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Composicion del paisaje como determinante de la diversidad y de grupos funcionales alimentarios de macroinvertebrados acuaticos en rios de la Araucania, Chile.

Landscape composition as a determinant of diversity and functional feeding groups of aquatic macroinvertebrates in southern rivers of the Araucania, Chile

INTRODUCTION

Among the world's biogeographical regions, the ecosystems of the Andean region are among the most diverse on Earth (Udvardy, 1975; Myers et al., 2000; Olson et al., 2001; Morrone, 2006). The watersheds of these ecosystems have been affected in recent years by disturbances of anthropic origin, which directly or indirectly affect the functioning of aquatic systems (Barletta et al., 2010). Important environmental stressors are those generated by productive activities such as agriculture, deforestation, plantations of exotic species, industry and mine waste pollution (Roldan, 1999). Although these activities are recognised as the principal generators of the local economies of developing countries (Barbier, 2004), in many cases no control or management measures are applied for the protection of biological communities, and as a result biodiversity is disappearing rapidly (Mittermeier et al., 2011).

Benthic macroinvertebrates are one of the most important components of freshwater ecosystems. These are mainly immature stages of insects, most of which spend at least one stage of their life cycle in aquatic systems before emerging in the adult state (Hauer & Resh, 2006). This fauna plays an important role in aquatic systems since they are of vital importance in the nutrient cycle, acting as decomposers of organic matter, forming part of food chains and transferring energy to higher links; this makes them useful as bioindicators of organic pollution, etc. (Wallace & Webster, 1996). The seasonal and spatial distribution of these invertebrates in watercourses has been extensively debated (Summerville & Crist, 2003; Sporka et al., 2006). One area of discussion is the analysis of their life cycles; another concern is the principal factors which determine their diversity in lotic systems, i.e., disturbances to water flow, substrate structure-composition, physical and chemical factors in the water and high variations in the ecotone (Wais, 1987; Evans & Norris, 1997; Bradley & Ormerod, 2001; Huttunen et al., 2012). The latter generates a great diversity of habitats, offering macroinvertebrates a wide range of food supply and thus allowing functional feeding groups (FFGs) to vary throughout the course of a river (Vannote et al., 1980).

The south-central region of Chile belongs to the Mediterranean forest biome (Olson et al., 2001), it possesses a great diversity of natural ecosystems. In particular, its coastal forests harbour great biological diversity, making it a world biodiversity hotspot (Myers et al., 2000; Valdovinos, 2006). A wide variety of ecosystems are also found in this geographical zone, such as plains, wetlands and mountain ranges, which contain the densest and most diverse evergreen forests of southern South America (Villagran, 1991; Pena-Cortes et al., 2009). Historically this territory has experienced high levels of anthropic activity (Pena-Cortes et al., 2011) causing changes to the ecological landscape, especially the south-central region of Chile, which is one of the zones most affected by deforestation of native forest and its replacement by exotic species such as Pinus spp. and Eucalyptus spp. (4.1% annual loss of native forests) (Altamirano & Lara, 2010).

The purpose of this study is to relate the diversity of macroinvertebrates and functional feeding groups across different land uses in contrasting seasons of the year. The results of the study will also provide a taxonomic database of freshwater macroinvertebrates, which may be used in future conservation and biomonitoring studies in a zone of high biological diversity.

MATERIALS AND METHODS

Study area

The study area corresponded to four basins on the Pacific slope of the Araucania, Chile (37[degrees]35'-39[degrees]37'S). The climate of this region is oceanic with Mediterranean influence, with an average annual precipitation between 1,200 and 1,600 mm (Di Castri & Hajek, 1976). The atmospheric data for temperature, rainfall and wind speed were also recorded, from the Climatological Yearbook 2010 for the city of Temuco (DGAC, 2011). The geomorphology varies from mountain systems to marine abrasion platforms. The maximum and minimum altitudes of the basins are 870 to -2 m above sea level (Pena-Cortes et al., 2011). Eleven sampling stations were selected and classified into six groups according to the land use of coastal basins of southern Chile (Pena-Cortes et al., 2009) (see Table 1). Based on the sizes of the four basins, the following stations were selected: one in the Danquil basin (Station 1), one in the Boyeco basin (Station 2), three in the Moncul basin (Stations 4, 6 and 8) and six in the Queule basin (Stations 3, 5, 7, 9, 10 and 11). All eleven studied streams are 3rd (St. 1, 4, 5 and 8), 4th (St. 2, 6, 7, 9 and 10) and 5 th (St. 3 and 11) order, after Strahler (1957) (Fig. 1, Table 1).

Benthic macroinvertebrates sampling

The samples of freshwater benthic macroinvertebrates were collected by seasons (summer: January, autumn: April, winter: July and spring: November 2010). At each sampling station three replicates were taken with a Surber sampler (900 [cm.sup.2], 500 [micro]m pore size) from riffles (the most common habitat type). The samples were fixed in situ with 90% ethanol and subsequently taken to the Benthos Laboratory of the Institute of Marine and Limnological Sciences, Universidad Austral de Chile, where they were separated and identified to the lowest possible taxonomic level under microscope and stereoscopic microscope. The macroinvertebrates were then classified into seven Functional Feeding Groups (FFGs): shredders, collector-gatherers, collector-filterers, scrapers, predators, detritivores and parasites, using the criteria of Merrit & Cummins (1996), Miserendino & Pizzolon (2003) and Perez et al. (2004).

Water sampling

Water samples were collected together with the macroinvertebrate samples during the morning (8-11 am); they were deposited in bottles and taken to the Analytical Chemistry Laboratory of the Institute of Chemistry and Natural Resources, Universidad de Talca, for determination of the following parameters: bio-chemical oxygen demand, suspended solids, dissolved oxygen, chlorides, sulphates, dissolved solids, nitrates and phosphates. All the methods of analysis were carried out according to the standard methods for the examination of water and waste-water (APHA, 2005). In addition, temperature, pH and conductivity were measured in situ. The physical and chemical variables were analysed to obtain a measurement of water quality for each sampling station, using the methodology employed by Fierro et al. (2012) according to the secondary environmental quality standard for the protection of Chilean continental waters (CONAMA, 2004).

Statistical analysis

Two way ANOVA analyses, with sampling stations and seasons as categorical variables as treatments, and abundance or species richness as response variables followed by post hoc tests when significant (Tukey test P < 0.05) were used to assess differences in sampling stations uses and seasons. These analyses were conducted using the software package Statistica v7.0.

In addition, the biological data were compared considering the data of mean macroinvertebrates density (means for each season) per station. In order to avoid over estimating the abundance of infrequent taxa, the data were first transformed to [log.sub.10] (x+1) to construct the Bray-Curtis similarity matrix (Bray & Curtis, 1957), from which a dendrogram was constructed using group average as criterion (999 permutations). The Simprof test was used on the dendrogram to identify statistically significant groups (P < 0.05). The similarity matrix was also analyzed using a non-metric multidimensional scaling analysis (nMDS) as the ordination method, representing the similitude of the sampling stations in two dimensions, based on the abundance and composition of the macroinvertebrates communities.

The BIOENV (Bioenvironmental, Clarke & Ainsworth, 1993) analysis was used to determine possible associations between the environmental variables and the biological data, using Spearman correlation. This analysis used the Bray-Curtis similitude data based on the abundance and richness of benthonic macroinvertebrates (transformed to log x+1) and the physical and chemical parameters (land use, altitude, lotic order, temperature, conductivity, total dissolved solids, pH, dissolved oxygen biochemical oxygen demand, phosphates, nitrates, apparent colour, chlorides and sulphates); these data were first transformed to [log.sub.10] (x+1) to normalise them. This analysis allowed us to evaluate the physical and chemical variables that were significantly related to the structure of the biota.

The structure of the macroinvertebrate community was analysed using Margalefs index, Pielou's evenness index and the Shannon-Weaver index (with base "e"). To represent the proportional abundance of each FFG, the cumulative values of the four seasons were used. All the above analyses were performed using PRIMER V.6 software (Clarke & Warwick, 1994).

RESULTS

Environmental parameters

Precipitation within the study area varied between 14.6 and 170.6 mm in April and June 2010 respectively; the minimum mean air temperature was 6.1[degrees]C in July and the maximum 14.7[degrees]C in January 2010. Finally, the wind varied between 3 and 11 knots in April-May and June 2010 respectively.

Following the secondary environmental quality standard for the protection of Chilean continental waters all the physical and chemical analyses indicated exceptional water quality for all stations sampled throughout the year (Table 3).

Macroinvertebrates community

A total of 104 taxa of aquatic benthic macroinvertebrates were collected; the dominant taxa were immature phases of insects throughout the study area and all year round. The most representative orders were Diptera (26 taxa), Trichoptera (19 taxa), Ephemeroptera (17 taxa), Plecoptera (15 taxa) and Coleoptera (8 taxa) (Appendix 1). The greatest abundance and richness of taxa across all sampling stations occurred in summer, with 24,112 ind [m.sup.-2] (80 taxa, the most abundant species was Meridialaris diguillina (Leptophlebiidae, Ephemeroptera) with 5,004 ind [m.sup.-2]), followed by autumn with 22,363 ind [m.sup.-2] (79 taxa, the most abundant was Limnoperla jaffueli (Gripopterygidae, Plecoptera) with 3,533 ind [m.sup.-2]), spring with 14,907 ind [m.sup.-2] (63 taxa, Andesiops torrens (Baetidae, Ephemeroptera) was the most abundant species with 1,821 ind [m.sup.-2]) and winter with 9,141 ind [m.sup.-2] (64 taxa, the most abundant was again L. jaffueli with 2,406 ind [m.sup.-2]) (Appendix 1).

The highest mean density value during the whole year was recorded at land use native forest (station 10, Queule basin), especially during summer where peak abundance was found: 5,505 ind [m.sup.-2]; while the least abundant was recorded at forest plantation and herbaceous vegetation (station 1, Danquil basin), especially during autumn, where the lowest abundance was recorded: 399 ind [m.sup.-2] (Table 1, Fig. 2).

Significant differences in taxon richness (P < 0.001) and abundance (P < 0.001) of macroinvertebrates were found among sampling stations (land uses) and seasons (Table 2). According to the analysis of the classification and ordination of seasons based on abundance data in Appendix 1, which indicated five groups. Sites with more anthropic activities having significantly lower richness and abundance than the rest, and sampling stations located in dominant native forest having higher richness than mixed land use (native forest, forest plantation and livestock farming). This agreed with their spatial locations in the basins, namely stations 1 (Danquil basin), 2 (Boyeco basin) and 4 (Moncul basin), which were at the lowest altitude (<250 masl) and more affected by anthropic activity (Table 1, Fig. 3). In addition, station 10 (native forest predominate) presented the largest number of taxa (66), while the lowest number was obtained at station 1 (40 taxa), which coincided with Margalefs index of species richness. According to Pielou's evenness index (J) for the distribution of abundance for each taxa, all the stations presented dominant taxa (values greater than 0.55). Finally the Shannon-Wiener index values (H') ranged between 2.16 for station 5 (mixed use) and 2.91 for station 10 (Table 4).

Seasonally, Shannon-Weaver diversity values ranged between 2.82 and 1.21; maximum values were recorded at station 10 in autumn and spring, while minimum values were recorded at stations 2 and 5 (mixed land use), both in winter. Most stations showed values greater than 0.55 for Pielou's evenness index (J), indicating presence of dominant taxa; only three stations showed values less than 0.55: station 2 and 5 in winter and station 7 in spring. The highest values of Margalef's index of species richness were recorded in station 10 throughout the year (data not shown).

The BIOENV procedure showed a strong relationship between community macroinvertebrate distribution and the measured environmental variables. The variables that best explained the multivariate relationships between the biotic and abiotic matrices were land use, altitude, temperature, suspended solids and nitrates, with a highly significant Spearman correlation (p = 0.730; P < 0.008).

Functional Feeding Groups (FFGs)

According to the FFGs, 31 taxa were assigned to collector-gatherers, 25 to predators, 18 to collector-filterers, 14 to shredders, 10 to grazers, 4 to detritivores and 2 to parasites (Appendix 1).

The most representative FFGs of all land use were collector-gatherers, which were dominant in eight stations: station 1 with 46.9% of the total community; station 3 with 56.4%; station 6 with 55.8%; station 7 with 48.4%; station 8 with 51.2%; station 9 with 56.1%; station 10 with 36.7% and station 11 with 54.4% of the total community. Shredders were somewhat dominant in station 2 with 36.8% of the total community and station 5 with 44.9%; finally collector-filterers were dominant only in station 4 (41.6%). The predators presented consistently abundances below 25%, detritivores less than 5%, scrapers less than 2% and finally parasites less than 1% (Fig. 4).

Among seasons, collectors were dominant in summer, autumn and spring with 53.8%, 45.6% and 39.9% relative abundance, respectively. In winter two FFGs were dominant; the shredders (35.3%) and the collectors (34.2%). The representation of the other FFGs was less than 20% (Fig. 5).

DISCUSSION

Our main objective was to investigate the invertebrate community composition between different landscape compositions. This is a very significant factor influencing the freshwater macrofauna, affecting their abundance, spatial distribution, community parameters, etc. (Standford, 2006). We found a high taxonomic diversity of aquatic benthic macroinvertebrates in coastal basins of south central Chile, consistent with the exceptional quality of the water sampled in the rivers.

In the basins located in the coastal zone of the Araucania Region, macroinvertebrate assemblages were mainly affected by basin-related variables (land use, altitude) and water (temperature, suspended solids and nitrates). Similar trends were found in other studies (Miserendino & Masi, 2010; Egler et al., 2012) which indicate that macroinvertebrate fauna can be altered by land use practices (e.g., agriculture, forest plantations). Macroinvertebrates showed significant differences between stations and seasons responding to this gradient; sites with strong anthropogenic pressures had lower abundances than low impacted sites. The Queule basin, specifically station 10 (high altitude), presented the greatest richness and abundance of the whole study area, due to the high proportion of native forest, roble (Nothofagus obliqua), rauli (N. alpina) and coihue (N. dombeyi), and the low proportion of the matrix consisting of farmland and forestry plantation (Pena-Cortes et al., 2009). In the opposite situation, the stations 1 (Danquil basin), 2 (Boyeco basin) and 4 (Moncul basin), reflected in the cluster analysis which assigned them to separate groups with specific species ensembles. These stations were characterised by low altitude and by being subjected to strong pressures of use, e.g., for agricultural, forestry and tourism activities (Pena-Cortes et al., 2009). The geomorphological slopes at these stations are almost zero, and therefore there are zones with greater deposits (i.e., potamon environments). This agrees with the findings of Brown & Brussock (1991) and Buffagni & Comin (2000) who reported lower richness and abundance in the macroinvertebrate community on pools habitats. The lowest values for Shannon's diversity index were obtained at station 5 (Queule basin), specifically in autumn when only 23 taxa and 510 ind [m.sup.-2] were recorded. This was due in part to disturbance of the bed by the construction of a bridge, which increased the concentration of suspended solids in the water; according to Suren et al. (2005) and Billota & Brazier (2008) this is one of the principal factors influencing the presence of aquatic biota. However this situation was reversed in the later samples, evidence of rapid recovery of the habitat, possibly by colonisation from tributaries (Rice et al., 2001).

Some taxa, especially families, tend to present wide geographical distributions, since they tolerate greater changes in the environment and are therefore generally less sensitive to pollution (e.g., organic) (Winterbourn et al., 1981). The species Meridialaris diguillina (Leptophlebiidae), Limnoperla jaffueli (Gripopterygidae) and Andesiops torrens (Baetidae) were the most abundant throughout the study area. These same taxa have been described as a principal component of the macroinvertebrate community in central and southern rivers of Chile (Campos et al., 1984; Habit et al., 1998; Guevara-Cardona et al., 2006; Fierro et al., 2012), and indeed in other South American rivers (Miserendino, 2001; Miserendino & Pizzolon, 2003; Molina et al., 2008; Kleine et al., 2011). All these situations occurred in undisturbed rivers with lotic and rhithron environments (i.e., sectors with great slope, high current velocities, stable low temperatures, high concentration of oxygen, etc.), properties that would tend to favour the presence of these taxa.

Various authors (e.g., Linke et al., 1999; Huttunen et al., 2012) propose performing at least one year of sampling in order to avoid underestimating taxon richness for use in bio-assessments. This is because the macroinvertebrate community changes not only due to anthropic effects, but also due to seasonal and/or biological changes. The seasonal changes are mainly the result of different life cycles (i.e., univoltine or bivoltine) which are correspondingly synchronized (Cayrou & Cereghino, 2005).

In the study area, the physical and chemical variables of the water presented no great variations attributable to anthropic activities in the basins, so any variation in the macroinvertebrates was due especially to their own seasonality (Figs. 2-5), with a greater abundance present in summer than in winter. Similar results were reported by Marchant (1988) in Australia and by Miserendino & Pizzolon (2003) in Argentina, with the highest abundance occurring in summer and the lowest in winter. The temperature and the hydrological regime have been mentioned as dominant factors in the seasonal structuring of the macroinvertebrate community (Hawkins & Sedell, 1981; Statzner & Higler, 1986; Beltran et al., 2011), meaning that in dry seasons (low water) macroinvertebrates have greater possibilities of colonising the river area, since the habitat becomes homogenised and their densities and specific richness can increase (Poff & Ward, 1989; Poff et al., 1997; Reynaga & Dos Santos, 2013). In rainy seasons such as winter, when the water flow increases due to the high level of precipitation, macroinvertebrates are transported downstream by dramatic drifts (Lancaster, 2008; Gualdoni & Oberto, 2012). Furthermore, the increased flow causes the habitat to fragment, producing heterogeneous zones within the same river, which would favour certain FFGs (Newbury & Bates, 2006).

Seasonal differences were observed in FFGs. The collector-gatherers were more conspicuous in summer, autumn and spring (>39%), while in winter they shared dominance with the shredders (34% and 35% respectively). The shredders are responsible for processing and reducing allochthonous detritus (e.g., leaves and remains of wood) to small particles (<1 mm), which are subsequently "collected" as food by the collector-gatherers; both groups use leaves as a substrate for adherence and refuge (Cummins, 1974; Bird & Kaushik, 1985; Cummins et al., 1989). This group colonises the leaves which fall into rivers and accumulate there in small reservoirs, so their abundance will depend on the season when the forest leaves fall (Lake et al., 1985). In our study, the shredders were most abundant during rainy seasons, which is when the highest leaf fall occurs of both deciduous (i.e., roble and rauli) and evergreen species (i.e., coihue, tepa, Eucalyptus) in the study area. This same situation was recorded by Miserendino & Pizzolon (2004) in southern Argentina; they recorded scrapers and shredders in higher abundance in autumn and winter seasons (literfall period), where fine and coarse organic matter was more abundant, Later, when wind and precipitations decrease (Fig. 2), the input of allochthonous organic matter tends to diminish; consequently the abundance of shredders decreases while that of collector-gatherers starts to increase, reaching its peak in the drier seasons (Roeding & Smock, 1989).

According to the continuum river concept, low order rivers should contain mainly collector-gatherers and shredder organisms (Vannote et al., 1980). This situation has been found both in this study and in other places, e.g, Winterbourn et al. (1981) in New Zealand, Figueroa et al. (2000) in Chile and Callisto et al. (2001) in Brazil. Nevertheless, this is not a generalized pattern, since Miserendino & Pizzolon (2003) in Argentinean Patagonia, Lake et al. (1985) in Australia and Duncan & Brusven (1985) in Alaska recorded only collectors as the most abundant group in their study areas. Despite this difference, the marked dominance of collector-gatherers and shredders in the study area shows that these two groups play an important role in processing organic matter in coastal rivers of low-medium order (3rd, 4th and 5th) of this region.

Any disturbance in the land use in these basins has the potential to affect the biodiversity of aquatic ecosystems, due to the close relation between the terrestrial and aquatic components (Clarke et al., 2008). As a result, the diversity of fauna inhabiting these ecosystems continues to be threatened worldwide (Moss, 2000; Vieira et al., 2008). One of the most diverse groups found in these ecosystems is aquatic benthic macroinvertebrates, which have been greatly reduced and in some cases become extinct throughout the world (Lydeard et al., 2004, Poole & Downing, 2004; Strayer, 2006). Conservation strategies in aquatic systems in South America, and Chile in particular as a biodiversity hotspot, must therefore give special consideration to aquatic invertebrate fauna. This study therefore contributes to a better knowledge of the spatial distribution of benthic macroinvertebrates of these ecosystems.

DOI: 10.3856/vol43-issue1-fulltext-16

ACKNOWLEDGEMENTS

The authors would like to thank Raul Arriagada and Eduardo Fernandez for their help in field work, and Dr. Lafayette Eaton for his help checking this manuscript. This study was financially supported by FONDECYT Projects 1080317 and 1110798. P. Fierro receives funding from a grant from the Comision de Ciencia y Tecnologia de Chile (CONICYT) for Master's degree studies in Chile.

REFERENCES

Altamirano, A. & A. Lara. 2010. Deforestacion en ecosistemas templados de la precordillera andina del centro-sur de Chile. Bosque, 31: 53-64.

American Public Health Association (APHA). 2005. Standard methods for the examination of water and wastewater. Washington, D.C., 1368 pp.

Barletta, M., A.J. Jaureguizar, C. Baigun, N.F. Fontoura, A.A. Agostinho, V.M.F. Almeida-Val, A.L. Val, R.A. Torres, L.F. Jimenes-Segura, T. Giarrizoo, N.N. Fabre, V.S. Batista, C. Lasso, D.C. Taphorn, M.F. Costa, P.T. Chaves, J.P. Vieira & M.F.M. Correa. 2010. Fish and aquatic habitat conservation in South America: a continental overview with emphasis on Neotropical systems. J. Fish. Biol., 76: 2118-2176.

Barbier, E.B. 2004. Explaining agricultural land expansion and deforestation in developing countries. Am. J. Agr. Econ., 86: 1347-1353.

Beltran, L., M.L. Miserendino & P. Pessacq. 2011. Life history, seasonal variation and production of Andesiops torrens (Lugo-Ortiz & McCafferty) and Andesiops peruvianus (Ulmer) (Ephemeroptera: Baetidae) in a headwater Patagonian stream. Limnologica, 41: 57-62.

Bilotta, G.S. & R.E. Brazier. 2008. Understanding the influence of suspended solids on water quality and aquatic biota. Water Res., 42: 2849-2861.

Bird, G.A. & N.K. Kaushik. 1985. Processing of elm and maple leaf discs by collectors and shredders in laboratory feeding studies. Hydrobiologia, 126: 109-120.

Bradley, D.C. & S.J. Ormerod. 2001. Community persistence among stream invertebrates tracks the North Atlantic oscillation. J. Anim. Ecol., 70: 987-996.

Bray, J.R. & J.T. Curtis. 1957. An ordination of the upland forest communities of southern Wisconsin. Ecol. Monogr., 27: 325-349.

Brown, A.V. & P.P Brussock. 1991. Comparisons of benthic invertebrates between riffles and pools. Hydrobiologia, 220: 99-108.

Buffagni, A. & E. Comin. 2000. Secondary production of benthic communities at the habitat scale as a tool to assess ecological integrity in mountain streams. Hydrobiologia, 422: 183-195.

Callisto, M., P. Moreno & F.A.R. Barbosa. 2001. Habitat diversity and benthic functional trophic groups at Serra do Cipo, Southeast Brazil. Rev. Bras. Biol., 61: 259-266.

Campos, H., J. Arenas, C. Jara, T. Gonser & R. Prins. 1984. Macrozoobentos y fauna ictica de las aguas limneticas de Chiloe y Aysen continentales (Chile). Medio Ambiente, 7: 52-64.

Cayrou, J. & R. Cereghino. 2005. Life-cycle phenology of some aquatic insects: implications for pond conservation. Aquat. Conserv., 15: 559-571.

Clarke, K.R. & M. Ainsworth. 1993. A method of linking multivariate community structure to environmental variables. Mar. Ecol. Prog. Ser., 92: 205-219.

Clarke, K.R. & R.M. Warwick. 1994. Change in marine communities. An approach to analysis and interpretation. Nat. Environ. Res. Counc., Plymouth, 144 pp.

Clarke, A., R. Mac Nally, N. Bond & P. Lake. 2008. Macroinvertebrate diversity in headwater streams: a review. Freshwater Biol., 53: 1707-1721.

Comision Nacional del Medio Ambiente (CONAMA). 2004. Guia relativa al desarrollo de la dictacion de normas secundarias de calidad ambiental para aguas continentales superficiales y aguas marinas NSCA. Comision Nacional del Medio Ambiente. Santiago, 23 pp.

Cummins, K.W. 1974. The importance of different energy sources in freshwater ecosystems. In: D.E. Reichle, J.F. Franklin & D.W Goodall (eds.). Productivity of world ecosystems. Proc. Symp. IBP General Assembly, Nat. Acad. Sci., Washington DC, pp. 50-54.

Cummins, K.W., M.A. Wilzbach, D.M. Gates, J.B. Perry & T.W. Taliaferro. 1989. Shredders and riparian vegetation. BioScience, 39: 24-30.

Direccion General de Aeronautica Civil (DGAC). 2011. Anuario Climatologico, Santiago, 103 pp.

Di Castri, F. & E.R. Hajek. 1976. Bioclimatologia de Chile. Pontificia Universidad Catolica de Chile, Santiago, 157 pp.

Duncan, W.F.A. & M.A. Brusven. 1985. Benthic macroinvertebrates in logged and unlogged low-order southeast Alaskan streams. Fresh. Invertebr. Biol., 4: 125-132.

Egler, M.A., D.F. Buss, J.C.B. Moreira & D.F. Baptista. 2012. Influence of agricultural land-use and pesticides on benthic macro invertebrate assemblages in an agricultural river basis in southeast Brazil. Braz. J. Biol., 3: 437-443.

Evans, L. & R. Norris. 1997. Prediction of benthic macroinvertebrate composition using microhabitat characteristics derived from stereo photography. Fresh. Biol., 37: 621-633.

Fierro, P., C. Bertran, M. Mercado, F. Pena-Cortes, J. Tapia, E. Hauenstein & L. Vargas-Chacoff. 2012. Benthic macroinvertebrates assemblages as indicators of water quality applying a modified biotic index in a spatial-seasonal context in a coastal basin of southern Chile. Rev. Biol. Mar. Oceanogr., 47: 23-33.

Figueroa, R., E. Araya & C. Valdovinos. 2000. Deriva de macroinvertebrados bentonicos en un sector de riton: rio Rucue, Chile centro-sur. Boln. Soc. Biol. Concepcion, 71: 23-32.

Gualdoni, C.M. & A.M. Oberto. 2012. Estructura de la comunidad de macroinvertebrados del arroyo Achiras (Cordoba, Argentina): analisis previo a la construccion de una presa. Iheringia, Ser. Zool., 102: 177-186.

Guevara-Cardona, G., C. Jara, M. Mercado & S. Elliott. 2006. Comparacion del macrozoobentos presente en arroyos con diferente tipo de vegetacion riberena en la reserva costera Valdiviana, Sur de Chile. A.C.L. "Neolimnos", 1: 98-105.

Habit, E., C. Bertran, S. Arevalo & P. Victoriano. 1998. Benthonic fauna of the Itata River and irrigation canals (Chile). Irrigation Sci., 18: 91-99.

Hauer, F.R. & V.H. Resh. 2006. Macroinvertebrates. In: R.F. Hauer & G.A. Lamberti (eds.). Methods in stream ecology. Academic Press, New York, pp. 435-463.

Hawkins, C.P. & J.R. Sedell. 1981. Longitudinal and seasonal changes in functional organization of macroinvertebrate communities in four Oregon streams. Ecology, 62: 387-397.

Huttunen, K.L., H. Mykra & T. Muotka. 2012. Temporal variability in taxonomic completeness of stream macroinvertebrate assemblages. Fresh. Sci., 31: 423-441.

Kleine, P., S. Trivinho-Strixino & J.J. Corbi. 2011. Relationship between banana plant cultivation and stream macroinvertebrate communities. Acta Limnol. Bras., 23: 344-352.

Lake, P.S., T. Doeg & D.W. Morton. 1985. The macroinvertebrate community of stones in an Australian upland stream. Verh. Internat. Verein. Limnol., 22: 2141-2147.

Lancaster, J. 2008. Movement and dispersion of insects of stream channels: what role does flow play? In: J. Lancaster & R.A. Briers (eds.). Aquatic insects: challenges to populations. Wallingford, CABI, pp. 139-157.

Lydeard, C., R.H. Cowie, W.F. Ponder, A.E. Bogan, P. Bouchet, S.A. Clark, K.S. Cummings, T.J Frest, O. Gargomin, D.G. Herbert, R. Hershler, K.E. Perez, B. Roth, M. Seddon, E.E. Strong & F.G. Thompson. 2004. The global decline of non marine molluscs. Bioscience, 54: 321-330.

Linke, S., C.R.C. Bailey & J. Schwindt. 1999. Temporal variability of stream bioassessments using benthic macroinvertebrates. Fresh. Biol., 42: 575-584.

Marchant, R. 1988. Seasonal and longitudinal patterns in the macroinvertebrate communities of cobbles from the upper La Trobe River, Victoria, Australia. Verh. Internat. Verein. Limnol., 23: 1389-1393.

Merrit, R.W. & K.W. Cummins. 1996. Trophic relations of macroinvertebrates. In: R.F. Hauer & G.A. Lamberti (eds.). Methods in stream ecology. Academic Press, San Diego, pp. 453-473.

Miserendino, M.L. 2001. Macroinvertebrate assemblages in Andean Patagonian Rivers and streams: environmental relationships. Hydrobiologia, 444: 147-158.

Miserendino, M.L. & L.A. Pizzolon. 2003. Distribution of macroinvertebrate assemblages in the AzulQuemquemtreu River basin, Patagonia, Argentina. N.Z. J. Mar. Fresh., 37: 525-539.

Miserendino, M.L. & L.A. Pizzolon. 2004. Interactive effects of basin features and land-use change on macroinvertebrate communities of headwater streams in the Patagonian Andes. River. Res. Applic., 20: 967-983.

Miserendino, M.L. & C.I. Masi. 2010. The effects of land use on environmental features and functional organization of macroinvertebrate communities in Patagonian low order streams. Ecol. Indicat., 10: 311-319.

Mittermeier, R.A., W.R. Turner, F.W. Larsen, T.M Brooks & C. Gascon. 2011. Global biodiversity conservation: the critical role of hotspots. In: F. Zachos & C. Habel (eds.). Biodiversity hotspots. Springer, Berlin, pp. 3-22.

Molina, C.I., F.M. Gibon, J. Pinto & C. Rosales. 2008. Estructura de macroinvertebrados acuaticos en un rio Altoandino de la cordillera real, Bolivia: variacion anual y longitudinal en relacion a factores ambientales. Ecol. Apl., 7: 105-116.

Morrone, J. 2006. Biogeographic areas and transition zones of Latin America and the Caribbean Islands based on panbiogeographic and cladistic analyses of the entomofauna. Annu. Rev. Entomol., 51: 467-494.

Moss, B. 2000. Biodiversity in freshwaters--an issue of species preservation or system functioning? Environ. Conserv., 27: 1-4.

Myers, M., R. Mittermeier, C.G. Mittermeier, G.A. Da Fonseca & J. Kent. 2000. Biodiversity hotspots for conservation priorities. Nature, 403: 853-858.

Newbury, R.W. & D. Bates. 2006. Dynamics of flow. In: F.R. Hauer & G.A. Lamberti (eds.). Methods in stream ecology. Academic Press, New York, pp. 79-102.

Olson, D.M., E. Dinerstein, E.D. Wikramanayeke, N.D. Burgess, G.V. Powell, E.C. Underwood, J.A. D'Amico, I. Itoua, H.E. Strand, J.C. Morrison, C.J. Loucks, T.F. Allnutt, T.H. Ricketts, Y. Kura, J.F. Lamoreux, W.W. Wettengel, P. Hedao & K.R. Kassem. 2001. Terrestrial ecoregions of the world: a new map of life on earth. BioScience, 51: 933-938.

Pena-Cortes, F., M. Cisternas, C. Bertran, E. Hauenstein, J. Tapia, G. Rebolledo & M. Escalona. 2009. Unidades geoecologicas en cuencas del borde costero de la Region de la Araucania, sur de Chile. An. Soc. Chil. Cienc. Geogr., 29: 106-112.

Pena-Cortes, F., J. Pincheira-Ulbrich, C. Bertran, J. Tapia, E. Hauenstein, E. Fernandez & D. Rozas. 2011. A study of the geographic distribution of swamp forest in the coastal zone of the Araucania Region, Chile. Appl. Geogr., 31: 545-555.

Perez, R.M., R.F. Pineda & V. Campos. 2004. Estructura trofica de las asociaciones de macroinvertebrados acuaticos de manantiales carsticos en la Huasteca Mexicana. Biologicas, 6: 37-47.

Poff, N.L. & J.V. Ward. 1989. Implications of streamflow variability and predictability for lotic community structure: a regional analysis of streamflow patterns. Can. J. Fish. Aquat. Sci., 46: 1805-1818.

Poff, N.L., J.D. Allan, M.B. Bain, K.R. Karr, K.L Prestegaard, B.D. Richter, R.E. Sparks & J.C. Stromberg. 1997. The natural flow regime, a paradigm for river conservation and restoration. BioScience, 47: 769-784.

Poole, K.E. & J.A. Downing. 2004. Relationship of declining mussel biodiversity to stream-reach and watershed characteristics in an agricultural landscape. J. N. Am. Benthol. Soc., 23: 114-125.

Reynaga, M.C. & D.A. Dos Santos. 2013. Contrasting taxonomical and functional responses of stream invertebrates across space and time in a Neotropical basin. Fundam. Appl. Limnol., 183: 121-133.

Rice, S.P. & M.T. Greenwood & C.B. Joyce. 2001. Tributaries, sediment sources, and the longitudinal organization of macroinvertebrate fauna along river systems. Can. J. Fish. Aquat. Sci., 58: 824-840.

Roeding, C.E. & L.A. Smock. 1989. Ecology of macroinvertebrate shredders in a low-gradient sandy-bottomed stream. J. N. Am. Benthol. Soc., 8: 149-161.

Roldan, G. 1999. Los macroinvertebrados y su valor como indicadores de la calidad del agua. Rev. Acad. Colombiana Cienc. Exact. Fis. Natur., 23: 375-387.

Sporka, F., H.E. Vlek, E. Bulankova & I. Krno. 2006. Influence of seasonal variation on bioassessment of streams using macroinvertebrates. Hydrobiologia, 566: 543-555.

Stanford, J.A. 2006. Landscapes and riverscapes. In: R.F. Hauer & G.A. Lamberti (eds.). Methods in stream ecology. Academic Press, New York, pp 3-22.

Statzner, B. & B. Higler. 1986. Stream hydraulics as a major determinant of benthic invertebrate zonation patterns. Freshwater Biol., 16: 127-139.

Strahler, A.N. 1957. Quantitative analysis of watershed morphology. Trans. Am. Geophys. Union, 38: 913-920.

Strayer, D.L. 2006. Challenges for freshwater invertebrate conservation. J. N. Am. Benthol. Soc., 25: 271-287.

Summerville, K.S. & T.O. Crist. 2003. Determinants of lepidopteran community composition and species diversity in eastern deciduous forest: roles of season, eco-region and patch size. Oikos, 100: 134-148.

Suren, A.M., M.L. Martin & B.J. Smith. 2005. Short-term effects of high suspended sediments on six common New Zealand stream invertebrates. Hydrobiologia, 548: 67-74.

Udvardy, M. 1975. A classification of the biogeographical provinces of the world. IUCN. Morges, Suiza, Paper, 18: 1-49.

Valdovinos, C. 2006. Invertebrados dulceacuicolas. In: CONAMA (eds.). Biodiversidad de Chile. Patrimonio y desafios. Ocho Libros, Santiago, pp. 204-225.

Vannote, R.L., G.W. Minshall, K.W. Cummins, J.R. Sedell & C.E. Cushing. 1980. The river continuum concept. Can. J. Fish. Aquat. Sci., 37: 130-137.

Vieira, I.C.G., P.M. Toledo, J.M.C. Silva & H. Higuchi. 2008. Deforestation and threats to the biodiversity of Amazonia. Braz. J. Biol., 68: 949-956.

Villagran, C. 1991. Historia de los bosques templados del sur de Chile durante el Tardiglacial y Postglacial. Rev. Chil. Hist. Nat., 64: 447-460.

Wais, I.R. 1987. Macrozoobenthos of Negro River basin, Argentine Patagonia. Stud. Neotrop. Fauna. E., 22: 73-91.

Wallace, J.B. & J.R. Webster. 1996. The role of macroinvertebrates in stream ecosystem function. Annu. Rev. Entomol., 41: 115-139.

Winterbourn, M.J., J.S. Rounick & B. Cowie. 1981. Are New Zealand stream ecosystems really different? N.Z. J. Mar. Fresh., 15: 321-328.
Appendix 1. List of taxa of macroinvertebrates recorded in the 11
sampling stations (mean of 4 seasons). The population abundance (ind
[m.sup.-2]) and Functional Feeding Group (FFG) for each taxa are also
indicated. S: shredders, CG: collector-gatherers, CF: collector
-filterers, SC: scrapers, P: predators, D: detritivorous and PA:
parasites.

                                           Sampling station

                            FFG    1     2      3      4      5

Plecoptera
Austronemoura chilena        S    30     9      0      39     0
Neofulla sp.                 S     0     0      0      0      0
Diamphipnoa helgae           S     0     0      3      3      0
Diamphipnopsis samali        S     3     0      9      0      6
Inconeuria porteri           P     3     21     3      15     0
Kempnyella genualis          P     6     0      0      3      9
Pictetoper/a gayi            P     0     0      0      0      0
Klapopteryx armillata        S     0     54     3      0      12
Penturoperla barbota         S     0     0      0      0      0
Ceratoperia schwabei         S     0     0      3      0      0
Limnoperla jaffueli          S    312   1008   750    186    2226
Antarctoperla michaelseni    S     0     15     0     294     0
Notoperlopsis femina         S    15     3     444     30     3
Pelurgoperla personata       S    48    561     0     135     12
Neuroperlopsis paths         S     3     0      0      21     0
Ephemeroptera
Andesiops peruvianus        CG    450   573    414    312    690
Andesiops torrens           CG    117    6     126     87     69
Chiloporter eatoni           P     0     0      9      0      42
Chaquihua bullocki           P     0     0      0      0      0
Hapsiphlebia anastomosis    CG     0     0      21     6      9
Meridialaris dignillina     CG    225    39    1266   609    747
Meridialaris chilooense     CG    96     63     0      0      15
Nousia sp.                  CG     9     0      0      0      0
Nousia maculata             CG     0    174     15     63     63
Nousia delicata             CG     0     0      0      0      0
Penaphlebia sp.             CG    21     0      0      3      0
Penaph/ebia chilensis       CG    12    237     12     81     24
Penaphlebia vinosa          CG     0     0      0      0      0
Massarttellopsis            CG     0     0      0      0      3
  irrarazavali
Siphonella gutatta          CG     0     0      0      0      0
Caen is chilensis           CG     0     0      0      3      0
Murphyella needhami         CF     0     0      0      0      0
Trichoptcra
Ecnomidae indeterminate     CG     0     42     0      93     9
Austrotinodes sp.           CG     0     0      0      0      0
Hydrobiosidae                P     6     12     9     177     27
  indeterminate
Rheochorema sp.              P     0     0      6      0      21
Hydroptilidae               SC     0     0      12     3      0
  indeterminate
Hydroptila sp.              CG     0     0      0      0      0
Metrichia sp.               CG     0     0      0      0      0
Neotrichia sp.              CG     0     0      0      0      0
Neotrichia chilensis        CG     0     0      0      0      0
Polycentropus sp.            P     0     0      0      0      0
Parasericostoma sp.          S     3     0      0      3      3
Smicridea sp.               CF    21    522     18     18     81
Smicridea annulicornis      CF     0     93     42     69     21
Leptoceridae                SC     0     3      3      3      0
  indeterminate
Oecetis sp.                 SC     0     0      0      0      0
Brachysetodes sp.           SC     0     0      0      0      6
Triplectides sp.             S    18     0      0      0      0
Eosericostoma sp.           CG     0     0      0      0      0
Dolophilodes sp.             S     0     0      0      0      0
Coleoptera
Coleoptera indeterminate     P     6     0      3      0      0
Austrelmis sp.              CG     0     0      0      15     0
Austrolimnius sp.           CG    75     6     1194   270    162
Luchoelmis sp.              CG     0     0      12     12     3
Tychepsephenus felix        SC     0     3      6      0      6
Haliplidae indeterminate    SC     0     0      0      0      0
Haliplus sp.                SC     0     0      0      0      0
Gyrinidae indeterminate      P     0     0      0      0      0
Diptera
Stilobezzia sp.              P     0     0      0      0      0
Alluadomyia sp.              P     0     3      9      6      15
Tipulidae indeterminate      P     3     3      0      0      0
Tipula sp.                   P     0     0      0      3      0
Hexatoma sp.                 P     3     6      30     12     45
Atherix sp.                  P     0     75     0      3      12
Limoni a sp.                 P    18     12     42     84     48
Empididae indeterminate      P     0     0      0      0      0
Hemerodromia sp.            CG     3     21     36     6      6
Psychodidae indeterminate   CG     0     0      3      3      0
Blephabericeridae           SC     0     0      0      0      0
  indeterminate
Simulium sp.                CF    24     24     90     42     21
Gigantodax sp.              CF     0     0      0      15     9
Arauchnephioides sp.        CF     0     0      0      3      0
Dicrotendipes sp.           CF     0     0      0      27     18
Corynoneura sp.             CG    42     6     132     0      57
Thienemaniella sp.          CG    15     0      12     12    123
Pentaneura sp.              CG    12     3      15     42     33
Paratrichocladius sp.       CG     3     0      0      3      0
Rheotanytarsus sp.          CG     0     3     162     0      0
Tanytarsus sp.              CG    39     0      69     3      3
Eukiefierella sp.           CG    186   222    273    1305   111
Orthocladius sp.            CG    231   366     90    423     24
Lopesciadius sp.            CG    69     3      51     54     30
Coelotanypus mendax         CG     0     0      9      6      0
Symbiocladius               PA     0     0      12     0      12
  wygodzinskyi
Odonata
Neogomphus sp.               P     0     0      3      0      21
Megaloplera
Protochauliodes sp.          P     3     3      0      0      0
Decapoda
Aegla sp.                    P     0     0      0      0      0
Aegla araucaniensis          P     0     15     54     36    129
Aegla manni                  P     0     54     0      0      0
Isopoda
Helenas exul                CG     0     0      3      15     6
Amphipoda
Hyalella sp.                CG     3     3      0      0      0
Hyalelia costera            CG     0     0      6      0      0
Paracorophium               CG     0     15     0      0      0
  hartmannorum
Trombodi forme
Hydracarina                  P     3     0      0      0      9
Araneae
Araneae indeterminate        P     0     0      0      0      0
Collembola
Collembola indeterminate    CG     0     0      0      0      0
Prosobranchia
Littoridina cumingi         SC     3     0      0      0      0
Bassomatophora
Chilina dombevana           SC     0     0      0      3      21
Tubifieida
Tubifex sp.                  D    12    129     30    174     6
Haploxatida
Naididae indeterminate       D     0     63     0      6      9
Lumbriculida
Lumbriculidae                D     0     3      0      0      0
  indeterminate
Tricladida
Dugesia sp.                  D     3     0      0      0      0
Temnocephalida
Temnocephala chilensis      PA     0     3      0      18     0

                                          Sampling station

                             6      7      8      9      10     11

Plecoptera
Austronemoura chilena        15     3      9      5      24     6
Neofulla sp.                 3      0      0      0      0      0
Diamphipnoa helgae           3      24     21     5      51     9
Diamphipnopsis samali        0     123     3      90    852     9
Inconeuria porteri           0      9      6      10     57     12
Kempnyella genualis          0      12     0      24     0      3
Pictetoper/a gayi            0      0      3      0      3      0
Klapopteryx armillata        33    309     81    177    1128    81
Penturoperla barbota         3      0      0      0      0      0
Ceratoperia schwabei         3      0      0      0      0      3
Limnoperla jaffueli         570    210    1173   313    336    1419
Antarctoperla michaelseni    9      12     3      5      48     0
Notoperlopsis femina         6      87    435     21    111    378
Pelurgoperla personata       6      0      0      9      15     63
Neuroperlopsis paths         33     6      36     15     21     0
Ephemeroptera
Andesiops peruvianus        273    438    594    152    528    645
Andesiops torrens           846    2322   747    1230   2238   234
Chiloporter eatoni           3      21     15     14     48     18
Chaquihua bullocki           0      3      0      0      0      0
Hapsiphlebia anastomosis     66    159    330     55     0      6
Meridialaris dignillina     1005   906    2058   1728   993    2181
Meridialaris chilooense      0     342     0      0      0      3
Nousia sp.                   0      0      0      0      0      0
Nousia maculata              30     6      36     0      54     0
Nousia delicata              0     102     6      14     36     9
Penaphlebia sp.              0      0      0      0      0      0
Penaph/ebia chilensis       228     12    111    443    207     0
Penaphlebia vinosa           36     0      0      0      0      0
Massarttellopsis             0     246     0      0      0      0
  irrarazavali
Siphonella gutatta           0      0      6      0      3      0
Caen is chilensis            0      0      0      0      0      0
Murphyella needhami          3      9      0      26    111     0
Trichoptcra
Ecnomidae indeterminate      9      3      0      38     33     39
Austrotinodes sp.            0      0      0      0      3      0
Hydrobiosidae                57     15    177     0      33     24
  indeterminate
Rheochorema sp.              0      18     0      0      0      33
Hydroptilidae                0      0      0      0      0      0
  indeterminate
Hydroptila sp.               0      0      0      0      21     0
Metrichia sp.                3      0      6      3      0      0
Neotrichia sp.               0      0      0      9      15     0
Neotrichia chilensis         0      3      0      0      0      0
Polycentropus sp.            6      3      0      0      6      0
Parasericostoma sp.          0      9      0      0      27     0
Smicridea sp.                30     9     123     70    198     9
Smicridea annulicornis       12    147     0      0      33    168
Leptoceridae                 3      3      3      0      6      0
  indeterminate
Oecetis sp.                  0      0      0      0      6      0
Brachysetodes sp.            0      18     27     9     111     0
Triplectides sp.             0      0      0      0      0      0
Eosericostoma sp.            0      0      0      0      3      0
Dolophilodes sp.             0      3      0      0      0      0
Coleoptera
Coleoptera indeterminate     3      0      0      0      0      0
Austrelmis sp.               0      3      3      0      0      0
Austrolimnius sp.           315    366    330     94    189    318
Luchoelmis sp.               3      0      0      0      3      0
Tychepsephenus felix         36     24     12     73    141     9
Haliplidae indeterminate     0      0      0      0      3      0
Haliplus sp.                 0      9      0      0      0      0
Gyrinidae indeterminate      0      0      0      0      0      0
Diptera
Stilobezzia sp.              0      15     3      0      3      0
Alluadomyia sp.              6      39     12     42     12     3
Tipulidae indeterminate      0      12     0      0      21     0
Tipula sp.                   0      75     6      93     15     0
Hexatoma sp.                432    2190   1176   133    183     39
Atherix sp.                  51     0     114    245    108     0
Limoni a sp.                378     45     45     39     87     15
Empididae indeterminate      0      0      0      0      9      0
Hemerodromia sp.             12     45     3      5      0      0
Psychodidae indeterminate    0      6      0      0      3      0
Blephabericeridae            0      3      0      0      0      0
  indeterminate
Simulium sp.                 24    162     84     29    111    162
Gigantodax sp.               3      27     3      9      0      6
Arauchnephioides sp.         0      0      0      0      0      0
Dicrotendipes sp.            0      0      0      0      0      0
Corynoneura sp.              30    165     21    257     42    138
Thienemaniella sp.          111    660     57    128    450     0
Pentaneura sp.               9     162     48     38     9      6
Paratrichocladius sp.        0      0      0      3      0      0
Rheotanytarsus sp.           0      0      0      6      0      0
Tanytarsus sp.               0      0      0      0      0      0
Eukiefierella sp.            57    108    171     58    690     27
Orthocladius sp.             84    243     54    611    1767    24
Lopesciadius sp.            147    120     75     15    252     33
Coelotanypus mendax          0      3      3      0      15     0
Symbiocladius                0      9      0      0      0      3
  wygodzinskyi
Odonata
Neogomphus sp.               0      0      0      5      0      0
Megaloplera
Protochauliodes sp.          3      0      0      5      6      6
Decapoda
Aegla sp.                    0      0      6      0      0      0
Aegla araucaniensis          30     48     0      8      15    135
Aegla manni                  0      0      0      0      0      0
Isopoda
Helenas exul                 0      0      0      0      3      0
Amphipoda
Hyalella sp.                 6      0      0      0      18     0
Hyalelia costera             0      0      0      0      3      0
Paracorophium                0      0      0      0      0      0
  hartmannorum
Trombodi forme
Hydracarina                  3      0      0      9      12     6
Araneae
Araneae indeterminate        0      0      0      0      3      0
Collembola
Collembola indeterminate     0      0      0      0      3      0
Prosobranchia
Littoridina cumingi          0      3      3      0      30     0
Bassomatophora
Chilina dombevana            0      0      0      0      42     3
Tubifieida
Tubifex sp.                  39     21     15    346     48     24
Haploxatida
Naididae indeterminate       0      0      0      0      0      0
Lumbriculida
Lumbriculidae                3      0      3      3     222     3
  indeterminate
Tricladida
Dugesia sp.                  0      0      0      0      0      0
Temnocephalida
Temnocephala chilensis       0      84     0      0      0      0


Received: 21 November 2013; Accepted: 23 October 2014

Pablo Fierro (1,2), Carlos Bertran (1), Maritza Mercado (3), Fernando Pena-Cortes (4) Jaime Tapia (5), Enrique Hauenstein (4), Luciano Caputo (1) & Luis Vargas-Chacoff (1)

(1) Instituto de Ciencias Marinas y Limnologicas, Universidad Austral de Chile, Chile

(2) Departamento de Zoologia, Universidad de Concepcion, Chile

(3) Laboratorio Benthos de Entomologia Acuatica, Valdivia, Chile

(4) Laboratorio de Planificacion Territorial, Universidad Catolica de Temuco, Chile

(5) Instituto de Quimica y Recursos Naturales, Universidad de Talca, Chile

Corresponding author: Luis Vargas-Chacoff (luis.vargas@uach.cl)

Corresponding editor: Sergio Palma

Caption: Figure 1. Study area showing the locations of the 11 sampling stations in the four river basins of the coastal zone of the Araucania Region (Chile) during the study period.

Caption: Figure 2. Seasonal variation in the abundance of macroinvertebrates recorded in the 11 sampling stations in the coastal zone of the Araucania.

Caption: Figure 3. Classification and ordination of 11 sampling sites of the coastal zone of the Araucania Region, through a) cluster analysis and b) non-metric multidimensional scaling (nMDS), obtained from a Bray & Curtis dissimilarity matrix of abundance data (ind [m.sup.-2]). The groups were defined using the Simprof test (P < 0.05). Axes appear without legend because they are relative scales.

Caption: Figure 4. Station variation in the relative abundance of the functional feeding groups recorded in the 11 sampling stations in the coastal zone of the Araucania Region.

Caption: Figure 5. Average seasonal variation in the relative abundance of the different Functional Feeding Groups (FFGs) recorded in the 11 sampling stations located in the coastal zone of the Araucania Region.
Table 1. Altitude, type of vegetation and land use in the 11 sampling
stations located in the coastal zone of the Araucania Region (Chile)
during the study period (based on Pena et al., 2009). *Co: Coihue
(Nothofagus dombeyi), Ra: Rauli (Nothofagus alpina), Te: Tepa
(Laureliopsis philippiana), Ro: Roble (Nothofagus obliqua), Ca:
Canelo (Drimys winteri), Myrt: Myrtaceae.

Sampling    Altitude    Type of vegetation     Land use
station      (masl)

1              <50      Dune-type              Beaches, forest
                                               plantation and
                                               herbaceous vegetation
                                               which advances into
                                               the dunes.

2           Up to 100   Marshy, Ca, Myrt       Mixed use, dominant
                                               matrix arable and
                                               livestock farming.
                                               Regeneration and swamp
                                               forest.

3, 4         100-250    Evergreen, Ro-Ra-Co,   Mixed use, dominant
                        Ca, Myrt               matrix arable and
                                               livestock farming.
                                               Recent forest
                                               plantation and swamp
                                               forest.

5, 6         200-400    Evergreen, Ro-Ra-Co    Mixed use, arable and
                                               livestock farming
                                               matrix, dominant.
                                               Forest plantation and
                                               native forest.

7, 8         400-600    Evergreen, Ro-Ra-Co    Mixed use, arable and
                                               livestock farming
                                               matrix, forest
                                               plantation and
                                               dominant native
                                               forest.

9, 10, 11     >600      Evergreen, Co-Ra-Te,   Native forest
                        Ro-Ra-Co               predominates.

Table 2. F and P-values from two-way ANOVA
of abundance and richness.

Parameter        Season            Station       Season x Station

              F         P        F        P       F        P

Abundance   51.340   < 0.001   18.76   < 0.001   6.15   < 0.001
Richness    30.86    < 0.001   19.21   < 0.001   2.23   < 0.001

Table 3. Average ([+ or -] SD) physical and chemical parameters of
the water in the 11 sampling stations located in the coastal zone of
the Araucania Region. TDS: total dissolved solids, SS: suspended
solids, DO: dissolved oxygen, BOD5: biochemical oxygen demand,
P[O.sub.4.sup.-3]: phosphate, N[O.sup.3-]: nitrate; CL: chlorides;
SU: sulphates.

Stations      Temperature        Conductivity             TDS
             ([degrees]C)          ([micro]S        (mg [L.sup.-1])
                                 [cm.sup.-1])

1          10.4 [+ or -] 3.1   57.8 [+ or -] 1.0   49.4 [+ or -] 17.6
2          10.6 [+ or -] 3.6   53.4 [+ or -] 1.7   37.9 [+ or -] 19.5
3          12.3 [+ or -] 3.2   34.1 [+ or -] 2.1   24.1 [+ or -] 12.4
4          10.3 [+ or -] 3.0   40.9 [+ or -] 0.3   29.4 [+ or -] 14.9
5          12.4 [+ or -] 3.8   33.4 [+ or -] 1.3   23.6 [+ or -] 11.8
6          10.8 [+ or -] 3.2   40.2 [+ or -] 2.6   35.0 [+ or -] 12.9
7          11.3 [+ or -] 2.7   33.9 [+ or -] 0.9   24.1 [+ or -] 12.9
8          11.0 [+ or -] 3.4   44.2 [+ or -] 9.3   27.1 [+ or -] 13.5
9          10.4 [+ or -] 4.0   24.7 [+ or -] 0.8   18.0 [+ or -] 9.3
10         10.5 [+ or -] 3.6   22.8 [+ or -] 1.3   16.1 [+ or -] 8.3
11         11.0 [+ or -] 2.7   37.3 [+ or -] 1.9   26.4 [+ or -] 13.8

Stations          pH                 SS                  DO
                               (mg [L.sup.-1])     (mg [L.sup.-1])

1          6.8 [+ or -] 0.3   7.5 [+ or -] 3.9    10.9 [+ or -] 1.1
2          6.9 [+ or -] 0.2   12.7 [+ or -] 5.5   10.6 [+ or -] 1.3
3          6.7 [+ or -] 0.1   5.5 [+ or -] 4.9    8.2 [+ or -] 5.0
4          6.7 [+ or -] 0.3   8.6 [+ or -] 5.4    10.7 [+ or -] 1.1
5          6.8 [+ or -] 0.2   4.3 [+ or -] 1.6    8.3 [+ or -] 5.1
6          6.9 [+ or -] 0.3   5.8 [+ or -] 1.2    11.0 [+ or -] 1.2
7          6.8 [+ or -] 0.1   2.4 [+ or -] 1.9    10.9 [+ or -] 1.0
8          6.8 [+ or -] 0.3   7.0 [+ or -] 8.6    11.1 [+ or -] 1.2
9          7.0 [+ or -] 0.3   1.8 [+ or -] 0.8    11.2 [+ or -] 1.1
10         6.7 [+ or -] 0.3   3.0 [+ or -] 1.3    11.0 [+ or -] 1.3
11         6.8 [+ or -] 0.1   6.3 [+ or -] 3.3    10.6 [+ or -] 0.8

Stations         BOD5         P[O.sub.4.sup.-3]       N[O.sup.3-]
           (mg [L.sup.-1])     (mg [L.sup.-1])      (mg [L.sup.-1])

1          1.8 [+ or -] 0.8   43.1 [+ or -] 22.3   27.8 [+ or -] 15.0
2          1.9 [+ or -] 0.5   54.7 [+ or -] 32.6   52.1 [+ or -] 7.9
3          1.8 [+ or -] 0.5   72.9 [+ or -] 27.8   44.4 [+ or -] 19.4
4          2.1 [+ or -] 0.7   58.0 [+ or -] 30.9   42.4 [+ or -] 7.8
5          1.8 [+ or -] 0.1   71.7 [+ or -] 31.6   40.6 [+ or -] 16.9
6          2.3 [+ or -] 0.6   47.6 [+ or -] 52.1   .32.0 [+ or -] 8.9
7          2.4 [+ or -] 0.6   61.9 [+ or -] 44.4   39.3 [+ or -] 15.7
8          2.4 [+ or -] 0.4   42.0 [+ or -] 31.9   37.0 [+ or -] 11.7
9          2.6 [+ or -] 1.0   59.9 [+ or -] 26.7   39.1 [+ or -] 14.3
10         2.3 [+ or -] 0.7   76.5 [+ or -] 15.1   38.0 [+ or -] 13.2
11         2.1 [+ or -] 0.4   54.9 [+ or -] 22.5   45.4 [+ or -] 19.2

Stations          CL                  SU
            (mg [L.sup.-1])    (mg [L.sup.-1])

1          16.6 [+ or -] 2.9   2.4 [+ or -] 2.7
2          14.1 [+ or -] 2.4   1.2 [+ or -] 0.2
3          12.6 [+ or -] 0.9   1.8 [+ or -] 0.9
4          14.3 [+ or -] 1.6   1.4 [+ or -] 0.7
5          11.2 [+ or -] 2.3   1.0 [+ or -] 0.3
6          13.5 [+ or -] 1.6   0.8 [+ or -] 0.2
7          10.8 [+ or -] 1.1   1.1 [+ or -] 0.3
8          12.0 [+ or -] 2.1   1.1 [+ or -] 0.2
9          9.7 [+ or -] 0.6    1.9 [+ or -] 1.4
10         11.3 [+ or -] 1.7   1.3 [+ or -] 0.3
11         11.0 [+ or -] 1.6   1.4 [+ or -] 0.3

Table 4. Number of taxa (S), total population abundance (ind [m.sup.-
2]) (n [+ or -] SD), richness of species according to Margalef (d),
Pielou's Evenness index (J) and Shannon-Weaver Diversity index (H')
of the macroinvertebrates in the 11 sampling stations in the coastal
zone of the Araucania Region averaged across all seasons.

Station   S             n              d       J       H'

1         40    2154 [+ or -] 181    5.081   0.7262   2.679
2         42    4479 [+ or -] 371    4.877   0.691    2.581
3         45    5514 [+ or -] 818    5.107   0.646    2.458
4         52    4857 [+ or -] 819    6.008   0.697    2.754
5         48    5037 [+ or -] 693    5.513   0.558    2.160
6         50    5079 [+ or -] 745    5.742   0.689    2.694
7         60   10239 [+ or -] 1016   6.389   0.669    2.740
8         47    8256 [+ or -] 1028   5.101   0.658    2.532
9         48    6719 [+ or -] 856    5.333   0.686    2.654
10        66   11877 [+ or -] 1941   6.928   0.696    2.917
11        41    6312 [+ or -] 1206   4.571   0.591    2.195
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Title Annotation:Research Article
Author:Fierro, Pablo; Bertran, Carlos; Mercado, Maritza; Pena-Cortes, Fernando; Tapia, Jaime; Hauenstein, E
Publication:Latin American Journal of Aquatic Research
Article Type:Ensayo
Date:Mar 1, 2015
Words:9043
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