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27 May 2012 Does Nature and Persistence of Substrate at a Mesohabitat Scale Matter for Chironomidae Assemblages? a Study of Two Perennial Mountain Streams in Patagonia, Argentina
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Chironomid substrate—specific associations regarding the nature (organic—inorganic) and stability (stable—unstable) of different habitats were investigated at two low order Patagonian streams, during high and low water periods. Nant y Fall and Glyn rivers were visited twice (October 2007 and March 2008) and seven different habitat types were identified. A total of 60 samples were collected using a Surber sampler (0.09 m -2 and 250 µm) and a set of 23 environmental descriptors including physicochemical parameters and different fractions of particulate organic matter were assessed. 35 Chironomidae taxa were recorded with Orthocladiinae (20), Chironominae (7), and Podonominae (4) being the most well—represented subfamilies. Paratrichocladius sp. 1, Parapsectrocladius sp. 2, Parametriocnemus sp. 1, Pseudochironomus sp., and Rheotanytarsus sp. were the most abundant taxa. According to the relative preference index, at least 14 taxa showed strong affinity for a particular substrate. The structurally complex macrophyte Myriophyllum quitense supported 11 taxa compared with only five taxa found on the less complex Isoetes savatieri. Generally, stable substrates (boulders, cobbles, and rooted plants) supported significantly higher chironomids richness, abundance, and diversity than unstable ones (gravel—sand). Canonical correspondence analysis revealed that detritus (leaves, seeds, and biomass), macrophyte biomass, and secondarily hydraulic variables had high explanatory power on chironomids species composition and structure. This work suggests that more complex substrates showing persistence in the temporal dimension supported a diverse array of chironomids, meaning that the maintenance of natural habitat heterogeneity is essential for the community. Land—use practices having significant effects on ecological stream attributes such as increased turbidity, sediment deposition, and runoff patterns will alter assemblages. Understanding environmental associations of the Chironomidae assemblage at the habitat scale is significant for conservation purposes and for the management of low order streams in Patagonia.


Running waters can vary dramatically in size, current velocity, and substrate composition, offering a diverse range of habitats for aquatic insects (Ward 1992). The abiotic habitat template is generally considered to be the major determinant of community organization in fluvial systems, in which physical features of streams create specific habitat conditions supporting different types and forms of food for the aquatic biota (Buss et al. 2004). Spatial and temporal heterogeneity rules the persistence of species in community assemblages (Hynes 1970; Southwood 1977; Ward 1989; Townsend et al. 1997). Consequently, macroinvertebrate assemblage structure in streams is determined by physical factors, such as stream bed geomorphology (Cummins and Lauff 1969; Wallace and Webster 1996), hydraulic features (Statzner et al. 1988), biological interactions (Power 1992; Thomson et al. 2002), and also by the land— use adjacent to the river channel (Resh et al. 1988).

At the reach spatial scale, riverbed morphology shows an alternating sequence of pool and riffle habitats. Pools are slowly flowing depositional zones dominated by fine particles of mineral substrates, while riffles are turbulent, shallower, fast—flowing erosional zones dominated by large particles of mineral substrates (Brussock and Brown 1991; Gordon et al. 1992; Giller and Malmqvist 1998). The contrasting differences in abiotic (i.e., current velocity, substrate composition, water depth) as well as biotic (i.e., food sources, predation) factors between riffles and pools may exert a strong effect on the organization of macroinvertebrate assemblages (Allan 1995; Rabeni et al. 2002). In fact, riffles are generally considered to support higher densities of benthic macroinvertebrates than pools (Hynes 1970; Kerans et al. 1992; Allan 1995; Weigel et al. 2003; Townsend et al. 2004).

The family Chironomidae has a worldwide distribution and is an ecologically important group of aquatic insects, often occurring in high densities and diversity (Merritt and Cummins 1997; Ferrington et al. 2008). They are key members of stream macroinvertebrate assemblages, playing an important role in detritus processing and food chains, since they are consumed by macroinvertebrates and fish (Pinder 1986; Ruse 1992; Armitage et al. 1995; Paggi 2009). Some chironomids are also known to be opportunistic and rapid colonizers adapting to fluctuating conditions (Ladle et al. 1985; Huryn 1990; Ruse 1995).

Furthermore, the high diversity displayed by the group has allowed scientists to use them as bioindicators of water quality (Wilson and Bright 1973). In the last decades chironomids have been used to characterize the status of fluvial systems (Wilson 1979; Laville 1981; Fend and Carter 1995; Cortelezzi et al. 2011).

In Argentina, the composition and distribution of Chironomidae species in rivers and streams and their environmental relationships has been documented in different fluvial systems, including small— to medium—sized mountain streams from the Northwest Andes (Medina and Paggi 2004; Tejerina and Molineri 2007; Scheibler et al. 2008), large subtropical rivers (Marchese and Paggi 2004), and Patagonian reservoirs (Paggi and Rodrígues Capítulo 2002). The use of midge species in biomonitoring was explored in Paggi (2003), and García and Añón Suárez (2007) assessed the structure of Chironomidae community in an Andean Patagonian stream. Nevertheless, the approach about habitat type and Chironomidae species preference has received less attention (Príncipe et al. 2008).

As exposed in recent works, the ecological integrity of river systems in Patagonia is being endangered by land—use changes (Miserendino et al. 2011). Anthropogenic actions can potentially modify habitat suitability (Hall et al. 2001), having dramatic and persistent impacts on biotic assemblages (Niemi et al. 1990). Like other members of aquatic invertebrate fauna in the region, Chironomidae show a high level endemism (Donato et al. 2009). In consequence, the knowledge of Chironomidae community and their environmental relationships at the habitat scale are important for conservation purposes and for the management of low order streams in Patagonia.

The question of how does substrate heterogeneity and midge habitat preferences shape Chironomidae diversity at a given site has been tested by several authors. As stated by Rosa et al. (2011), a high species richness and diversity of midge larvae can be promoted by large environmental heterogeneity. In line with these observations, Principe et al. (2008) found that the highest richness of Chironomidae corresponded to the most complex habitats; those habitats offering the greatest number of niches for species were more preferred.

This research was conducted at two low order streams (Nant y Fall and Glyn, Northwest Patagonia) during high and low water periods with the aims to (1) compare the attributes of chironomid communities in different habitats, (2) determine substrate—specific Chironomidae associations regarding the nature (organic—inorganic) and stability (stable—unstable) of the habitat, and (3) establish environmental variables determining spatial and temporal distribution of taxa at the habitat scale.

Materials and Methods

Study area

The study area belongs to the Andean—humid and sub—Andean sub—humid regions (Paruelo et al. 1998), and is located in a transitional mountain and piedmont area in the Northwest of Chubut province, Argentina. From a phytogeographical perspective, the study area is located in the ecotone between the sub— Antarctic forest and the Patagonian steppe, and exhibits a marked altitudinal gradient.

Catchments are dominated by granites and diorite rocks. Extensive outcrops of crystalline bedrock produce ionically dilute waters, a distinctive characteristic of the Andean—Patagonian Cordillera region (Drago and Quirós 1996). The catchment area of Nant y Fall is 161.8 km2, and that of Glyn is 21.7 km2. The studied streams, Nant y Fall (3rd order) and Glyn (2nd order), are tributaries of the Futaleufú River and Corcovado River, respectively. Nant y Fall dominant land—use is pasture, whereas Glyn is under mixed management, with wood collection (Nothofagus antarctica and N. pumilio) and extensive livestock (mainly cows and sheep) that is sustained by the herbaceous stratum.

Stream flow in the region is strongly linked to rainfall and snowmelt, which result in predictable winter and spring spates. However, during summer, river flow is low and stable (Coronato and del Valle 1988).

Dominant riparian vegetation at Glyn stream is composed of native Nothofagus antarctica (30%), whereas the shrub coverage (40%) is represented by Berberis buxifolia, Schinus patagonica, Maytenus chubutensis, Ribes cucullatum, Ovidia andina, and Chusquea culeou. In the herbaceous strata, Acaena ovalifolia, Fragaria chiloeensis, Calceolaria polyrrhiza, Prunella vulgaris, Verbascum thapsus, lupulina, and Cerastium arvense are the most common species. Aquatic vegetation is composed mostly of Veronica serpyllifolia. Riparian vegetation at Nant y Fall stream is represented by some specimens of Nothofagus antarctica, Schinus patagonica, and Berberis buxifolia. The dominant strata is herbaceous (60–70%), characterized by Plantago lanceolata, Trifolium repens, Cerastium arvense, Taraxacum officinale, and Rumex acetosella among others. Aquatic vegetation is composed of Isoetes savatieri, Myriophyllum quitense, Limosella australis, Ranunculus flagelliformis, and Callitriche lechleri, the subemergent Lilaeopsis macloviana and Mimulus glabratus, and the emergent macrophytes Veronica anagallis-aquatica, Eleocharis albibracteata, Juncus burkartii, J. diemii, and J. microcephalus.

Sampling design and reach characterization

Nant y Fall and Glyn rivers were visited twice: once during high (October 2007) and once during low (March 2008) water periods. Current speed was measured in mid channel (average of three trials) by timing a float as it moved over a distance of 10 m (Gordon et al. 2004). Average depth was estimated from five measurements with a calibrated stick along a transverse profile across the channel. Wet and dry widths (from bank to bank) of the channel were also determined. Discharge (m3·s-1) was obtained by combining depth, wet width, and current velocity as in Gordon et al. (2004).

On each sampling occasion, the water temperature, pH, specific conductivity (µS20 cm-1), dissolved oxygen (mg O2 L-1), oxygen saturation percentage, and total dissolved solids (TDS) were measured with a multi— parameter probe (Hach SensION 156, In order to perform nutrient analyses, water samples were collected below the water surface, kept at 4 °C and transported to the laboratory. Total nitrogen (TN) and total phosphorus (TP) were determined on unfiltered samples digested with persulphate, whereas nitrate plus nitrite nitrogen (NO3 + NO2), ammonia (NH4), and soluble reactive phosphate (SRP) were analyzed using standard methods (APHA 1994).

Attributes of the riparian vegetation were examined at each site using an adaptation of the QBR index (riparian corridor quality index, Munné et al. 2003) for Patagonian streams: the QBRp (Kutschker et al. 2009).

The total QBRp score ranges from 0 points (extreme degradation) to 100 points (excellent quality, natural riparian forest). Habitat quality was evaluated (HCI: habitat condition index) using the assessment procedure for high gradient streams by Barbour et al. (1999). The HCI scores range from 0 to 200, with a score of 200 points indicating that the river is natural and pristine and in its best possible condition. This index evaluates the ability of the stream's physical habitat to support a given fauna, and also acts as a measure of the spatial heterogeneity of the stream (Castela et al. 2008).

Habitat selection

Flow type, dominant substrate, depth, and vegetation were used to define each habitat type. Flow types were assessed according to Urbanic et al. (2005) and classified as no perceptible flow (1), smooth flow (2), lateral moving water (3), unbroken standing waves (4), and chute flow (5). Dominant particles of substrate were assessed visually, and depth was measured at each habitat with a calibrate stick. The macrophytes, Myriophyllum quitense (Saxifragales: Haloragaceae) and Isoetes savatieri (Isoetales: Isoetaceae), were consistently represented both spatially and temporally, and were selected as possible habitats in the design.

A total of seven different habitat types were identified. In depositional areas (pools) three habitat types were sampled: gravel—sand (GS), leaf—pack (LP), and macrophytes (M. quitense) (M). In riffle areas, two different habitats were sampled: boulder—pebble (BP) and boulder—pebble with filamentous algae (BF). In run areas cobble—pebble (CP) and cobble—pebble with the submerged I. savatieri (IS) were examined. Habitat GS, BP, and CP were common at both Glyn and Nant y Fall rivers, whereas LP and BF were present at Glyn, and M and IS at Nant y Fall.

Chironomid and detritus analysis

Three Surber samples (0.09 m2, 250 µm pore size) were taken at each habitat in each stream, during the dry and wet seasons, for a total of 60 samples. Samples were fixed with formaldehyde in the field. Individuals and detritus from each sample were sorted in the laboratory.

Sorting involved elutriation and the collection of materials on a series of sieves (mesh width 250–1000 µm). Detritus was divided into fine (250–1000 µm, FPOM) and coarse (> 1000 µm, CPOM) particulate fractions. CPOM was separated into wood, leaves (mainly entire leaves), seeds, and others (fragments of leaves, grass, roots, buds, etc.) (Voelz and Ward 1990). Additionally, macrophyte and bryophyte biomass was obtained from the samples. All fractions were dried (110 °C for four hours) and weighed with electronic balance to ± 0.5 mg.

Larvae were sorted manually under 5× magnification, counted, and preserved in 70% alcohol. In the laboratory, specimens were observed under stereomicroscope, and when necessary, individuals were mounted in glycerin on a microscope slide and examined (Epler 2001; Paggi 2001). Chironomidae larvae were identified to the lowest taxonomic level possible using available keys (Wiederholm 1983; Epler 2001; Paggi 2009). Density was calculated from counts of all the individuals in a sample. Functional feeding groups were assigned by gut analyses and use of available references (Merritt et al. 2008).

Data analyses

Principal component analysis (PCA) on log (x + 1) transformed data was used to examine variation in physical and chemical parameters between sites and season. PCA is a method of breaking down or partitioning a resemblance matrix into a set of orthogonal axes (linear model). This method used within its intended limits is a valuable procedure to detect structure in the relationships between variables (Ludwing and Reynolds 1988). Variables considered in the analyses are presented in Table 1.

The chironomid assemblages characteristic of each habitat (of both rivers) was determined by the relative preference index (RPI) (Tickner et al. 2000), which is calculated by dividing the abundance of each taxon in a certain habitat by the total abundance of that taxon recorded in all the habitats. The RPI can vary between 0 (no preference for a particular habitat) to 1 (strong affinity for that place).

Canonical correspondence analysis (CCA) was performed to relate changes in species abundance (35 taxa) with environmental descriptors of the habitat assessed (7). The environmental variables considered in the CCA were flow, depth, filamentous algae, bryophytes, macrophytes, CPOM, FPOM, woods, others, leaves, and seeds. All species and environmental data (excepting pH values) were log (x + 1) transformed prior to analyses. An unrestricted random Monte Carlo permutation test with 999 permutations was performed to determine the statistical significance of environmental variables and canonical axes. Where a variable is highly intercorrelated with others, a high inflation factor (> 20) is identified for that variable during initial analysis. These variables were then removed (CPOM and wood) and analysis carried out on the remaining environmental variables (ter Braak and Smilauer 1998). CCA was performed using the statistical package CANOCO version 4.02 (ter Braak and Smilauer 1998).

Table 1.

Environmental variables at Nant y Fall and Glyn streams (Patagonia, Argentina), recorded during high and low water periods in October 2007 and March 2008, respectively.



Environmental background

Wet width ranged from 16 to 17.2 m at Nant y Fall, and from 3.5 to 3.88 m at Glyn during low and high water periods, respectively. As expected, four physical variables (depth, discharge, current speed in riffle and pool) showed maximum values during the high water periods at both sites (Table 1). Water temperature was ranged from 5 (Glyn) to 18.7 ° C (Nant y Fall). Conductivity and pH values were higher at Nant y Fall than at Glyn. Dissolved oxygen ranged from 7.88 to 14.97 mg·L-1 at Glyn stream, and from 9.95 to 13.88 mg·L-1 at Nant y Fall.

Chemical and physical data provided a clear distinction between streams (PCA1) and water period (PCA2) as shown in the PCA ordination graph (Figure 1). The first two factors accounted for most of the variation in the data set (97.9%). The PCA1 (79.7%) highlighted the gradient in chemical conditions of the sites (i.e., high positive loadings by soluble reactive phosphate and nitrate plus nitrite nitrogen; negative loadings by conductivity, pH, and total nitrogen). The PCA2 (18.1%) evidenced a gradient in oxygen content, flow attributes, and level of total phosphorous (i.e., negative loadings by dissolved oxygen, depth, pool and riffle velocity, and high positive loading by total phosphorous).

Riparian corridor quality index for Patagonia (QBRp) values were 62 and 74 for Nant y Fall and Glyn, respectively, indicating that the former had an important riparian ecosystem alteration, whereas Glyn showed incipient disturbance. Regarding habitat conditions the score was 123 (suboptimal) for Nant y Fall and 151 (optimal) for Glyn.

Table 2.

Mean density (ind·m-2) and frequency (in brackets) of 35 Chironomidae taxa on different habitat types at Nant y Fall and Glyn streams (Patagonia, Argentina).


The macrophytes item was the best represented at Nant y Fall stream (Figure 2), being dominant at M and IS habitats. The fractions FPOM and others were also represented in M habitats showing maximum values during the high water period. Wood and CPOM items contributed mostly at M and GS habitats. Bryophytes peaked at BP habitats during the high water period (15.1 g DM·m-2).

At Glyn stream CPOM and wood were the dominant detrital items at LP habitats (Figure 2), reaching values of 457 and 320 g DM·m 2 respectively. Moreover, the fractions others and FPOM peaked at LP habitat during the high water period. During the low water period, bryophytes dominated at BF (5.93 g DM·m-2) and LP (4.46 g DM·m-2) habitats, whereas macrophytes dominated at GS (6.36 g DM·m-2).

At both sites, CP habitat sustained the lowest detritus biomass (12.8 and 38.8 g DM·m-2 at Nant y Fall and Glyn, respectively).

Spatial selectivity of Chironomidae species

35 Chironomidae taxa and morphotypes were recorded in the study, with Orthocladiinae (20), Chironominae (7), and Podonominae (4) as the best represented subfamilies. Total Chironomidae taxa was similar at both sites (23 and 25 for Nant y Fall and Glyn, respectively); however, 12 taxa were exclusively recorded at Glyn stream whereas 10 taxa were found only at Nant y Fall. Paratrichocladius sp. 1 was the most frequent and abundant taxa at both sites (Table 2). Ablabesmyia sp. and Parapsectrocladius sp. 2 contributed mostly at Nant y Fall, while Parametriocnemus sp. 1 dominated at Glyn.

A comparison on taxa richness, density, and diversity (H) during the low and high water period is presented in Figure 3. Boulder— pebble (BP) sustained significantly higher richness than gravel—sand (GS) at Nant y Fall at both seasons (Kruskal-Wallis p < 0.05). No differences per habitat were found at Glyn.

However, richness and Shannon-Weaver index (H) was significantly higher during the high water period at Glyn (Kruskal-Wallis p < 0.01).

According to RPI values (> 0.4), at least 11 taxa associated with macrophytes (M) (Nant y Fall), eight taxa with boulder—pebble (BP) (Nant y Fall), and seven taxa with leaf—packs habitats (Glyn) (Table 3). At Nant y Fall Eukiefferiella sp. 1, Orthocladius sp., and Tanytarsus sp. were linked to macrophytes (M) (Table 3), while Eukiefferiella sp. 3 was associated with cobble—pebble (CP), Parametriocnemus sp. 1 with BP, and Eukiefferiella sp. 2 with Isoetes habitat.

Taxa with specific habitat association at Glyn stream were: Alotanypus sp. with LP, Diamesinae sp. with cobble—pebble habitats, and Parapsectrocladius sp. 1, Polypedilum sp., Rheotanytarsus sp., and Tanytarsus sp. with gravel—sand habitats.

Regarding temporal patterns of taxa distribution, Eukiefferiella sp. 3 (at leaf—packs and boulder with filamentous algae (BF)), Orthocladiinae sp. 2 (at BF), Orthocladiinae sp. 4 (at cobble—pebble), and Pseudochironomus sp. (at leaf—packs) presented high densities during the high water period (Figure 4), and only Corynoneura sp. (at gravel—sand) peaked during the low water period. However, at Nant y Fall, most species showed high density values during the low water period. Ablabesmyia sp., Paramerina sp. and Rheotanytarsus sp. showed high densities at macrophytes habitat, whereas both Parapsectrocladius sp. 2 and Paratrichocladius sp. 1 at boulder—pebble and Isoetes habitats, and Apedilum sp. at Isoetes habitat (Figure 4).

Table 3.

Chironomids associated with each functional habitat and their relative preference index (RPI), for Nant y Fall and Glyn streams.


Table 4.

Results of canonical correspondence analysis (CCA). The species—environmental correlations scale the strength of the relationship between species and environment for the axes.


Chironomidae species and environmental relationships

The results of CCA ordination for 35 chironomids taxa, seven habitats, and 13 environmental variables showed that 21.2% of the variance in taxa abundance was accounted for by the first two ordination axes (Table 4). CCA resulted in a significant model as was shown by the Monte Carlo test. The species— environment correlations were 0.93 and 0.87 for the first and second axes, respectively (Table 4), indicating a strong relationship with the environmental variables selected. The first ordination axis (36.7% of the variance of species—environment) reflected a gradient mostly associated with detritus (leaves and seeds), macrophytes, and bryophytes biomass (Figure 5A). Therefore, seed and leaf biomass decreased from the positive to the negative end of the CCA1, whereas bryophyte and macrophyte biomass decreased from the negative toward the positive end of same axis. The CCA2 indicated that stream depth and filamentous algae biomass had the second largest effect on the occurrence of species. Thus, deeper habitats were placed at the positive extreme of CCA2, and shallower habitats at the negative extremes of CCA2.

Table 5.

Significant relationships between functional feeding groups (FFG) and environmental variables (R of Spearman's, p < 0.05).


Species ordination with regards to the first two axes is presented in Figure 5B. Species occurring in fast flowing habitats with bryophytes (i.e., Podonominae sp. 1, Eukiefferiella sp.1, Parapsectrocladius sp. 2, and Eukiefferiella sp. 2) were positioned in the upper left quadrant. Species of slow flowing and shallow waters with filamentous algae were placed in the lower right quadrant (i.e., Parametriocnemus sp. 2 and Corynoneura sp.). Species mostly associated with leaf—pack (Eukiefferiella sp. 3, Podonominae sp. 2 and sp. 3, Pseudochironomus sp.) were located toward the positive end of CCA1.

Several significant relationships were observed between functional feeding groups (FFG) and environmental variables (Table 5).

Collector—filterers increased with macrophyte biomass and decreased with depth and biomass of some detrital items (leaves, wood, seeds, CPOM, and BPOM). Grazers—scrapers increased in density with increases of FPOM, leaves, CPOM, and BPOM. Predators showed positive correlation with bryophyte and others biomass.


Chironomid richness observed at our study was comparable to that reported by Príncipe et al. (2008) in upland reaches at Cordoba province (31 taxa), but was significantly higher than that documented by Tejerina and Molineri (2007) for Monte and Yungas (16 taxa), and by Scheibler et al. (2008) in an Andean stream in Uspallata (Mendoza) (seven taxa). Nevertheless, richness values were lower than observed by Garcia and Añón Suárez (2007), which reported 55 taxa for Ñireco stream (at a lower latitude in the Patagonian Mountains). Pupal exuviae were analyzed, which undoubtedly increased the level of taxonomic resolution, and pointed out the need for further taxonomical studies, because richness in Chironomidae inventories from Patagonia often appear low when compared to those in rivers from the Northern Hemisphere (Ruse 1995; García and Laville 2000).

As previously observed in low order streams in the region (Velásquez and Miserendino 2003), Orthocladiinae and Chironominae were the best represented subfamilies in terms of richness and abundance at both sites. Members of these two subfamilies seem to dominate mountain streams in temperate areas in both the Southern (Collier 1993) and Northern Hemispheres (Syrovátka et al. 2009). Orthocladiinae chironomids prefer low water temperatures, which are associated with high latitude and altitude and well— oxygenated conditions (Pinder 1995; Paggi 2009). The cold stenothermic Podonominae and Diamesinae were less abundant in our study, similar to the results of Garcia and Anon Suárez (2007) in a Patagonian mountain stream.

It has been stated that abundance of aquatic macroinvertebrates seems to be considerably higher on aquatic plants than in non—vegetated areas (i.e., Orth et al. 1984; Hemminga and Duarte 2000), increasing with plant density or biomass (Diehl and Kornijów 1998; Attrill et al. 2000). Of the two species of macrophytes studied in the present work (M. quitense and I. savatieri), just I. savatieri sustained significantly higher chironomid density than gravel sand habitats. Concerning chironomid richness, Myriophyllum supported higher values than gravel—sand. However, at least 11 chironomid taxa were associated with M. quitense, compared with only five taxa found on the less complex I. savatieri, suggesting that a structurally complex macrophyte sustained an important part of the chironomid community. According to Thomaz et al. (2008), food (basically algae and organic detritus) also may increase with increases in macrophyte complexity, and thus may account for the higher invertebrate richness. A major plant complexity may provide refuges from predation (Warfe and Barmutta 2004). However, plant morphology alone can serve as a behavioral stimulus for certain invertebrate taxa, as shown in an experimental study on Myriophyllum spicatum, Chara baltica, and Potamogeton pectinatus in which the most complex M. spicatum was preferred (Hansen et al. 2011).

Stability and persistence facing discharge events are other important factors that should be considered when analyzing invertebrate habitat preferences (Death and Winterbourn 1994). Quinn and Hickey (1990) recognized that the effect of substrate size on invertebrate distribution was a consequence of larger substrates being more stable, and thus accumulating more periphyton and coarse organic matter. In the present work, stable substrates (boulders, cobbles, and rooted plants) supported significantly higher chironomid richness, abundance, and diversity than unstable substrates (gravel sand) in pair comparisons at Nant y Fall (Kruskal Wallis, p < 0.05), meaning that habitat persistence was quite relevant in defining chironomid assemblages. As revealed in a previous study, the macrophyte Myriophyllum seems to sustain a similar density of invertebrates in depositional areas (pools), as do boulders and cobbles, suggesting it provides a stable substratum and feeding site (Velásquez and Miserendino 2003). Aquatic vegetation certainly plays an important role conditioning distribution of Chironomidae in rivers (Principe et al. 2008), especially in those environments at the time of year when variable, high flows can be expected (Miserendino and Pizzolón 2003).

Temperature and current speed are two important parameters that influence the distribution pattern of Chironomidae larvae (Cranston 1995); these variables also affect the availability of trophic resources and substrate size (Lindegaard and Brodersen 1995; Paggi 2003; Rosa et al. 2011). According to the CCA analysis, detritus (leaves, seed biomass), and macrophyte biomass had high explanatory power on chironomid species composition, meaning that the nature of the substrate and the distribution of trophic resources at a habitat scale were key factors. Hydraulic features such as depth and flow played a secondary role. Syrovátka et al. (2009) found that particulate organic matter in sediments was more important than hydraulic conditions explaining chironomid distribution in a stony bottomed river, and Ruse (1994) noticed the same pattern in gravel habitats of the River Pank. Recently, Rosa et al. (2011) showed that although the nature of a substrate acted as a main factor of chironomid distribution in relation to water flow differences, the presence of natural mechanisms of retention contributed to support similar assemblages in areas of different flows.

More common species can be visualised easily for their abundance or frequency, and they usually respond mainly to conspicuous environmental variables. In the present work, some species were recorded in low numbers and were not abundant in the entire study (e.g., Diamesinae sp., Podonominae sp., Tanytarsus sp.). According to Siqueira et al. (2011), rare species may be affected by variables that are difficult to measure, particularly biotic factors. Competence and predation can be factors that drive rare species distribution, and this should be taken into account in future studies.

Giller and Malmqvist (1998) claimed that most benthic taxa are substrate generalists, although many may show a degree of preference for broad substrate categories. According to the present study, the collector filterer Rheotanytarsus sp. increased with macrophyte biomass and was strongly associated with M. quitense. Passive filter— feeders can benefit from the unimpeded velocities and turbulence transmitted through the open plant stand as those of Myriophyllum (Wallace and Merritt 1980). At least two species of Eukiefferiella were associated with higher flow velocity, which is coincident with hydraulic condition preferences documented for this genus (Collier 1993; Príncipe et al. 2008). A group of taxa was strongly associated with leaf—pack habitats: the collector—gatherers Podonominae sp. 2, sp. 3, and Pseudochironomus sp, and the scraper Eukiefferiella sp. 3. This diverse array of trophic groups suggest that these taxa may be using this habitat as refuge more than as a food resource. The smaller body sized Corynoneura sp. showed an affinity for gravel—sand habitats (Cranston et al. 1983), whereas Thienemaniella sp. appeared as a habitat generalist in agreement with Tejerina and Molineri (2007).

The predators Ablabesmyia sp. and Paramerina sp. were associated with M. quitense; these results are supported by Cremona et al. (2008) and Hansen et al. (2008), who reported that the highest predator abundance occurred on Myriophyllum when compared with other habitats. On the other hand, the collector gatherers Paratrichocladius sp. 1 and Parapsectrocladius sp. 2 co—dominated on Isoetes and boulder—pebble habitats. Interestingly, boulder—pebble was the habitat that sustained the highest bryophyte biomass that probably enhanced food availability and space for colonization.

As previously discussed, heterogeneous habitats can potentially offer a great number of niches for invertebrates because they are used as refuges and feeding areas, and decrease the probability of predation. More complex substrates showing persistence in the temporal dimension supported more diverse assemblages of chironomids. Thus, the nature and persistence of mesohabitat were important predictors of composition and abundance of the studied taxa. As expected, the simple and less stable gravel—sand habitat was the least preferred. This phenomenon suggests that an increase in fine sediment inputs could result in severe modifications of habitats and fauna in headwater streams. It has been observed that land—use practices such as forestry and pastoral development increase sedimentation symptoms and severely alter benthos assemblages (Miserendino and Masi 2010; Miserendino et al. 2011), meaning that anthropogenic interventions are resulting in pervasive changes in aquatic ecosystems. Because habitat degradation is increasing rapidly in the region, further work is needed to understand the magnitude of changes. Results given in the present paper may be valuable for conservation purposes and management of Patagonian streams.

Figure 1.

Ordination of sites according to PCA on the environmental variables measured at Nant y Fall and Glyn streams (Patagonia, Argentina) during high (October 2007) and low (March 2008) water period. High quality figures are available online.


Figure 2.

Inter—habitat and seasonal variation in mean total values (g DM·m-2) ± SD of organic matter categories (n = 3) per stream (Nant y Fall and Glyn, Patagonia, Argentina). Note the scales on the y—axes differ among streams. Habitats codes: M, macrophytes; CP, cobble—pebble; BP, boulder—pebble; IS, Isoetes; GS, Gravel—sand; LP, Leaf—packs; BF, boulder—filamentous algae. High quality figures are available online.


Figure 3.

Seasonal values of taxa richness, density (ind·m-2), and Shannon diversity of Chironomidae larvae per habitat at two low order streams of Patagonia. Range bars show maxima and minima, boxes are interquartile ranges (25–75%), small squares are means. Habitats codes: M, macrophytes; CP, cobble—pebble; BP, boulder—pebble; IS, Isoetes; GS, Gravel—sand; LP, Leaf—packs; BF, boulder—filamentous algae. High quality figures are available online.


Figure 4.

Mean total density (ind·m-2) ± SD of 12 chironomids taxa showing habitat preference at studied streams, during high (October 2007) and low (March 2008) water period in Patagonia, Argentina. Habitats codes: M, macrophytes; CP, cobble—pebble; BP, boulder—pebble; IS, Isoetes; GS, Gravel—sand; LP, Leaf— packs; BF, boulder—filamentous algae. High quality figures are available online.


Figure 5.

Canonical correspondence analysis ordination plot for sites and environmental variables based on abundance values of chironomids taxa from Nant y Fall and Glyn streams, Patagonia, Argentina. (A) Habitat—environmental biplot; (B) Species distribution according to CCA. Full species names are shown in Table 2. High quality figures are available.



We would like to thank to Dr. Analía Paggi for assistance in identification of some taxa. Thanks to Dr. Miguel Archangelsky for fieldtrip support. Lic. Sofia Lopez assisted in laboratory tasks. This paper was partially financed by PIP 11220080101907 CONICET-Argentina. This is Scientific Contribution n° 75 from LIESA.





boulder—pebble with filamentous algae






canonical correspondence analysis






course detritus



fine detritus; GS, gravel—sand



QBRp, riparian corridor quality index for Patagonian streams



cobble—pebble with the submerged I. savatieri



leaf—pack (LP)



macrophytes (M. quitense)



solid reactive phosphate



total dissolved solids



total nitrogen



total phosphorus



JD. Allan 1995. Stream Ecology: Structure and Function of Running Waters. Chapman and Hall. Google Scholar


American Public Health Association. 1994. Standard Methods for the Examination of Water and Wastewater. American Water Works Association. Google Scholar


P Armitage, PS Cranston, LCV Pinder. 1995. The Chironomidae: The Biology and Ecology of Non Biting Midges. Chapman and Hall. Google Scholar


MJ Attrill, JA Strong, AA. Rowden 2000. Are macroinvertebrate communities influenced by seagrass structural complexity? Ecography 23: 114–121. Google Scholar


MT Barbour , J Gerritsen , BD Snyder , JB. Stribling 1999. Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers: Periphyton, Benthic Macroinvertebrates and Fish. United States Environmental Protection Agency. Google Scholar


PP Brussock , AV. Brown 1991. Riffle—pool geomorphology disrupts longitudinal patterns of stream benthos. Hydrobiologia 22: 99–108. Google Scholar


DF Buss , DF Baptista , JL Nessimian , M. Egler 2004. Substrate specificity, environmental degradation and disturbance structuring macroinvertebrate assemblages in neotropical streams. Hydrobiologia 518: 179–188. Google Scholar


J Castela , V Ferreira , MAS. Graca 2008. Evaluation of stream ecological integrity using litter decomposition and benthic invertebrates. Environmental Pollution 153: 440–449. Google Scholar


KJ. Collier 1993. Flow preferences of larval Chironomidae (Diptera) in Tongariro River, New Zealand. New Zealand Journal of Marine and Freshwater Research 27: 219– 226. Google Scholar


FR Coronato , HF. del Valle 1988. Caracterización hídrica de las cuencas hidrográficas de la provincia del Chubut. Cenpat-Conicet. Google Scholar


A Cortelezzi , AC Paggi , M Rodríguez , Capítulo A. Rodrigues 2011. Taxonomic and nontaxonomic responses to ecological changes in an urban lowland stream through the use of Chironomidae (Diptera) larvae. Science of the Total Environment 409: 1344– 1350. Google Scholar


PS Cranston , DR Oliver , OA. Sæther 1983. The larvae of Orthocladiinae (Diptera: Chironomidae) of the Holartic Region. Key and diagnoses. In: T Wiederholm , Editor. Chironomidae of the Holartic Region: Keys and Diagnoses. Volume 1. Larvae. Entomologica Scandinavica. Google Scholar


PS. Cranston 1995. Introduction. In: P Armitage , PS Cranston , LC Pinder , Editors. The Chironomidae: The Biology and Ecology of Non Biting Midges , pp. 1–7. Chapman and Hall. Google Scholar


F Cremona , D Planas , M. Lucotte 2008. Biomass and composition of macroinvertebrate communities associated with different types of macrophyte architectures and habitats in a large fluvial lake. Fundamental and Applied Limnology 171: 119–130. Google Scholar


KW Cummins , GH. Lauff 1969. The influence of substrate particle size on the microdistribution of stream macrobenthos. Hydrobiologia 34: 145–181. Google Scholar


RG Death , MJ. Winterbourn 1994. Environmental stability and community persistence: a multivariate approach. Journal of the North American Benthological Society 13: 125–139. Google Scholar


S Diehl , R. Kornijów 1998. Influence of submerged macrophytes on trophic interactions among fish and macroinvertebrates. In: E Jeppesen , M Søndergaard , M Søndergaard , K Christoffersen , Editors. The Structuring Role of Macrophytes in Lakes , pp 24–46. Springer. Google Scholar


M Donato , J Massaferro , SJ. Brooks 2009. Estado del conocimiento taxonómico de la fauna de Chironomidae (Diptera: Nematocera) de la Patagonia. Revista de la Sociedad Entomológica Argentina 68: 187–192. Google Scholar


E Drago , R. Quirós 1996. The hydrochemistry of the inland waters of Argentina a review. International Journal Salt Lake Resources 11 : 1–11. Google Scholar


JH. Epler 2001. Identification Manual for the Larval Chironomidae (Diptera) of North and South Carolina. North Carolina Department of Environmental and Natural Resources: Division of Water Quality. Google Scholar


SV Fend , JL. Carter 1995. The relationship of habitat characteristics to the distribution of Chironomidae (Diptera) as a measure by pupal exuviae collections in a large river system. Journal of Freshwater Ecology 10(4): 342–359. Google Scholar


LC Ferrington , WP Coffman , MB. Berg 2008. Chironomidae. In: RW Merritt , KW Cummins , MB Berg , Editors. Aquatic Insects of North America , 4th edition, pp. 847–989. Kendall/Hunt Publishing Company. Google Scholar


XF García , H. Laville 2000. First inventory and faunistic particularities of the chironomid population from a 6th order section of the sandt River Loire (France). Archiv für Hydrobiologie 147: 465–484. Google Scholar


PE García , Suárez DA. Añón 2007. Community structure and phenology of chironomids (Insecta: Chironomidae) in a Patagonian Andean stream. Limnologica 37: 109–117. Google Scholar


PS Giller , B. Malmqvist 1998. The Biology of Streams and Rivers. Oxford University Press. Google Scholar


ND Gordon , TA McMahon , BL. Finlayson 1992. Stream Hydrology: an Introduction for Ecologists. John Wiley and Sons. Google Scholar


ND Gordon , TA McMahon , BL Finlayson , CJ Gippel , RJ. Nathan 2004. Stream Hydrology: an Introduction for Ecologists. John Wiley and Sons. Google Scholar


MJ Hall , P Closs , RH. Riley 2001. Relationships between land—use and stream invertebrate community structure in a South Island, New Zealand, coastal stream catchment. New Zealand Journal of Marine and Freshwater Research 35: 591–603. Google Scholar


JP Hansen , SA Wikström , L. Kautsky 2008. Effects of water exchange and vegetation on the macroinvertebrate fauna composition of shallow land—uplift bays in the Baltic Sea. Estuarine Coastal and Shelf Science 77: 535– 547 Google Scholar


JP Hansen , SA Wikström , H Axemar , L. Kautsky 2011. Distribution differences and active habitat choices of invertebrates between macrophytes of different morphological complexity. Aquatic Ecology 45: 11–22. Google Scholar


MA Hemminga , CM. Duarte 2000. Seagrass Ecology. Cambridge University Press. Google Scholar


AD. Huryn 1990. Growth and voltinism of lotie midge larvae: Patterns across an Appalachian Mountain basin. Limnology and Oceanography 35: 339–351. Google Scholar


HBN. Hynes 1970. The Ecology of Running Waters. Liverpool University Press. Google Scholar


BL Kerans , JR Karr , SA. Ahlstedt 1992. Aquatic invertebrate assemblages: spatial and temporal differences among sampling protocols. Journal of the North American Benthological Society 11: 377–390. Google Scholar


A Kutschker , C Brand , ML. Miserendino 2009. Evaluación de la calidad de los bosques de ribera en ríos del NO del Chubut sometidos a distintos usos de la tierra. Ecología Austral 19: 19–34. Google Scholar


M Ladle , DA Cooling , JS Welton , JAB. Bass 1985. Studies on Chironomidae in experimental recirculating stream systems. II. The growth, development and production of a spring generation of Orthocladius (Euorthocladius) calvus Pinder. Freshwater Biology 15: 133–137. Google Scholar


H. Laville 1981. Collections of pupal exuviae of Chironomids (Diptera) from the source (1295 m) of the upper River Lot to its confluence with the Truyére (223 m). Annales de Limnologie 17(3): 255–289. Google Scholar


C Lindegaard , KP. Brodersen 1995. Distribution of Chironomidae (Diptera) in the river continuum. In: PS Cranston , Editor. Chironomids: From Genes to Ecosystems. pp. 257–271. CSIRO Publications. Google Scholar


JA Ludwing , JF. Reynolds 1988. Statistical Ecology. Wiley Interscience. Google Scholar


M Marchese , AC. Paggi 2004. Diversidad de Oligochaeta (Annelida) y Chironomidae (Diptera) del Litoral fluvial argentino. In: FC Aceñolaza , Editor. Temas de la Biodiversidad del Litoral fluvial argentino. pp. 217–223. INSUGEO, Miscelánea. Google Scholar


AI Medina , AC. Paggi 2004. Composición y abundancia de Chironomidae (Diptera) en un río serrano de zona semiárida (San Luis, Argentina). Revista de la Sociedad Entomológica Argentina 63: 107–118. Google Scholar


RW Merritt , KW. Cummins 1997. An Introduction to the Aquatic Insect of North America. Kendall/Hunt Publishing Company. Google Scholar


RW Merritt , KW Cummins , MB. Berg 2008. An Introduction to the Aquatic Insects of North America , 4 edition. Kendall/Hunt Publishing Company. Google Scholar


ML Miserendino , LA. Pizzolón 2003. Distribution of macroinvertebrate assemblages in the Azul-Quemquemtreu river basin, Patagonia, Argentina. New Zealand Journal of Marine and Freshwater Research 37: 525– 539. Google Scholar


ML Miserendino , CI. Masi 2010. The effects of land—use on environmental features and functional organization of macroinvertebrate communities in Patagonian low order streams. Ecological Indicators 10: 311–319. Google Scholar


ML Miserendino , R Casaux , M Archangelsky , CY Di Prinzio , C Brand , AM. Kutschker 2011. Assessing land—use effects on water quality, in—stream habitat, riparian ecosystems and biodiversity in Patagonian northwest streams. Science of the Total Environment 409: 612–624. Google Scholar


A Munné , N Prat , C Solá , N Bonada , M. Rieradevall 2003. A simple field method for assessing the ecological quality of riparian habitat in rivers and streams: QBR index. Aquatic Conservation: Marine and Freshwater Ecosystems 13: 147–163. Google Scholar


GJ Niemi , P De Vore , N Detenbeck , D Taylor , JD Yount , A Lima , J Pastor , RJ. Naiman 1990. Overview of case studies on recovery of aquatic systems from disturbance. Environmental Management 14: 571–588. Google Scholar


RJ Orth , KL Heck , Montfrans J. van 1984. Faunal communities in seagrass beds: a review of the influence of plant structure and prey characteristics on predator—prey relationships. Estuaries 7: 339–350. Google Scholar


AC. Paggi 2001. Diptera: Chironomidae. In: HR Fernández , E Domínguez , Editors. Guía para la determinación de los artrópodos bentónicos sudamericanos. pp. 167–193. Universidad Nacional de Tucumán, Facultad de Ciencias Naturales e Instituto Miguel Lillo. Google Scholar


AC. Paggi 2003. Los Quironoómidos (Diptera) y su empleo como bioindicadores. Biología Acuática 21: 50–57. Google Scholar


AC. Paggi 2009. Diptera Chironomidae. In: E Domínguez , HR Fernández , Editors. Macroinvertebrados bentónicos sudamericanos. Sistemática y biología. pp. 383–409.Fundación Miguel Lillo. Google Scholar


AC Paggi , Capítulo A. Rodrígues 2002. Chironomids composition from drift and bottom samples in a regulated north— patagonian river (Rio Limay, Argentina). Verhandlungen des International Verein Limnologie 28: 1229–1235. Google Scholar


JM Paruelo , A Beltrán , E Jobbágy , OE Sala , OE. Golluscio 1998. The climate of Patagonia: general patterns and controls on biotic processes. Ecología Austral 8: 85–101. Google Scholar


LCV. Pinder 1986. Biology of freshwater Chironomidae. Annual Review of Entomology 31:1–23. Google Scholar


LCV. Pinder 1995. The habitats of chironomid larvae. In: PD Armitage , PS Cranston , LCV Pinder , Editors. The Chironomidae: Biology and Ecology of Non Biting Midges. pp. 107–135. Chapman and Hall. Google Scholar


ME. Power 1992. Habitat heterogeneity and the functional significance of fish in river food webs. Ecology 73: 1675–1688. Google Scholar


E Príncipe , MF Boccolini , MC. Corigliano 2008. Structure and Spatial—Temporal Dynamics of Chironomidae Fauna (Diptera) in Upland and Lowland Fluvial Habitats of the Chocancharava River Basin (Argentina). International Review of Hydrobiology 93: 342–357. Google Scholar


JM Quinn , CW. Hikey 1990. Magnitude of effects of substrate particle size, recent flooding, and catchment development on benthic invertebrates in 88 New Zealand rivers. New Zealand Journal of Marine and Freshwater Research 24: 411–427. Google Scholar


SF Rabeni , KE Doisy , DL. Galat 2002. Testing the biological basis of stream habitat classification using benthic invertebrates. Ecological Applications 12: 782–796. Google Scholar


VH Resh , AV Brown , AP Covich , ME Gurtz , GH Li , GW Minshall , SR Reice , AL Sheldon , JB Wallace , RC. Wissmar 1988. The role of disturbance in stream ecology. Journal of the North American Benthological Society 7: 433– 455. Google Scholar


BFJV Rosa , VC Oliveira , RG. Alves 2011. Structure and spatial distribution of the Chironomidae community in mesohabitats in a first order stream at the Poço D' Anta Municipal Biological Reserve in Brazil. Journal of Insect Science 11: 36. Available online,  Google Scholar


LP. Ruse 1992. Correlations between chironomid pupal skin collections and habitats recorded from a Chalk river. Netherlands Journal of Aquatic Ecology 26: 411–417. Google Scholar


LP. Ruse 1994. Chironomid microdistribution in gravel of an English chalk river. Freshwater Biology 32: 533–551. Google Scholar


LP. Ruse 1995. Chironomid emergence from an English chalk stream during a three year study. Archiv für Hydrobiologie 133(2): 223– 244. Google Scholar


EE Scheibler , V Pozo , AC. Paggi 2008. Distribución espacio—temporal de larvas de Chironomidae (Diptera) en un arroyo andino (Uspallata, Mendoza, Argentina). Revista de la Sociedad Entomológica Argentina 67(3–4): 45–58. Google Scholar


T Siqueira , LM Bini , FO Roque , SRM Couceiro , S Trivinho-Strixino , K. Cottenie 2011. Common and rare species respond to similar niche processes in macroinvertebrate metacommunities. Ecography 34: 1–10. Google Scholar


TRE. Southwood 1977. Habitat, the templet for ecological strategies? Journal of Animal Ecology 46: 337–365. Google Scholar


B Statzner , JA Gore , VH. Resh 1988. Hydraulic stream ecology: Observed patterns and potential applications. Journal of the North American Benthological Society 7: 307– 360. Google Scholar


V Syrovátka , J Schenková , K. Brabec 2009. The distribution of chironomid larvae and oligochaetes within a stony—bottomed river stretch: the role of substrate and hydraulic characteristics. Fundamental and Applied Limnology 174(1): 43–62. Google Scholar


E Tejerina , C. Molineri 2007. Comunidades de Chironomidae (Diptera) en arroyos de montaña del NOA: comparación entre Yungas y Monte. Revista de la Sociedad Entomológica Argentina 66(3–4): 169–177. Google Scholar


Braak CJF ter , P. Smilauer 1998. CANOCO Reference manual and User's guide to Canoco for Windows: software for Canonical Community Ordination (version 4). Microcomputer Power. Google Scholar


SM Thomaz , ED Dibble , LR Evangelista , J Higuti , LM. Bini 2008. Influence of aquatic macrophyte habitat complexity on invertebrate abundance and richness in tropical lagoons. Freshwater Biology 53: 358– 367. Google Scholar


JR Thomson , PS Lake , BJ. Downes 2002. The effect of hydrological disturbance on the impact of a benthic invertebrate predator. Ecology 83: 628–642. Google Scholar


D Tickner , PD Armitage , MA Bickerton , KA. Hall 2000. Assessing stream quality using information on mesohabitat distribution and character. Aquatic Conservation: Marine and Freshwater Ecosystems 10: 170–196. Google Scholar


CR Townsend , MR Scarsbrook , S. Doledec 1997. The Intermediate Disturbance Hypothesis, Refugia, and Biodiversity in Streams. Limnology and Oceanography 42: 938–949. Google Scholar


CR Townsend , BJ Downec , K Peacock , CJ. Arbuckle 2004. Scale and the detection of land—use effects on morphology, vegetation and macroinvertebrate communities of grassland streams. Freshwater Biology 49: 448–462. Google Scholar


G Urbanic , MJ Toman , C. Krusnik 2005. Microhabitat type selection of caddisfly larvae (Insecta: Trichoptera) in a shallow lowland stream. Hydrobiologia 541: 1–12. Google Scholar


SM Velásquez , ML. Miserendino 2003. Habitat type and macroinvertebrate assemblages in low order Patagonian streams. Archiv für Hydrobiologie 158: 461–483. Google Scholar


NJ Voelz , JV. Ward 1990. Macroinvertebrate responses along a complex regulated stream environmental gradient. Regulated Rivers Research and Management 5: 365–374. Google Scholar


JB Wallace , RW. Merritt 1980. Filter–feeding ecology of aquatic insects. Annual Review of Entomology 25: 103–132. Google Scholar


JB Wallace , JR. Webster 1996. The role of macroinvertebrates in stream ecosystem function. Annual Review of Entomology 41: 115-–139. Google Scholar


JV. Ward 1989. The four–dimensional nature of lotie ecosystems. Journal of the North American Benthological Society 8: 2–8. Google Scholar


JV. Ward 1992. Aquatic Insect Ecology, Volume 1. Biology and Habitat. Wiley. Google Scholar


DM Warfe , LA. Barmuta 2004. Habitat structural complexity mediates the foraging success of multiple predator species. Oecologia 141:171–178. Google Scholar


NM Weigel , L Wang , PW Rasmussen , JT Butcher , PM Stewart , TP Simon , MJ. Wiley 2003. Relative influence of variables at multiple spatial scales on stream macroinvertebrates in the Northern Lakes and Forest ecoregion, USA. Freshwater Biology 48: 1440–1461. Google Scholar


T. Wiederholm 1983. Chironomidae of the Holartic Region: Keys and Diagnoses. Volume 1. Larvae. Entomologica Scandinavica. Google Scholar


RS. Wilson 1979. Classifying rivers using chironomid pupal exuviae. Chironomidae: Ecology, systematics, cytology and physiology. Proceeding of the Seventh International Symposium on Chironomidae. pp. 209–226. Google Scholar


RS Wilson , PL. Bright 1973. The use of chironomids pupal exuviae for characterizing streams. Freshwater Biology 3: 283–302. Google Scholar
This is an open access paper. We use the Creative Commons Attribution 3.0 license that permits unrestricted use, provided that the paper is properly attributed.
Luis Beltrán Epele, María Laura Miserendino, and Cecilia Brand "Does Nature and Persistence of Substrate at a Mesohabitat Scale Matter for Chironomidae Assemblages? a Study of Two Perennial Mountain Streams in Patagonia, Argentina," Journal of Insect Science 12(68), 1-20, (27 May 2012).
Received: 28 June 2011; Accepted: 1 October 2011; Published: 27 May 2012

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