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Mollusc communities along upstream–downstream gradients in small coastal basins of the south-western Iberian Peninsula

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Mollusc communities along upstream–downstream gradients in small coastal basins of the south-western Iberian Peninsula
  PRIMARY RESEARCH PAPER Mollusc communities along upstream–downstreamgradients in small coastal basins of the south-westernIberian Peninsula J. C. Pe´rez-Quintero Received: 16 April 2012/Revised: 4 October 2012/Accepted: 8 October 2012/Published online: 29 October 2012   Springer Science+Business Media Dordrecht 2012 Abstract  Freshwater mollusc communities readilyrespond to various human-induced stressors, and thusare appropriate models for studying the effects of suchstressors on the structure and dynamics of streammacroinvertebrate communities. This paper examinedthe distribution of freshwater molluscs in 35 streamreaches of 18 small coastal basins in the south-westernIberian Peninsula. Using several multivariate tech-niques, I showed that mollusc distribution mainlyresponded to gradients in drainage area, water avail-ability, pollution and salinity. Upstream and down-stream communities were clearly differentiated, withthe former dominated by freshwater species (  Bithyniatentaculata ,  Galba truncatula ,  Radix balthica ,  Ancy-lus fluviatilis  and  Planorbarius metidjensis ) and thelatter by species typical of brackish waters ( Peringiaulvae  and  Myosotella myosotis ). There was a cleardecrease in species richness from upper to lowerreaches. The conservation of mollusc communities of these small basins requires a deeper understandingof their ecological requirements, effective control of urban discharges and an analysis of their interactionwith invasive species. Keywords  Conservation    Drainage area   Freshwater molluscs    Heterogeneity   Invasive species    Mediterranean streams    Pollution   Water availability Introduction Numerous recent and classic studies have providedinformation on factors affecting the distribution of ben-thic macroinvertebrate communities along upstream–downstream gradients. These studies suggest that thespecificcompositionofmacroinvertebratecommunitiesis influenced by multiple factors of both natural andanthropogenic srcin, including habitat characteristics(Effenberger et al., 2006; Cuffney et al., 2010), water quality (Cross et al., 2003; Bowman et al., 2005), flow modification (Armitage, 2006; Chester & Norris, 2006) or the presence of exotic species (Ricciardi & Rasmus-sen, 1999).Freshwater molluscs are a group of macroinverte-brates particularly well suited for studying the effectsof human-induced stressors on community structureand dynamics, because they readily respond to suchstressors (Gallardo et al., 1994; Grac¸a et al., 2004). However, little is known about changes in freshwatermollusc distribution in response to environmentalchanges along headwater-estuary gradients. While Handling editor: Luz BoyeroJ. C. Pe´rez-Quintero ( & )Departamento de Biologı´a Ambiental y Salud Pu´blica,Facultad de Ciencias Experimentales,Universidad de Huelva, Campus Universitario de ElCarmen, Avda. Tres de Marzo s/n, 21071 Huelva, Spaine-mail:  1 3 Hydrobiologia (2013) 703:165–175DOI 10.1007/s10750-012-1356-x  several mollusc studies have focussed on headwaterstreams (Gallardo et al., 1994; Sousa et al., 2005) or large rivers (Pe´rez-Quintero, 2007, 2011a, b), their distribution in small coastal streams remainsunknown. Here I explore, for the first time, thedistribution of freshwater molluscs in small coastalstreams of a Mediterranean area, with the aim of (1)testing several predictions about the key environmen-talfactorsaffectingtheirdistributionand(2)providinginformation on mollusc distribution in this unexploredtype of ecosystem which may be critical for theirconservation.My first prediction was that water supply, togetherwith the size of the drainage area, would be the maindriving forces controlling the distribution and com-position of freshwater mollusc communities in smallMediterranean coastal basin streams (Dillon, 2000;Pe´rez-Quintero, 2011b). Mediterranean streams havemore or less predictable flood and dry periods(Gasith & Resh, 1999), and the harsh conditionsimposed by summer drought may act as a criticalfilter for their inhabitants, limiting the colonisation,diversity, resilience and survival in these environ-ments (Bonada et al., 2007, 2008; Be ˆche & Resh,2007; Sa´nchez-Montoya et al., 2010). During thesummer drought, the water of some small streamsdries out or stagnates in pools. The probability of finding permanent habitats or large pools increases inlarge river basins, which minimises the risk of localextirpation due to the severe environmental condi-tions, predation or starvation (Fritz & Dodds, 2005;Downing et al., 2010).My second prediction was that other importantstressors for the communities inhabiting thesestreams would be the human-induced deteriorationof water quality and the presence of invasive species.Most Mediterranean streams of the south-westernIberian Peninsula are subject to pollution as a resultof urban and rural sewage and agricultural practices(Ma´rquez, 2008), and native mollusc species richnessis known to decrease with pollution (Pe´rez-Quintero,2011a). Invasive mollusc and fish species are wide-spread in these streams, and often affect the abun-dance and distribution patterns of native freshwaterfauna (Clavero & Garcı´a-Berthou, 2005; Prendaet al., 2006). Therefore, in such Mediterranean smallcoastal streams, the need to cope with the synergisticaction of these two anthropogenic stressors, togetherwith the harsh environmental conditions during thedrought periods, may impose severe constraints onthe diversity and distribution of freshwater benthicmacroinvertebrate communities in general, and mol-luscs in particular. Methods Study areaThe study area was located in a coastal region of  & 10,000 km 2 in the south-western Iberian Peninsula(Fig. 1), between Cape San Vicente in Portugal (themost south-westerly point in continental Europe;36  59 0 40 00 N and 8  56 0 12 00 W) and Punta de Tarifa inSpain (junctionpoint ofthe Mediterranean Seaand theAtlantic Ocean; 36  00 0 29 00 N and 5  36 0 09 00 W). Thisarea lies within the Ko¨ppen temperate climate belt(Csa and Csb), with average annual temperatures andtotal rainfall ranging between 17.5 and 20.0  C andbetween 400 and 1,400 mm, respectively (AEMET,2011). The study was conducted in 18 coastal basinsdrainingintotheAtlanticOcean (Table 1).Freshwatermolluscs were surveyed in 35 reaches within thestudied basins (Fig. 1; Table 1), which were classified as ‘‘upper’’ or ‘‘lower’’ according to their distancefrom the tidal influence zone (greater or less than500 m, respectively).Habitat characterisation and mollusc samplingTwo measurements of abiotic and biotic in situ datawere taken into two 25 m 2 surfaces, 100 m away fromeach other, and the average values were used for thestatistical analyses. The habitat was characterised bymeasuring eighteen environmental variables impor-tant for the physiology, distribution and food of freshwater molluscs and also as refuge from predators(Gordon et al., 2004) (Table 2). At basin scale: mean temperature (  C), total rainfall (mm) (both from thewebsite ‘‘Atlas Clima´tico Digital de la Penı´nsulaIbe´rica’’), solid waste production (Tm 100 inhabit-ants - 1 ) (Ma´rquez, 2008), main channel length (km),basin area (km 2 ) (both measured using GIS) and orderat mouth following the Strahler scale (Gordon et al.,2004). At reach scale, ten variables were measuredin situ: altitude at the sampling point (m) using GPS,channel width (m), water depth (cm), substrate 166 Hydrobiologia (2013) 703:165–175  1 3  diversity, using the Wentworth scale (Lincoln et al.1998) and the Shannon–Weiner diversity index,habitat heterogeneity (percentage of the channeloccupied by leaf litter, trunks and branches), percent-ageofmacrophytescoverage(thelatterthreevariableswere visually estimated), pH (pH units), conductivity( l S cm - 1 ), turbidity (mg l - 1 ) and water temperature(  C) (these last four using a Crison  multimeter); inaddition,twovariableswereoff-sitemeasuredatreachscale:lineardistancetotheestuary(km)usingGISandorderatthesamplingpointfollowingtheStrahlerscale(Gordon et al., 2004).Freshwatermolluscswere semi-quantitativelysam-pled. I visually inspected rocks and vegetation, thenfiltered the finer substrate through a 250- l m meshsieve. All molluscs were manually sorted, identifiedin situ to species level when possible, and released.Specimens not identified to species were preserved in70% ethanol and identified in the laboratory usingregional identification guides (Glo¨er, 2002; Glo¨er &Meier-Brook, 2003; Killeen et al., 2004). I used native species richness, from presence–absence data, todescribe mollusc communities. Invasive species weredefined according to the International Union forConservation of Nature criterion (IUCN website),using the list of invasive species in the IberianPeninsula (Garcı´a-Berthou et al., 2007; Boix et al.,2009; A´lvarez et al., 2012).Statistical analysisTwo Non-Metric Multidimensional Scaling analyses(NMDS) were performed, at basin and reach scales, toextract the mainsources ofvariationinthe compositionof freshwater mollusc communities (Legendre &Legendre, 1998); only native species occurring in—atleast—onebasinorreachwereincludedintheNMDS(5species were left out). Habitat variables, at basin andreach scales, were summarised by means of a PrincipalComponents Analysis (PCAb and PCAr, respectively)after varimax normalised rotation factor. Gradientsrelated to PC1 and PC2 were made with loading valuesgreater than0.7. Kruskal–WallisANOVA byranks testwas used to test for differences in environmentalfeatures and native species richness. Two Clusteranalyses, based on Bray–Curtis similarity, were per-formed to graphically display similarities in environ-mental features and native mollusc species richness,both at basin and reach scales. Relationships betweenenvironmental variables and native species richnesswereevaluated byPearson’s correlation coefficientandforward-stepwise multiple regressions. Data werechecked for normality and homogeneity of variancesusing Kolmogorov–Smirnov and Levene’s tests. If necessary, appropriate transformations ln(  x  ?  1) (con-tinuous variables)orarcsine (percentages)wereusedtoimprove normality and remove heteroscedascity. All Fig. 1 a  Location of thesampled reaches,  black circles  upper reaches,  whitecircles  lower reaches (forcodes, see Table 1). b  Location of the sampledbasins ( black circles ) andthe four reviewed basins inthe south-western IberianPeninsula context ( whitecircles ).  1  Odiel River,  2 Tinto River,  3  GuadaleteRiver,  4  Majaceite River,  I   western basins,  II   centralbasins, III: eastern basinsHydrobiologia (2013) 703:165–175 167  1 3  analyseswereperformedusingSPSS17.0.0(SPSSInc.)and PAST (Hammer et al., 2001). Results Freshwater mollusc speciesNineteenspecieswerecollected:16gastropods(includ-ing 12 native species and 4 invasive) and 3 bivalves(2 natives and 1 invasive) (Table 3). Native species  Ancylus fluviatilis ,  Radix balthica  and  Planorbariusmetidjensis  were the most widespread species in upperreaches;  Peringia ulvae  and  Myosotella myosotis  werethemostwidespreadspeciesinestuarineareas,althoughthey also occupied upper reaches with conductivityhigherthan1,300  l S cm - 1 .Amonginvasives, Physellaacuta  was the most widely distributed species, whichoccupied both upper and lower reaches with conduc-tivities between 1,800 and 9,200  l S cm - 1 . Table 1  List of basins andreaches studied. Reachcodes are the same as thosein Fig. 1  N   native species richness,  I   invasive species richness, U   upper,  L   lowerBasin Codes N I Reach Codes N IBenacoita˜o B 3 1 U. Benacoita˜o Ub 3 1Vale do Bara˜o V 5 2 U. Vale do Bara˜o Uv 3 2L. Vale do Bara˜o Lv 2 1Bensafrim E 5 3 U. Bensafrim Ue 3 3L. Bensafrim Le 2 0Farelo F 5 3 U. Farelo Uf 3 3L. Farelo Lf 2 2Boina O 5 3 U. Boina Uo 3 3L. Boina Lo 2 0Alcantarilha A 5 2 U. Alcantarilha Ua 3 2L. Alcantarilha La 2 0Gila˜o I 6 3 U. Gila˜o Ui 4 3 L. Gila˜o Li 2 1Almargem L 5 3 U. Almargem Ul 3 3L. Almargem Ll 2 0Prado P 4 1 U. Prado Up 2 1L. Prado Lp 2 0Tariquejo T 5 4 U. Tariquejo Ut 3 4L. Tariquejo Lt 3 4Culata C 2 3 U. Culata Uc 0 3L. Culata Lc 2 2Martal M 1 2 U. Martal Um 0 2L. Martal Lm 1 2Domingo Rubio D 7 3 U. Domingo Rubio Ud 5 3L. Domingo Rubio Ld 2 0Roche R 2 1 U. Roche Ur 2 1L. Roche Lr 2 0Salado S 8 2 U. Salado Us 6 2L. Salado Ls 2 0Valle Ll 7 1 U. Valle Ull 5 1L. Valle Lll 2 0Jara J 8 2 U. Jara Uj 6 2L. Jara Lj 2 0Vega G 9 2 U. Vega Ug 7 2L. Vega Lg 2 0168 Hydrobiologia (2013) 703:165–175  1 3  Basin-scale analysesThefirsttwoPCAbcomponentsexplainedalmost80%of the variance (43.9 and 35.3% respectively, eigen-values: 2.6and2.1).Thegradientdefined byPC1 b hadhigher physiographic variables towards its positiveextreme (Table 2; Fig. 2a). Climatic variables are at the positive end of PC2 b , while basins with highconcentrations of dissolved solids are located towardsits negative extreme (Table 2; Fig. 2a). Only the ordination of basins made by PC2 b  was positivelycorrelated with total and native species richness( r   =  0.64,  P \ 0.01 in both cases).Clusteranalysisofenvironmentalfeaturesshowedahigh degree of separation among basins (Fig. 3a). Thefirstsplitseparatedtheenvironmentalcharacteristicsinthe eastern basins (Valle, Jara and Vega basins) fromthe rest, and the second split separated the environ-mental characteristics in most of the western basins(Vale do Bara˜o, Benacoita˜o, Boina and Bensafrim)from the remaining western and central basins. Totalrainfall and solid waste production were significantlydifferentbetweeneasternbasinsandtherest(Kruskal–Wallis test,  H   =  7.2,  P \ 0.01, and  H   =  4.7, P \ 0.05, respectively). Mean temperature, total rain-fall and solid waste production were also significantlydifferent between most western basins and the rest of the western and central basins (Kruskal–Wallis test,  H   =  9.6,  P \ 0.01,  H   =  8.5,  P \ 0.05, and  H   =  7.1, P \ 0.05, respectively). Similarly, cluster analysis of native species richness showed a clear separation of basins (Fig. 4a). The first split separated basins with 7or more native species (Vega, Jara, Salado, Valle andDomingo Rubio basins) from those with less than 7species; the highest similarity was found between themost eastern basins (Vega, Jara, Valle and Salado), allof them with [ 7 species. In the forward stepwiseregression analysis, the inclusion in the model of mainchannel length, basin area, order at mouth and totalrainfall explained most of the variation in nativespecies richness (Table 4).The NMDS Analysis produced two significantdimensions with stress and squared correlation indistances  =  0.50 and 0.99, respectively (Fig. 5a). Table 2  Range of environmental variables used to characterise basins and reaches (see ‘‘Methods’’)Code Range Range (U) Range (L) PC1 PC2Basin variableMean temperature Mt 16.7–17 0.10 0.83Total rainfall Tr 450–975 0.14 0.86Solid waste production Sw 15–100 0.14  - 0.86Main channel length Mc 2.5–25.8 0.91  - 0.10Basin area Ba 0.4–203.1 0.97 0.05Order at mouth Om 1–3 0.86 0.16Reach variableAltitude Al 0–350 2–350 0–7 (4) - 0.71 0.54Linear distance to the estuary De 0–27.3 1.2–27.3 0–2 (4) - 0.60 0.66Order at the sampling point So 1–3 1–2 1–3 (2) 0.68 0.14Channel width Cw 50–1,000 50–500 200–1,000 (2) 0.69  - 0.35Water depth Wd 30–150 30–80 30–150 (3) 0.84  - 0.05Substrate diversity Sd 0.2–1.4 0.2–1.4 0.3–1.3 (1) 0.01 0.80Habitat heterogeneity He 0–200 1–200 0–20 (3) - 0.35 0.49Instream cover Ic 0–90 1–90 0–50 (4) - 0.74 0.16pH pH 7.5–8.7 7.5–8.7 7.5–8.6 (ns) 0.01  - 0.52Conductivity Co 165–10,000 165–5,200 1,300–10,000 (3) 0.49  - 0.68Turbidity Tu 109.6–6,200 109.6–1790 500–6,200 (3) 0.60  - 0.56Water temperature Wt 10.9–27 10.9–25.4 11.8–27 (ns) 0.08  - 0.80Range (U) and Range (L): ranges in upper and lower sites, respectively. PC1 and PC2: PCA loadings (see ‘‘Methods’’). In Range (L),numbers in brackets are the significance levels in Kruskal–Wallis ANOVA test comparing upper and lower sites ( 1 P  B  0.05; 2 P \ 0.01;  3 P \ 0.001;  4 P \ 0.0001;  ns no significant)Hydrobiologia (2013) 703:165–175 169  1 3
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