 0 0.03± 0.18 0.05 ± 0.22 Smelt 0 0 0 1.76 ± 7.28 Zander 0 0 0 0.10 ± 0.36 Vimba 0 0 0 0.05 ± 0.29 Rudd 0 0 0.01± 0.11 0 Trout 0.28 ± 0.59 0 0 0 Burbot 0.03± 0.19 0.04 ± 0.20 0.03± 0.18 0 4.3 Effect on guilds
The results from the Kruskall Wallis test showed a significant channelization effect in all guilds, rheophilic, limnophilic as well as eurytopic species (Table 6).
Table 6 The table gives the mean catch ± SD and the P value for the guilds limnophilic, intermediate and rheophilic species.
Chann 0 Chann 1 Chann2 Chann 3
Guilds mean ± SD mean ± SD mean ± SD mean ± SD
Limnophilic 0,03± 0,19 0,46± 0,81 1,01± 1,58 7,00± 12,02 P < 0,001 Eurytopic 3,90± 5,14 0,80± 1,65 2,92± 4,30 5,63± 8,62 P < 0,001 Rheophilic 0,69 ± 0,81 0,07± 0,33 0,05± 0,21 0,03± 0,18 P = 0,002 The relative proportions of the guilds (Fig 5) varied with regard to
channelization severeness. Proportionally the rheophilic species showed a rapid decline from channelization 0 to channelization 3. An opposite trend can be seen among the limnophilic fish species where catches increased with channelization severeness. The proportion of euryotopic species followed the same pattern as the total abundance of fish with the lowest abundance at channelization rate 1. The proportions are based on the CPUE.
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Figure 5 Proportions based on the CPUE for Rheophilic, Limnophilic and Eurytopic species caught along the gradient of channelization severeness. Channelized areas are categorized from 0-3.
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5 Discussion
Fish abundance was strongly influenced by channelization but not significantly influenced by the other test variables. This points to anthropogenic impact as one of the primary factors controlling the fish abundance in the studied streams. These results are confirmed by other studies regarding channelization
(Scarnecchia 1988, Engman 2012, Knight et al 2012) showing a significant effect on fish abundance and composition in channelized parts of streams and rivers.
Whenadverseconditions prevail, fish communities in streams are regulated by habitat complexity and availability of shelter (Cunjak 1996), over time causing greater variability in fish community structure at disturbed sites with simplified habitats ( Paller 2002). Channelization results in loss of structural complexity and simplified flow patterns. A channelized stream is typically a stream with a high but non-turbulent velocity, deeper than a riffle (Rankin 1989).
The channelized part of a stream becomes dominated by tolerant species and lacks a high abundance of sensitive species. Tolerant species have the ability to thrive in environments altered by anthropogenic disturbances, whereas sensitive species have a reduced range of environmental tolerance and are generally not present in degraded habitats (Smoger and Angermeier 1999). These findings may explain the results of the present study that examined the fish fauna over a gradient of channelization severeness. The results show increased species richness as well as higher abundance in the most channelized areas of the investigated streams. There is also a shift in species composition along the channelization gradient.
This shift in species composition with an increased channelization was best seen when species were grouped into guilds. Stream parts with low channelization severeness contain rheophilic and eurytopic species, while a high channelization severeness leads to a higher occurrence of eurytopic and limnophilic species. Rheophilic fish species depend on flowing water for food, shelter, spawning and movement between different habitats. Limnophilic and eurytopic species
however do not in the same extent dependent on such conditions and thereby taking advantage of the tranquil nature following channelization
(Naturvårdsverket 2006).
It has been shown that many species that are normally found in lakes or slow flowing, lower parts of the rivers are favored by water regulation where
channelization is a common element (Calles 2005). In the present case there is no significant difference between the highly regulated Gavleån and the mostly natural but partly channelized Testeboån. This indicates that it is the
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channelization itself acting as the determining factor, forming the fish community structure in the investigated streams.
An unexpected outcome of the study was the low abundance as well as the low species richness in channelization category 1, in relation to channelization category 0. The areas with channelization degree 1 have high naturalness but is deeper than the null areas. This suggests that the bottom may be more distorted than been observed in the field. However the depth did not have a significant impact on the relative abundance, but channelization did. This indicates that even a low impact on the watercourse can have a large impact on the fish community. A possible reason for the low abundance of fish and also the low species richness, may be that areas with channelization degree 1 are sufficiently affected to put rheopholic species to disadvantage. However, they are not so affected that limnophilic or eurytopic species are significantly favored, thus leaving a gap with low abundance areas.
Studies on the effects of channelization on fish communities have reported a wide range of often conflicting results (Gidley 2012). Results from some studies indicate that channelization results in a lower relative abundance as well as a low species richness (Sullivan et al., 2004, Rhoads et al 2003), while other studies describe the opposite (Lyons et al 1996, Mundahl and Simom 1999). Reasons for the differing results among these studies are likely to be different sampling scales, different sampling methods and sampling in different aquatic environments.
The outcome of this study, rests on and is influenced by the characteristics of the new sampling method. The new method made it possible to sample also difficult areas not normally investigated. These areas differ from those sampled with conventional methods in respect to depth, bottom substrate and stream velocity. Thus, the new approach contributes to a greater knowledge of fish communities in running water.
The new sampling method proved to be easy to use and gives just as ordinary multi-mesh survey nets a picture of the fish community, in terms of length, distribution,relative density and species diversity. The nets do not require a specific depth and can be set from about 0.5 meters and deeper, making studies of whole streams possible. No comparisons with other sampling methods were made in this study, however earlier studies has shown that there is no difference in fishing capacity between the NSSN and fyke nets (Johansson 2011). There has also been limited comparisons between NSSN and electrofishing boat showing a dominant catch of perch and roach in the survey nets while more pelagic species such as bleak dominated when electro fishing (Johansson et al 2012).
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6 Conclusions
Channelization is one of the primary factors affecting the abundance and species richness in the studied streams
Increased channelization severeness results in a shift in species composition, causing changes in the stream ecosystem.
A limited impact on the watercourse can have a large impact on the fish community in terms of both relative abundance and species richness.
Nordic multi-mesh Stream Survey Nets proved to be relatively easy to operate and were found well suitable for these kinds of investigations.
They will make possible studies that will yield new knowledge of fish communities in running waters
7 Acknowledgement
First I would like to thank my supervisor Arne Fjälling at the Swedish
University of Agriculture for his valuable support and contribution. Further I would like to thank Erik Degerman at the Swedish University of agriculture. I would also like to send a special thanks to Lars Westerberg at IFM Biology for great help at the closing stages of the project. Big thanks go to the Fisheries Director Karl Gullberg at the County Administrative Board Gävleborg for coordination of state, material, shelter etc. Thanks also to field staff Peter Olsson, Marcus Lindgren, Daniel Källman and Elin Svensson who made the fieldwork with The Nordic Multi-mesh Stream Survey Net possible.
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