macroinvertebrate patterns along environmental gradients and hydrological connectivity within a...

Research Article

Macroinvertebrate patterns along environmental gradients andhydrological connectivity within a regulated river-floodplain

Belinda Gallardo*, Mercedes Garc�a, �lvaro Cabezas, Eduardo Gonz�lez, Mar�a Gonz�lez, Cecilia Ciancarelliand Francisco A. Com�n

Pyrenean Institute of Ecology, Spanish Research Council (IPE-CSIC), 50192 Zaragoza, Spain

Received: 25 June 2007; revised manuscript accepted: 27 February 2008

Abstract Flood and flow pulses are primary factorsthat regulate macroinvertebrate community structurein river-floodplain ecosystems. In order to assess theimpacts of these important hydrological events in aregulated Mediterranean river, bimonthly water andmacroinvertebrate samples were collected in 2006 inthe Middle Ebro River channel and six floodplainwetlands (NE Spain). We found significant differencesamong the river sites (permanently connected), twoconstructed wetlands (groundwater seepage) andthree natural oxbow lakes (surface connected at 400,800 and 1200 m3/s). River sites were dominated byaquatic worms (e.g., Naididae) and showed a highdegree of eutrophication. Constructed wetlands pro-vided new habitat for predatory insects (e.g., Coenag-rion scitulum and Trithemis annulata) that benefitedfrom the absence of fish. Natural oxbow lakes weredominated by crustaceans (e.g., Atyaephyra desmar-estii, Procambarus clarkii) and were highly overlap-ped in Correspondence Analysis. Canonical Corre-

spondence Analysis, coupled with variance partition-ing, showed that hydrological connectivity accountedfor 28 % of the variability in the invertebrate com-munity, followed by physicochemical (10 %) andtrophic (7 %) factors. Differences in frequency andduration of flood pulses in natural oxbow lakes werenot enough to generate distinctive macroinvertebrateassemblages in the different wetlands. Analysis ofvariance showed that richness and total abundanceincreased with hydrological connectivity, while diver-sity showed a rather unimodal distribution. General-ized Additive Models indicated that among themeasured environmental variables, nitrate concentra-tion strongly affected the composition, abundance anddiversity of aquatic communities. Our data indicatethat increasing the diversity of water body types indegraded floodplains enhances biodiversity and aidsin the functional and ecological recovery of theriverine landscape.

Key words. Macroinvertebrates; river-floodplain system; Ebro River; Canonical Correspondence Analysis;variance partitioning.

Introduction

The structure and function of river-floodplain ecosys-tems are directly, and indirectly, affected by riverdischarge fluctuations (sensu “flood” and “flow puls-es”, Junk, 1989; Tockner et al. , 2000). Hydrologicalconnectivity (sensu, Amoros and Roux, 1988) involves

* Corresponding author phone: +34 976 716142;fax: +34 976 716019; e-mail: [email protected] Online First: July 1, 2008

Aquat. Sci. 70 (2008) 248 – 2581015-1621/08/030248-11DOI 10.1007/s00027-008-8024-2� Birkh�user Verlag, Basel, 2008

Aquatic Sciences

patterns and processes across the river-floodplainsystem, such as transport of dissolved or suspendedelements and organisms, reorganization of habitats,productivity and biodiversity of aquatic and terrestrialcommunities (Amoros and Roux, 1988; Junk, 1989;Poff and Ward, 1989; Heiler et al. , 1995; Ward andStanford, 1995; Poff et al. , 1997; Tockner et al. , 1999a;Ward et al. , 2002; Tockner et al. , 2000).

Several factors beyond river flow fluctuations caninfluence floodplain hydrological connectivity. Thedistance from the river to the wetlands is directlyrelated to overbank flood frequency wherever thereare no natural or artificial barriers to water flow. Themorphology of the upstream and downstream wetlandborders is related to the magnitude and duration ofsurface connectivity with the main channel (Amorosand Bornette, 2002). Groundwater seepage, whichalso makes significant contributions to wetland waterlevels, is limited by subsurface geological materialsand sediment accumulation. The combination of thesefeatures results in a shifting mosaic of aquatic andterrestrial patches that provides highly diverse aquatichabitats, communities and processes within the river-floodplain system (Arscott et al. , 2005; Marshall et al. ,2006).

Given that higher habitat diversity will promoteincreased biological diversity, aquatic assemblages(from phytoplankton to fish) provide an adequatemeasure of habitat structure and function at differentspatial and temporal scales, and are often used toassess hydrological patterns (e.g., Boulton et al. , 1992;Clausen and Biggs, 1997; Tockner et al. , 1999b;Gibbins et al. , 2001; Sheldon et al. , 2002; Arscott etal. , 2003; Robinson et al. , 2003, 2004; Arscott et al. ,2005;Whiles and Goldowitz, 2005; Gallardo et al. ,2007; Reese and Batzer, 2007). Among freshwaterorganisms, invertebrates are particularly useful be-cause of their short life cycles and multiple adaptationstrategies (e.g., body form, cycles per year, life span,feeding habitats, and dispersal and resistance forms)to environmental gradients (Gasith and Resh, 1999).Since many benthic invertebrates exhibit a sessile lifestyle, their presence can be particularly telling abouthabitat quality. Moreover, specific groups of macro-invertebrates show a series of overlapping optima ofabundance and diversity along both spatial andenvironmental gradients, although little is knownabout them (e.g., Van der Brink et al. , 1996; Tockneret al. , 1999b; Heino, 2000; Griffith et al. , 2001; Arscottet al. , 2005; Monaghan et al. , 2005).

In this study, we investigated the relationshipsbetween physical, chemical and biological character-istics of floodplain wetlands in the Middle Ebro River(northeastern Spain). We identified wetlands by theirhydrological connectivity with the main river channel

and hypothesized that the macroinvertebrate assemb-lages of those wetlands, quantified through composi-tion, diversity and abundance measurements, woulddemonstrate significant differences. We also identifiedmultiple environmental gradients that affected aquat-ic communities and, by partitioning the variability ofthose gradients, we were able to test their importancein explaining invertebrate community variability.

Study Area

The study area was a 13-km segment of the MiddleEbro River Floodplain in NE Spain (hereafter,MERF, Fig. 1) which is the largest river in Spain(watershed area 85,362 km2, length 910 km, averageannual discharge 18,138 hm3, average monthly dis-charge 235 m3/s, ordinary floods >600 m3/s occurbetween October and March) (CEDEX, 1997). Mostof the floodplain area is used for agricultural orindustrial activities, and wetlands cover only 3.6% ofthe total floodplain. In the last century, regulation ofthe river to control flooding and water abstractionreduced the number and extent of permanent waterbodies within the floodplain.

Sampling sites included six floodplain wetlandsand the main river channel (river site, RS, Fig. 1). Oneof the wetlands was a natural oxbow lake (NOL1),situated 1-km upstream from the city of Zaragoza; theother five wetlands were located 12 km downstreamfrom Zaragoza. The five downstream wetlands in-

Figure 1 Study site locations (six wetlands and the river channel) inthe Middle Ebro River Floodplain, Spain. The dashed linerepresents a separation of 13 km between sampling sites (furtherdescription: see text). WWTP = Waste Water Treatment Plant.

Aquat. Sci. Vol. 70, 2008 Research Article 249

cluded three old, natural oxbow lakes (NOL2, NOL3and NOL4) and two artificial wetlands constructed in2005 specifically to mitigate wetland loss (COL1 andCOL2). The study sites represented the widest rangeof hydrological connectivity within the river flood-plain system. They ranged from sites with a surfacewater connection to the main channel (RS), to sitesthat were generally disconnected from the surfacewater (NOL 3 and 4) or sites with groundwaterseepage only (COL1 and 2). The remaining sitesexhibited intermediate levels of connectivity (NOL1and 2).

Both COL1 and COL2, which were constructedclose to NOL3, have gravel substrata that allow waterseepage from the river and hillslope aquifers. However,their relatively high elevation does not allow for asurface connection with the river at flows <2500 m3/s,which has probably contributed to the lack of fish inthese systems. Aquatic vegetation has rapidly colonizedCOL1 (Typha latifolia and submerged macrophytes),but COL2 remains unvegetated.

Materials and methods

SamplesIn 2006, water and macroinvertebrate samples werecollected bimonthly from various locations at theseven study sites. In four of the wetlands, samplingstations were established at three points (upstream,mid-stream and downstream), but only two stationswere established in both COLs and NOL4 because oftheir small size. One sampling station was establishedin the Middle Ebro River at the centre of the studyarea, 500 m downstream from the Zaragoza waste-water treatment plant (WWTP). Between 12 and 16March 2006, an extraordinary flood (1,586 m3/s, 2-yrreturn period, Fig. 2) raised the floodplain water levelto a point where all of the natural oxbow lakes, exceptCOLs, were connected to the river. Excluding this oneflood event, river flow remained unusually low in 2006(average 2006 monthly mean = 143 m3/s; averagemonthly mean from 1912 to 2003 at Zaragoza gaugingstation = 235 m3/s, Fig. 2). The wetland connectivitycaused by the 2006 flood provided an opportunity toassess wetland response to surface connection gra-dients across the floodplain.

Dissolved oxygen (DO), temperature, conductiv-ity and pH were measured in situ using portableprobes previously calibrated (WTW� Multiline P4).Two-litre water samples were collected directly intoacid-washed polycarbonate bottles, at a depth of20 cm and placed on ice. On the same day, sampleswere filtered through Whatman� GF/F glass fibrefilters (pre-combusted at 4508C for 4 h) to determine

the amount of suspended, dissolved and ash-freesolids (APHA, 1989). Alkalinity was measured usingpotentiometric automatic titration with 0.04 N H2SO4

(APHA, 1989). Ionic chromatography was used todetermine dissolved nutrient and anion concentra-tions (Br-, Cl-, SO4

2-, F-, NO3-, NO2

-, PO43-, K+, Mg2+,

Na+ and NH4+) and a continuous flow analyzer

(FLOWSYS-SYSTEA�) was used to determine totalnitrogen and total reactive phosphorus (APHA,1989). Finally, phytoplankton photosynthetic pig-ments were analyzed using the SpectrophotometricMethod (APHA, 1989).

A sweep net (45 x 45 cm frame net, 500 mm sieve,1 min sampling) was used to collect invertebrates(catch per unit effort, CPUE) at various microhabitatswithin each wetland. The microhabitats includedemergent vegetation (e.g. , Phragmites australis andTypha latifolia, which were present in dense standsalong the margins of all the natural oxbow lakes), leafpacks (coarse organic matter), littoral areas that werefree of vegetation and had a silt or gravel substratum,and stagnant waters. Samples were preserved in 5 %formalin and then washed through nested sieves (2500mm, 1000 mm, and 500 mm). Samples were hand-sortedand organisms were identified to genus level exceptfor the Oligochaeta (Class level) and Diptera (Familylevel). Results from different habitats in each sam-pling station were pooled. To quantify the ecologicalcharacteristics of the macroinvertebrate communities,we used a set of metrics that included the Shannon-Wiener Diversity Index, evenness, genera richness,and total abundance.

Hydrological classificationIn order to classify wetlands by their hydrologicalconnectivity, we considered several factors at land-scape and wetland scales. River regulation and lack offlow fluctuations negatively affects all of the studysites, but especially those located farther from theriver channel, where connections are established onlyduring extraordinary floods. As a consequence, the

Figure 2 Hydrograph of the Ebro River, Spain, in 2006 (Zaragozagauging station). Triangles indicate the average monthly flowbetween 1912 and 2003.

250 B. Gallardo et al. Macroinvertebrates in a river floodplain system

intervals between “reconnection” events have beengrowing longer in the last century (e.g., 3,000 m3/sreturn period has shifted from 10 to 60 years in the lastdecades). River to wetlands distance is usually relatedto the frequency of hydrological connectivity; how-ever, the height of the river embankment is alsoimportant. Levee construction at the downstream endof some natural oxbow lakes (NOL2 and NOL4) limitssurface connectivity and requires higher river flows totop the high banks. Morphology of upstream anddownstream wetland borders impacts both the flowand turnover of water during flood pulses. In addition,dense stands of emergent vegetation are a naturalbiological filter of water entering natural oxbow lakes,causing a drop in water velocity and concurrentsettling of suspended material. On the other hand,sediment accumulation has been enhanced by the lackof intensive, erosive floods during the last few decades,thus reducing groundwater seepage in natural oxbowlakes. As a consequence, when and how long afloodplain wetland is connected to the main riverchannel varies with river flow and other wetlandcharacteristics.

To assess macroinvertebrate assemblages along agradient of hydrological connectivity, we constructeda categorical variable called connectivity, which hadfive categories (Type 1, 2, 3, 4 and 5), based on the typeof wetland hydrological connection (Table 1). Riversites and constructed oxbow lakes (RS and COLs)were connected all year (through surface and subsur-face pathways, respectively). Natural oxbow lakeswere sequentially surface-connected to the mainchannel at 400, 800 and 1200 m3/s, depending on theparticular wetland. Flow thresholds were based on adetailed Digital Elevation Model (DEM), coupledwith field measurements. Connectivity, therefore, wasnot treated as a continuous variable, but rather atypology that involved multiple patterns and proc-esses throughout the river floodplain system. Water

table variability was taken into account as thecoefficient of variation of the river flow 30 days beforeeach sampling date (CV river).

Statistical analysesTo reduce the effect of absolute values, the abundan-ces of the invertebrate densities were square-roottransformed (

ffiffiffiffiffiffiffiffiffiffi

Xþ1p

), rare species were downweight-ed and environmental data were log-transformed(log10 (X+1)) (ter Braak and Smilauer, 2002). Toassess the general differences among wetlands, inver-tebrate data (grouped into classes/orders) and hydro-chemical data were subjected to non-parametricanalysis of variance (Kruskal-Wallis test, p � 0.05).To further identify patterns in the abundance of 48invertebrate genera, we used direct ordination meth-ods, such as Correspondence Analysis (CA) (terBraak and Smilauer, 2002).

To identify the primary environmental gradientsaffecting macroinvertebrate assemblages, we usedCanonical Correspondence Analysis (CCA; terBraak and Smilauer, 2002) between 29 environmentalvariables and 11 groups of macroinvertebrates. Hy-drological connectivity was introduced as five dummyvariables (Type 1, 2, 3, 4 and 5) along with the rest ofthe physical and chemical variables. Because environ-mental gradients had not previously been evaluated inthe study area, we ran a manual, forward-selectionCANOCO procedure, which included variables thathad a conditional effect significant at the 10% level(p � 0.1). P-values were calculated using the MonteCarlo Permutation Test (ter Braak and Smilauer,2002). Once the main environmental gradients im-pacting aquatic community structure were identified,the model was subjected to variation partitioning inorder to quantify the amount of variation uniquelyexplained by each set of variables in the model(physicochemical, trophic and hydrological), theshared variance among them and the variance that

Table 1. Lateral hydrological connectivity definitions for floodplain wetlands in the Middle Ebro River. Type corresponds to hydro-connectivity categories. Depth is at the deepest part of the wetlands in summer. Age is the time since the cut-off of oxbow lakes, orconstruction, depending on origin. Area was measured using summer aerial photographs. FT= river flow-threshold to overbank flood, P=number of perturbation events (flow exceeding the flood threshold) in 2006, DC= total number of days connected in 2006.

Type Depth(m)

Age(yr)

Area(ha)

FT(m3/s)

P DC(days)

Hydrological Connectivity Definition

RS – – 125.5 – – 365 Surface connected. Gravel substrata.NOL1 0.8 42 70.31 400 3 25 High surface-connected. A thick layer of sediment reduces

groundwater connectivity.COL1 and 2 0.5 0.5 –1 0.25–0.58 – – 365 Groundwater-connected. Gravel substratum allows groundwater

seepage from both river and hillslope aquifers. Topography doesn�t allowsurface connection, even at extraordinary floods.

NOL2 1.73 61 35.45 800 2 7 Moderate surface-connected. A thick layer of sediment limitsgroundwater connectivity. Levee construction limits overbank floods.

NOL3 and 4 0–2.42 61 4.82–10.33 1200 1 3 Low surface-connected. A thick layer of sediment limitsgroundwater connectivity. Downstream levee construction in NOL4.


remained unexplained, (Borcard et al. , 1992; M�ot etal. , 1998; Borcard et al. , 2004).

Generalised additive models (GAM, p � 0.05)were used to test the relationship between theinvertebrate community (measured by abundanceand diversity) and key environmental variables(Wood, 2004). A nonparametric analysis of variance(Kruskal Wallis test, p < 0.05) was used to identifydifferences in richness and abundance among types ofconnectivity. The regression models were run usingthe statistical software R (version 2.5.1; R Develop-ment Core Team, 2007; “mgcv” package).

Results

Environmental conditionsMean 2006 annual values for the measured physicaland chemical parameters, and significant differencesamong hydrological connectivity types in the MERF,are shown in Table 2. The wetlands differed mainly ininorganic ion concentrations (TDS, HCO3

-, NO3-,

PO43-) and organic (ADFM, DON, DOP, Chl-a)

elements. While the river was the main source ofthese inorganic and organic constituents, leaf litter,sediment scouring, hillslope aquifer inputs, agricul-tural irrigation and rainfall also made substantialcontributions. Both COLs and NOL2 had signifi-cantly higher TDS and NO3

- concentrations butlower organic matter contents than the rest of thewetlands. NOL3 and 4 had significantly higherchlorophyll-a concentrations. These two wetlandshave a relative low frequency of hydrological con-nection with the main river channel, which mayfoster increased primary productivity through stabil-ity and nutrient availability. Finally, NOL1 showed

intermediate concentrations of both organic andinorganic elements.

Patterns of macroinvertebrate abundanceMean annual macroinvertebrate abundance and sig-nificant differences among hydrological connectivitytypes are shown in Table 3. We recorded 77,200individual macroinvertebrates belonging to 48 generaand 6 classes. Crustacea and Oligochaeta were themost common invertebrate classes (35 % each). Wet-lands differed mainly in their diversity values andabundance of aquatic worms, insects and crustaceans(Fig. 3). RS was dominated by aquatic worms (Naidi-dae), though insects were also abundant and includedaquatic bugs (e.g., Micronecta sp.) and midges (e.g.,Chironomus sp., Orthocladius sp.). Both COLs weredominated by Odonata (e.g., Trithemis annulata,Coenagrion scitulum), Ephemeroptera (e.g., Caenisluctuosa, Baetis fuscatus) and Diptera families (e.g.,Chironomidae, Ceratopogonidae). The three NOLswere dominated by crustaceans. In particular, macro-crustaceans (e.g., Atyaephyra desmarestii, Echino-gammarus sp. , Procambarus clarkii) were more abun-dant in highly connected wetlands (NOL1) than theother NOLs.

Differences in macroinvertebrate assemblagesamong sites were reinforced in the CA model, wherethe first and second ordination axes accounted for28 % of the initial variance (Fig. 4). Dominant inver-tebrate groups in each wetland type were similar tothose identified through nonparametric analysis ofvariance. The first factor indicated a gradient frominvertebrates with effective dispersal and resistancestrategies such as insects, towards non-insect inverte-brates that inhabit more stable environments, such ascrustaceans, snails and aquatic worms (Fig. 4B). This

Table 2. Water quality of six floodplain wetlands and the Ebro River. Data are mean (s.d.) of bimonthly samples in 2006. TDS = Totaldissolved solids, AFDM = ash-free suspended solids, T = temperature, DO = dissolved oxygen, Chl-a = Chlorophyll-a, DON = dissolvedorganic nitrogen, DOP = dissolved organic phosphorous.*= significant differences (nonparametric Kruskal Wallis test, p � 0.05) amongwetlands. Variables in bold were significant in multivariate models.

RS(n=6)

NOL1(n=17)

COL1 and 2(n=16)

NOL2(n=18)

NOL3 and 4(n=24)

TDS (mg/l)* 1002 (304) 1779 (952) 3609 (1347) 1805 (420) 1890 (767)AFDM (mg/l)* 13.9 (6.1) 8.08 (4.33) 7.70 (7.63) 13.5 (29.0) 17.2 (11.5)Mg2+ (mg/l) 28.4 (7.3) 87.4(43.4) 41.8 (20.9) 41.9 (4.6) 44.6 (18.5)SO4

2- (mg/l) 502 (322) 1841 (900) 721 (385) 534 (91) 1121 (512)Cl- (mg/l) 331 (102) 779 (247) 576 (392) 583 (102) 346 (120)K- (mg/l) 6.25 (2.86) 7.35 (2.90) 7.90 (2.03) 3.98 (1.04) 10.0 (2.3)HCO3

- (mg/l)* 164 (87) 126.7 (68.9) 136 (58) 275.2 (65.0) 133 (32)pH* 8.11 (0.26) 8.01 (0.30) 7.91 (17.18) 7.63 (0.18) 7.83 (0.30)T (8C) 14.5 (3.5) 16.38 (7.34) 17.2 (5.5) 14.7 (4.4) 15.6 (6.3)DO (mg/l) 8.46 (2.70) 7.23 (1.98) 9.25 (1.59) 8.43 (1.70) 8.26 (5.40)Chl-a (mg/l)* 21.6 (18.7) 14.4 (17.2) 4.04 (3.48) 11.8 (17.2) 36.7 (26.4)NO3

- (mg/l)* 16.0 (4.6) 1.82 (3.11) 44.4 (42.0) 42.2 (7.1) 1.36 (3.06)DON (mg/l)* 0.36 (0.44) 0.11 (0.20) 0.07 (0.13) 0.12 (0.45) 0.28 (0.27)PO4

3+ (mg/l) 5.0 (0.0) 5.0 (0.0) 9.1 (11.2) 14.1 (34.42) 32.0 (73.5)DOP (mg/l)* 12.7 (11.1) 4.4 (4.2) 2.2 (3.4) 4.6 (3.8) 36.4 (70.3)


analysis reflected the relatively small differences inNOLs macroinvertebrate assemblages, even in situa-tions where wetlands differed substantially in environ-mental conditions (organic and inorganic elements)and their hydrological connection to the main riverchannel (Fig. 4A).

Primary gradients affecting aquatic communitystructure of the MERFOf the initial 29 environmental variables included inthe CCA model, 14 were retained as significantcontributors to the model (Table 2). The non-retained15 were redundant or did not increase the significance

of the model (Types 2 and 5 dummy variables, Br-,HCO3

-, Na+, Fl-, total suspended solids, temperature,pH, chlorophyll-b and c, NO2

-, NH4+, PO4

3+ andDOP). The final model accounted for 65 % of the totalvariance in invertebrate composition and all canonicalaxes were significant (Monte Carlo test, p = 0.002).The first factor showed a gradient from highlyeutrophicated to highly salinizated sites (Fig. 5A).

Variance partitioning showed that the hydrologicalset of variables (including Type 1, 3 and 4 dummyvariables and water-table variability) accounted for28 % of the invertebrate variability. Retained physicaland chemical variables included DO, K+, Cl-, TDS,SO4

2- and Mg2+, which explained 10 % of the inverte-brate variability. Trophic variables (NO3

-, DON,chlorophyll-a and AFDM) explained 7 % of theinvertebrate variability. Shared variance between thethree sets of variables accounted for 20 % of theinvertebrate variability; 35 % remained unexplained(Fig. 5C).

In the ordination space of Factors 1 and 2, COLs,NOLs and RS were clearly distinguished by environ-mental variables and invertebrate composition, in thesame manner as the previous analyses (Fig. 5A).There were no apparent differences among theNOLs despite their differing connection flow condi-tions and flood duration (21 days in NOL1; 7 days inNOL2; 3 days in NOL3). However, in the ordinationspace of Factors 1 and 3, NOL2 was clearly separatedfrom the other NOLs by its nitrate concentration,which probably originated from the intensive agricul-tural industry on the surrounding land (Fig. 5B). Incontrast, denitrification in the benthic layers of NOL3and 4 may be responsible for the very low inorganicnitrogen concentrations in those wetlands. As inprevious analyses, Insecta, Crustacea and Oligochaeta

Table 3. Invertebrate composition and metrics of six floodplain wetlands and the Ebro River. Data are mean (s.d.) from bimonthlysamples in 2006. R = Invertebrate richness, N = Total invertebrate abundance, H = Invertebrate Shannon diversity, J = Invertebrateevenness. * = significant differences (non-parametric Kruskal Wallis test, p � 0.05) among wetlands.

RS(n=6)

NOL1(n=17)

COL1 and 2(n=16)

NOL2(n=18)

NOL3 and 4(n=24)

R* 11.2 (2.7) 11.33 (4.45) 8.20 (3.50) 8.10 (2.60) 6.12 (2.33)N* 2824 (2573) 643 (477) 1030 (915) 123 (163) 279 (305)H* 0.59 (0.26) 1.11 (0.48) 0.98 (0.62) 1.33 (0.29) 0.80 (0.41)J* 0.09 (0.05) 0.21 (0.09) 0.20 (0.16) 0.37 (0.10) 0.29 (0.24)Hirudinea* 3.50 (7.62) 0 0 0 0Coleoptera 0.08 (0.20) 0.16 (0.31) 0.47 (0.83) 0.03 (0.13) 0.13 (0.31)Diptera* 124 (179) 67.4 (78.9) 289 (333) 9.90 (12.70) 23.7 (33.4)Ephemer.* 23.1 (49.0) 24.6 (48.9) 74.0 (88.6) 2.77 (7.60) 0.80 (1.59)Gastropoda* 13.6 (32.1) 10.5 (26.5) 0.13 (0.52) 0.27 (0.46) 0.33 (0.56)Heteroptera* 244 (297) 54.1 (186.6) 19.3 (46.0) 1.70 (2.71) 0.17 (0.33)Macrocrust.* 1.75 (1.80) 1.9 (3.0) 0 27.5 (64.2) 0.15 (0.38)Microcrust.* 23.2 (36.2) 390 (418) 82.9 (179.9) 60.7 (95.4) 215 (278)Odonata* 0 3.45 (9.76) 292 (603) 0.07 (0.17) 0.24 (0.56)Oligochaeta* 2266 (2294) 15.9 (16.8) 1.73 (2.60) 9.40 (11.00) 14.0 (36.9)Trichoptera* 1.50 (1.61) 4.05 (5.96) 0.07 (0.26) 0.73 (1.25) 1.25 (2.70)

Figure 3 Abundance of main invertebrate groups in six floodplainwetlands and the Ebro River. Data are mean values of bimonthlysampling in 2006. Differences in total abundance between wetlandsare significant (Kruskal-Wallis test, p<0.001). CPUE= catchmentsper unit effort.


Figure 4 Results of Correspondence analysis performed with invertebrate data from the Ebro River and six floodplain wetlands. (A): plotof sample scores. (B): plot of genera scores.

Figure 5 Results of Canonical Correspondence analysis performed with invertebrate and environmental data from the Ebro RiverFloodplain using forward selection of variables (p <0.1). (A) Triplot of significant environmental variables, invertebrates and samplescores of axis 1 and 2; (B) Biplot showing significant environmental variables and sample scores of axis 1 and 3; (C) Results of variationpartitioning.


provided the most telling discrimination amongCOLs, NOLs and RS, respectively.

The Kruskal-Wallis and GAM models indicatedthat greater hydrological connectivity was associatedwith greater invertebrate richness and total abun-dance and decreased evenness (Fig. 6). Shannondiversity showed a rather unimodal shape acrosshydrological types (Fig. 6). A benchmark concentra-tion of 40 mg NO3

-/L caused apparent changes inmacroinvertebrate composition, abundance and di-versity (Fig. 6). At this level, Shannon diversity andevenness were highest, whereas invertebrate abun-dance and richness were lowest.

Discussion

Macroinvertebrate assemblages in the MERFIn our study of the MERF, non-insect taxa, partic-ularly aquatic worms and crustaceans, were numeri-cally dominant components of the wetland macro-invertebrate communities, as in other rivers (Arscott

et al. , 2003; Whiles and Goldowitz, 2005). In the mainriver channel, organic matter pollution in the riverchannel, downstream the Waste Water TreatmentPlant, enhances pollution-tolerant species such usaquatic worms and midges. On the other hand, therelatively long periods of stability in oxbow lakes havefavoured the development of taxa that have longer lifecycles and less effective colonization strategies, suchas crustaceans (Gasith and Resh, 1999). Finally,insects that have short life cycles (e.g., chironomids,ceratopogonids and culicids) were abundant in newly-constructed oxbow lakes that can be colonized fromthe air, and where larger predatory insects benefitfrom the absence of predatory fish (Mallory et al. ,1994).

Marked overlap was observed between the macro-invertebrate assemblages of the NOLs despite theirsmall differences in invertebrate composition (Figs. 4,5). Initially, based on the hydrological relationshipswith the river, we identified three types of NOLs(categories 2, 4 and 5), but differences in the lakeswere not sufficient to generate measurable differencesin invertebrate composition and abundance. Differ-ences in hydrological connectivity may be reflected inmacroinvertebrate community attributes not quanti-fied in this study, such as biomass, diversity withintaxonomic groups and feeding behaviour (Heino,2000; Griffith et al. , 2001).

Primary gradients affecting aquatic communitystructure in the MERFThe Hydrological Connectivity Typology. The criticalinfluence of floods and flow pulses on aquaticcommunities in river-floodplain ecosystems has beenevaluated by various researchers (e.g., Boulton et al. ,1992; Clausen and Biggs, 1997; Tockner et al. , 1999b;Gibbins et al. , 2001; Sheldon et al. , 2002; Arscott etal. 2003; Robinson et al. , 2003, 2004; Arscott et al. ,2005; Whiles and Goldowitz, 2005; Gallardo et al. ,2007; Reese and Batzer, 2007). In the current inves-tigation, we identified several other variables thatimpact wetland hydrological connectivity, such usnatural or artificial barriers for river flow, morpho-logical characteristics of upstream and downstreamwetland borders, subsurface geological materials andsediment accumulation.

The most important factor associated with macro-invertebrate assemblages was hydrological connectiv-ity with the river channel. A major finding was thathydrological typology explained a substantial amountof the macroinvertebrate variance, even after thevariation shared with other significant variables wasremoved. In this and other studies, the remainder ofthe variance is generally attributed to environmentalfactors, such as nutrients and temperature (Van der

Figure 6 (A-D) Box-plots of macroinvertebrate metrics acrossTypes of connectivity. (A) Invertebrate richness (number ofgenera); (B) Invertebrate total abundance (CPUE); (C) Inverte-brate Shannon diversity; (D) Invertebrate evenness. (E-H) Gen-eralized Additive models performed between macroinvertebratemetrics as response variable and NO3

- as explanatory variable. (E)Effect on Shannon diversity scores; (F) Effect on total invertebrateabundance scores (CPUE); (G) Effect on invertebrate richnessscores (number of genera); (H) Effect on invertebrate evennessscores. Dashed lines represent the 95% confidence interval for themodel.


Brink et al. , 1996; Heino, 2000; Zimmer et al. , 2000;Griffith et al. , 2001; Monaghan et al. , 2005; Murphyand Davy-Bowker, 2005). However, the impact ofthese factors may be somewhat spurious since eventemperature and nutrient levels are related to hydro-logical connectivity. For example, river water, beingcolder and containing higher concentrations of nu-trients, affects floodplain wetlands through surface orgroundwater inputs. Consequently, the effects ofhydrological connectivity on macroinvertebrate abun-dance may be even more substantial than suggested bythe statistical analyses conducted in this study, due tothe additional correlations with other environmentalvariables (Zimmer et al. , 2000). In fact, if moreenvironmental variables potentially intercorrelatedwith hydrological connectivity were included in ourmodel, the importance of the hydrological gradientmight be further reduced (Peres-Neto et al. , 2006). Weconclude that aquatic communities and environmen-tal conditions are driven by a common hydrologicalgradient, which generates complex relationships be-tween them (Legendre and Troussellier, 1988).

Macroinvertebrate attributes differed among wet-land hydrological types and environmental gradients(Fig. 6). In our study, invertebrate richness and totalabundance increased with hydrological connectivity,whereas Shannon diversity showed a rather unimodalresponse. Other authors have reported an increase ininvertebrate richness with hydrological connectivity,which peaked at intermediate-connected sites (Ward,1998; Ward et al. , 2002; Tockner et al. , 1999b; Amorosand Bornette, 2002 ; Whiles and Goldowitz, 2005).Most of these studies indicated that hydrologicalconnectivity produces antagonistic effects even withinthe same waterbody, but that hydrological connectiv-ity provides complementary habitats that are requiredby different life stages of some species.

Other environmental gradients. Salinization and nu-trient status were also found to influence invertebratepatterns across the river floodplain. Certainly, bothgradients are known to influence aquatic communitiesdirectly or indirectly (Blumenshine et al. , 1997;Tockner et al. , 1999a; Jeppesen et al. , 2003; Wang etal. , 2007). In floodplain wetlands, nutrients anddissolved solids can come from several natural andartificial sources. Suspended and dissolved solids fromallochthonous (outside sources introduced throughoverbank flooding or seepage) or autochthonous(internal primary production and proximal riparianecosystems) natural sources accumulate in floodplainwetlands during periods of confinement; oxbow lakescan become a source of these compounds during large,intensive floods (Junk, 1989; Tockner et al. , 1999a).The lack of flood pulses increases sedimentation rates

and eutrophication in floodplain wetlands. In addi-tion, anthropogenic factors, such as agricultural andurban wastewater influx can transfer nutrients.

The influence of nutrient status on aquatic com-munities was further reflected in significant trends ofrichness, abundance and diversity along the nitrategradient (Fig. 6). Nitrate is the most common dis-solved form of nitrogen in river and agriculturalwastewaters and is often used to assess water qualityand ecosystem ecological integrity (Smith et al. , 2007).As a conclusion, because salinization and eutrophica-tion are major factors affecting floodplain wetlands,water quality management in the river catchment isneeded to improve wetland ecological integrity. Otherfactors that might account for some of the variance inour study are morphometry (Heino, 2000; Jeppesen etal. , 2003), submerged macrophyte cover (Carpenterand Lodge, 1986), riparian vegetation (Wissmar,1991), substrate structure and composition (Griffithet al. , 2001; Murphy and Davy-Bowker, 2005), trophicinteractions (Blumenshine et al. , 1997; Jeppesen et al. ,2003) and pollution (Petridis, 1993; Woodcock andHuryn, 2007).

Effects of wetland creation at floodplain-scaleConstructed oxbow lakes in the study area consistedof two ponds recently built to mitigate habitat loss.Ground movements after construction, wind-drivenbottom re-suspension and shore scouring may haveincreased recent salt concentrations, but re-suspen-sion is expected to decline once aquatic plant com-munities colonize and stabilize the lakes. Also, nitrateconcentrations were high in the constructed lakesbecause there was little vegetation, biofilm or organicsediment layers where uptake and de-nitrificationcould occur (Bachand and Horne, 2000; Saunders andKalff, 2001). In fact, the low chlorophyll-a concen-tration at these sites are probably associated with highturbidity and general wetland instability. The newhabitat formed in the constructed oxbow lakesdiffered from those already present and was rapidlycolonized by macroinvertebrates that had not beendocumented previously (e.g., Trithemis annulata,Coenagrion scitulum). Those new taxa dispersed toold, degraded oxbow lakes within the study area, thusenhancing biological diversity over the whole flood-plain.

Concluding Remarks. The environmental character-istics of the MERF are similar to those of otherregulated Mediterranean rivers, which are character-ized by highly irregular flows that are caused by thehigh spatial and temporal variability of the Mediter-ranean climate (Gasith and Resh, 1999). The saliniza-tion of Mediterranean rivers is caused by river


regulation, pollution and changes in land use, whichreduce water flow and enhance river incision, sedi-ment scouring, and water eutrophication (Ward andStanford, 1995; Ward, 1998; Gasith and Resh, 1999).

Our results suggest that hydrological connectivitystrongly influences the composition of macroinverte-brate assemblages in floodplain wetlands. The com-plexity of the relationship is substantial and has beenobserved in other lowland rivers (Boulton et al. , 1992;Clausen and Biggs, 1997; Tockner et al. , 1999b;Gibbins et al. , 2001; Sheldon et al. , 2002; Arscott etal. , 2003; Robinson et al. , 2003, 2004; Arscott et al. ,2005; Whiles and Goldowitz, 2005; Gallardo et al. ,2007; Reese and Batzer, 2007). Water diversion andlevee construction threaten the natural variation inhydrology, which reduces the magnitude, frequencyand duration of flows, and potentially reduces fre-quency and duration of connectivity between waterbodies (Poff and Ward, 1989; Dynesius and Nilsson,1994; Heiler et al. , 1995; Poff et al. , 1997; Tockner etal. , 1999b; Ward et al. , 2002; Thoms and Sheldon,2000). Consequently, the recruitment and dispersal offlora and fauna, coupled with the exchange of water,nutrients and organic matter between floodplainwetlands and the main channel are inhibited, whichhas negative repercussions for river ecosystem bio-diversity, functions and processes (Amoros and Roux,1988; Heiler et al. , 1995; Walker et al. , 1995). Beyondconnectivity, other factors that influence the structureof aquatic communities include transport and accu-mulation of dissolved salts and micronutrients, whichenhance ecosystem productivity, but reduce the eco-logical integrity of strongly eutrophic sites. Thepresent results provide guidance for the managementand restoration of riverscapes, which should take intoaccount the principal forces that drive ecosystemintegrity, and should also be designed so as tocompensate for the lack of conservation in the studyarea. In the short term, at least, wetland constructionhas a positive effect on riverscape habitats andinvertebrate diversity. Such findings underscore theimportance of increasing the diversity of water bodiesin degraded floodplains as a means to facilitate therecovery of riverine biodiversity.

Acknowledgments

This study was supported financially by the SpanishMinistry of Education and Science (MEC CGL2005-07059-C02– 01) and the Departments of Environmentand Science of the Government of Aragon (Collab-oration Agreement 2005 and E-61 Research Group).Most of the authors were funded by the Governmentof Aragon, the Spanish Ministry of Education or the

Spanish National Research Council (CSIC). We thankKlement Tockner and three anonymous referees�comments that greatly improved the quality of thispaper.

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