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Ecological Engineering 37 (2011) 796–805

Contents lists available at ScienceDirect

Ecological Engineering

journa l homepage: www.e lsev ier .com/ locate /eco leng

acrozoobenthos patterns along environmental gradientsnd hydrological connectivity of oxbow lakes

rystian Obolewskiepartment of Aquatic Ecology, Pomeranian University, 76-200 Slupsk, Poland

r t i c l e i n f o

rticle history:eceived 15 December 2009eceived in revised form 28 June 2010ccepted 29 June 2010vailable online 19 August 2010

eywords:acroinvertebratesetland

łupia Riverariance partitioning

a b s t r a c t

Hydrological connectivity and the frequency and intensity of floods are the key factors determiningthe structure of macroinvertebrates inhabiting wetland ecosystems in river valleys. In 2007, water andmacroinvertebrate samples were collected on four occasions in the middle course of the Słupia River andin five oxbow lakes (Northern Poland) to determine the hydrological relations in a regulated lowlandriver environment marked by a moderate climate. The water bodies selected for the study featured dif-ferent types of connections with the main river valley: two of them were completely cut off from thevalley, one was connected via a single branch, one featured a forced-flow connection through drainagepipes, and one was connected by a system of drainage channels. Macroinvertebrates, mostly Chirono-midae larvae, were predominant in the eutrophic waters of the river. The prevalent macroinvertebratesfound in the eutrophicated oxbow lakes isolated from the river were Chironomidae larvae and Crustacea(mainly Asellus aquaticus). In unobstructed oxbow lakes, the main component of benthic fauna was Crus-tacea, while Ephemeroptera were found mostly in the water body connected to the river via a drainagechannel. A canonical correspondence analysis (CCA) showed that hydrological connectivity was the mainfactor responsible for the structure of invertebrate populations, followed by the physical and chemical

parameters of the local environment. A non-conformance analysis revealed that hydrological connectiv-ity enhanced invertebrate abundance and biological diversity, while the overall abundance was markedby unimodal distribution. The developed general model indicates that in the group of measured environ-mental variables, nitrite concentrations were highly correlated with Shannon diversity and invertebratecomposition, while sulphate levels were closely associated with invertebrate abundance in the waters ofthe analyzed ecosystems.

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. Introduction

The structure and functioning of wetland ecosystems in riveralleys, including oxbow lakes, are directly and indirectly respon-ible for the distribution of water table fluctuations throughout theear (Junk, 1989; Tockner et al., 2000). Hydrological connectivityombines complex processes observed in the river and the sur-ounding wetlands, including changes in the transport of dissolvednd suspended elements and organisms, environmental reorgani-ation as well as the productivity and biodiversity of aqueous andand fauna groups (Amoros and Roux, 1988; Junk, 1989; Heiler et al.,995; Ward and Stanford, 1995; Tockner et al., 1999, 2000; Ward

t al., 2002).

The river and the adjacent wetlands form a cohesive (inter-onnected) hydrological system which is disrupted by regulatory

E-mail address: obolewsk@apsl.edu.pl.

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925-8574/$ – see front matter © 2010 Elsevier B.V. All rights reserved.oi:10.1016/j.ecoleng.2010.06.037

© 2010 Elsevier B.V. All rights reserved.

nd land improvement works. To restore the system’s connectiv-ty, wetlands have to be included in the river’s ecosystem throughevitalization measures that involve the re-opening of oxbow lakesn part or in whole. The hydrological connectivity of the river val-ey protects wetlands against natural succession. The absence ofydrological connectivity supports the growth of vegetation whichcts as a biological filter, turning oxbow lakes into natural wastereatment plants and sedimentation tanks.

Several factors affect the structure of wetlands and they cane applied to classify those areas as a cohesive (interconnected)ydrological system. Those factors are responsible for fluctua-ions in river water levels and affect the hydrological connectivityf wetlands. They are: the distance between the river and theetland, causes of a flood, the absence of natural and artificial bar-

iers obstructing water flow, morphology of the river valley which

etermines the boundaries and the size of wetlands, and the con-ectivity between the river valley and the main channel (Amorosnd Bornette, 2002). A rising groundwater table also significantlyontributes to the preservation of water levels in wetlands. This

ngineering 37 (2011) 796–805 797

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K. Obolewski / Ecological E

rocess may be obstructed by impermeable geological substratand sediment accumulation. To reinstate the hydrological con-ectivity between wetlands and rivers, various eco-engineeringolutions can be deployed to connect selected wetlands to the rivered (Obolewski et al., 2009a,b). These measures create a variedosaic of aqueous and land ecosystems which are characterized

y different biotopes and which determine the level of biodiver-ity in the river-wetland system (Arscott et al., 2005; Lakly andcArthur, 2000; Marshall et al., 2006).A high diversity of habitats increases the biodiversity of aqueous

cosystems, it is an effective measure of environmental structuresnd their functioning in space and time, and it supports an evalu-tion of hydrological models (e.g. Boulton et al., 1992; Sheldon etl., 2002; Robinson et al., 2003, 2004; Arscott et al., 2005; Whilesnd Goldowitz, 2005; Gallardo et al., 2007; Reese and Batzer, 2007).wing to their short life cycle and high environmental adaptability

e.g. body shape, annual cycles, resistance and distribution), macro-oobenthos constitute highly valuable study material in the groupf freshwater organisms. Some macrozoobenthos species lead anpen lifestyle, and their presence is usually an indicator of a cleannvironment. For this reason, they are regarded as bioindicators ofnvironmental condition, and they are used to monitor the qual-ty of aqueous ecosystems in many countries (e.g. Bonn, 1988;bolewski et al., 2009a,b). Selected macrozoobenthos groups peri-dically reach optimal levels of abundance and diversity relative topatial and environmental variables, although the above is scantlyocumented in the available literature (e.g. Heino, 2000; Griffith etl., 2001; Arscott et al., 2005; Monaghan et al., 2005).

This study investigates the relationships between the physical,hemical and biological variables of wetlands marked by variedegrees of hydrological connectivity with the Słupia River (North-rn Poland). The analyzed wetlands have been selected based on aypothesis that the degree of connectivity between flowing (lotic)aters and the waters of oxbow lakes is reflected in the qualitative

nd quantitative relations of macrozoobenthos groups inhabitinghe studied wetlands. Various environmental variables affectinghe local invertebrate fauna have been identified to analyze theirmpact on changes in the examined ecological formation.

.1. Study area

The studied area covered a section of the middle course of thełupia River (RS) in Northern Poland (Fig. 1). The investigated regioneatures many wetlands, and it is one of the largest watercoursesn the slope of the East European Platform (Baltic Sea) in Polandith a direct outlet to the Baltic Sea (catchment area of 1620 km2,

ength of 138.6 km, average annual flow rate 15.5 m3/s, averageood rate > 22 m3/s between October and March) (Obolewski et al.,009a,b). Most wetlands are used for agricultural production, how-ver they cover only 5.6% of the studied area. A regulation projectas carried out in the Słupia River at the beginning of the 20th cen-

ury. River beds were cut off, producing nearly 50 cut-off meandersObolewski and Glinska-Lewczuk, 2006). The aim of the regulationroject was to make the river suitable for timber floating to the seaort in Ustka, to drain wetlands in the river valley and adapt themor farming purposes. Similar measures were carried out in the val-eys of most European rivers at the turn of the 19th and the 20thenturies. Experimental sites were set-up in five oxbow lakes and inhe main river bed (the Słupia River, Fig. 1). One monitoring site waset up on the Słupia River in the centre of the investigated area – theDolina Słupia” Landscape Park. High river stages (39.8 m3/s, 3-year

ycle, Fig. 2) were noted between 1 and 6 February 2007. The rise inhe wetland water table led to a complete flooding of oxbow lakesith river waters. Except for this single flood event, the river wasarked by average water levels throughout 2007 (average monthly

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ig. 1. Study site locations (five wetlands and the river channel) in the Middle Słupiaiver Floodplain, Poland.

ow rate = 17 m3/s; average monthly flow rate between 2004 and007 at the test site in Słupsk = 15.8 m3/s, Fig. 2). As a result ofn engineering project to connect the analyzed oxbow lakes withłupia’s River bed, the studied wetlands became part of a cohesiveinterconnected) hydrological system. The project supported a bio-ogical evaluation of the wetlands’ inclusion into a uniform floodlain.

The investigated wetlands are human-made reservoirs; two ofhem (OLS4 and OLS5) are situated in the city of Słupsk, whilehe remaining three are found 15 km up the river from Słupskn the vicinity of the large tributary – the Kwacza River. Oxbowakes OLS1 and OLS2 lack hydrological connections with the river,LS3 is connected via a single arm with the tributary of the Słupiaiver, Kwacza, OLS4 features an artificial hydrological connectionith the involvement of drainage pipes (inlet and outlet pipes),

nd OLS5 has been dredged and connected with Słupia via a sys-em of drainage channels with a length of 1000 m. The analyzedites were characterized by the most extensive reach of hydrolog-cal connections between the river valley and wetlands, extendingrom locations featuring a permanent connection between sur-ace waters (OLS4) and the main channel (RS), to sites that haveimited contact with the river (OLS5) and locations from whichroundwater is evacuated but which lack permanent hydrologicalonnections with the river (OLS2).

OLS1 and OLS2 are interconnected, forming a single hydrologi-al system. OLS2 has a gravel substrate which supports the passagef water from the river and water-bearing strata. The above leadso relatively high fluctuations in the water table, which are higher

798 K. Obolewski / Ecological Engineering 37 (2011) 796–805

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han could be implied by the oxbow lake’s connection with theiver. That is probably responsible for the low abundance of fish inhat system. Only single representatives of Esox lucius L., Tinca tinca. and Pungitius pungitius L. were observed there, while Carassiusarassius L. occurred relatively abundantly in OLS1. There was nosh fry. In case of OLS3, the ichthyofauna was represented by E.

ucius This species was also observed in OLS4 and OLS5, accompa-ied by Leuciscus cephalus L., Leuciscus leuciscus L., Rutilus rutilus L.nd Gobio gobio L.

Rush vegetation quickly colonized OLS4 and OLS5 (e.g. Typhaatifolia L., Phragmites australis Trin Ex, Stued., Glyceria max-ma (Hartm.) Holmb. and elodeid macrophytes Nuphar luteum L.,tratiotes aloides L.), while OLS1 and OLS2 are overgrown withleustonic flora (e.g. Lemna minor L., Lemna trisulca L., S. aloides).LS3, connected with the river by a single arm, was predominatedy submerged Elodea canadensis Michx., Equisetum palustre L. and. australis in the littoral zone (Obolewski et al., 2009a,b).

. Materials and methods

.1. Samples and indices used

In 2007, water and invertebrate samples were collected at 3-onth intervals (seasonally) from different locations at five test

ites. In five oxbow lakes, monitoring sites were set up at three

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able 1ateral hydrological connectivity definitions for oxbow lakes in the Middle Słupia River. The wetlands in summer. Age is the time since the cut off of oxbow lakes, or construction

Types Depth (m) Age (year) Area (m2) Value (m

RS – – 162 × 107 –

OLS1 1.32 93 6023 2901

1 OLS2 1.62 93 6183 3310

2 OLS3 1.22 93 2416 4749

3 OLS 4 1.82 78 2964 1960

4 OLS5 1.58 81 14763 8856

). Triangles indicate the average monthly flow between 2004 and 2007.

oints (in the upper and the lower arm and in the centre of theater body). This method was applied regardless of differences in

he surface area of the studied oxbow lakes.Dissolved oxygen (DO), temperature, nitrate, ammonium nitro-

en concentrations, total dissolved solids (TDS) and pH wereeasured in situ with the use a calibrated portable probe (YSI

600). 2.0 l water samples were collected at an approximate depthf 20 cm into polycarbonate bottles rinsed with acid. In the coursef 24 h, samples were filtered with the use of Whatman® glassbre filters and GF/F glass fibre filters (incubation at 450 ◦C forh) to determine the quantity of dissolved particles (APHA, 1989).he samples were analyzed by ion chromatography to identify theoncentrations of chemical oxygen demand (COD) and dissolvednions and cations (Cl−, SO4

2−, N-NO2, P-PO4, HCO3−, K+, Ca2+,

g2+ and Na+). A continuous flow analyzer was used to determinerganic phosphorus concentrations.

Invertebrates were sampled with the Eckmann dredge (areaf 225 cm2, 3 replications) in three zones in every wetland. Theampled locations differed with regard to sediment thickness andomposition which could have affected the results of the exper-ment. The samples were passed through a benthological sieve

300 �m), fixed in 5% formalin and stored in containers. The col-ected material was arranged in a laboratory, and the studiedrganisms were identified at genus level, except for Oligochaetaclass level) and Diptera (family level). The results of analyses of

ype corresponds to hydro-connectivity categories. Depth is at the deepest part of, depending on origin. Area was measured using summer aerial photographs.

3) Hydrological connectivity definition

The main river system connected to oxbow lakes. Sand and gravelsubstrateNo connection with the river. A thick sediment layer minimizeshydrological connectivity with groundwaters. A connection with OLS2is established during a high river stageDue to the absence of connection with the river as well as a gravelsubstrate, the flow is able to penetrate the groundwater table of theriver and the water-bearing strataConnected with the river by a single arm via the tributary of the SłupiaRiver – Kwacza River. A thick sediment layer restricts connectivitywith groundwater resourcesConnected with the river on both sides via PVC pipes that restrictwater exchange. A thick sediment layer restricts connectivity withgroundwater resourcesDredged oxbow lake connected with the river via a network ofdrainage channels. A thin sediment layer only minimally restrictsconnectivity with groundwater resources

K. Obolewski / Ecological Engineering 37 (2011) 796–805 799

Table 2Water quality of oxbow lakes and the Słupia River. Data are mean (s.d.) for every month samples in 2007. TDS = total dissolved solids, COD = chemical oxygen demand,DO = dissolved oxygen.

A-OLS1 (n = 4) B-OLS2 (n = 4) C-OLS3 (n = 4) D-OLS4 (n = 4) E-OLS5 (n = 4) F-RS (n = 4)

Temperature (◦C) 8.5 (3.5) 8.7 (3.1) 8.3 (3.8) 16.4 (7.3) 17.2 (5.5) 8.8 (5.7)pH 7.2 (0.4) 7.3 (0.4) 7.2 (0.6) 8.0 (0.4) 7.8 (0.1) 7.2 (0.2)TH 6.5–8.5DO (mg/l)* 4.1F (1.45) 4.0F (0.99) 6.3 (1.45) 5.8 (0.82) 5.5 (1.71) 8.0A,B (0.55)TH* 0–5.0COD (mg/l) 13.6 (2.8) 13.6 (2.4) 15.8 (3.1) 15.6 (6.3) 14.0 (4.5) 14.2 (2.3)TDS (mg/l) 204 (8.1) 225 (13.4) 213 (32.3) 213 (26.5) 219 (25.4) 275 (12.0)Cl− (mg/l)* 21.8 (4.1) 26.3D (8.1) 17.3 (8.5) 14.8 D,E (5.9) 32.3D (4.9) 18.0 (20.1)TH 2–60SO4

2− (mg/l) 56.6 (31.5) 46.3 (28.2) 71.9 (21.3) 97.3 (48.2) 56.9 (119.9) 33.3 (29.9)TH 5–60HCO3

− (mg/l) 116.5 (7.1) 125.5 (7.1) 117.2 (19.7) 128.6 (15.3) 148.5 (4.3) 124.0 (35.0)TH 60–360N-NO3 (mg/l)* 0.112 (0.034) 0.237E (0.091) 0.145 (0.042) 0.257E (0.253) 0.105B,D,F (0.114) 0.255E (0.198)TH 0–5.0N-NO2 (mg/l)* 0.006F (0.002) 0.007F (0.004) 0.011E (0.007) 0.006F (0.005) 0.005C,F (0.002) 0.014A,B,D,E (0.001)TH 0–0.03N-NH4 (mg/l)* 0.200 (0.301) 0.238E (0.104) 0.145F (0.266) 0.257E (0.058) 0.125B,D,F (0.114) 0.255C,E (0.378)TH 0–1.0P-PO4 (mg/l)* 0.316E (0.069) 0.266 (0.035) 0.202 (0.063) 0.178A,F (0.042) 0.156F (0.167) 0.358E (0.039)TH 0.01–1.0T-P (mg/l)* 1.523C (0.388) 1.151 (0.345) 0.965A,F (0.167) 1.134 (0.200) 1.036 (0.309) 1.581C (0.508)K+ (mg/l) 2.0 (0.26) 2.1 (0.50) 1.9 (0.30) 2.1 (0.37) 2.9 (0.08) 1.9 (0.97)TH 0.5–10Na+ (mg/l) 16.3 (4.9) 14.8 (1.7) 11.5 (6.3) 9.4 (3.8) 24.9 (2.2) 12.4 (14.7)TH 1–60Ca2+ (mg/l) 46.0 (4.9) 45.9 (1.5) 41.5 (3.7) 47.0 (6.1) 58.8 (6.5) 53.9 (10.4)TH 2–200Mg2+ (mg/l) 6.3 (1.6) 5.4 (2.9) 7.6 (1.7) 5.7 (2.4) 5.2 (2.9) 5.7 (0.3)TH 0.5–30.0

A–F: significant differences (non-parametric Dunns test, p ≤ 0.05) among wetlands, TH – hydrogeochemical background (range of typical concentration, Witczak andA* nds.

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damczyk, 1995), bold variables were used in ordination analysis.Significant differences (non-parametric Kruskal–Wallis test, p ≤ 0.05) among wetla

nvertebrates collected from different parts of the studied areasere summed up.

The quantitative and ecological variables of invertebrate groupsere determined with the use of zoocenotic indicators, including

he Shannon index of diversity (natural logarithm), evenness, genusbundance and total abundance.

.2. Hydrological classification

Several factors affecting the structure of the studied wetlandsere applied to classify those areas as a cohesive (interconnected)ydrological system. River regulation and limited fluctuation inater levels had an adverse effect on all tested sites, in partic-lar wetlands situated further away from the river bed whichecame connected to the river only during periodically hightages. In consequence, the existing hydrological connections wereess frequently reinstated, and in recent years, the time inter-al between reinstatement events was extended from 1 to 4ears.

During the analysis of hydrological connectivity’s influence onacrozoobenthos composition, the studied wetlands were clas-

ified into four categories (Types 1, 2, 3 and 4) in view of theironnection with the river (Table 1). The test site in the river (RS) andxbow lakes in the river’s flood terrace (OLS) were disconnectedrom the river or connected into a single hydrological system tovaried degree (connected on both sides, connected via one arm,

onnected by drainage channels or flood pulsing). For this reason,ydrological connectivity was not regarded as a continuous vari-ble but as typology which reflected the changes taking place inhe entire flood plain of the river valley.

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.3. Statistical analyses

To reduce the effect of absolute values, the abundances of thenvertebrate densities were square-root transformed (

√X + 1), rare

pecies were downweighted and environmental data were log-ransformed (log10(X + l)) (ter Braak and Smilauer, 2002). Due toon-normality, in order to assess the general differences amongetlands, invertebrate data (grouped into classes/orders) andydro-chemical data were subjected to non-parametric analysisf variance. Kruskal–Wallis test (p < 0.05) showed the presencef significant differences between wetlands while the Dunns testp < 0.05) indicated exactly between which wetlands they occurred.o further identify patterns in the abundance of 60 invertebrateenera, indirect ordination methods, such as detrended correspon-ence analysis (DCA) (ter Braak and Smilauer, 2002) were used.he length of the first DCA axis > 4 (unimodal responses) indicatedanonical correspondence analysis (CCA; ter Braak and Smilauer,002) to be the proper one in order to investigate relationshipsetween benthic invertebrates and environmental parameters.

Therefore, to identify the primary environmental gradientsffecting macroinvertebrate assemblages, CCA was used between7 environmental variables and 13 groups of macroinvertebrateselonging to genus: Oligochaeta, Asellidea, Gammaridea, Glossi-honiidae, Erpobdellidae, Pisicolidae, Helobdeliidae, Limnephilidae,eshnidae, Libelluidae, Corduliidae, Chironomidae, Ceratopogonidae,sychomyidae, Corixidae, Tabanidae, Baetidae, Ephemeridae, Siali-ae, Lestidae, Tychopteridae, Notonectidae, Dytiscidae, Sphaeriidae,

iviparidae. Hydrological connectivity was introduced as fourummy variables (Types 1, 2, 3 and 4) along with the rest ofhe physical and chemical variables. Because environmental gra-ients had not previously been evaluated in the study area, we ran

800 K. Obolewski / Ecological Engineering 37 (2011) 796–805

Table 3Invertebrates of oxbow lakes and the Słupia River. Data are mean (s.d.) for every month samples in 2007. H′ – Shannon index, J′ – evenness.

A-OLS1 (n = 4) B-OLS2 (n = 4) C-OLS3 (n = 4) D-OLS4 (n = 4) E-OLS5 (n = 4) F-RS (n = 4)

No. of taxa 18 17 23 19 23 17Total abundance 2896.3 1410.1 1938.6 2004.6 3789.5 384.3H′ 0.354 0.377 0.488 0.923 0.466 0.715J′ 0.553 0.459 0.606 0.492 0.511 0.720Dominant taxa Diptera Crustacea Crustacea Crustacea Ephemeroptera Diptera

(D = 56%) (D = 30%) (D = 37%) (D = 47%) (D = 44%) (D = 47%)Oligochaeta* 71.6C,E (98.0) 256.4 (407.3) 503.7A,F (707.4) 155.6 (73.3) 511.1A,F (1120.4) 102.8C,E (127.5)Hirudinea* 80.9 (31.9) 55.6 (18.4) 163.2F (107.6) 20.7E (8.1) 434.0A,B,D,F (511.9) 11.0 (0.0)Crustacea* 804.2F (774.6) 421.2F (653.6) 718.5F (768.3) 935.2F (994.6) 434.1F (559.7) 49.8 (51.7)A,B,C,D,E

Odonata* 39.5B,C,F (11.8) 0.0A,D,E 0.0A,D,E 14.8B,C,E,F (0.0) 1669.1A,B,C,D,F (1984.9) 0.0A,D,E

Ephemeroptera 90.4F (116.1) 113.6F (52.0) 22.2F (9.2) 44.4F (6.7) 59.3F (26.8) 0.0A,B,C,D,E

Plecoptera 0.0F 0.0F 0.0F 0.0F 0.0F 13.8A,B,C,D,E (27.5)Megaloptera* 5.9B,C,F (0.0) 59.8A,F (53.4) 74.1A,F (25.3) 44.4A,F (24.2) 14.8F (0.0) 0.0A,B,C,D,E

Trichoptera 37.0 (35.3) 29.6 (0.0) 93.8 (136.2) 72.6 (22.6) 55.6 (26.8) 2.8 (5.5)Diptera* 1609.9F (1238.9) 314.6 (402.1) 249.6 (192.9) 616.3 (210.9) 241.5 (64.4) 180.5A (118.8)Coleoptera 44.4D,F (12.8) 29.6D,F (5.8) 29.6D,F (13.2) 0.0A,B,C,E 44.4D,F (9.2) 0.0A,B,C,E

Hemiptera 22.2F (10.5) 14.8F (0.0) 7.4F (0.0) 14.8F (0.0) 44.4F (17.3) 0.0A,B,C,D,E

Gastropoda 22.2C,D,F (10.5) 59.3C,D,F (0.0) 0.0A,B,F 0.0A,B,F 14.8C,D,F (0.0) 0.0A,B,C,D,E

Bivalvia 68.1 (47.5) 55.6 (50.4) 29.6 (35.3) 71.1 (38.3) 29.6 (21.0) 23.6 (13.7)

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manual, forward-selection CANOCO procedure, which includedariables that had a conditional effect significant at the 10% levelp < 0.1). p-Values were calculated using the Monte Carlo Per-

utation Test (ter Braak and Smilauer, 2002). Once the mainnvironmental gradients impacting aquatic community structureere identified, the model was subjected to variation partitioning

n order to quantify the amount of variation uniquely explainedy each set of variables in the model (physicochemical – DO, Cl;rophic – N-NO3, N-NO2, N-NH4, P-PO4, T-P; hydrological – hydro-ogical connectivity), the shared variance among them and theariance that remained unexplained.

Linear regression was used to test the relationships between thenvertebrate community (measured by invertebrate abundance,nvertebrate richness and Shannon diversity) and key environmen-al variables.

. Results

.1. Environmental conditions

The average values of the studied physical and chemical vari-bles and significant differences in hydrological connectivity in007 are shown in Table 2. Wetlands differed mostly with regard tohe concentrations of inorganic substances (N-NH4, N-NO3, N-NO2,-PO4, Cl−, DO, T-P). River water was characterized by significantlyigher TDS, similarly to OLS2, and higher concentration of P-PO4

ust like it was observed in OLS1 and OLS2. Despite the above, riverater was generally marked by lower inorganic substance con-

entrations than those noted in wetlands. Phosphorus compoundP-PO4 and T-P) concentrations were significantly higher in OLS1nd OLS2 than in the remaining lenitic ecosystems. The most sig-ificant differences (the lowest p-levels) as regards organic and

norganic compound concentrations were noted in OLS5.

.2. Patterns of macroinvertebrate abundance

The differences in the annual abundance and structure ofacrozoobenthos observed between the identified hydrological

onnectivity groups are presented in Table 3. A total of 12,125acrozoobenthos representatives belonging to 26 genera and 11

lasses were identified. Crustacea and Diptera were the mostbundant invertebrate classes (each with the share of 28–29%).

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he studied wetlands differed mostly with regard to the abun-ance of water worms, insects and crustaceans (Fig. 3A). In thełupia River, macrozoobenthos were most abundantly representedy Diptera (e.g. Chironomus, Procladius), although large popula-ions of oligochaetes (Tubificidae) were also found, contributingo the reported density values. Oxbow lakes which rarely formedydrological systems with the river, i.e. OLS1 and OLS2, were

nhabited mainly by Insecta, including the families Diptera (e.g. Chi-onomus, Procladius, Bezzia), Crustacea (e.g. Asellus aquaticus) andligochaeta (e.g. Tubificidae). Owing to more frequent connectivityith the river, OLS3 was marked by higher Shannon diversity. Itsacrozoobenthic fauna was dominated by crustaceans (A. aquati-

us and Gammarus), but the presence of Ephemeroptera (Cloëon,phemera), which occur in clear water habitats, was also deter-ined. Large populations of Crustacea (mainly A. aquaticus) and

hironomidae larvae were observed in the oxbow lake perma-ently connected to the river. The wetlands fed via a systemf drainage channels were inhabited mainly by EphemeropteraCloëon), Oligochaeta, Hirudinea and Crustacea. In comparison withhe remaining test sites, statistically higher benthic fauna densitiesere noted in the above oxbow lake (Fig. 3B).

Differences in the macrozoobenthic composition of the stud-ed sites have been presented in the CCA model, with the first andhe second axis explaining 35% and 21% of variance, respectivelyFig. 4). Macrozoobenthos groups encountered in each wetlandype were similar to the fauna groups determined by a non-arametric analysis of variance (Fig. 4B). The analysis revealedelatively minor differences in the macrozoobenthic compositionf the examined oxbow lakes, even across wetlands that differedignificantly with regard to their habitat conditions (concentrationsf organic and inorganic elements) and hydrological connectivityith the river bed (Fig. 4A). Abundance and seasonal distribution

aried throughout the period of the experiment, and the obtainedesults indicate that most of benthofauna representatives were notbserved in the winter (Fig. 4C).

From the group of 17 environmental variables that underwentpreliminary analysis with the use of the CCA model, 13 were

elected as factors that exert a significant effect on model qual-+

ty (Table 2). The remaining 4 variables (temperature, pH, K and

a2+) were redundant or minimally improved the quality of theesulting model. The final model was capable of explaining 56%f observed variability in invertebrate structure, and all canonical

K. Obolewski / Ecological Engineering 37 (2011) 796–805 801

F five flw

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ig. 3. Percentage structure (A) and abundance (B) of main invertebrate groups inetlands are significant (Kruskal–Wallis test, p < 0.001).

xes were statistically significant (Monte Carlo test, p = 0.002). Therst factor produced a gradient from high dissolved oxygen to highl− concentration at the studied sites. The second factor was con-ected with the processes of total decomposition of organic matter

(hvo

ig. 4. Results of canonical correspondence analysis performed with invertebrate andariables (p < 0.1). (A) Triplot of significant environmental variables, invertebrates and sample scores; (C) biplot showing significant invertebrate data and seasons.

oodplain wetlands and the Słupia River. Differences in total abundance between

P-PO4, N-NO3) (Fig. 4A). Variance partitioning showed that theydrological set of variables (containing Types 1, 3 and 4 dummyariables describing the hydrological connectivity) explained 28%f the changes in benthic fauna structure. The analyzed physi-

environmental data from the Słupia River Floodplain using forward selection ofample scores of axis 1 and 2; (B) biplot showing significant invertebrate data and

802 K. Obolewski / Ecological Engineering 37 (2011) 796–805

Fig. 5. Box-plots of macroinvertebrate metrics across types of connectivity. (A) Invertebrate Shannon diversity; (C) invertebrate richness (number of genera); (E) invertebratet etrics − 2−

S f genet

cfNt

otal abundance. Linear regression models performed between macroinvertebrate mhannon diversity scores; (D) correlation on invertebrate richness scores (number ohe 95% confidence interval for the model.

al variables and changes in the concentration of Cl− accountedor 10% of macrozoobenthos variability. Trophic variables (N-NO2,-NH4, P-PO4, T-P.) provided an explanation for 5% cases. Varia-

ion uniquely explained by each set of variables amounted 15% of

cup(

as response variable and NO2 or SO4 as explanatory variable. (B) Correlation onra); (F) correlation on total invertebrate abundance scores. Dashed lines represent

hanges in the benthic fauna structure, while 31% cases remainednexplained. As regards the distribution of benthofauna in CCAlot, invertebrate structure in OLS differed from the one in RSFig. 4A). No obvious differences were found between oxbow lakes

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K. Obolewski / Ecological E

espite the varied degree and duration of hydrological connectivityith the river bed (36 days for OLS1 and OLS2, 365 days for OLS3,LS4 and OLS5). An analysis of the distribution of factors 1 and 2

howed that OLS5 partly differed from the remaining oxbow lakess regards its concentrations of Cl− ions which were most probablyupplied from the adjacent afforested areas via drainage ditchesFig. 4A). As demonstrated by previous analyses, Insecta, Crus-acea and Oligochaeta showed the highest level of discriminationetween OLS and RS. According to the Kruskal–Wallis and linearegression models, an increase in hydrological connectivity wasollowed by an increase in the diversity, the number of observedaxa and the abundance of invertebrates (Fig. 5). According to thehannon index, hydrological types were generally marked by lin-ar distribution; however, the Shannon values were higher in theiver than in oxbow lakes (Fig. 5A). Concentrations were stronglyorrelated with Shannon diversity. Significant correlations werelso determined between NO2

− concentrations, invertebrate rich-ess and invertebrate abundance (Fig. 5B and D). The highestegative correlation was noted between sulphate concentrationsnd macroinvertebrate abundance (r = −0.71 at p = 0.05) (Fig. 5F).elationships between Shannon diversity, invertebrate richnessnd NO2

− concentrations were proportional and at a similarevel.

. Discussion

This article presents the structure of aquatic invertebratesnhabiting wetlands, mostly worms, insects and crustaceans whichresence is also determined in other European rivers (Gallardo etl., 2008; Whiles and Goldowitz, 2005).

Hydrological connectivity with the river was initially believedo be the main determinant of differences in the composition andbundance of invertebrate fauna. In view of the above, four wet-and types (OLS categories 1, 2, 3 and 4) were identified, but theifferences between oxbow lakes were not pronounced enough toenerate significant deviations. The differences in the hydrologicalonnectivity of oxbow lakes could not have been fully evaluatedased on macrozoobenthos populations because their diversitynd abundance are also determined by biological factors, such ashe food chain (Heino, 2000; Griffith et al., 2001; Gallardo et al.,008). The structure of benthofauna was influenced by fish, repre-ented in the studied oxbows by benthivorous species. The adversenfluence of flood pulsing in wetland ecosystems has been investi-ated by various authors (e.g. Boulton et al., 1992; Sheldon et al.,002; Robinson et al., 2003, 2004; Arscott et al., 2005; Whiles andoldowitz, 2005; Gallardo et al., 2007; Reese and Batzer, 2007).his study identifies several new variables determining changes inetlands, including the hydrological connectivity of the area, theresence of natural or artificial flow barriers, morphological prop-rties, the type of geological substrate and deposit accumulation.he studied oxbow lakes were characterized by the establishmentf relatively infrequent hydrological connections with the rivered which supported the accumulation of biogenic elements anduccession. For benthic invertebrates the hydrological connectivityith the river bed seems to be the most important factor, which

llows their existence but not only through water exchange. Itlso enables their unlimited migration. The main discovery washe development of hydrological typology explaining a given levelf variation uniquely explained by each set of variables, even afterther variables have been eliminated. In this and other studies, gen-

ral inconsistencies have been attributed to environmental factorsuch as the quantity and quality of food as well as temperatureHeino, 2000; Zimmer et al., 2000; Griffith et al., 2001; Monaghan etl., 2005; Murphy and Davy-Bowker, 2005). Although the weight of

ttoT

ering 37 (2011) 796–805 803

hose factors could be somewhat attributed to similar temperaturesnd nutritional quantity, it should nevertheless make a referenceo hydrological connectivity. To illustrate, colder river water whichontains higher nutrient quantities affects wetlands via both sur-ace and groundwater. The Słupia River was the main source ofollutants dissolved in water (N-NO2, P-PO4, T-P) as well as water-orne leaves, sediments, precipitation water and drainage water

eaked from farmland which affected the quality of the studiedetlands’ ecosystem. Low levels of inorganic nitrogen were alsooted in OLS5 due to dredging. I think that hydrological connec-ivity could have a greater effect on macrozoobenthos counts thanuggested by statistical analyses carried out in this and other stud-es (Gallardo et al., 2008). The above is largely due to additionalorrelations with other environmental variables (Zimmer et al.,000). When environmental variables that are potentially corre-

ated with hydrological connectivity are additionally analyzed inhe presented model, the significance of hydrological connectiv-ty is minimized, which has been also confirmed by other studiesPeres-Neto et al., 2006). Therefore, I conclude that aquatic faunaroups and their environment form a cohesive (interconnected)ystem affected by environmental factors which are responsibleor the complex correlations between the system’s constituent ele-

ents (Legendre and Troussellier, 1988).The analyzed environmental factors and the attributes of

acrozoobenthos groups did not statistically differ across thenvestigated hydrological types of wetlands (p > 0.05, Fig. 5). Shan-on diversity was slightly higher in areas marked by greaterydrological connectivity, while invertebrate abundance producedrather unimodal response. A different situation was noted in a

tudy of the Ebro River (Spain) where the abundance of inver-ebrate species increased with hydrological connectivity, whileiodiversity was marked by unimodal distribution (Gallardo et al.,008). The works of other authors suggest a positive correlationetween invertebrate abundance and hydrological connectivity,nd maximum values were noted in indirectly connected waterodies (Ward, 1998; Ward et al., 2002; Amoros and Bornette, 2002;hiles and Goldowitz, 2005). Most of the cited authors share

he opinion that the described type of hydrological connectivityroduces antagonistic effects in the water body, and hydrologicalonnections improve environmental conditions (Glinska-Lewczuk,009). That supports the evolution of habitats suitable for a broadpectrum of hydrobionts. The results of this study validate thebove observations – invertebrate abundance and Shannon diver-ity were high in the oxbow lake connected to the river via a singlehannel (OLS3).

Various authors have demonstrated that environmental andydrological factors directly or indirectly influence hydrobiontopulations (Blumenshine et al., 1997; Tockner et al., 1999;

eppesen et al., 2003; Wang et al., 2007). In this study less sensitiveaxa were influenced by the concentration of nutrients while theresence of more sensitive taxa (e.g. Gammarus) correlated withater oxygenation (Henry and Danielopol, 1999) (Fig. 4). In cut-off

xbow lakes the structure of invertebrates indicated the domi-ation of individuals resistant to bad ecological conditions (e.g.rocladius, Segentia, Viviparus, other Chironomidae, Oligochaeta,lossiphonia) while the partly open lakes were predominated byctively migrating species (e.g. A. aquaticus, Libellula, Atracides,piteca). In turn, various taxa were the most abundant in openxbow lakes (e.g. Lestes, Psychomyidae).

Floodplains may be supplied with nutritional substances fromeveral natural and artificial sources, including external (migra-

ory) and internal (productive) sources. High concentrations ofhose substances are noted mostly in periods marked by an absencef hydrological connectivity and during intense floods (Junk, 1989;ockner et al., 1999). The absence of flood pulsing speeds up sedi-

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04 K. Obolewski / Ecological E

entation rates and the eutrophication of wetlands. The cohesionevel of wetlands also influenced the concentration of metals inottom sediments (Cd, Cr, Cu, Ni, Mn, Pb, Zn, As). OLS3 was con-ected with the river by a single arm and its bottom sedimentsontained the lowest levels of Co, Pb and Cu, opposite to OLS1nd OLS2. At the same time, high contents of Zn (98–150 mg/kg)ere observed in OLS3. In OLS4, connected with the river on both

ides, bottom sediments contained considerable amounts of Pb88.6 mg/kg). Only in OLS5 were the concentrations of trace metalsow. In turn, bottom sediments in the Slupia River were charac-erized by higher contents of the studied metals, particularly ofr, and the levels of content were similar to the ones observed inetlands hydrologically connected with the main river (Obolewski

nd Glinska-Lewczuk, 2006). The fertility of wetlands is addition-lly enhanced by human activity, such as agricultural productionnd urbanization. The fertility of water bodies, mainly nitrite con-entration, directly affects abundance and Shannon diversity, whileulphates contribute mostly to macrozoobenthos counts (Fig. 5).itrites are one of the most important forms of dissolved nitrogen

n river waters, and they are a reliable measure of water qual-ty and ecosystem integrity (Smith et al., 2007). As nitrites are aransitory form in nitrogen transformations, their correlation withhe Shannon diversity and abundance of invertebrate fauna testi-es to the high dynamics of changes in wetlands. High content ofitrite nitrogen is toxic to fauna, particularly to juvenile or sensi-ive individuals (Obolewski et al., 2009a). However, it also increaseshe Shannon’s diversity index, which takes into account both theumber of species and the evenness of the species (Głowacki,009). Reservoirs characterized by worse ecological conditionsre predominated by little specialized species that can reach highbundances (e.g. Obolewski et al., 2010; Blumenshine et al., 1997).he system of oxbow lakes analyzed in this study was also pre-ominated by taxa of low or moderate habitat requirements. Theighest share in benthofauna abundance mostly had Oligochaeta,rustacea (A. aquaticus) and Diptera larvae, e.g. Chironomidae. OnlyLS5 was predominated by Odonata, probably because of the highbundance of invertebrate fauna, which Odonata feed on. Nitriteevels may also be monitored to investigate the level of ecosystemntegrity in those areas. Sulphates may be assimilated by vascularlants which are a source of nutrition for a large group of ben-hic fauna species (Obolewski et al., 2010). When oxygen reservesecome depleted, in particular in wetlands marked by a low level ofydrological connectivity with the river, sulphates are transformed

nto hydrogen sulphide, a toxic substance for hydrobionts. Otheractors which could explain the reported inconsistencies include

orphometry (Heino, 2000; Jeppesen et al., 2003), the presencef macrophytes (Carpenter and Lodge, 1986; Wissmar, 1991), lit-oral vegetation, substrate structure and composition (Griffith etl., 2001; Murphy and Davy-Bowker, 2005), trophic interactionsBlumenshine et al., 1997; Jeppesen et al., 2003) and pollutionPetridis, 1993; Woodcock and Huryn, 2007).

Two oxbow lakes were permanently connected with the river’sydrological system to minimize environmental losses caused byhe excessive growth of littoral vegetation in oxbow lakes which areot supplied with fresh water from the river during flood pulsing.ater inflows wash out bottom deposits, lower salt concentrations,

upport the revitalization of aqueous vegetation and stabilize lakesObolewski et al., 2009a,b). Biogenes concentrations were high inut-off lakes due to an abundance of vegetation, biofilm and thickediment layers. Decomposition rates exceeded production, andhe above additionally contributed to eutrophication (Bachand and

ome, 2000; Saunders and Kalff, 2001). The man-engineered envi-

onment of oxbow lakes, created with the involvement of dredgingnd re-opening measures, differed from the existing habitat, and itas rapidly colonized by macroinvertebrates that were not previ-

G

ering 37 (2011) 796–805

usly observed (e.g. Gammarus, Ephemera, Cloëon). The emergencef new taxa, in particular bioindicators of water quality, points ton improvement in Shannon diversity not only during the floodeason (Obolewski et al., 2009b).

. Conclusions

The ecosystem of the Słupia River resembles that of regu-ated lowland rivers in Central Europe which are characterized byighly irregular flows due to spatial and temporal variation. Theutrophication of Central European rivers results mostly from reg-lation measures, pollution and changes in the type of valley usehich limits flooding, minimizes water flow, increases gradients

nd restricts the self-purification of waters inhabited by macroin-ertebrates. The presented results only partly confirm that theydrological connectivity of a river and the surrounding wetlandsignificantly affects the composition of macrozoobenthos popu-ations. Restricted hydrological connectivity and the presence ofydroengineering structures in river valleys with a moderate gradi-nt leads to permanent hydrological changes that could contributeo the loss of valuable habitats, including oxbow lakes (Heiler etl., 1995; Ward et al., 2002). In consequence of these adverse phe-omena, the local flora and fauna becomes widely distributed only

n periods of water exchange between wetlands and the river bed,nd the above has a negative impact on biodiversity and the river’scosystem (Amoros and Roux, 1988; Heiler et al., 1995). At the sameime the hydrological connectivity enables penetration by benthiv-rous fish, which according to this study may have a strong effectn benthofauna, even more than nutrient’s concentrations or othernvironmental parameters. The efforts to reinstate hydrologicalonnectivity in river valleys protect the ecosystem against suddenvents in the main river bed. Following strong floods, the rein-tatement of the ecosystem’s biodiversity begins in the floodplainsdjacent to the river bed. Owing to a vastly diversified habitat,he local fauna populations are able to survive periods of intenseutwashing and re-colonize the river ecosystem (Obolewski andlinska-Lewczuk, 2006).

cknowledgement

This study was supported financially by the Polish Ministry ofducation and Science No. NN305 324733.

eferences

moros, C., Bornette, G., 2002. Connectivity and biocomplexity in waterbodies ofriverine floodplains. Freshwater Biol. 47, 761–776.

moros, C., Roux, A.L., 1988. Interaction between water bodies within the flood-plain of large rivers: function and development of connectivity. MiinsterscheGeograph. Arb. 29, 125–130.

PHA, 1989. Standard Methods for the Examination of Water and Wastewater, 17thed. American Public Health Association (APHA), Washington, DC, USA.

rscott, D.B., Tockner, K., Ward, J.V., 2005. Lateral organization of aquatic inverte-brates along the corridor of a braided floodplain river. J. N. Am. Benthol. Soc. 24,934–954.

achand, P.A.M., Home, A.J., 2000. Denitrification in constructed free-water surfacewetlands. II. Effects of vegetation and temperature. Ecol. Eng. 14, 17–32.

lumenshine, S.C., Vadeboncoeur, Y., Lodge, D.M., Cotting-ham, K.L., Knight, S.E.,1997. Benthic–pelagic links: responses of benthos to water-column nutrientenrichment. J. N. Am. Benthol. Soc. 16, 466–479.

onn, P.J., 1988. The impact of river regulation on invertebrate communities in theU.K. Regul. Rivers 2, 389–409.

oulton, A.J., Peterson, C.G., Grimm, N.B., Fisher, S.G., 1992. Stability of an aquaticmacroinvertebrate community in a multiyear hydrologic disturbance regime.Ecology 73, 2192–2207.

arpenter, S.R., Lodge, D.M., 1986. Effects of submerged macrophytes on ecosystem

processes. Aquat. Bot. 26, 341–370.

allardo, B., Garcia, M., Cabezas, A., Gonzalez, E., Ciancarelli, C., Gonzalez, M., Comin,F.A., 2007. First approach to understanding riparian wetlands in the Middle EbroRiver floodplain (NE, Spain): structural characteristics and functional dynamics.Limnetica 26, 373–386.

ngine

G

G

G

G

H

H

H

J

J

L

L

M

M

M

O

O

O

O

P

P

R

R

R

S

S

S

t

T

T

W

W

W

W

W

W

W

K. Obolewski / Ecological E

allardo, B., Garcia, M., Cabezas, A., Gonzalez, E., Gonzalez, M., Ciancarelli, C.,Comin, F.A., 2008. Macroinvertebrate patterns along environmental gradientsand hydrological connectivity within a regulated river-floodplain. Aquat. Sci.70, 248–258.

linska-Lewczuk, K., 2009. Water quality dynamics of oxbow lakes in young glaciallandscape of NE Poland in relation to their hydrological connectivity. Ecol. Eng.35 (1), 25–37.

łowacki, Ł., 2009. What is “true diversity” and diversity partitioning? Kosmos 58(1–2), 97–111.

riffith, M.B., Kaufmann, P.R., Herlihy, A.T., Hill, B.H., 2001. Analysis of macroinver-tebrate assemblages in relation to environmental gradients in Rocky Mountainstreams. Ecol. Appl. 11, 489–505.

eiler, G., Hein, T., Schiemer, F., Bornette, G., 1995. Hydro-logical connectivity andflood pulses as the central aspects for the integrity of a river-floodplain system.Regul. River 11, 351–361.

eino, X., 2000. Lentic macroinvertebrate assemblage structure along gradientsin spatial heterogeneity, habitat size and water chemistry. Hydrobiologia 418,229–242.

enry, K.S., Danielopol, D.L., 1999. Oxygen dependent habitat selection in sur-face and hyporheic environments by Gammarus roeseli Gervais (Crustacea,Amphipoda): experimental evidence. Hydrobiologia 390, 51–60.

eppesen, E., Jensen, X.P., Jensen, C., Faafeng, B., Hessen, D.O., Sondergaard, M., Lau-ridsen, T., Brettum, P., Christoffersen, K., 2003. The impact of nutrient state andlake depth on top-down control in the pelagic zone of lakes: a study of 466 lakesfrom the temperate zone to the arctic. Ecosystems 6, 313–325.

unk, W.X., 1989. The use of Amazonian floodplains under an ecological perspective.Interciencia 14, 317–322.

egendre, P., Troussellier, M., 1988. Aquatic heterotrophic bacteria-modelling in thepresence of spatial auto-correlation. Limnol. Oceanogr. 33, 1055–1067.

akly, M.B., McArthur, J.V., 2000. Macroinvertebrate recovery of a post-thermalstream: habitat structure and biotic function. Ecol. Eng. 15, 87–100.

arshall, X.C., Sheldon, F., Thorns, M., Choy, S., 2006. The macroinvertebrate faunaof an Australian dryland river: spatial and temporal patterns and environmentalrelationships. Aust. J. Mar. Fresh. Res. 57, 61–74.

onaghan, M.T., Robinson, C.T., Spaak, P., Ward, X.V., 2005. Macroinvertebratediversity in fragmented Alpine streams: implications for freshwater conserva-tion. Aquat. Sci. 67, 454–464.

urphy, X.F., Davy-Bowker, X., 2005. Spatial structure in lotic macroinvertebratecommunities in England and Wales: relationship with physical, chemical andanthropogenic stress variables. Hydrobiologia 534, 151–164.

bolewski, K., Glinska-Lewczuk, K., 2006. Contents of heavy metals in bottom sed-iments of oxbow lakes and the Słupia River. Polish J. Environ. Stud. 15 (2a (Pt.II)), 440–444.

bolewski, K.T., Glinska-Lewczuk, K., Kobus, S., 2009a. An attempt at evaluatingthe influence of water quality on the qualitative and quantitative structure ofepiphytic fauna dwelling on Stratiotes aloides L., a case study on an oxbow lakeof the Lyna River. J. Elementol. 14 (1), 119–135.

bolewski, K.T., Glinska-Lewczuk, K., Kobus, S., 2009b. The effect of flow on the

macrozoobenthos structure in a re-opened oxbow lake – a case study of theSłupia River, northern Poland. In: Ecohydrology of Surface and GroundwaterDependent Systems: Concept, Methods and Recent Developments (Proc. of JS. 1at the Joint JAHS&IAH Convention, Hyderabad, India, September 2009), vol. 328.IAHS Publ., pp. 13–23.

W

Z

ering 37 (2011) 796–805 805

bolewski, K., Gotkiewicz, W., Strzelczak, A., Osadowski, Z., Astel, A.M., 2010.Influence of anthropogenic transformations of river bed on plant andmacrozoobenthos communities. Environ. Monit. Assess., doi:10.1007/s10661-010r-r1420-9.

eres-Neto, P.R., Legendre, P., Dray, S., Borcard, D., 2006. Variation partitioningof species data matrices: estimation and comparison of fractions. Ecology 87,2614–2625.

etridis, D., 1993. Macroinvertebrate distribution along an organic pollution gradi-ent in Lake Lysimachia (Western Greece). Arch. Hydrobiol. 128, 367–384.

eese, E.G., Batzer, D.P., 2007. Do invertebrate communities in floodplains changepredictably along a river’s length? Freshwater Biol. 52, 226–239.

obinson, C.T., Uehlinger, U., Monaghan, M.T., 2003. Effects of a multi-year experi-mental flood regime on macroinvertebrates downstream of a reservoir. Aquat.Sci. 65, 210–222.

obinson, C.T., Uehlinger, U., Monaghan, M.T., 2004. Stream ecosystem response tomultiple experimental floods from a reservoir. River Res. Appl. 20, 359–377.

aunders, D.L., Kalff, X., 2001. Nitrogen retention in wetlands, lakes and rivers.Hydrobiologia 443, 205–212.

heldon, F., Boulton, A.X., Puckridge, X.T., 2002. Conservation value of variable con-nectivity: aquatic invertebrate assemblages of channel and floodplain habitatsof a central Australian arid-zone river, Cooper Creek. Biol. Conserv. 103, 13–31.

mith, A.X., Bode, R.W., Kleppel, G.S., 2007. A nutrient biotic index (NBI) for use withbenthic macroinvertebrate communities. Ecol. Indic. 7 (2), 371–386.

er Braak, C.X.F., Smilauer, P., 2002. CANOCO Reference Manual and CanoDraw forWindows User’s Guide: Software for Canonical Community Ordination, Version4.5. Microcomputer Power, Ithaca, NY, USA, 500 pp.

ockner, K., Pennetzdorfer, D., Reiner, N., Schiemer, F., Ward, X.V., 1999. Hydrologicalconnectivity, and the exchange of organic matter and nutrients in a dynamicriver-floodplain system (Danube, Austria). Freshwater Biol. 41, 521–535.

ockner, K., Malard, F., Ward, X.V., 2000. An extension of the flood pulse concept.Hydrol. Process. 14, 2861–2883.

ang, L.Z., Robertson, D.M., Garrison, P.X., 2007. Linkages between nutrients andassemblages of macroinvertebrates and fish in wadeable streams: implicationto nutrient criteria development. Environ. Manage. 39, 194–212.

ard, X.V., 1998. Riverine landscapes: biodiversity patterns, disturbance regimes,and aquatic conservation. Biol. Conserv. 83, 269–278.

ard, X.V., Stanford, X.A., 1995. Ecological connectivity in alluvial river ecosystemsand its disruption by flow regulation. Regul. River 11, 105–119.

ard, X.V., Tockner, K., Arscott, D.B., Claret, C., 2002. Riverine landscape diversity.Freshwater Biol. 47, 517–539.

hiles, M.R., Goldowitz, B.S., 2005. Macroinvertebrate communities in CentralPlatte River wetlands: patterns across a hydrologic gradient. Wetlands 25,462–472.

issmar, R.C., 1991. Forest detritus and cycling of nitrogen in a mountain lake. Can.J. Forest Res. 21, 990–998.

itczak, S., Adamczyk, A., 1995. Catalogue of Selected Physical and Chemical Fac-tors of Underground Water Pollution and Methods of Their Determination. Bib.Monit. Srod., Warsaw, 579 pp.

oodcock, T.S., Huryn, A.D., 2007. The response of macroinvertebrate productionto a pollution gradient in a headwater stream. Freshwater Biol. 52, 177–196.

immer, K.D., Hanson, M.A., Butler, M.G., 2000. Factors influencing invertebratecommunities in prairie wetlands: a multivariate approach. Can. J. Fish. Aquat.Sci. 57, 76–85.