Trophic availability buffers the detrimental effects
of clogging in an alpine stream
Alberto Dorettoa, Francesca Bonaa, Elena Pianoa, Ilaria Zanina, Anna Chiara Eandia, Stefano
Fenogliob
aDBIOS, Università degli Studi di Torino, Via Accademia Albertina 13, I-10123 Torino, Italy. bDISIT, Università del Piemonte Orientale, Viale Teresa Michel 25, I-15121 Alessandria, Italy.
*Corresponding author. E-mail address: stefano.fenoglio@uniupo.it
Abstract
Clogging, the streambed colmation by fine sediments, is an important widespread source of impact affecting freshwaters. Alterations in stream morphology and hydrology, added to the effects of global climate change, are responsible for this phenomenon, that is particularly pernicious in mountainous lotic systems naturally characterized by coarse substrates. Among the studies investigating this issue some were descriptive, while others used artificial substrates to compare ongoing fine sediment accumulation and macroinvertebrate assemblage recruitment. Other studies used from the outset artificial substrates arranged with different levels of clogging. Our study fits into this line, but adding an innovative element simulating different availability of coarse particulate organic matter, i.e. the main trophic input in low-order, mountainous stream. To investigate how clogging and CPOM can influence macroinvertebrate communities, we placed 135 artificial substrates in the upper Po river (NW Italy). We set up a three way factorial design with three different levels of sedimentation and terrestrial leaf material. Artificial substrates were removed on three different dates. Benthic invertebrates were identified and classified according to their bio-ecological traits. We also measured macroinvertebrate dry mass and CPOM degradation in the different trap types. Our findings show that clogging acts as a selective filter influencing taxa 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 1
richness, density, functional composition and biomass of benthic assemblage. Moreover, fine sediments affect the energetic dynamics in the river ecosystem, decreasing the mass loss rate of terrestrial leaves. Interestingly, our results clearly demonstrate that high availability of CPOM can buffer the negative effect of clogging, suggesting that an adequate input of allochthonous organic matter may lessen the impact of fine sediment deposition. Because land use transformation and removal of wooded riparian areas increase clogging and simultaneously reduces the input of CPOM, our findings stress the importance to include the management of river basins in the conservation strategies of mountainous streams.
Key-words: hydrological alterations, climate change, fine sediments, benthic macroinvertebrates, allochthonous organic matter, functional groups.
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1. Introduction
The unnatural increase of fine sediments (i.e. inorganic and organic particles of less than 2 mm in diameter) currently represents one of the most important, widespread and pervasive concern for lotic environments around the world (Naden et al., 2016). In last decades, anthropogenic pressures have altered morphological and hydrological features of most lotic systems, increasing the transport and deposition of unnatural amounts of fine sediment (Wood and Armitage, 1997; Wohl et al., 2015). Intensive agriculture, logging and riparian vegetation removal facilitate the superficial run-off and increase sediment input into watercourses (Burdon et al., 2013). Mining activities have also been recognized as an important source of anthropogenic fine sediments (Milisa et al., 2010; Bona et al., 2016). Moreover, flow regulation and urbanization of catchments affect the transport and deposition dynamics resulting in increased fine sediment amounts (Hogg and Norris, 1991; Buendia et al., 2014). Problems associated to excessive fine sedimentation could also occur as a result of episodic and small scale disturbances, such as flushing form reservoirs (Crosa et al., 2010; Espa et al., 2015) and road construction (Kaller and Hartman, 2004; Kreutzweiser et al., 2005). Finally, in the context of the current climate change scenario, clogging is likely to increase in both frequency and intensity in many watersheds. In fact, heavy fine sediment accumulation (i.e., clogging) is strictly associated with flow reduction and droughts, because lower water velocity enables more sediments to settle out of suspension (Dewson et al., 2007; Rolls et al., 2012).
Increased inputs of fine sediment cause conspicuous physical modifications of the river environment, with consequent chemical, biological and ecological impacts. Indeed, fine sediment is a significant environmental stressor both as suspended or deposited particles (Connolly and Pearson, 2007; Bilotta and Brazier, 2008; Kefford et al., 2010; Larsen and Ormerod, 2010). For example, excessive fine transport enhances turbidity and reduces transparency (Davies-Colley and Smith, 2001), increasing the abrasion of benthic environment (Hedrick et al., 2013) and altering photosynthetic efficiency and biomass of benthic algae (Izagirre et al., 2009; Jones et al., 2014). 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 5
Moreover, clogging causes the loss of interstitial volumes, reduces the substrate permeability to dissolved gases, water, nutrients and metabolites, and enhances the retention of toxic substances, with significant impacts on lotic biota (Brunke and Gonser, 1997; Bo et al., 2007; Archaimbault et al., 2010). In particular, benthic macroinvertebrate communities are significantly impaired by clogging (Jones et al., 2012), with both direct and indirect impacts. The former involve the direct occlusion of gills and filter-feeding apparatus (Lemly, 1982), the burial of less motile organisms (Wood et al., 2005), the reduction of habitat availability and of the available space for occasional hyporheic organisms (Jones et al., 2012). Indirect impacts include alterations in the quality and quantity of energy inputs, considering both in-stream production (Ryan, 1991; Henley et al., 2000; Bona et al., 2016) and allochthonous coarse organic matter availability (Doretto et al., 2016).
Benthic invertebrates are a pivotal component of lotic ecosystems, in terms of biodiversity, biomass and ecological functionality. These organisms show a patchy distribution mostly depending on the local conditions of the substrate (Beisel et al., 2000; Rempel et al., 2000). In particular, particle size and trophic availability are usually recognized as two main drivers affecting the diversity and distribution of macrobenthos (Minshall, 1984; Burdon et al., 2013; Buendia et al., 2014). This is particularly true in mountainous low-order lotic systems, naturally characterized by coarse substrates, where most of the energy input derives from allochthonous non-living coarse particulate organic matter (CPOM), mainly terrestrial leaves (Tank et al. 2010; Bo et al., 2014). To date, leaf-litter breakdown represents one of the most relevant measure of ecosystem processes (Friberg et al., 2011). In these alpine or pre-alpine aquatic systems, clogging can thus have particularly dramatic effects. Despite several studies dealt with the response of benthic communities along a gradient of fine sediments or CPOM conditions (Couceiro et al., 2010; Larsen et al., 2011; Benoy et al., 2012; Bletter et al., 2015), most of them are mainly descriptive and focused on the effects of only one of these factors. By contrast, it cannot be excluded that these two factors interact with each other. For example, Danger and collaborators (2012) demonstrated that the burial of leaf litter by sediments reduces availability, quality and palatability of this resource, resulting in evident alterations of both 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 7
the community of microbic decomposer and the growth rate of invertebrate shredders. Despite the great importance of this topic, few studies have been made using a manipulative approach, which allows to control and manage selected environmental parameters.
To fill this gap, we carried out an experimental field study in which standardized conditions of fine sediment and CPOM were manipulatively combined using artificial substrates. Aim of this study was to evaluate how benthic macroinvertebrate communities respond to the coupled effect of different levels of fine sediment and CPOM in mountainous lotic systems. This study is the first to adopt a manipulative approach to investigate the combined effect of clogging and benthic trophic availability through a quantitative analysis, which can valuably support an effective biomonitoring and management of mountain streams.
Material and methods 1.1 Study area
The study was realized in a homogeneous reach of the upper Po, a typical alpine low-order stream (Paesana, Monviso Natural Park, NW Italy UTM: 360107E, 4949488N; elevation 730 meters a.s.l.). The area is surrounded by a mixed broadleaf forest dominated by Castanea sativa, Fagus sylvatica,
Acer sp., Fraxinus excelsior, and Alnus glutinosa. Over the entire sampling period (November 9th
2015 to January 11th 2016) no relevant morpho-hydrological or chemical changes were observed.
Overall, the sampling reach was 20 m length and characterized by streambed 7.5-10.3 m wide, cold (4.04°C ±0.03 SE), well-oxygenated (99.50 Dissolved Oxygen saturation ±4.45 SE) and oligotrophic (conductivity = 0.172 µS/cm ±0.003 SE; nitrates = 0.70 mg/l; Soluble Reactive Phosphorous < 0.001 mg/l, BOD5 = 3.09 mg/l) condition. During the study period, mean water
depth was 14.4 cm (±0.66 SE), while the average flow velocity was 0.07 m/s (±0.003 SE). Field measurement were performed using a current meter (Hydro-Bios Kiel) and a multiparametric probe (Hydrolab Quanta). 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 9
1.2 Experimental design
To assess how the interaction of different amounts of fine sediments and CPOM influences colonization processes and community composition of macroinvertebrates, we used artificial substrates to have standardized and replicable sampling units. We placed artificial substrates in a large and uniform reach of the Po riverbed, using a random distribution. Each artificial substrate consisted of a parallelepiped trap built with a metal net (18 cm long, 6 cm wide and 6 cm high, mesh width 0.8 cm, total volume = 0.65 dm3). We realized 135 traps, with 3 different levels of
clogging and CPOM obtaining a three way factorial design (Table 1). Traps were filled with different proportions of sand (range size 0.5-1 mm) and pea pebbles (average size 14-20 mm) to provide three different clogging conditions: 45 traps contained 100% pebbles (WFS - without fine sediment), 45 traps contained 50% sand and 50% pebbles (MED - medium clogging condition) and 45 traps contained 66% sand e 33% pebbles (CLO - clogging condition). Sand and pea pebbles are both quite homogeneous in size and represent bare substrates, coming from a building material trader. In addition, to simulate different levels of trophic availability, for each of the clogging categories 15 traps were filled with 0 g, 1 g and 5 g (dry mass) of CPOM respectively. CPOM consisted of recently fallen leaves of European beech (Fagus sylvatica), collected from the ground in a nearby area, then transported to the laboratory and dried for 15 days at room temperature. All traps were marked with a colored and numbered label and a fine net (250 µm) was applied to their lateral and basal sides to avoid the loss of fine sediment and to allow colonization by macroinvertebrates from the upper layer. Artificial substrates were randomly placed on the same day (9th November 2015), buried in the streambed such that the upper side was flush with the bottom, allowing the colonization of benthic taxa. We paid particular attention to guarantee that all artificial substrates were fixed into the stream bottom with the same orientation and in similar conditions of water depth and velocity. To evaluate the colonization dynamic of macroinvertebrates on the different clogging/CPOM conditions, the artificial substrates were removed on three different sampling dates, namely after 7, 21 and 63 days, for a total of 45 random sampling units (5 for each 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 11
typology) on each sampling date. As soon as cages were removed from the streambed, they were immediately placed into a plastic bucket and opened. All the content was transferred in separated plastic tins, preserved in 90% alcohol and returned in laboratory for the sorting and the systematic identification. All benthic invertebrates were systematically identified to the lowest possible level (family level for all taxa except for Plecoptera, Ephemeroptera and Turbellaria that were identified to the genus level according to I.B.E., Ghetti 1997) and counted. Based on their trophic strategies and their biological and ecological requirements, macroinvertebrates were classified into the Functional Feeding Groups (FFGs - Merritt et al., 2008) and biological and ecological traits (Usseglio-Polatera et al., 2000). Because of its importance in bioenergetics pathways, we also measured the biomass of benthic assemblages colonizing the different trap types: after identification, quantitative samples of the last removal date (i.e., when highest density values were achieved) were dried in an oven at 60 °C for 24 hours. Moreover, the remains of the beech leaves initially added to the cages were collected from each trap in each sampling date, separately stored in laboratory and then oven dried at 105 °C until a constant mass was reached (according to Bo et al., 2014). This operation allowed us to assess differences in the CPOM processing in the clogging treatments over the sampling dates.
1.3 Statistical analyses
1.3.1 Community composition analysis
A three-way factorial design examined the effect of clogging and CPOM availability over time on macroinvertebrate community. We first visually inspected whether taxa composition differs among the levels of the three factors, i.e. “Clogging”, “CPOM” and “Removal Date” by means of a Non Metric Multidimensional Scaling (NMDS). We tested whether the observed differences in species composition were significantly different from a random distribution across Clogging, CPOM and Removal Date categories with a Permutational Multivariate Analysis of Variance (PERMANOVA) 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 13
(Anderson, 2001). Taxa composition data were firstly square-rooted transformed to reach a symmetrical distribution. Statistical significance was tested via 9999 random permutations. We then applied the principal response curves (PRC) analysis, a multivariate technique which permits to analyse time-dependent multivariate responses of biological communities to experimental treatments. In other words, it measures how much the experimental units differ in time from the control, which is set to zero (Van den Brink et al., 2009). With this analysis we were able to focus on the way the effect of treatments (Clogging and CPOM) on taxa assemblages changes over time, taking into account the variation between replicates and sampling dates. In order to perform this analysis we crossed together the three treatments of Clogging and CPOM and we obtained a total of nine treatments to be tested. The combination of absence of clogging and high CPOM (WFS5) was chosen as the control and the remaining eight combinations were considered treatments.
1.3.2 Taxa selection mechanisms: turnover vs nestedness
In order to test whether clogging and CPOM availability affected the community structure by either species replacement or species loss, pair-wise dissimilarities were calculated on the abundance data using the approach suggested by Baselga (2013). This framework consists of decomposing the Bray–Curtis dissimilarity index (dBC) into two additive components accounting for the balanced
variation in abundances (dBC-bal) and abundance gradients (dBC-gra). The balanced variation in
abundances (dBC-bal) describes the variation in species density with the overall species density
remaining constant (Baselga, 2013). This is analogous to species replacement in incidence-based patterns, as some individuals are substituted by individuals of different species from site to site, that is it corresponds to true species turnover. The measure for abundance gradients (dBC-gra) describes
the decrease or increase in species density from one site to the other with the overall species density declining or increasing, respectively. This is equivalent to species nestedness in incidence-based patterns, as some individuals may be lost from on site to the other without any substitution. For 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 15
each of the three dissimilarity matrices, we chose the columns referred to the WFS5 samples collected at 63rd day, which represent the reference samples.
We then calculated the Bray-Curtis pair-wise dissimilarity indices (dBC, dBC-bal and dBC-gra) of all
samples against the WFS5 samples collected at 63rd day. In this way, we obtained a measure of the distance of each sample from the control communities.
We explored data in accordance with Zuur et al. (2009, 2010, 2016). We used Cleveland dotplots and boxplots to assess the presence of extreme values and consequently removed the three outliers in order to avoid unusual observations to exert an undue influence on estimated parameters (Zuur et al., 2009).
The effect of Clogging, CPOM and Removal Date as well as the interaction between the Clogging and CPOM factors were firstly checked on dissimilarity measures by means of linear models (LMs). Levels of Clogging (WFS, MED, CLO), CPOM (0 g, 1 g, 5 g) and Removal Date (7, 21, 63) and their interactions were used as fixed factors. Models were then selected with a backward elimination. We assumed a normal error distribution after visually checking for normality of the data.
1.3.3 Taxonomic and functional metrics
In order to get more insights on community alteration, we repeated data exploration as described above to the (i) taxonomic variables (i.e., taxa richness, organisms abundance, EPT Ephemeroptera, Plecoptera and Trichoptera richness – EPTS, and Abundance-EPTN), (ii) functional feeding groups, iii) biological groups and (iv) ecological groups (Zuur et al., 2010, 2016). We here focused on the most representative groups in terms of abundance and ecological relevance to the aim of this study, i.e. shredders, ecological group A (reophilous, xeno to oligo-saprobic, living in cold waters on coarse substrate in the upper section of mountainous lotic systems) and biological group f (medium 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 17
sized, monovoltine, crawlers and shredders, with aquatic respiration; Usseglio-Polatera et al. 2000). We tested the response of these dependent variables against Clogging, CPOM and Removal Date as well as the interaction between Clogging and CPOM by means of Generalized Linear Models (GLMs). Models were then selected with a backward elimination. For taxonomic variables, functional feeding groups, biological groups and ecological groups we firstly assumed a Poisson error distribution and potential deviations from the model assumptions were checked by visually inspecting the distribution of the residuals and by assessing the degree of overdispersion in the Poisson model. After this check, for all the dependent variables relying on abundance measures, we chose the negative binomial error distribution to account for overdispersion. Differences between Clogging, CPOM and Removal Date levels were subsequently checked with a Tukey’s post-hoc test.
Furthermore, to have a deeper view of the effect of CPOM, we split our dataset into three subsets based on the levels of Clogging and we modelled the effect of CPOM and Removal Date on the number of shredders. We focused on shredders since they were expected to be the most sensitive to clogging and especially CPOM availability. Moreover, they are the most representative FFG in alpine, low-order lotic systems (Fenoglio et al., 2015).
Statistical differences in the dry weight of macroinvertebrates and CPOM mass loss at the last removal date (calculated as the difference between the initial dry weight and that measured at the removal date) between clogging levels were tested by means of one-way ANOVA. Dry weight data were first log-transformed in order to achieve a normal distribution. Since only data referred to the last sampling session were used, we initially checked if we had a representative community via accumulation curves. Analyses were conducted in R version 3.2.3 (R Development Core Team, 2015), with the vegan package (Oksanen et al., 2015) for the multivariate analysis, while the MASS (Venables and Ripley, 2002) and multcomp (Hothorn et al., 2008) packages were used for performing statistical models.
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2. Results
2.1 Richness and abundance of colonising assemblages in the different artificial substrates We collected a total of 15908 macroinvertebrates, belonging to 37 different taxa, with a mean of 117.8 individuals and 10.7 taxa per trap, being WFS5 the traps with the highest density and taxonomic richness and CLO0/CLO1 the traps with the lowest values.
NMDS produced a three-dimensional outcome with final stress of 0.20, indicating a good representation of the variance of communities along the three dimensions. Visual inspection of the ordination showed a difference in species composition in response to clogging (Fig. 1). In particular WFS samples, characterised by the absence of fine sediment, resulted more clustered, while the other samples were more scattered. This pattern is further confirmed by the PERMANOVA analysis, which showed a significant effect not only of the Clogging factor but also of CPOM and Removal Date. The combined percentage of variance was of 28% (Tab. 2).
Results of the PRC analysis showed significant differences among treatments along time (F = 2.2246; P < 0.001) (Fig. 2), with the WFS samples (WFS1 and WFS0) resulting the most similar to the control. Considering the MED and CLO samples characterised by high CPOM levels, at the end of the experiment they were more similar to each other than to their respective treatments with lower values of CPOM. The taxa more related to the reference conditions were Amphinemura,
Leuctra, Habroleptoides, Dugesia, Sericostomatidae, Ecdyonurus, Nemoura, Baetis, Athericidae
and Elmidae, while the taxa with higher affinity for clogged conditions were Limonidae and Lumbriculidae.
Final selected models only included the three factors, while the interactions were dropped by the backward elimination. Concerning the dissimilarity, we recorded a significant effect of all treatments on the Bray-Curtis index (dBC), with increasing significant dissimilarity from the CLO
substrates to the WFS substrates (Tukey post-hoc test, P < 0.01) and from 0-1 g to 5 g CPOM 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 21
samples (Tukey post-hoc test, P < 0.01) (Tab. 3). This pattern was mainly explained by the component dBC-gra, for which we observed a significant effect of clogging with higher values of
dissimilarity in the CLO substrates compared to the other treatments (Tukey post-hoc test, P < 0.005). This result indicates that the communities in most compromised samples represented a nested subset of the communities of the control samples, highlighting how dissimilarity among samples is due to the filtering out of most sensitive taxa rather than to the replacement of taxonomic entities.
For all considered taxonomic and functional metrics, an increasing trend was detected from the first to the last removal date, with the exception of EPT taxonomic richness and the ecological group A, for which the Removal Date was not significant.
Taxa richness showed significant differences between Clogging levels, with higher values in non-(WFS) or medium (MED) clogged substrates compared to the high (CLO) ones (Tukey post-hoc test, P < 0.0008). In samples with absence of CPOM (0 g) we could observe lower values of taxa richness than in samples with low (1 g) and high (5 g) CPOM (Tab. 3 and Fig. 3a), although the difference is not significant.
The total abundance was significantly affected by all the experimental treatments (Tab. 3 and Fig. 3b). Significant differences were observed between all pairs of levels of Clogging (Tukey post-hoc test, P < 0.0218), with an increasing trend from clogged to sediment-free samples, and between the high level of CPOM compared to the low and the absence levels (Tukey post-hoc test, P < 0.0168), the high CPOM level positively affecting this metric.
When considering richness (S) and abundance (N) of EPT, i.e. the most sensitive taxa, the trends observed for total abundance and taxa richness were confirmed and even strengthened (Tab. 3 and Fig. 3c, 3d). We observed a significant effect of Clogging on EPT-S, with significant higher values in the absence of fine sediment than in clogged samples (Tukey post-hoc test, P < 0.0001). For EPT-N we observed a significant effect of all treatments. When considering clogging, we detected significant differences between all the levels (Tukey post-hoc test, P < 0.005), with an increasing 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 23
trend from high to absence of clogging, while, for CPOM, higher values were observed in the samples with 5 g of CPOM than in the other two categories of organic matter (Tukey post-hoc test,
P < 0.001).
2.2 Functional composition and biomass of colonising assemblages in the different artificial
substrates
Considering shredders, we observed a significant effect of clogging with differences between all the pairs of clogging levels (Tukey post-hoc test, P < 0.01). Shredder abundance decreased with the increasing of clogged conditions, while for CPOM significant differences were observed between the traps with high CPOM level against the traps with intermediate and low CPOM levels (Tukey post-hoc test, P < 0.001). When we tested the role of CPOM against the subset of samples with high Clogging level, we observed a stronger, positive effect of CPOM on shredders abundance than that found in the subset of WFS samples, thus indicating a buffering effect of CPOM on highly compromised substrates (Tab. 4 and Fig. 4a).
Considering biological and ecological groups, we observed a significant effect of both clogging and CPOM, with differences between all the three levels of Clogging (Tukey post-hoc test, P < 0.005), and between the high level of CPOM against the other two levels (Tukey post-hoc test, P < 0.005) for both biological group f and ecological group A. Their abundance was higher on sediment-free substrates than in the clogged ones and high quantity of CPOM had a positive effect (Tab. 3 and Fig. 4b, 4c).
Regarding the dry weight of colonising assemblages in the last removal date, we detected a significant effect of fine sediment (F2,41 = 6.217; P = 0.004). In particular, dry weight was lower in
clogged samples than in the other two categories of Clogging (Tukey’s Post-hoc test: P < 0.05) (Fig. 5). Before performing this analysis, we checked the representativeness of our sampling by means of a species accumulation curve (Fig. 6).
2.3 CPOM degradation in different artificial substrates 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 25
We detected a significant effect of fine sediment on the CPOM mass loss (F2,12 = 9.954; P = 0.003).
In particular, lower values of mass loss were observed in clogged samples (Tukey’s Post-hoc test: P < 0.05), suggesting a decreased degradation rate of allochthonous organic matter under siltation conditions (Fig. 7).
3. Discussion
Relatively few lotic systems remain unaffected or unaltered by anthropogenic impacts (Gilvear et al., 2016). Alpine and mountainous streams in general also suffer because of a variety of different pressures that have resulted in the alteration and sometimes even almost complete destruction of these ecosystems. In particular, the increasing water abstraction (for hydroelectric power generation, drinkable waters, irrigation and snow generation) and the diffusion of channel and catchment alterations (with the intensification of logging, mining, flood protection measures and dams) add up to the global climate change effects, generating severe effects on alpine stream ecology (Maiolini and Bruno, 2007). In this context, the increase of fine sediments constitutes one of the most widespread and pernicious environmental impacts (Jones et al., 2012; Bona et al., 2016). Sedimentation increase can result in significant changes in many aspects of stream ecosystem communities, and in particular it can have dramatic impacts on benthic invertebrate assemblages (Buendia et al., 2013). Substrate conditions and food availability have long been recognized as key factors that primarily influence structural and functional aspects of benthic communities (Giller and Malmqvist, 1998). Mountainous, low-order streams represent in this context an interesting case study because they are peculiar and distinctive systems characterized by coarse riverbed, high flow velocities and great tractive forces, and strong dependence from allochthonous energetic inputs, because of multiple limitations for primary production (Vannote et al., 1980). A series of studies investigated the impact of clogging in lotic environments, but most of them were purely descriptive, with no manipulative design (e.g., Hedrick et al., 2013). Recently, some studies approached the problem using traps as sampling units, with the aim to compare 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 27
ongoing fine sediment accumulation and macroinvertebrate assemblage recruitment: trap shape varied noticeably, from cylindrical (Mathers and Wood, 2016) to parallelepiped (Bona et al., 2016), and other features varied as well, such as sampling scheme, removal dates and total permanence in the riverbed (Kochersberger et al., 2012). An interesting approach comes from studies that did not consider the different amount of fine sediments accumulated in the traps in a given period, but used artificial substrates pre-arranged with different levels of clogging (Bo et al. 2007; Larsen et al. 2011; Descloux et al. 2013). However, these studies did not consider other pivotal elements in stream functional dynamics, like a variable availability of allochthonous coarse organic matter (McGinley et al., 2013). The breakdown of CPOM is a process of fundamental importance in low-order, mountainous streams, where decomposition processes represent the main pathways of energy flow and nutrient cycling (Vannote et al., 1980). Generally, we detected an evident time-dependent colonisation process in all the traps, with an increasing taxonomic richness and organism density during the study period. However, our findings evidenced that the combination of different amounts of fine sediment and CPOM strongly influences macroinvertebrate communities. Fine sediment significantly reduced taxa richness and total abundance of macroinvertebrates, with a stronger impact on the most stenoecious taxa, such as Ephemeroptera, Plecoptera and Trichoptera. Moreover, in agreement with recent studies (Couceiro et al., 2011; Leitner et al., 2015), our findings remarked that clogging acts as an important environmental filter shaping the community in accordance to life-history parameters and ecological requirements. Indeed, benthic invertebrates with the following traits: shredding trophic strategy, medium to large body size, monovoltine reproductive strategy (Biological group f) and microhabitat preferences for fast flowing water and coarse mineral substrata (Ecological group A) were heavy disadvantaged by sedimentation. These results are in accordance with those documented by other authors (Kreutzweiser et al., 2005; Conroy et al. 2016) and both direct and indirect mechanisms underlying these effects can be identified. For instance, the riverbed colmation by fine sediment proportionally reduces the interstitial space among cobbles and other substrate elements. This aspect is expected to directly 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 29
affect the body size of colonizing invertebrates because under clogging conditions small sized organisms are more advantaged than the medium or large-sized ones (Buendia et al., 2013). Moreover, fine sediment significantly reduced the abundance of uni- and semivoltine invertebrates, advantaging organisms with rapid life cycles and fast growth. In addition, elevated fine sediment amounts in the riverbed could increase the embeddedness of the coarser elements of the substrate, producing a loss of its heterogeneity and lowering at the same time its CPOM retention capacity. Both these habitat changes may account for the reduced abundance of shredders and rheophilous taxa (Ecological group A) observed in this study.
Taxonomic richness, density and also dry mass of benthic macroinvertebrate assemblages were affected by clogging, with poorest communities associated with medium and high siltation levels. In the perspective of an increasing clogging we thus may expect a loss in taxa and an impoverishment of the community.
On the contrary, increased availability of CPOM played a positive effect on macroinvertebrates, facilitating the development of richer and well-structured assemblages also under siltation conditions. These findings agree with previous works that evidenced how, in pristine conditions, food resource abundance can enhance invertebrate community taxonomic composition and carrying capacity (Wallace et al., 1999; Fenoglio et al., 2005). In fact, under the same clogging conditions, traps with higher availability of CPOM were the most colonised. Interestingly, we also detected a negative impact of increased clogging conditions on the CPOM mass loss, suggesting that sedimentation reduces the availability of allochthonous leaf material to shredders. These results underline how clogging affects not only the accessibility to the organic material but also alters the breakdown process and the microbial conditioning, resulting in an alteration of chemical contents and palatability, as suggested by Danger et al. (2012). Moreover, these results stress how the presence of a high quantity of CPOM can improve the community composition even on compromised substrates. 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 31
4. Conclusions
In conclusion, our findings confirm the importance of fine sediment and CPOM as key factors determining the distribution of macroinvertebrate taxa in micro-habitats (Larsen et al., 2009), suggesting that an adequate input of allochthonous organic matter may lessen the impact of fine sediment deposition on benthic communities.
In particular, our study strongly emphasizes how the health of river systems is closely associated to the conditions of the surrounding terrestrial environments. In the current climate change scenario, deforestation and removal of wooded riparian areas can dramatically alter the biological characteristics of a river system, increasing clogging and reducing the input of allochthonous organic material. This study therefore brings new emphasis on the fact that the protection of the mountainous rivers necessarily involves the protection of their basins.
Ackowledgements
We are grateful to Monviso Natural Park for the interest and support. This work was realized within the framework of Italian MIUR (Ministry of Education, Universities and Research) - PRIN NOACQUA project. 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 33
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Figure 1. Ordination of the sampled macroinvertebrate communities according to the first two NMDS ordination axes. Samples are coloured according to clogging levels (black = WFS, grey = MED, white = CLO). Ellipses represent standard deviations around the centroids of the three groups.
Figure 2. Graphical representation of the PRC analysis. Codes in the legend refers to the combination of the different levels of Clogging and CPOM from the best to the worse treatment The distance of lines representing different treatments from the control (grey line) is proportional to their difference in community composition. Distance of taxa from each line represents their affinity for that treatment. Variance explained by time = 18.5%; variance explained by treatment = 27.0%; unconstrained variance = 54.5%. Values on the Y-axis represent the distances among the communities in an Euclidean space.
592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 47
Figure 3. Boxplots depicting the difference in a) taxa richness, b) abundance of individuals, c) richness in EPT taxa, d) abundance of EPT individuals in response to Clogging and CPOM levels. The black line represents the median and the box represents the quartile interval. Wiskers refer to the Min-Max range.
Figure 4. Boxplots depicting the difference in a) abundance of shredders, b) abundance of individuals belonging to biological group f, c) abundance of individuals belonging to ecological group A in response to Clogging and CPOM levels. The black line represents the median and the box represents the quartile interval. Wiskers refer to the Min-Max range.
Figure 5. Differences in the dry weight of benthic invertebrates between the Clogging conditions. 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 49
Figure 6. Accumulation curve showing the contribution of each sampling trap to the total taxa richness of the last sampling session.
624 625 626 627 628 629 630 631 632 633 634 51
Figure 7. Variation in the mass loss of CPOM according to the Clogging conditions.
CPOM conditions
0 g of CPOM 1 g of CPOM 5 g of CPOM
C lo gg in g co n d it io n s CLO (Clogged traps) 66% sand
and 33% pebbles
CLO0
CLO1
CLO5
MED (Medium) 50% sand and 50%
pebbles
MED0
MED1
MED5
WFS (Without Fine Sediment)
100% pebbles
WFS0
WFS1
WFS5
Table 1. Scheme of the experimental design and the nine artificial substrate categories. 635 636 637 638 639 640 641 642 643 644 645 53
DF SS MS F R2 P Clogging 2 1.6631 0.8316 9.9395 0.1123 0.0001 CPOM 2 0.4566 0.2283 2.7290 0.0308 0.0013 Date 2 1.9796 0.9898 11.8308 0.1337 0.0001 Residual s 128 10.7088 0.0837 0.7232
Table 2. Results of the test for differences in taxa composition between Clogging, CPOM and Date levels as inferred from PERMANOVA analysis (SS = Sum of Squares, MS = Mean Squares). Significant values are highlighted in bold.
Variable Factor DF χ2 P S Clogging 2 18.7289 < 0.0001 CPOM 2 4.616 0.0994 Date 2 11.6614 0.0029 N Clogging 2 46.859 < 0.0001 CPOM 2 7.104 0.0286 Date 2 82.557 < 0.0001 EPTS Clogging 2 27.6001 < 0.0001 CPOM 2 3.4241 0.1805 Date 2 3.8841 0.1434 EPTN Clogging 2 68.586 < 0.0001 CPOM 2 13.468 0.0012 Date 2 22.401 < 0.0001 Sh Clogging 2 63.517 < 0.0001 CPOM 2 13.349 0.0013 Date 2 25.109 < 0.0001 f Clogging 2 68.193 < 0.0001 CPOM 2 13.52 0.0012 Date 2 23.762 < 0.0001 A Clogging 2 65.547 < 0.0001 CPOM 2 14.989 0.0006 Date 2 4.126 0.1271 dBC-bray Clogging 2 0.7864 < 0.0001 CPOM 2 0.2145 0.0019 Date 2 0.9659 < 0.0001 dBC-bal Clogging 2 0.0149 0.3691 CPOM 2 0.0197 0.2693 Date 2 0.1864 < 0.0001 dBC-gra Clogging 2 0.5985 < 0.0001 CPOM 2 0.1115 0.064 Date 2 1.8355 < 0.0001
Table 3. Results of the GLM tests for the response towards Clogging, CPOM and Removal Date of: S = taxa richness; N = total abundance; EPTS = richness in EPT taxa; EPTN = abundance of individuals belonging to EPT taxa; Sh = Shredders; f = biological group f; A = ecological group A; and of LM tests for the response towards Clogging, CPOM
646 647 648 649 650 651 652 55
and Removal Date of: dBC-bray = Bray-Curtis dissimilarity; dBC-bal = turnover component of dissimilarity; dBC-gra = nestedness component of dissimilarity. Significant values are highlighted in bold.
CLO MED WFS
Factor DF χ2 P χ2 P χ2 P
CPOM 2 14.702 < 0.0001 7.623 0.0221 2.585 0.2746
Date 2 11.175 0.0037 1.331 0.5141 10.637 0.0049
Table 4. Results of the GLM tests for the response towards CPOM and Date of shredders keeping the data from the three levels of Clogging separated in three different classes. Significant values are highlighted in bold.
653 654 655 656 657 658 659 660 57
