Responses of primary production, leaf litter decomposition and associated communities to stream eutrophication

Environmental Pollution 202 (2015) 32e40

Contents lists available at ScienceDirect

Environmental Pollution journal homepage: www.elsevier.com/locate/envpol

Responses of primary production, leaf litter decomposition and associated communities to stream eutrophication
rbara Dunck a, *, 1, Eva Lima-Fernandes b, 1, Fernanda Ca
ssio b, Ana Cunha c, Ba
udia Pascoal b Liliana Rodrigues a, d, Cla
, Maringa
, Parana
, Brazil Graduate Program in Ecology of Continental Aquatic Environments, University of Maringa Centre of Molecular and Environmental Biology (CBMA), Department of Biology, University of Minho, Braga, Portugal c Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB, University of Minho Pole), Department of Biology, University of Minho, Braga, Portugal d
, Brazil Department of General Biology and Center of Research in Limnology, Ichthyology and Aquaculture, University of Maringa a

b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 2 December 2014 Received in revised form 12 March 2015 Accepted 14 March 2015 Available online

We assessed the eutrophication effects on leaf litter decomposition and primary production, and on periphytic algae, fungi and invertebrates. According to the subsidy-stress model, we expected that when algae and decomposers were nutrient limited, their activity and diversity would increase at moderate levels of nutrient enrichment, but decrease at high levels of nutrients, because eutrophication would lead to the presence of other stressors and overwhelm the subsidy effect. Chestnut leaves (Castanea sativa Mill) were enclosed in mesh bags and immersed in five streams of the Ave River basin (northwest Portugal) to assess leaf decomposition and colonization by invertebrates and fungi. In parallel, polyethylene slides were attached to the mesh bags to allow colonization by algae and to assess primary production. Communities of periphytic algae and decomposers discriminated the streams according to the trophic state. Primary production decomposition and biodiversity were lower in streams at both ends of the trophic gradient. © 2015 Published by Elsevier Ltd.

Keywords: Fungi Invertebrates Periphyton Streams Subsidy-stress model

1. Introduction Human impacts promote changes in biotic communities with consequences to the functioning of aquatic ecosystems (Goudie, 1999; Pascoal et al., 2003; Loreau and de Mazancourt, 2013). Excess nitrogen and phosphorus in freshwaters (Liang et al., 2014; Smith et al., 1999) mainly from urbanization (Agostinho et al., 2005), deforestation (Allan, 2004) and increased use of agricultural fertilizers has led to eutrophication, which is one of the € ro € smarty et al., leading causes of water pollution worldwide (Vo 2010). Primary production and decomposition are two key complementary ecosystem processes that ensure organic matter turnover, nutrient cycling and the provisioning of many ecosystem services (Hooper et al., 2012). Leaf litter decomposition and primary

* Corresponding author. Periphytic Algae Laboratory, Av. Colombo, 5790, Sala 08
, PR, Brazil. Bloco G-90, University of Maring
a (UEM), CEP 87020-900 Maringa E-mail address: [email protected] (B. Dunck). 1 Both authors gave equal contribution. http://dx.doi.org/10.1016/j.envpol.2015.03.014 0269-7491/© 2015 Published by Elsevier Ltd.

production have been extensively studied in freshwaters, but researchers have rarely examined both processes in tandem (Danger et al., 2013). Nitrogen and phosphorus are proven regulators of aquatic primary production, although the response of primary producers may be altered by other factors, such as light limitation, hydrology and herbivory (Smith et al., 2006). Nutrients, at moderate levels, can stimulate primary production and, consequently, the production of organisms at higher trophic levels, such as invertebrates (Niyogi et al., 2007). This higher ecosystem production might be linked to higher diversity of producers and consumers (Rosenzweig, 1995; Thompson and Townsend, 2005). However, high levels of eutrophication can lead to algal blooms that are stressful to several organisms due to low dissolved oxygen and poor habitat quality (Niyogi et al., 2007). Leaf litter decomposition responds to the increase in nutrient availability in the stream water through effects on microbial and invertebrate communities that drive this process (Pascoal et al., 2003; Duarte et al., 2009). Moderate nutrient concentrations in the stream water are reported to stimulate fungal diversity,
ssio, 2004; Ferreira et al., 2006; biomass and activity (Pascoal and Ca Duarte et al., 2009; Fernandes et al., 2014). Similarly, invertebrate

B. Dunck et al. / Environmental Pollution 202 (2015) 32e40

diversity, biomass and density seem to be enhanced by moderate nutrient levels (Greenwood et al., 2007; Chung and Suberkropp, 2008; Rosemond et al., 2010; but see Ferreira et al., 2006). Fungi are able to uptake nutrients from the stream water (Gessner et al., 2007) thereby stimulating their biomass production, diversity and activity (Ferreira and Chauvet, 2011; Fernandes et al., 2014). Under these conditions, invertebrates may benefit from the increased fungal biomass on leaf litter and enhance their biomass and activity. However, in highly eutrophic streams, a reduction in fungal biomass and diversity (Baldy et al., 2007; Duarte et al., 2009) as well as in invertebrate biomass, diversity and density is often observed (Pascoal et al., 2005a; Lecerf et al., 2006; Baldy et al., 2007). Inorganic nitrogenous compounds, such as ammonia (Lecerf et al., 2006; Duarte et al., 2009), and the hypoxic conditions commonly
ssio, 2004; associated with eutrophic streams (Pascoal and Ca Pascoal et al., 2005a) can negatively affect the biota in detritusbased foodwebs. Here, we used an integrative approach to assess effects of eutrophication in streams by examining leaf litter decomposition, primary production and associated periphytic algae, fungi and invertebrates. According to the subsidyestress model (Odum et al., 1979), we expected a unimodal response of leaf litter decomposition and productivity to a trophic gradient. We hypothesized that, when nutrients were limited, biomass and activity of primary producers and decomposers would exhibit a subsidy response (increase) to moderate levels of nutrient enrichment, but a stress response (decrease) at high levels of nutrients, because eutrophication would lead to the presence of other stressors, that could overwhelm the subsidy effect of nutrients (Rosenzweig, 1995; Mittelbach et al., 2001). We also expected that at moderate nutrient levels, more species would coexist because competitively dominant species would not monopolize all resources, creating opportunities for less competitive species (Odum et al., 1979). Finally, we expected that general response patterns to eutrophication would be similar across communities, but the stress response thresholds might vary among periphytic algae, fungi and invertebrates. To test these hypotheses, mesh bags containing chestnut leaves (Castanea sativa Mill) were immersed in five streams of the Ave River basin (northwest Portugal) with different eutrophication levels to allow colonization by fungi and invertebrates, and to follow leaf decomposition. In parallel, periphytic algae and primary production were examined on polyethylene slides that were attached to the leaf bags. 2. Material and methods

33

2.2. Physical and chemical parameters of stream water Dissolved oxygen, conductivity and pH were measured in situ with field probes (Multiline F/set 3 no. 400327, WTW). Water samples were collected in plastic bottles, transported in cool boxes (4
C) and analysed on the same day. Nutrient concentrations in the stream water were measured by spectrophotometry (DR2000 spectrophotometer, Hach company, Loveland, CO, USA), according to manufacturer specifications, as follows: nitrate by the cadmium reduction method, nitrite by the diazotization method, ammonium by the salycilate method, and phosphate by the ascorbic acid method. Hydro-morphological measures (maximum width, depth, and current velocity) were taken according to Wetzel and Likens (1991) (Table 1). Maximum and minimum solar radiations (mmol m2 s1) were estimated through radiometer model LI-250 (Li-COR, Inc.) connected to a quantum sensor model Li-190SA (Table 1). 2.3. Experimental setup Chestnut leaves were collected before abscission in autumn 2009 and stored air-dried. Twelve coarse mesh bags (5 mm mesh size; 30  23 cm) were filled with 3 g (±0.001 g) of air-dried leaves. Four transparent polyethylene slides were attached to each mesh bag (7 cm  2.5 cm) and used as substrate to allow colonization by periphytic algal community. On 30 March 2013, mesh bags were immersed in each river for 28 days. Three coarse-mesh bags and attached slides were randomly collected from each stream every seven days. Each mesh bag was individually placed in plastic bags and each slide was placed in dark flasks with distilled water. All samples were transported in cool boxes (4
C) to the laboratory. The periphytic material was removed from the slides (17.5 cm2) with a toothbrush and jets of distilled water, fixed and preserved in 0.5% acetic Lugol solution (Bicudo and Menezes, 2006). Three slides were used to assess community attributes, namely algal density, algal biomass, and photosynthesis rate. From each bag, leaves were washed under tap water through sieves (250 and 800 mm mesh) to retain the invertebrates. Leaves were cut into 12 mm diameter disks, and used to assess fungal biomass and sporulation. The remaining leaf material was freezedried (48 h ± 24 h) to constant mass, weighed to the nearest 0.0001 g, and then ignited (500
C, 4 h) and reweighted to calculate the ash-free dry mass. Leaf disks used for fungal biomass and sporulation were also freeze-dried and weighted to the nearest 0.0001 g.

2.1. Study area 2.4. Periphytic algae The experiment was carried out in five streams of the Ave river basin (northwest Portugal) during spring 2013. Agra Stream flows through a mountain area with little human influence. Oliveira and Andorinhas streams flow through areas influenced by minor agricultural activities and suffer from diffuse nutrient inputs. Selho ~es while Couros Stream crosses River flows near the city of Guimara the city. Study sites in Selho River and Couros Stream were downstream the city and surrounded by agricultural fields, therefore influenced by diffuse nutrient inputs. Agra, Oliveira and Andorinhas streams were bordered by riparian vegetation mainly composed of alder (Alnus glutinosa Gaertn.), oak (Quercus sp.) and chestnut (C. sativa). The riverbed in Agra and Oliveira streams was composed of stones and pebbles, while in Andorinhas Stream was composed of gravel and sand. The Selho River and the Couros Stream were bordered by a narrow corridor of riparian vegetation composed of alder and poplar (Populus sp.), and sand was the dominant substrate.

€ hl method The algae were quantified by applying the Utermo (1958) through inverted microscope with 400 magnification. A minimum of 100 individuals (cells, colonies and filaments) were identified and counted from random fields taking into account the most abundant species according to the species accumulation curve (Ferragut and Bicudo, 2012). Species density was estimated according to Ros (1979) and results expressed as number of individuals per unit area (ind/cm2). The algal richness was estimated from this analysis. Algal biomass was estimated based on chlorophyll-a concentration in each sample, adapted to substrate area scraped. Chlorophyll-a analysis was done using 90% acetone extraction according to Golterman et al. (1978) and results were expressed as mg/cm2. The algal photosynthetic activity in each stream was estimated by chlorophyll fluorescence analysis by pulse amplitude modulation (PAM) fluorometry (Schreiber et al., 1986). A PAM-210

34

B. Dunck et al. / Environmental Pollution 202 (2015) 32e40

Table 1 Chemical and physical parameters (mean ± standard deviation) of the stream water in five streams of the Ave River basin during the study period.

Location Depth (cm) Width (m) Current velocity (cm/s) Radiation (mmol) Temperature (
C) Dissolved O2 (mg) Conductivity (mS/cm) pH NeNO 2 (mg/L) NeNO 3 (mg/L) NeNHþ 4 (mg/L) 3 PO4 (mg/L)

Agra

Oliveira

Andorinhas

Selho

Couros

41
360 12.2400 N; 8
20 54.4700 W 36.5 ± 0.70 2.50 ± 0.71 0.050 ± 0.01 660.6 ± 889.9 11.1 ± 0.7 10.70 ± 0.31 15 ± 0.0 6.12 ± 0.11 3.4 ± 1.5 80.0 ± 12.2 2.0 ± 4.5 14.0 ± 20.7

41
350 10.6700 N; 8
130 30.4600 W 30.00 ± 14.1 4.50 ± 0.70 0.17 ± 0.03 72.00 ± 67.88 12.8 ± 1.1 11.47 ± 0.65 33 ± 0.5 6.76 ± 0.10 3.6 ± 1.5 264.0 ± 0.057.3 8.0 ± 8.4 14.0 ± 8.9

41
340 11.2400 N; 8
100 37.3400 W 27.00 ± 4.24 4.75 ± 0.35 0.155 ± 0.06 176.00 ± 229.3 13.6 ± 1.2 11.03 ± 0.44 48 ± 0.5 6.69 ± 0.08 5.4 ± 1.3 1264.0 ± 844.7 6.0 ± 5.5 58.0 ± 63.8

41
260 17.6000 N; 8
190 21.2200 W 33.00 ± 15.55 3.50 ± 0.70 0.165 ± 0.02 342.30 ± 364.4 14.9 ± 1.7 10.77 ± 0.11 118 ± 4.1 6.96 ± 0.10 18.2 ± 8.0 1970.0 ± 1342.4 558.0 ± 499.8 130.0 ± 0.081.5

41
260 14.9300 N; 8
190 19.0900 W 30.50 ± 4.94 4.95 ± 0.07 0.170 ± 0.01 393.1 ± 405.70 15.4 ± 1.4 7.12 ± 0.44 235 ± 16.4 7.20 ± 0.34 171.8 ± 62.6 3160.0 ± 296.6 1778.0 ± 1143.6 684.0 ± 139.9

fluorometer (Heinz Walz GmbH, Germany), controlled via PAMWin software, was used. The emitter-detector unit consists of the following essential components: measuring light LED with shortpass filter (<690 nm), peaking at 650 nm; actinic LED, unfiltered, peaking at 665 nm; far-red LED, long-pass filter (>710 nm), peaking at 730 nm; PIN photodiode and dichroic filter, reflecting fluorescence at 90
towards the detector. Samples removed from the substrates were centrifuged with 5 ml of distilled water (5 min at 5000 rpm), and 1 ml of the supernatant was subsequently analysed using the fluorescence cuvette (Walz GmbH, Germany). Samples were previously adapted to an actinic light for 5 min, of 90 mmol m2 s1 after which Rapid Light-response Curves (RLC) experiments (Schreiber et al., 1997; White and Critchley, 1999) were performed, assessing the rate of photosynthetic electron transport (ETR) through photosystem II (PSII) in response to increasing light intensities. Samples were exposed for 20 s at each of the 10 increasing light intensities (from 90 to 690 mmol m2 s1) used. The RLCs were then fitted to the equation of Eilers and Peeters (1988) to estimate photochemical efficiency of PSII under limiting light intensities and maximum relative electron transport rates (ETRm). The maximum relative electron transport rates (ETRm) can be interpreted as maximum rate of photosynthesis (Stamenkovic and Hanelt, 2011). 2.5. Invertebrates Invertebrates associated with decomposing leaves were fixed with 96% alcohol, before identification and counting. Identifications were conducted under a stereomicroscope (Leica Zoom 2000) until the family level (Tachet et al., 2010). To assess invertebrate biomass, organisms were oven-dried at 80
C for 72 h and weighed to the nearest 0.0001 g. 2.6. Aquatic fungi Fungal sporulation was induced through aeration of sets of eight leaf disks from each leaf bag in 75 ml of filtered stream water for 48 h ± 4 h (16
C). Aliquots of conidial suspension of each flask were filtered (0.45 mm pore size, Millipore) and the conidia were stained with 0.05% cotton blue in lactic acid. At least 300 conidia were identified and counted per filter through light microscopy to assess the contribution of each aquatic hyphomycete taxon to the total conidial production. Fungal sporulation rates were calculated for each species as the number of conidia/g leaf ash-free dry mass/day. Mycelium biomass was estimated from ergosterol concentration on leaves (Gessner, 2005). Lipids were extracted from sets of 10 leaf disks through heating (80
C, 30 min) in 8 g/L KOH in methanol, purified by solid phase extraction and eluted in isopropanol.

Ergosterol was purified through high-performance liquid chromatography (Beckmann Gold System) using a LiChrospher RP18 column (250  4 mm, Merck). The system was run isocratically with HPLC-metanol, at 1.4 ml/min and 33
C. Ergosterol was detected at 232 nm and quantified based on a standard curve of ergosterol in isopropanol. Ergosterol concentration was converted into fungal biomass assuming 5.5 mg ergosterol/mg of mycelium dry mass (Gessner and Chauvet, 1993).

2.7. Data analysis A principal component analysis (PCA) was applied to ordinate the streams according to physical and chemical parameters in the stream water. Data were log (X þ 1) transformed prior to this analysis. Axis retention was evaluated under the Broken-Stick criterion (Jackson, 1993). A linear mixed model ANOVA with type III sums of squares (SS) was used to test for differences in algal, fungal and invertebrate richness and biomass among streams, with time as random factor and stream as fixed factor (Quinn and Keough, 2002). Prior to the analysis, data was ln (X þ 1) transformed whenever necessary to meet the assumptions of normality and homoscedasticity. Tukey's post hoc tests were used to further assess where differences occurred. Leaf decomposition rate in each stream was calculated by fitting percentage dry mass remaining to the negative exponential model Mt/M0 ¼ ekt, where Mt indicates remaining leaf dry mass at time t, M0 indicates initial leaf dry mass, and k is the rate of leaf decom€rlocher, 2005). position (Ba Correspondence analysis (direct ordination; Hill, 1974) was applied to mean density of algal species, invertebrate families and fungal sporulating species to verify how community structure differed among streams. Data were log (X þ 1) transformed (Legendre and Legendre, 1998) and rare species (<1% in density) were disregarded. Procrustean analysis (Jackson, 1995) was used to compare if the ordination patterns of algal, invertebrate and fungal communities shown by correspondence analysis were similar. The Procrustean analysis is powerful to detect matrix association (Peres-Neto and Jackson, 2001). P-values were evaluated after Monte-Carlo random permutations. Mantel tests with Pearson correlation coefficients were further used to examine patterns in community similarity across streams between algae, invertebrates and fungi using community distance matrices (BrayeCurtis coefficient of dissimilarity). All data were log (X þ 1) transformed prior to this analyses. Multivariate analyses were done in R software (R Development Core Team, 2013) and univariate analyses were done in STATISTICA 8.0 for Windows (Statsoft, Tulsa, OK, USA).

B. Dunck et al. / Environmental Pollution 202 (2015) 32e40

3. Results 3.1. Physical and chemical parameters of stream water The PCA ordination of stream water variables showed that axis 1 explained 86% of the total variance (eigenvalue of 6.07) and axis 2 explained 11% (eigenvalue of 0.77) (Fig. 1). PCA ordination revealed an eutrophication gradient as follows: Agra Stream, the most oligotrophic stream with the lowest values of nitrate and ammonium, followed by Oliveira and Andorinhas streams and Selho River, and, finally, the most eutrophic stream, Couros Stream with the highest values of nitrite, phosphate and ammonium (Table 1, Fig. 1).

Table 2 ANOVAs of the effects of stream and time of immersion on taxon richness and biomass of algae, fungi and invertebrates associated with substrates immersed in five streams of the Ave River basin.

Periphytic algae

Fig. 1. Principal component analysis (PCA) of the stream water physical and chemical variables at the five streams of the Ave River basin (NO3- Nitrates, NO2- Nitrites, PO4Phosphate, NH4- ammonium, CO- conductivity, DO- dissolved oxygen).

Richness

Biomass

Fungi

3.2. Communities of algae, fungi and invertebrates Algal, fungal and invertebrate richness associated with the substrates changed significantly among streams (algae: F ¼ 11.02, p < 0.05; fungi: F ¼ 15.54, p < 0.05; invertebrates: F ¼ 16.47, p < 0.05; Table 2). For all communities, average richness was lower at both extremes of the eutrophication gradient (Agra and Couros streams) and higher at intermediate levels (Oliveira and Andorinha streams and Selho River) (Tukey's tests, p < 0.05; Fig. 2). Agra Stream had the lowest richness: 11 algal species (Fig. 2A), 7 fungal species (Fig. 2B) and 3 invertebrate families (Fig. 2C). The highest algal richness occurred in Andorinhas Stream (23 species; Fig. 2A), the highest fungal richness occurred in Selho River (16 species: Fig. 2B) and the highest invertebrate richness was found in Andorinhas Stream and Selho River (8 families; Fig. 2C). Time of substrate immersion only affected fungal richness, which increased throughout the study period (F ¼ 7.95, p < 0.05; Table 2; Fig. S1) and interactions between stream and time were significant for algal and fungal richness (algae: F ¼ 1.66, p < 0.05; fungi: F ¼ 3.15, p < 0.05; Table 2). The average biomass of each group of organisms differed among streams (algae: F ¼ 6.42, p < 0.05; fungi: F ¼ 5.49, p < 0.05; invertebrates: F ¼ 8.37, p < 0.05; Table 2). Algal biomass ranged from 0.018 mg/cm2 in Oliveira Stream and 0.25 mg/cm2 in Couros Stream (Fig. 3A). Fungal biomass varied between 0.5 mg/cm2 in Couros Stream and 2.29 mg/cm2 in Oliveira Stream (Fig. 3B). Finally, invertebrate biomass varied between 0.04 mg/cm2 in Agra Stream and 2.85 mg/cm2 in Couros River (Fig. 3C). Overall, average algal

35

Richness

Biomass

Invertebrates

Richness

Biomass

Effect

SS

df

F

p

Stream Time Stream*Time Error Stream Time Stream*Time Error Stream Time Stream*Time Error Stream Time Stream*Time Error Stream Time Stream*Time Error Stream Time Stream*Time Error

6.09 0.96 1.66 0.19 62.50 18.06 29.19 136.36 855.73 328.18 165.59 170.67 25.91 28.28 14.20 12.00 243.73 2.99 44.44 122.50 129.06 38.14 46.28 74.08

4 3 12 40 4 3 12 40 4 3 12 39 4 3 12 39 4 3 12 38 4 3 12 40

11.02 2.33 28.98

0.001 0.126 0.000

6.42 2.48 0.71

0.005 0.111 0.729

15.54 7.95 3.15

0.000 0.003 0.003

5.49 7.99 3.85

0.009 0.003 0.001

16.47 0.27 1.15

0.000 0.847 0.353

8.37 3.30 2.08

0.002 0.058 0.041

and invertebrate biomass were higher in the most eutrophic streams, while fungal biomass was highest in streams with intermediate levels of eutrophication (Fig. 3). Biomass of fungi varied with the time of immersion (F ¼ 7.99, p < 0.05; Fig. S2) and significant interactions between time and stream were found for fungal and invertebrate biomass (fungi: F ¼ 3.85, p < 0.05; invertebrates: F ¼ 2.08, p < 0.05; Table 2). Correspondence analysis for periphytic algal community showed that Andorinhas Stream was separated by axis 1 from the other streams (54% of the total variance; Fig. 4A). Algal communities of the oligotrophic and mesotrophic streams (Agra and Oliveira streams, respectively) were separated by the second axis (25% of total variance) from communities of the eutrophic streams (Selho River and Couros Stream; Fig. 4A). Achnanthidium minutissimum, Eunotia sudetica and Eunotia minor were the dominant algal species in Agra e Oliveira, while Niszchia palea and A. minutissimum were dominant in Selho River and Couros Stream. The cyanophyceae Chamaesiphon sp.1 was the dominant algal species in Andorinhas stream. Correspondence analysis of fungal communities showed that axis 1 explained 61% of the total variance, while axis 2 explained 9% (Fig. 4B). The analysis discriminated 3 groups of fungal communities as follows: i) Selho and Couros streams, ii) Andorinhas stream, and iii) Agra and Oliveira streams. Dimorphospora foliicola and Tricladium chaetocladium were the dominant fungal species in Couros and Selho streams, respectively. The dominant fungal species in Andorinhas Stream was T. chaetocladium followed by Articulospora tetracladia, while Flagellospora sp. was dominant in Agra and Oliveira streams. Invertebrate communities of Selho River and Couros Stream separated from those of other streams by the axis 1, which explained 48% of the total variance (Fig. 4C). Invertebrate communities of Agra and Oliveira streams were separated from those of Andorinhas Stream by the axis 2 (12% of total variance; Fig. 4B). Chironomids and oligochaetes dominated the invertebrate communities in Selho and Couros streams and Physidae were also abundant in Couros Stream. Nemouridae, Hydropsychidae and Simuliidae were well represented in Agra and Oliveira streams, but

36

B. Dunck et al. / Environmental Pollution 202 (2015) 32e40

Fig. 2. Taxon richness of algae (A), fungi (B) and invertebrates (C) associated with the substrates immersed for 28 days in five streams of the Ave River basin. Different letters above bars indicate significant differences between streams (Tukey's test, p < 0.05). Streams are sorted according to the eutrophication gradient: Agra Stream < Oliveira Stream < Andorinhas Stream < Selho River < Couros Stream.

Fig. 3. Biomass of algae (A), fungi (B) and invertebrates (C) associated with the substrates immersed for 28 days in five streams of the Ave River basin. Different letters above bars indicate significant differences between streams (Tukey's test, p < 0.05). Streams are sorted according to the eutrophication gradient: Agra Stream < Oliveira Stream < Andorinhas Stream < Selho River < Couros Stream.

Hydropsychidae and Simuliidae were more abundant in Oliveira Stream. Andorinhas Stream separated from the other streams due to high abundance of Leptophlebiidae and Athericidae and the presence of odonates, which did not occur in any other stream. Procrustean analysis showed that invertebrate and fungal communities had similar ordination patterns (r ¼ 0.88, p ¼ 0.04), which differed from the ordination pattern of algal communities (invertebrate: r ¼ 0.80, p ¼ 0.24; fungal: r ¼ 0.76; p ¼ 0.43). Mantel test showed significant correlation between invertebrates and fungal similarities (r ¼ 0.89, p ¼ 0.008; Fig. 5A), but no significant correlations were found between algal and invertebrate or fungal similarities (r ¼ 0.10, p ¼ 0.64; r ¼ 0.10, p ¼ 0.49) (Fig. 5B, C). 3.3. Rates of leaf litter decomposition and primary production Rates of leaf litter decomposition and primary production followed the same pattern along the eutrophication gradient (Fig. 6). In the most oligotrophic stream (Agra Stream), leaf decomposition rate was low and primary productivity was below the detection limit. Both process rates reached their maximum in the Oliveira Stream, the second least eutrophic stream, and then decreased as the degree of eutrophication increased. 4. Discussion In this study, we showed that primary production and leaf litter decomposition responded in a similar way to stream eutrophication with low process rates at the extremes of the eutrophication gradient and high rates at intermediate levels. This suggests that subsidy response (increase) of process rates in moderate levels of nutrient enrichment is common among aquatic communities, but a stress response (decrease) at high levels of nutrient enrichment can also happen due to the co-occurrence of other stressors in highly

eutrophic streams (Mittelbach et al., 2001). In our study, eutrophication was probably related to anthropogenic activities from agriculture and urbanization in the Ave River basin. The oligotrophic stream (Agra Stream) is in a less impacted area and had higher cover canopy from riparian vegetation, while Couros Stream showed the highest values for ammonium, phosphate and nitrite and had a narrow corridor of riparian vegetation. Previous studies have reported that eutrophication occurs in streams of the Ave River basin with implications to aquatic biota involved in organic matter turn-over (Pascoal et al., 2005a; Lima-Fernandes et al., 2014). Even though primary production and leaf litter decomposition showed a similar response pattern to eutrophication, process rates in the studied streams varied ca. 3 times for leaf litter decomposition and 2 times for primary production. In general, primary production driven by periphytic algae is constrained in shaded environments (Hill et al., 1995). Although we found high algal biomass in the most eutrophic stream (Couros Stream), probably due to high phosphorus availability and low canopy cover, primary production rate was low. Such results suggest that primary production may be influenced not only by the canopy cover but also by other factors, such as turbidity that may affect species composition of algal communities. Some studies have shown that periphytic algal communities can harbour species with different abilities for primary production with consequences for overall community performance (Cardinale et al., 2005). The higher biomass and abundance of small-sized diatoms tolerant to eutrophication and turbid waters (Reynolds, 1995) in the Couros Stream may have resulted in lower primary production rates when compared with communities dominated by green algae as those found in Andorinhas Stream. Moreover, it is conceivable that pesticides from agricultural fields are present in the stream water of Couros Stream, and may have influenced algal community structure, growth dynamics and primary production (Villeneuve et al.,

B. Dunck et al. / Environmental Pollution 202 (2015) 32e40

37

2011). Leaf litter decomposition is an integrative process that links riparian vegetation, microbial decomposers and invertebrate detritivores. In oligotrophic streams, fungal contribution to plant litter decomposition may be lower when compared to that of invertebrate detritivores (15e18% versus 51e64%, respectively; Hieber and Gessner, 2002). The lowest rate of leaf decomposition at the oligotrophic end of the gradient (Agra Stream) might have been due to lower invertebrate biomass compared to the other studied streams. Fungal biomass was high in Agra stream, but this was not enough to ensure a high rate of leaf decomposition. However, we should point out that leaf decomposition rate in this oligotrophic stream (k ¼ 0.017 day1) was comparable to that found for alder leaves in non-impacted streams of northwest Portugal (Pascoal et al., 2001). The accelerated litter decomposition in streams with moderate levels of eutrophication likely resulted from stimulation of fungal activity on leaves and consequent increase of invertebrate leaf consumption (Woodward et al., 2012; Pascoal et al., 2005a). Nutrient enrichment is known to stimulate biomass and taxon richness of fungi (Gulis and Suberkropp, 2003; Ferreira et al., 2006; Chung and Suberkropp, 2008) and invertebrates (Greenwood et al., 2007; Chung and Suberkropp, 2008; but see Ferreira et al., 2006). It is conceivable that fungi, being stimulated by nutrients at moderate levels, were able to continue the decomposition process although not at levels as high as those ensured by the shredder activity. The highest shredder biomass occurred in Oliveira Stream decreasing sharply in Selho River and Couros Stream (not shown). In hypertrophic streams, the presence of toxic compounds has been associated with shifts in community structure of fungi (nitrite and ammonia: 103 and 7.1 mg/L, respectively; Duarte et al., 2009) and invertebrates (nitrite and ammonia: 34.2 and 388.1 mg/L, respectively; Lecerf et al., 2006) and a reduction in decomposer activity. In our study, nitrite and ammonia attained much higher concentrations in the most eutrophic stream (171.8 and 1778.0 mg/L in Couros Stream, respectively), probably explaining the strong reduction in fungal and invertebrate activity. Although periphytic algae presented the highest taxon richness when compared to fungi or invertebrates, the response of benthic communities to eutrophication was similar, with highest richness occurring in streams with intermediate levels of eutrophication (Oliveira, Andorinhas and Selho). At moderate nutrient levels, more species are expected to coexist due to a reduction in interspecific competition. However, the most eutrophic stream showed lower richness of benthic taxa as found in other studies (peryphitic algae, Hillebrand and Sommer, 2000; Worm et al., 2002; fungi, Pascoal

Fig. 4. Correspondence analysis of algal (A), invertebrate (B) and fungal (C) communities associated with the substrates immersed for 28 days in five streams of the Ave River basin. (Algal taxa: A1- Achnanthidium minutissimum, A2- Aulacoseira alpigena, A3- Chamaesiphon sp.1, A4- Epibolium sp.1, A5- Encyonema minuta, A6- Eunotia bilunaris, A7- Eunotia maior, A8- Eunotia minor, A9- Gomphoenam parvulum, A10- Gomphonema sp.1, A11- Hanszchia sp.1, A12- Leptolyngbya sp.1, A13- Monoraphidium arcuatum, A14- Monoraphidium contortum, A15- Monoraphidium curvulum, A16Monoraphidium griffithi, A17- Monoraphidium longisculum, A18- Navicula cryptocephala, A19- Nitzschia palea, A20- Surirella angusta, A21- Ulnaria ulna; Fungal taxa: F1- Alatospora flagellata, F2- Articulospora tetracladia, F3- Anguillospora crassa, F4- Anguillospora filiformis, F5- Anguillospora furtiva, F6- Anguillospora longuissima, F7-

Anguillospora sp., F8- Alatospora acuminate, F9- Alatospora pulchella, F10- Clavariopsis aquatica, F11- Clavatospora longibranchiata, F12- Culicidospora aquatica, F13- Cylindrocarpon sp.1, F14- Cylindrocarpon sp.2, F15- Dimorphospora foliicola, F16- Flagelospora sp., F17- Flagelospora penicillioides, F18- Fontanospora fusiramosa, F19- Fusarium sp., F20- Goniopila monticola/Margaritispora aquatica, F21- Heliscella stellata, F22- Heliscus lugdunensis, F23- Infundibura sp., F24- Lemonniera aquatica, F25- Lunulospora curvula, F26- Mycofalcella calcarata, F27- Tetrachaetum elegans, F28- Tetracladium marchalianum, F29- Tricladium chaetocladium, F30- Tricladium splendens, F31-Tripospermum myrti, F32Triscelophorus acuminatus; Invertebrate taxa: I1- Nemouridae, I2- Capniidae, I3Chloroperlidae, I4- Perlodidae, I5- Limnephilidae, I6- Rhyacophilidae, I7- Sericostomatidae, I8- Lepidostomatidae, I9- Polycentropodidae, I10- Calamoceratidae, I11Helichopsychidae, I12- Hydropsychidae, I13- Chironomidae, I14- Tipulidae, I15Simuliidae, I16- Athericidae, I17- Ceratopogonidae, I18- Psychodidae, I19- Calopterygidae, I20- Aeschnidae, I21- Baetidae, I22- Leptophlebiidae, I23- Caenidae, I24Ephemerellidae, I25- Asellidae, I26- Enchytraeidae, I27- Lumbricidae, I28- Lumbriculidae, I29- Naididae, I30- Tubificidae, I31- Physidae, I32- Hydrobiidae, I33- Elmidae, I34- Gyrinidae, I35- Dryopidae, I36- Hydrophilidae, I37- Dytiscidae, I38- Pyralidae, I39- Glossiphonidae, I40- Erpobdellidae, I41- Chrysomellidae, I42- Vellidae, I43Helophoridae).

38

B. Dunck et al. / Environmental Pollution 202 (2015) 32e40

Fig. 5. Correlation between community dissimilarities analysed by Mantel test. A- Invertebrates x Fungal dissimilarity, B- Algal x Invertebrates dissimilarity; C- Algal x Fungal dissimilarity.

et al., 2005c; and invertebrates, Lecerf et al., 2006). Results can be interpreted according to the subsidy-stress model, in which when algae and decomposers were nutrient limited, their activity and diversity would increase at moderate levels of nutrient enrichment, but decrease at high levels of nutrients, because eutrophication would lead to the presence of other stressors, which could overwhelm the subsidy effect of nutrients (Rosenzweig, 1995; Mittelbach et al., 2001). Algal communities in the Couros Stream and Selho River were dominated by Eunotia minuta F.W. Hilse, Gomphonema parvulum (Kützing) Kützing, Navicula cryptocephala Kützing, and Nitzschia

Fig. 6. Leaf decomposition rate (white bars) and primary production rate measured as electron transport rate (ETR) (black bars) in five streams of the Ave River basin. Electron transport rate (ETR) in the Agra stream was below the detection limit.

palea (Kützing) W. Smith. Such species are generally recognized as tolerant to organic pollution and eutrophication (Kobayasi and Mayama, 1989; Lobo et al., 1995). Agra and Oliveira streams were dominated by Achnanthidium minutissimum (Kützing) Czarnecki, E. minor (Kützing), E. sudetica O. Müller, Monoraphidium contortum
rkova
-Legnerov
(Thuret) Koma a, and Monoraphidium longisculum
k. Achnanthidium minutissimum is among the most frequently Hinda recorded diatom species in periphytic samples worldwide (Patrick and Reimer, 1966; Krammer and Lange-Bertalot, 1991) since it occurs in environments ranging from acid to alkaline, and oligotrophic to eutrophic, a feature that remains intriguing (Round, 2004; Potapova and Hamilton, 2007). Species of genus Eunotia in turn
n and Jarlman, 2008) which may favour are acid-tolerant (Andre them to settle in acidic and circumneutral freshwaters (Dunck et al., 2013), such as those found in our study. M. contortum and M. longisculum found in Agra and Oliveira streams are generally associated with environments with low to moderate nutrient concentrations (John and Tsarenko, 2002). Alterations in fungal communities due to eutrophication have
ssio, 2004) with been described (Duarte et al., 2009; Pascoal and Ca some fungal species or populations showing tolerance to water pollution (Pascoal et al., 2005b; Duarte et al., 2009; Fernandes et al., 2011). In our study, the fungal communities were able to discriminate the level of stream eutrophication. For instance, fungal community in the oligotrophic stream (Agra Stream) was dominated by Articulospora tetracladia Ingold, which became less represented as the level of eutrophication increased, until its disappearance in the Couros Stream. Some of the species associated with Selho River and Couros Stream, such as Dimorphospora foliicola Tubaki and Tetracladium marchalianum De Wild, have been reported in eutrophic streams of this region (Duarte et al., 2009).

B. Dunck et al. / Environmental Pollution 202 (2015) 32e40

The structure of invertebrate communities separated the Selho River and Couros Stream from the other streams. Families belonging to the Ephemeroptera, Plecoptera and Trichoptera orders, which are known to include taxa sensitive to eutrophication
re
ghino, 2003), were present mostly in Agra, Oli(Compin and Ce veira and Andorinhas streams. Invertebrate communities of Selho River and Couros Stream were mainly constituted by generalist and pollution tolerant taxa such as Oligochaeta and Chironomidae, which can be found in polluted environments (Pascoal et al., 2005a; Oscoz et al., 2010). Interestingly, a strong a correlation was found between invertebrate and fungal community similarities suggesting a common response pattern of both communities to eutrophication. 5. Conclusions In conclusion, rates of periphytic algal production and of leaf litter decomposition showed a similar response pattern to eutrophication with lower values at both ends of the trophic gradient. Fungal richness and biomass followed the same pattern as leaf litter decomposition and primary production. Shifts in periphytic and invertebrate communities with increasing eutrophication resulted in increased biomass and reduced taxonomic richness. Results may be explained by the subsidy-stress model, according to which activity and diversity of algae and decomposers increase at moderate levels of nutrients, and decrease at high levels of nutrients due to the presence of other stressors. Acknowledgements This study was supported by The European Regional Development Fund e Operational Competitiveness Programme (FEDERPOFC-COMPETE) and the Portuguese Foundation for Science and Technology (PEst-OE/BIA/UI4050/2014, PTDC/AAC-AMB/117068/ 2010). B. Dunck thanks to the Coordination for the Improvement of Higher Education Personnel (CAPES) for the scholarship granted in Sandwich PhD program (BEX process: 16506/12-0). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.envpol.2015.03.014. References Agostinho, A.A., Thomaz, S.M., Gomes, L.C., 2005. Conservation of the biodiversity of Brazil's inland waters. Conserv. Biol. 19, 646e652. http://dx.doi.org/10.1111/ j.1523-1739.2005.00701.x. Allan, J.D., 2004. Landscapes and riverscapes: the influence of land use on stream ecosystems. Annu. Rev. Ecol. Evol. Syst. 35, 257e284. http://dx.doi.org/10.1146/ annurev.ecolsys.35.120202.110122.
n, C., Jarlman, A., 2008. Benthic diatoms as indicators of acidity in streams. Andre Fundam. Appl. Limnol. Arch. Hydrobiol. 173, 237e253. http://dx.doi.org/ 10.1127/1863-9135/2008/0173-0237. Baldy, V., Gobert, V., Guerold, F., Chauvet, E., Lambrigot, D., Charcosset, J.Y., 2007. Leaf litter breakdown budgets in streams of various trophic status: effects of dissolved inorganic nutrients on microorganisms and invertebrates. Freshw. Biol. 52, 1322e1335. http://dx.doi.org/10.1111/j.1365-2427.2007.01768.x. €rlocher, F., 2005. Leaf mass loss estimated by litter bag technique. In: Methods to Ba Study Litter Decomposition: a Practical Guide. Springer, Dordrecth, pp. 37e42. ^neros de algas de a
guas continentais do Brasil: Bicudo, C., Menezes, M., 2006. Ge ~o e descriço ~es, second ed. Rima, Sa ~o Carlos. chave para identificaça Cardinale, B.J., Palmer, M.A., Ives, A.R., Brooks, S.S., 2005. Diversityeproductivity relationships in streams vary as a function of the natural disturbance regime. Ecology 86, 716e726. http://dx.doi.org/10.1890/03-0727. Chung, N., Suberkropp, K., 2008. Influence of shredder feeding and nutrients on fungal activity and community structure in headwater streams. Fundam. Appl. Limnol. Arch. Hydrobiol. 173, 35e46. http://dx.doi.org/10.1127/1863-9135/ 2008/0173-0035.
re
ghino, R., 2003. Sensitivity of aquatic insect species richness to Compin, A., Ce disturbance in the AdoureGaronne stream system (France). Ecol. Indic. 3,

39

135e142. http://dx.doi.org/10.1016/S1470-160X(03)00016-5. Danger, M., Cornut, J., Chauvet, E., Chavez, P., Elger, A., Lecerf, A., 2013. Benthic algae stimulate leaf litter decomposition in detritus-based headwater streams: a case of aquatic priming effect? Ecology 94, 1604e1613.
tian, F., Ca
ssio, F., Charcosset, J.Y., 2009. Microbial Duarte, S., Pascoal, C., Garabe decomposer communities are mainly structured by trophic status in circumneutral and alkaline streams. Appl. Environ. Microbiol. 75, 6211e6221. http:// dx.doi.org/10.1128/AEM.00971-09. Dunck, B., Nogueira, I.S., Felisberto, S.A., 2013. Distribution of periphytic algae in wetlands (Palm swamps, Cerrado), Brazil. Braz. J. Biol. 73, 331e346. Eilers, P.H.C., Peeters, J.C.H., 1988. A model for the relationship between light intensity and the rate of photosynthesis in phytoplankton. Ecol. Modell. 42, 199e215. http://dx.doi.org/10.1016/0304-3800(88)90057-9.
ssio, F., 2011. Intraspecific traits change biodiversity Fernandes, I., Pascoal, C., Ca effects on ecosystem functioning under metal stress. Oecologia 166, 1019e1028. http://dx.doi.org/10.1007/s00442-011-1930-3. Fernandes, I., Seena, S., Pascoal, C., 2014. Elevated temperature may intensify the positive effects of nutrients on microbial decomposition in streams. Freshw. Biol. 59, 2390e2399. Ferragut, C., Bicudo, D.C., 2012. Effect of N and P enrichment on periphytic algal community succession in a tropical oligotrophic reservoir. Limnology 13, 131e141. Ferreira, V., Chauvet, E., 2011. Synergistic effects of water temperature and dissolved nutrients on litter decomposition and associated fungi. Glob. Chang. Biol. 17, 551e564. http://dx.doi.org/10.1111/j.1365-2486.2010.02185.x. Ferreira, V., Gulis, V., Graça, M.A., 2006. Whole-stream nitrate addition affects litter decomposition and associated fungi but not invertebrates. Oecologia 149, 718e729. http://dx.doi.org/10.1007/s00442-006-0478-0. Gessner, M.O., Chauvet, E., 1993. Ergosterol-to-biomass conversion factors for aquatic hyphomycetes. Appl. Environ. Microbiol. 59, 502e507. Gessner, M.O., Gulis, V., Kuehn, K.A., Chauvet, E., Suberkropp, K., 2007. Fungal decomposers of plant litter in aquatic ecosystems. In: Kubicek, C.P., Druzhinina, I.S. (Eds.), The Mycota, Microbial and Environmental Relationships, second ed., vol. IV. Springer-Verlag, Berlin, pp. 301e324. Gessner, M.O., 2005. Ergosterol as a measure of fungal biomass. In: Methods to Study Litter Decomposition: a Practical GuideSpringer, Dordrecth, pp. 189e195. Golterman, H., Clymo, R., Ohmstad, M., 1978. Methods for Physical and Chemical Analysis of Freshwaters, IBP Handbook. Blackwell Scientific, Oxford. Goudie, A.S., 1999. The Human Impact on the Natural Environment, fifth ed. MIT Press, Cambridge. Greenwood, J.L., Rosemond, A.D., Wallace, J.B., Cross, W.F., Weyers, H.S., 2007. Nutrients stimulate leaf breakdown rates and detritivore biomass: bottom-up effects via heterotrophic pathways. Oecologia 151, 637e649. http://dx.doi.org/ 10.1007/s00442-006-0609-7. Gulis, V., Suberkropp, K., 2003. Interactions between stream fungi and bacteria associated with decomposing leaf litter at different levels of nutrient availability. Aquat. Microb. Ecol. 30, 149e157. http://dx.doi.org/10.3354/ame030149. Hieber, M., Gessner, M.O., 2002. Contribution of stream detrivores, fungi, and bacteria to leaf breakdown based on biomass estimates. Ecology 83, 1026e1038. http://dx.doi.org/10.1890/0012-9658(2002)083[1026:COSDFA]2.0.CO2. Hill, M., 1974. Correspondence analysis: a neglected multivariate method. Appl. Stat. 23, 340e354. Hill, W., Ryon, M., Schilling, E., 1995. Light limitation in a stream ecosystem: responses by primary producers and consumers. Ecology 76, 1297e1309. Hillebrand, H., Sommer, U., 2000. Diversity of benthic microalgae in repsonse to colonization time and eutrophication. Aquat. Bot. 67, 221e236. Hooper, D.U., Adair, E.C., Cardinale, B.J., Byrnes, J.E.K., Hungate, B.A., Matulich, K.L., Gonzalez, A., Duffy, J.E., Gamfeldt, L., O'Connor, M.I., 2012. A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486, 105e108. http://dx.doi.org/10.1038/nature11118. Jackson, D.A., 1993. Sttoping rules in principal components analysis: a comparison of heuristical and statistical approaches. Ecology 74, 2204e2214. Jackson, D.A., 1995. PROTEST: a Procrustean randomization test of community environment concordance. Ecoscience 2, 297e303. John, D.M., Tsarenko, P.M., 2002. Order Chlorococcales. In: John, D.M., Whitton, B.A., Brook, A.J. (Eds.), The Freshwater Algal Flora of the British Isles. An Identification Guide to Freshwater and Terrestrial Algae. Cambridge University Press, Cambridge, pp. 327e409. Kobayasi, H., Mayama, S., 1989. Evaluation of river water quality by diatoms. Korean J. Phycol. 4, 121e133. Krammer, K., Lange-Bertalot, H., 1991. Süßwasserflora von Mitteleuropa. Bacillariophyceae 3. Teil: Centrales, Fragilariaceae, Eunotiaceae. Spektrum, Heidelberg and Berlin. Lecerf, A., Usseglio-Polatera, P., Charcosset, J.Y., Lambrigot, D., Bracht, B., Chauvet, E., 2006. Assessment of functional integrity of eutrophic streams using litter breakdown and benthic macroinvertebrates. Arch. Hydrobiol. 165, 105e126. http://dx.doi.org/10.1127/0003-9136/2006/0165-0105. Legendre, P., Legendre, L., 1998. In: Numerical Ecology, second ed. Elsevier Science. Liang, X., Zhu, S., Ye, R., Guo, R., Zhu, C., Fu, C., Tian, G., Chen, Y., 2014. Biological thresholds of nitrogen and phosphorus in a typical urban river system of the Yangtz delta, China. Environ. Pollut. 192, 251e258. http://dx.doi.org/10.1016/ j.envpol.2014.04.007.
ssio, F., Pascoal, C., 2014. Lima-Fernandes, E., Fernandes, I., Pereira, A., Geraldes, P., Ca Eutrophication modulates plant-litter diversity effects on litter decomposition in streams. Freshw. Sci. http://dx.doi.org/10.1086/679223.

40

B. Dunck et al. / Environmental Pollution 202 (2015) 32e40

Lobo, E.A., Katoh, K., Aruga, Y., 1995. Response of epilithic diatom assemblages to water pollution in rivers in the Tokyo Metropolitan area. Jpn. Freshw. Biol. 34, 191e204. Loreau, M., de Mazancourt, C., 2013. Biodiversity and ecosystem stability: a synthesis of underlying mechanisms. Ecol. Lett. 16, 106e115. http://dx.doi.org/ 10.1111/ele.12073. Mittelbach, G.G., Steiner, C.F., Scheiner, S.M., Gross, K.L., Reynolds, H.L., Waide, R.B., Willig, M.R., Dodson, S.I., Gough, L., 2001. What is the observed relationship between species richness and productivity? Ecology 82, 2381e2396. Niyogi, D.K., Koren, M., Arbuckle, C.J., Townsend, C.R., 2007. Stream community along a catchment land-use gradient: subsidy-stress responses to pastoral development. Environ. Manage 39, 213e225. Odum, E.P., Finn, J.T., Franz, E.H., 1979. Perturbation theory and the subsidy-stress gradient. Bioscience 29, 344e352. Oscoz, J., Galicia, D., Miranda, R., 2010. Identification Guide of Freshwater Macroinvertebrates of Spain. Springer, Dordrecth. http://dx.doi.org/10.1007/978-94007-1554-7. Pascoal, C., C
assio, F., 2004. Contribution of fungi and bacteria to leaf litter decomposition in a polluted river. Appl. Environ. Microbiol. 70, 5266e5273. http://dx.doi.org/10.1128/AEM.70.9.5266.
ssio, F., Gomes, P., 2001. Leaf breakdown rates: a measure of water Pascoal, C., Ca quality? Int. Rev. Hydrobiol. 86, 407e416.
ssio, F., Marcotegui, A., 2005a. Role of fungi, bacteria, and inPascoal, C., Ca vertebrates in leaf litter breakdown in a polluted river. J. N. Am. Benthol. Soc. 24, 784e797.
, L., 2005b. Anthropogenic stress may affect aquatic Pascoal, C., C
assio, F., Marvanova hyphomycete diversity more than leaf decomposition in a low-order stream. Arch. Hydrobiol. 162, 481e496. http://dx.doi.org/10.1127/0003-9136/2005/ 0162-0481.
, L., Ca
ssio, F., 2005c. Aquatic hyphomycete diversity in Pascoal, C., Marvanova streams of Northwest Portugal. Fungal Divers. 19, 109e128. Pascoal, C., Pinho, M., C
assio, F., Gomes, P., 2003. Assessing structural and functional ecosystem condition using leaf breakdown: studies on a polluted river. Freshw. Biol. 48, 2033e2044. Patrick, R., Reimer, C.W., 1966. The Diatoms of the United States, Exclusive of Alaska and Hawaii. In: Fragilariaceae, Eunotiaceae, Achnanthaceae, Naviculaceae. Academy of Natural Sciences of Philadelphia Monograph No. 13, vol. 1. Peres-Neto, P., Jackson, D., 2001. How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test. Oecologia 129, 169e178. http://dx.doi.org/10.1007/s004420100720. Potapova, M., Hamilton, P.B., 2007. Morphological and ecological variation within the Achnanthidium minutissimum (Bacillariophyceae) species complex. J. Phycol. 43, 561e575. Quinn, G.P., Keough, M.J., 2002. Experimental Design & Data Analysis for Biologists. Cambridge University Press, New York. R Development Core Team, 2013. R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3900051-07-0. http://www.R-project.org/. Reynolds, C.S., 1995. The Intermediate disturbance hypothesis and its applicability
k and Wilson. to planktonic communities: comments on the views of Padisa

N. Z. J. Ecol. 19, 219e225.
cticas de ecología. Editorial Omega. Ros, J., 1979. Pra Rosemond, A.D., Swan, C.M., Kominoski, J.S., Dye, S.E., 2010. Non-additive effects of litter mixing are suppressed in a nutrient-enriched stream. Oikos 119, 326e336. http://dx.doi.org/10.1111/j.1600-0706.2009.17904.x. Rosenzweig, M.L., 1995. Species Diversity in Space and Time. Cambridge University Press, Cambridge, UK. Round, F.E., 2004. pH scaling and diatom distribution. Diatom 20, 9e12. Schreiber, U., Schliwa, U., Bilger, W., 1986. Continuous recording of photochemical and nonphotochemical chlorophyll fluorescence quenching with a new type of modulation fluorometer. Photosynth. Res. 10, 51e62. Schreiber, U., Gademann, R., Ralph, P.J., Larkum, A.W.D., 1997. Assessment of photosynthetic performance of Prochloron in Lissoclinum patella in hospite by chlorophyll fluorescence measurements. Plant Cell. Physiol. 38, 945e951. Smith, V.H., Joye, S.B., Howarth, R.W., 2006. Eutrophication of freshwater and marine ecosystems. Limnol. Oceanogr. 51, 351e355. http://dx.doi.org/10.4319/ lo.2006.51.1_part_2.0351. Smith, V.H., Tilman, G.D., Nekola, J.C., 1999. Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environ. Pollut. 100, 179e196. http://dx.doi.org/10.1016/S0269-7491(99)00091-3. Stamenkovic, M., Hanelt, D., 2011. Growth and photosynthetic characteristics of several Cosmarium strains (Zygnematophyceae, Streptophyta) isolated from various geographic regions under a constant light-temperature regime. Aquat. Ecol. 45, 455e472.
bre
s D'eau Tachet, H., Richoux, P., Bournaud, M., Usseglio-Polatera, P., 2010. Inverte


matique, Biologie, Ecologie. Douce: Syste CNRS Editions, Paris. Thompson, R.M., Townsend, C.R., 2005. Energy availability, spatial heterogeneity and ecosystem size predict food-web structure in streams. Oikos 108, 137e148. €hl, H., 1958. Zur Vervollkommnung der quantitativen PhytoplanktonUtermo Methodik. Mitt. Int. Ver. Theor. Angew. Limnol. 9, 1e38. Villeneuve, A., Montuelle, B., Bouchez, A., 2011. Effects of flow regime and pesticides on periphytic communities: evolution and role of biodiversity. Aquat. Toxicol. 102, 123e133. € ro € smarty, C., McIntyre, P., Gessner, M., 2010. Global threats to human water seVo curity and river biodiversity. Nature 467, 555e561. http://dx.doi.org/10.1038/ nature09440. Wetzel, R.G., Likens, G.E., 1991. Limnological Analysis, second ed. Springer-Verlag, New York. White, A.J., Critchley, C., 1999. Rapid light curves: a new fluorescence method to assess the state of the photosynthetic apparatus. Photosynth. Res. 59, 63e72. Worm, B., Lotze, H.K., Hillebrand, H., Sommer, U., 2002. Consumer versus resource control of species diversity and ecosystem functioning. Nature 417, 848e851. http://dx.doi.org/10.1038/nature00830. Woodward, G., Gessner, M.O., Giller, P.S., Gulis, V., Hladyz, S., Lecerf, A., Malmqvist, B., McKie, B.G., Tiegs, S.D., Cariss, H., Dobson, M., Elosegi, A., re, J.O., Nistorescu, M., Pozo, J., Ferreira, V., Graça, M.A.S., Fleituch, T., Lacoursie Risnoveanu, G., Schindler, M., Vadineanu, A., Vought, L.B., Chauvet, E., 2012. Continental-scale effects of nutrient pollution on stream ecosystem functioning. Science 336, 1438e1440.