History

A natural experiment of dietary overlap between introduced Rainbow Trout (Oncorhynchus mykiss) and native Puyen (Galaxias maculatus) in the Santa Cruz River, Patagonia

Description
ABSTRACT Diet overlap between the native Puyen (Galaxias maculatus) and juvenile exotic Rainbow Trout (Oncorhynchus mykiss) was studied in 52 sites located along 306 km of the mainstem of the Santa Cruz River, one of the largest rivers in Patagonia.
Categories
Published
of 15
All materials on our website are shared by users. If you have any questions about copyright issues, please report us to resolve them. We are always happy to assist you.
Related Documents
Share
Transcript
  A natural experiment of dietary overlap between introducedRainbow Trout ( Oncorhynchus mykiss)  and native Puyen( Galaxias maculatus ) in the Santa Cruz River, Patagonia Marina Tagliaferro  &  Ivan Arismendi  & Julio Lancelotti  &  Miguel Pascual Received: 3 February 2014 /Accepted: 16 October 2014 /Published online: 22 October 2014 # Springer Science+Business Media Dordrecht 2014 Abstract  Diet overlap between the native Puyen( Galaxias maculatus ) and juvenile exotic Rainbow Trout ( Oncorhynchus mykiss ) was studied in 52 sites locatedalong 306 km of the mainstem of the Santa Cruz River,one of the largest rivers in Patagonia. The relative abun-dance of both species varied along the river, with threeclearly defined areas including an upstream  “ highRainbow Trout to Puyen ratio ”  area (with abundances of 75 and 25 %, respectively), a midstream  “ intermediateRainbow Trout to Puyen ratio ”  area (relative abundances between 75 and 25 %), and a downstream  “ low RainbowTrout to Puyen ratio ”  area. The diet of the 2 species wasanalyzed across these 3 areas examining stomach content.Diet similarity between species was analyzed using a non-metricmultidimensionalscalingordinationtechnique;preyelectivity was evaluated with the Ivlev ’ s Index; feedingtactics were studied by estimating prey-specific abun-dance. Both species showed a generalist feeding tactic,with Puyen exhibiting a more varied diet. Prey electivitywas similar in both species, with the mayfly (  Meridialarischiloeensis ), stoneflies (  Klapopteryx kuscheli  and  Antarctoperla michaelseni ), and the amphipod (  Hyalella sp.) being the most frequently consumed prey. A signifi-cant diet overlap was found only in the downstream areaswhere a higher proportion of native fish occurs. The lowdiet overlap in upstream locations might be because of thehighdensityofRainbowTrout;whilemid-streamcouldbedue to the high secondary productivity spots. Our resultssuggest that the diet of native Puyenchangedinrelation tothe abundances of Rainbow Trout in the stream. Keywords  Troutinvasion.Galaxiids.n-MDS.Feedingtactics Introduction Major decreases in the biodiversity of aquatic systemsduring the last century have been attributed to habitat loss and species introduction (Mack et al. 2000; Muotka and Syrjänen 2007). Salmonids (genus  Oncorhynchus , Salmo  and  Salvelinus ) are among the most widely in-troduced fish taxa around the globe (Welcomme 1988),mostly for recreational and aquaculture purposes(McDowall 1994; Pascual and Ciancio 2007). Salmonid introductions have been broadly implicatedin the decline of native biota (Crowl et al. 1992; Greigand McIntosh 2006; Soto et al. 2007; Arismendi et al. 2009), with consequences at all levels of ecologicalorganization including behavior alterations at indi-vidual level (Simon and Townsend 2003), reduc-tion in population abundance (Moyle and Light  Environ Biol Fish (2015) 98:1311  –  1325DOI 10.1007/s10641-014-0360-6M. Tagliaferro ( * )División de Ciencias Básicas - Universidad Nacional deLuján. Ruta 5 y Av. Constitución,Luján (6700) Buenos Aires, Argentina e-mail: azulmarinita@gmail.comI. ArismendiDepartment of Fisheries and Wildlife, Oregon StateUniversity,3200 SW Jefferson Way, Corvallis, OR 97331, USAJ. Lancelotti : M. PascualCONICET, Centro Nacional Patagónico,Bld. Brown 2915, Puerto Madryn, Chubut, Argentina   1996; Townsend 2002), and trophic cascades (Simon and Townsend 2003).Starting in the early 20 th century, and pushed by thehigh value of salmonids for fisheries and aquaculture,governments in Chile (Basulto 2003), New Zealand(McDowall 1990; Flecker and Townsend 1994), and Argentina (Tulian 1908; MacCrimmon 1971; Lever  1996) promoted the introduction and establishment of salmonids in the Southern Hemisphere. More than tensalmonids species were introduced in southern rivers inChile(Arismendietal.2014)andArgentina(Pascualetal.2002). However, it has only been during the last 30 yearsthat the ecological consequences of salmonid establish-ment in these areas started to be observed and investigatedwith a special focus on their effect on native communities(e.g.,Crowletal.1992;Arismendietal.2009;Youngetal. 2010),theresourcesused(KusabsandSwales1991;Buria  et al. 2007; Penaluna et al. 2009), competition and preda- tion (McIntosh et al. 1992; Macchi et al. 1999; McDowall 2003), and niche overlap (Vargas et al. 2010; Arismendi et al. 2012; Correa et al. 2012; McHugh et al. 2012). The study of diet breadth between the exotic andselected native species provides a practical entry point to the understanding of the impacts of salmonids inPatagonia (Soto et al. 2007; Habit et al. 2010). Whereas niches may be characterized as measures of resource utilization (Giller  1984), diet breadth refers tothe utilization of some of the same type of resources bytwoormorespeciesofresourceconsumers(ColwellandFutuyma  1971; Abrams 1980). In particular, exotic spe- cies provide natural experiments where the ecologicaltheory (e.g. optimal foraging after an invasion) may betested empirically through evaluating habitat segrega-tion, density reduction, niche shifts, food intake reduc-tion, prey composition alteration, or size structurechanges (Bøhn et al. 2008), with possible temporalshifts in feeding habits (Coghlan et al. 2007).Experimental manipulations of the density of exoticspecies arguably provide the most powerful approach tostudysystem-level effects of single species onnative com-munities (Tilman 1987; Hansson et al. 1998). However, rivers are large and open systems where fish are highlymobile and thus, manipulation is often very difficult.Researchers are then limited to looking for natural exper-iments, where naturally contrasting densities occur. Thisapproachhasbeenapplied,forinstance,tostudytheeffectsof Rainbow Trout ( Oncorhynchus mykiss ) on galaxiids( Galaxias  spp.) niche width (Townsend 2002; McHughetal.2012)andthe interactionforfoodandspacebetween populationsofgalaxiidsandjuveniletroutinNewZealand(Glova et al. 1992; McIntosh 2000; McDowall 2003; McIntosh et al. 2010). It has also been used in SouthAmerica to study habitat use and segregation of nativefishes and trout in Chilean streams (Penaluna et al. 2009)and differential piscivory effects on galaxiids by native predators and trout in Northern Patagonia (Arismendiet al. 2012; Juncos et al. 2013). Oneofthemaindeficienciesinourcurrentknowledgeconcerning exotic trout in southern Patagonia is about trophic relationships and interactions with conspicuousnative fishes such as Galaxiids and Siluriforms (Pascualet al. 2002). The aim of the present study is to evaluatediet overlap of underyearling Rainbow Trout ( Oncorhynchus mykiss  Walbaum 1792) in sympatry withthe most abundant native species Puyen ( Galaxiasmaculatus  Jenyns, 1842), in the Santa Cruz River, oneof the largest rivers in the region. We concentrated our effort during the low flow season (springtime) along306kmofthemainstemoftheSantaCruzRiver,betweenthe head lake, Lago Argentino, and the outflow into theAtlantic Ocean (Fig. 1). We evaluated if Rainbow Trout and Puyen are using similar food resources along a gradientofcontrastingrelativeabundanceofbothspeciesas a preliminary exploration of mechanisms of competi-tion avoidance.Since no information regarding native galaxiids distri- butionandfeedinghabits before troutinvasionis availablefor large rivers, this study represents an important first approximation to examine interspecific interactions be-tween salmonids and native fishes in this understudiedregion. Because the Santa Cruz River can be considereda minimally human-influenced river (Brunet et al. 2005;Tagliaferro et al. 2013), our study will also provide a  baseline for future comparison with other large rivers. Materials and methods Study area The Santa Cruz River (50° S; 70° W) srcinates in twooligotrophic to ultra-oligotrophic large glacial lakes,Viedma and Argentino, and flows uninterrupted for 382 km across the Patagonian plateau to drain into theAtlanticOcean(Fig.1;Brunetetal.2005).Theriverhas anaveragedischargeof691m 3 s − 1 (min.278.1m 3 s − 1 inSeptember and max. 1,278 m 3 s − 1 in March), which ishighly predictable due to a glacial dominated regime 1312 Environ Biol Fish (2015) 98:1311  –  1325  (Tagliaferroetal.2013).Thisriverhaslow variabilityof theenvironmentalstructure(Tagliaferroetal.2013);itisan un-braided river (100  –  200 m wide×382 km length)and temperature between upstream/ downstream areasdiffersonly by3  –  5 °C ata given time ofthe year. Alongthe river, temperature varies only in 2 to 5 °C during a  period of few weeks, e.g. temperature variation duringsampling was 5.7±0.5 °C, 7.0±0.9 °C, and 8.6±0.9 °Cfor upstream, midstream and downstream areas respec-tively). The Santa Cruz River has been characterized asthe one of the poorest in terms of macroinvertebrateabundance among 40 Patagonian rivers (Miserendino2001).SamplingWe sampled fish and macroinvertebrates duringSeptember2010(lowflowperiod)in52sitesatintervalsof 6 km along the Santa Cruz River (50° S; 70° W,Fig. 1). The uppermost site was located in Charles Fuhr (9.8kmdownstreamfromtheLakeArgentino,50°16 ′ S;71°53 ′  W) and the lowermost site was located inComandanteLuis Piedra Buena (50°S;70°60 ′ W),closeto the river  ’ s estuary and 315.8 km from LakeArgentino. We captured fish (length range: 50  –  140 mm) using standard single-pass electrofishing pro-cedures from littoral zone to depths of 0.6 m (Jones andStockwell 1995; Meador et al. 2003). The equipment  used was a Smith-Root LR-24 electrofisher set to a frequency of 90 Hz and a pulse width of 3 ms. At eachsite, a coastal wadable stretch of 100 m was sampledfollowing a zig-zag track. Catchability may have dif-fered between fish species, but we assumed it to besimilar throughout sample sites. All fish were counted,fork length-measured with a digital caliper (0.01 mmnearest unit), and weighed on a Mettler PC 440 Delta Range balance (0.003 g nearest unit). We used thenumber of individuals captured in the 100 of river as Fig. 1  Map of the Santa Cruz River, Argentina. Sampling sites are located between Charles Fuhr Bridge and Comandante. Luis Piedra Buena Town (between arrows)Environ Biol Fish (2015) 98:1311  –  1325 1313  an indirect measurement of abundance (CPUE).Stomachsfrom5to10randomlyselectedfishfromeachspecies and site were removed and stored.Macroinvertebrate samples were obtained with a kick-net of 450  μ  m mesh size covering 0.25 m 2 , integratingone area for each sample (Tagliaferro et al. 2013). Drift samples were not included in the analyses because the biomass contribution to the total macroinvertebrate wasless than 2 % along the river (Tagliaferro 2014).Macroinvertebrate samples were stored in a portablefreezer at   − 18 °C. At the laboratory, both stomachcontents and macroinvertebrate samples were trans-ferred into 70 % ethanol for further separation andidentification of organisms to the lowest possible taxo-nomic level, employing a Zeiss stereomicroscope(6.5 X). We identified taxa following Lopretto and Tell(1995), and Domínguez and Fernández (2009). We measuredfree-living macroinvertebrates richnessand abundance, and dry weight of consumed prey for the dataanalysis.Tocalculate driedweight,weassignedindividuals to a given taxon, dried to a constant weight at 65 °C (24 h), and weighed on an analytical ShimadzuAUW-220 scale (range: 220 g  –   10 mg, error: 1 mg).Whenpreywas partially digested, weight was estimatedfrom complete items of the same length. Chironomidaespecies, which were similar in size and ecological role,were pooled as one group. Other small taxa (e.g.Oligochaeta, Glossosomatidae, and Trichoptera) werealso pooled as one group.Fish relative abundances were estimated for eachsampling site to assess patterns of distribution of Rainbow Trout and Puyen. Three different sections of the river were defined based on the Rainbow Trout toPuyenratio:an “ upstream ” area,withhighproportionof Rainbow Trout (over 0.75), a   “ downstream ”  with low proportion (less that 0.25), and a   “ mid-stream ”  withintermediate proportion (0.25 and 0.75). Stomach con-tents of 17 Puyen and 32 Rainbow Trout were analyzedinthe upstreamarea; while inmid-stream, 82Puyenand116 Rainbow Trout, and in downstream area 101stomachs of Puyen and 44 of Rainbow Trout wereexamined.Fish dietsWe used three methods to characterize the fish diets(Hyslop 1980; Chipps and Garvey 2007): including (a) the frequency of occurrence ( %Fi ) of a given prey type,defined as the mean number of stomachs in which that  prey occurs in relation to all the stomach studied for each area; (b) the biomass contribution  (%Bi ) of a preyto the dry weight of each stomach contents, and (c) preyspecific abundance (  Pi ; Amundsen et al. 1996). Theseindices were calculated as follow:%  F  i  ¼  N  i  N  %  B i  ¼ X it  S  i S  t  ! *100  P  i  ¼ X it  S  i S  ti ! *100where  N  i  is the number of fish with prey  i  in their stomach,  N   is the total number of fish with stomachcontents,  S  i  is the contribution of prey  i  to stomachfullness in dried mass,  S  t   is the total stomach biomassof all fish, and  S  ti  is the total stomach fullness of fishwith prey  i  in their stomach. At each area (upstream,mid-stream, and downstream),  Fi  and  Pi  were used tocreate a diagram of   “ feeding tactics ”  (Amundsen et al.1996).Multivariate analysis of dietsWe used a non-metric multidimensional scaling (N-MDS) ordination technique to compare the similarity of diets between species and across areas using the Bray  –  Curtis distance metric (Clarke 1993; Marshall and Elliott 1997). Based on an iterative optimization procedure, diet compositions were rearranged to minimize a measure of disagreement or stress between their distances in 2-D(Kruskal 1964). The resulting coordinates of each point from the 2-D plot provided a collective index of howunique the diet of a given fish was. The proximity of  pointsina2-Dplotindicatesahigherdegreeofsimilarity,whereas more dissimilar points are positioned further apart. We used the standard squared root transformationto down-weight the importance of the highly abundant  preys (see Clarke and Warwick  2001 for more details).We used the software PRIMER v6.1.5 (Clarke andGorley 2006) to produce the ordination plot of theBray  –  Curtis similarity coefficient of square root trans-formed % frequency of prey for each individual(Rainbow Trout or Puyen) and % biomass of each preyat each fish species (Clarke and Warwick  2001).We tested the hypothesis of no difference amonggroups(fish species and areas)of diets using an analysisof similarity (ANOSIM). The ANOSIM is a  1314 Environ Biol Fish (2015) 98:1311  –  1325        T    a      b      l    e      1     M   a   c   r   o    i   n   v   e   r    t   e    b   r   a    t   e   n   a    t   u   r   a    l   a    b   u   n    d   a   n   c   e    (    %    D    ) ,    f   r   e   q   u   e   n   c   y   o    f   o   c   c   u   r   r   e   n   c   e    (    %    F    i    )   a   n    d   p   r   e   y  -   s   p   e   c    i    f    i   c   a    b   u   n    d   a   n   c   e    i   n    b    i   o   m   a   s   s    (    P    i  -    B    )   o    f   p   r   e   y   s    i   n   s    t   o   m   a   c    h   c   o   n    t   e   n    t   s   o    f     O .   m   y    k   i   s   s    a   n    d     G .   m   a   c   u    l   a   t   u   s    ;   v   a    l   u   e   s   a   r   e   c   a    l   c   u    l   a    t   e    d   a    t   e   a   c    h   a   r   e   a    U   p   s    t   r   e   a   m    M    i    d  -   s    t   r   e   a   m    D   o   w   n   s    t   r   e   a   m    T   r   o   u    t    P   u   y   e   n    T   r   o   u    t    P   u   y   e   n    T   r   o   u    t    P   u   y   e   n    T   a   x   a    %    D    %    F    i    %    B    i    P    i    %    F    i    %    B    i    P    i    %    D    %    F    i    %    B    i    P    i    %    F    i    %    B    i    P    i    %    D    %    F    i    %    B    i    P    i    %    F    i    %    B    i    P    i    M   o    l    l   u   s   c   a     C    h   i    l   i   n   a    s   p .    (    C    h    )    2    2 .    5    –   –   –   –   –     6 .    5    0 .    3    1    9 .    9    3 .    7    0 .    2    1    3 .    6    0 .    7    –   –   –   –   –   –     H   e    l   e   o    b   i   a    s   p .    (    H   e    )    –   –   –   –   –   –   –   –   –   –   –   –     5 .    1    2 .    4    0 .    9    3    7 .    8    –   –   –     L   y   m   n   a   e   a    s   p .    (    L   y    )    –     2    0 .    6    2    1    3    3 .    6    2    3 .    9    3    8    9 .    7    4 .    8    3    5 .    7    1    4 .    8    0 .    8    4    1 .    8    5    2 .    9    2 .    3    2 .    6    7    9 .    5    4 .    0    4 .    9    3    0 .    4    A   n   n   e    l    i    d   a    H    i   r   u    d    i   n   e   a    (    H    i   r    )    0 .    1    –   –   –   –   –   –     0 .    3    –   –   –     3 .    7    0 .    3    1    8 .    7    1 .    8    –   –   –   –   –   –     N   a    i    d    i    d   a   e    (    N    )    0 .    2    –   –   –     2    0 .    1    2 .    0    6    0 .    1    3 .    2    0 .    9    1    0    0    7 .    4    0 .    8    3 .    6    –   –   –   –     4 .    0    0 .    3    2 .    0    A   c   a   r    i    A   c   a   r    i   s   p   p .    (    A   c    )    0 .    1    –   –   –     <    0 .    1    0 .    1    1 .    5    4    –   –   –   –   –   –   –   –   –   –   –     4 .    0    0 .    2    1 .    0    C   r   u   s    t   a   c   e   a     H   y   a    l   e    l    l   a    s   p   p .    (    H    )    2    2 .    6    4    2    1    3 .    4    2    1 .    0    4    5 .    0    3    1 .    4    2    0 .    5    1    8    7    1 .    0    2    1 .    2    3    7 .    4    5    5 .    6    2    4 .    1    3    3 .    5    1    7 .    4    3    5 .    0    9 .    5    2    1 .    5    2    0 .    0    5 .    7    1    7 .    0    E   p    h   e   m   e   r   o   p    t   e   r   a     A   n    d   e   s   i   o   p   s    s   p .    (    A    d    )    0 .    2    1    9    5 .    1    1    8 .    0    1    6 .    0    5 .    5    1    7    –     9 .    7    2 .    8    4 .    0    7 .    4    1 .    5    3 .    7    0 .    3    1    0 .    0    1 .    5    1    1 .    0    4 .    0    1 .    3    1    6 .    5     M   e   r   i    d   i   a    l   a   r   i   s   c    h   i    l   o   e   e   n   s   i   s     (    M   c    )    1    9 .    9    6    3    2    9    3    8 .    5    1    7 .    0    1    0 .    4    9    8    1    1    9 .    7    1    3 .    1    2    5 .    6    7 .    4    1    5 .    0    1    9 .    2    4 .    4    5    7 .    0    2    1 .    6    3    8 .    5    2    4 .    0    9 .    1    4    1 .    0    P    l   e   c   o   p    t   e   r   a     A   u    b   e   r   t   o   p   e   r    l   a   i    l    l   i   e   s   i     (    A    i    )    5 .    1    5    0 .    6    2    2 .    0    –   –   –     0 .    6    5    4 .    8    1 .    9    7    4 .    4    –   –   –     1 .    7    –   –   –     1    6 .    0    <    0 .    1    1    3 .    5     A   n   t   a   r   c   t   o   p   e   r    l   a   m   i   c    h   a   e    l   s   e   n   i     (    A   m    )    0 .    0    2    4    1    2    4    2 .    0    2    3 .    2    1    0 .    0    2    2 .    1    –     2    5 .    8    8 .    5    3    2 .    2    3    3 .    3    5 .    9    3    5 .    2    0 .    1    4    6 .    1    2    1 .    4    4    2 .    0    2    4 .    0    1    4 .    5    8    6 .    3     K    l   a   p   o   p   t   e   r   y   x    k   u   s   c    h   e    l   i     (    K    k    )    0 .    2    2    2    1    3    8    4 .    0    1    6 .    0    8 .    8    7    9 .    4    4 .    9    6 .    5    1    6 .    4    6    5 .    3    1    1 .    1    1    0 .    6    7    6 .    9    0 .    2    1    6 .    2    8 .    9    6    7 .    3    8 .    0    8 .    1    9    2 .    0     L   i   m   n   o   p   e   r    l   a   j   a    f    f   u   e    l   i     (    L    j    )    –     3    8    9 .    1    7 .    3    1    5 .    0    8 .    8    3    3    2 .    5    6    1 .    3    1    4 .    1    1    2 .    3    3    7 .    0    1    0 .    7    1    4 .    3    6 .    1    8    4 .    3    2    1 .    5    1    6 .    3    6    3 .    0    2    9 .    1    3    8 .    9    C   o    l   e   o   p    t   e   r   a     L   u   c    h   o   e    l   m   i   s   c   e    k   a    l   o   v   i   c   i     (    L   c    )    1    4 .    2    1    2    2    4 .    5    1    1 .    0    2 .    5    2    8    1    9    4    8 .    4    6 .    7    7 .    9    2    5 .    9    7 .    3    4 .    3    8 .    3    1    8 .    0    3 .    0    1 .    3    8 .    0    0 .    9    1    1 .    3     L   u   c    h   o   e    l   m   i   s   c   e    k   a    l   o   v   i   c   i    a    d   u    l    t    (   e    l    A    )    –   –   –   –     3    <    0 .    1    8 .    8    4    –     3 .    2    –     2 .    7    –   –   –   –   –   –   –   –   –   –     V   e    l   i   i    d   a   e    –   –   –   –   –   –   –   –   –   –   –     1    4 .    8    0 .    3    7    2 .    7    –   –   –   –   –   –   –     T   r    i   c    h   o   p    t   e   r   a    M   a   s    t    i   g   o   p    t    i    l   a   s   p .    (    M    )    0 .    3    1    2    –     7 .    2    2 .    5    0 .    2    2 .    0    6    –     1    9 .    4    0 .    3    2 .    0    3 .    7    0 .    2    0 .    9    –   –   –   –   –   –   –     R    h   e   o   c    h   o   r   e   m   a    /     A    t   o   p   s   y   c    h   e   s   p .    (    H   y    )    0 .    2    2    0    3 .    5    1    6 .    7    1    8 .    0    2 .    1    1    7    –     2    2 .    6    1 .    9    8 .    4    1    1 .    1    1 .    8    1    2 .    6    0 .    3    2    6 .    0    6 .    7    1    7 .    0    8 .    0    1 .    7    2 .    8     C   a   i    l    l   o   m   a    s   p .    (    C    )    0 .    0    4    2    0 .    4    7 .    0    3 .    7    6    –   –     0 .    4    –   –   –   –   –     3    0 .    2    8    –   –   –     S   m   i   c   r   i    d   e   a    d   i   t    h   y   r   a     (    S    d    )    2 .    2    8    0 .    1    2 .    1    8 .    0    0 .    8    7 .    6    6    1 .    2    6 .    5    0 .    1    4 .    5    –   –   –   –   –     0 .    1    –   –   –   – Environ Biol Fish (2015) 98:1311  –  1325 1315
Search
Similar documents
View more...
Related Search
We Need Your Support
Thank you for visiting our website and your interest in our free products and services. We are nonprofit website to share and download documents. To the running of this website, we need your help to support us.

Thanks to everyone for your continued support.

No, Thanks