Global warming effects on benthic macroinvertebrates

Global warming effects on benthic macroinvertebrates: a model case study from a small geothermal stream Ivana Živić, Miroslav Živić, Katarina Bjelanović, Djuradj Milošević, Sanja Stanojlović, Radoslav Daljević & Zoran Marković Hydrobiologia The International Journal of Aquatic Sciences ISSN 0018-8158 Volume 732 Number 1 Hydrobiologia (2014) 732:147-159 DOI 10.1007/s10750-014-1854-0

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Author's personal copy Hydrobiologia (2014) 732:147–159 DOI 10.1007/s10750-014-1854-0

PRIMARY RESEARCH PAPER

Global warming effects on benthic macroinvertebrates: a model case study from a small geothermal stream ˇ ivic´ • Miroslav Z ˇ ivic´ • Katarina Bjelanovic´ • Ivana Z Djuradj Milosˇevic´ • Sanja Stanojlovic´ • Radoslav Daljevic´ Zoran Markovic´

•

Received: 26 March 2013 / Revised: 4 March 2014 / Accepted: 6 March 2014 / Published online: 25 March 2014 Ó Springer International Publishing Switzerland 2014

Abstract The aim of this study was to predict global warming effects on benthic macroinvertebrate community structure by using a small temperate geothermal stream as a model system. We collected benthic macroinvertebrates, measured physical and chemical water properties at eight localities up the Kudosˇki stream steep water temperature gradient, and used 11 metrics and indexes to characterize community structure. Species richness and evenness decreased, but total abundance increased with the increase of average annual water temperature (tav), with species richness being most and total abundance least sensitive to this parameter. The increase of Gastropoda relative abundance and the decrease of Ephemeroptera, Plecoptera and Trichoptera richness, respectively, were the

earliest responses of taxonomic groups to tav increase. Relative abundance of Orthocladiinae decreased and that of Chironomini increased with the increase of tav. This indicates that Chironomidae are not reliable predictors of global warming effects in running waters, and that lower taxonomic levels, subfamily or tribe, are more suitable for that purpose. Changes in community structure did not linearly follow tav increase, since a great community shift was observed at tav & 20°C indicating that present trends of community responses to changes in climatic conditions should not be linearly extrapolated to future warming. Keywords Water temperature Geothermal stream Kudosˇki stream Biodiversity Ecological thresholds

Handling editor: Sonja Stendera I. Zˇivic´ (&) M. Zˇivic´ K. Bjelanovic´ University of Belgrade, Faculty of Biology, 11000 Belgrade, Serbia e-mail: [email protected] D. Milosˇevic´ Department of Biology and Ecology, Faculty of Sciences and Mathematics, University of Nis, 18000 Nis, Serbia S. Stanojlovic´ R. Daljevic´ Institute of General and Physical Chemistry, 11000 Belgrade, Serbia Z. Markovic´ University of Belgrade, Faculty of Agriculture, 11080 Belgrade, Serbia

Introduction Long-term warming of rivers and streams in response to global climate change is now a well-established fact, with several data sets showing that in Europe, Australia, and North America river temperatures have increased 0.1–1°C per decade in the past 20–30 years (Ormerod & Durance, 2012). Moreover, stream ecosystems are very sensitive to global warming (Heino et al., 2009; Woodward et al., 2010a). In contrast, studies on the effects of global warming on stream communities are relatively rare (e.g., Daufresne et al., 2003) and more focused on individuals or populations

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of particular species or organism groups (e.g., fish, Heino et al., 2009) rather than entire communities, (Woodward et al., 2010a), while macroinvertebrates are less investigated (Heino et al., 2009). Long-term studies directly measuring the impact of global warming on benthic macroinvertebrate communities have been mainly conducted in Europe (Daufresne et al., 2003, 2007; Durance & Ormerod, 2007, 2009; Feio et al., 2010) and to a smaller extent in North America (Lawrence et al., 2010) and Australia (Chessman, 2009). These studies have shown that during a 13–25 years period, water temperature increased with 1–3°C due to global warming, resulting in significant changes in benthic macroinvertebrate community composition with a decrease in relative abundances of lotic and cold-water taxa versus an increase in relative abundances of lentic and warmwater taxa. However, except for the temperate headwaters at Llyn Brianne (UK), where climate change induced a decrease in total spring-season abundances (Durance & Ormerod, 2007), no change in other benthic macroinvertebrate community metrics (e.g., diversity, biomass, taxonomic indices) was recorded. As mean annual air temperature in Europe is predicted to rise with 2.5–5.5°C toward the end of the 21st century (Alcamo et al., 2007), some regions will particularly experience increased summer temperature, with e.g., parts of France and the Iberian Peninsula are predicted to exceed 10°C (Raïsa¨nen et al., 2004). From this high temperature rise, it is clearly expected not only intensification of observed changes in benthic macroinvertebrate communities, but also changes in community metrics not recorded so far (biodiversity, biomass, etc.). Predicting and understanding those changes is a great challenge and a necessity in order to formulate and implement appropriate conservation measures. In order to predict and understand global warminginduced future changes in benthic macroinvertebrate communities, different kinds of simulations and modeling may be employed with predictive models based on the present long-term data being the most straightforward ones. Unfortunately, due to the lack of experimental data, such models are very scarce (e.g., Durance & Ormerod, 2007). An alternative for modeling global warming effects on benthic macroinvertebrates are geothermal streams where a temporal temperature gradient is substituted with a spatial one. The main advantage of geothermal

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ecosystems is that they often span a wide thermal gradient within a relatively small area, and are therefore not confounded by biogeographical and dispersal constraints as it is often the case with spacefor time-substitution surveys conducted over large latitudinal gradients (Woodward et al., 2010b; O’Gorman et al., 2012). However, in geothermal ecosystems, temperature differences are often confounded by other environmental gradients (e.g., conductivity and extreme pH; Duggan et al., 2007; Clements et al., 2011), probably the reason why there are only three studies, all performed in the Hengill area of Iceland, using geothermal streams as models for global warming effects on benthic macroinvertebrate communities (Friberg et al., 2009; Woodward et al., 2010b; O’Gorman et al., 2012). Two studies on continental geothermal streams in Yellowstone (Clements et al., 2011) and the Vrujci Spa (Zˇivic´ et al., 2006) directly compared benthic macroinvertebrate communities between thermally influenced and uninfluenced sites allowing interpretation of their results in terms of possible future effects of global warming. These studies showed that the increase of water temperature induced an increase in macroinvertebrate biomass and Gastropoda abundance and a decrease in evenness and Chironomidae abundance. However, there were some important differences since in Hengill streams, water temperature increase induced an increase in total abundance but no change in species richness, while in continental geothermal streams, it was the quite opposite with no change in total abundance but a severe reduction of the number of EPT species and thus overall species richness. Those discrepancies might be due to the specific characteristics of the Icelandic streams like low diversity of benthic fauna and spatial isolation (Friberg et al., 2009) aggravating the comparability of the results with other climatic zones and more species-rich systems. In addition, in continental streams water temperature was not considered as determining environmental parameter, thus other important instream factors like high conductivity and low pH in Yellowstone geothermal streams may also significantly alter the composition structure of macroinvertebrate communities. None of these studies have addressed the very important question for modeling the effects of water temperature rise: what kind of response in community metrics can be expected? It is generally accepted that ecosystems responses to climate changes are linear

Author's personal copy Hydrobiologia (2014) 732:147–159

(Andersen et al., 2008). However, in the Hengill studies, apart from a linear response of total abundance and evenness (Friberg et al., 2009), Chironomidae abundance (Woodward et al., 2010b) and Mollusca biomass (O’Gorman et al., 2012) showed a nonlinear response to water temperature elevation, which is in agreement with a number of studies from other ecosystems like forest in eastern China and coral reefs (Walther, 2010). In order to address some of the dilemmas in our study we tested the following hypotheses: (1)

(2)

(3)

(4)

Since species are generally well adapted to local thermal regimes (Woodward et al., 2010b), and Ephemeroptera and Plecoptera are especially sensitive to water temperature increase (Pritchard, 1991), we expect that both species and EPT richness in our system will decrease with water temperature increase just like in Yellowstone and Vrujci Spa studies. As gross primary productivity increases with increasing water temperature (Demars et al., 2011), we expect macroinvertebrate biomass and total abundance in combination with decreased species richness leading to reduced evenness at higher water temperatures similar to the results of the Hengill studies. Chironomidae along with Gastropoda represent the most abundant and diverse macroinvertebrate group in geothermal streams (Mitchell, 1974; Pritchard, 1991), thus we expect the increase of Chironomidae and Gastropoda relative abundances with water temperature increase, even though the increase of Chironomidae abundance would be opposed to the outcomes of the described studies. Further we expect even nonlinear response patterns of community structure metrics to water temperature increase.

These hypotheses were tested on the Kudosˇki stream, a small continental geothermal stream with steep water temperature gradient, where the water temperature is the most important environmental determinant of longitudinal changes in benthic macroinvertebrate community composition (Zˇivic´ et al., 2013). Here, we want to test whether the Kudosˇki stream is also an appropriate model system for studying global warming effects on the composition and biodiversity of stream benthic macroinvertebrate communities. In addition, we wanted to

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assess whether the observed changes in benthic macroinvertebrate community structure along the water temperature gradient replicate those recorded so far in long-term studies.

Materials and methods Study area The Kudosˇki Stream, the second order tributary of the Danube, originates from two main streams (Dubocásˇ & Veliki) on the southern side of Mt. Frusˇka Gora (Northern Serbia, Fig. 1) at elevations of 497 m a.s.l. (Dubocásˇ stream) and 435 m a.s.l. (Veliki Stream). These two streams join and form the Kudosˇki Stream within the area of a small town of Vrdnik. The Kudosˇki Stream (with the Veliki Stream as a source branch) is 30.6 km long, with the total drop of 354 m, and a slope of 1.6% (Fig. 1). A small artificial reservoir (0.57 km2) was built at the 19.5 km of the Kudosˇki stream watercourse. The watershed of the Kudosˇki stream consists of a mountainous and a lowland section. The mountainous area includes Vrdnik and the area north of the town, where the water flows down the slopes of the Frusˇka Gora Mountain. The lowlands include the area south of Vrdnik, where Kudosˇki stream flows through the arable fields at the southern edge of the Pannonian Plain. The watershed covers an area of 182 km2. The study area is located in the mountainous part of the watershed (Fig. 1), with a mean annual temperature of 11.2°C. It comprises five sites at the Veliki stream (V1–V5), one site at the Dubocásˇ stream (D1) and two sites at the Kudosˇki stream (K1 and K2, Fig. 1b). Geothermal water (TW) from the Vrdnik Spa is being released through the outlet into the Veliki stream approximately 20 m upstream from the site V3 (Fig. 1). Sampling Fieldwork was performed on six occasions: May 15th, July 23rd, September 24th, December 24th 2007 and February 18th and April 16th 2008. Benthic macroinvertebrates were collected with a Surber net (mesh size 250 lm) covering a sampling area of 300 cm2. Invertebrates were sampled within 15 m long reaches at each site. A single sample consisted of a

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a

b

c

Fig. 1 a Map of Serbia and the location of the Kudosˇki stream catchment area (shaded light gray). b Location of the sampling sites (white circles) in the Kudosˇki stream (V1–V5, D1, K1, K2). The urban area of Vrdnik is shaded light gray. c Longitudinal

and altitudinal location of sampling sites along the Kudosˇki stream. Exact values of mouth distance (km) and altitude (m a.s.l) for each site are given within the brackets

combination of three Surber samples collected randomly from each site. Substrate composition within each Surber sample was estimated visually and placed into one of five classes: boulder ([25 cm), cobble (6–25 cm), gravel (0.5–6 cm), fine gravel (0.5–2 cm), sand (0.5–0.1 cm) as well silt and mud (\0.1 cm). Substrate composition from each of the three subsamples was averaged and expressed as percent composition at a site. Bottom substrate at all sites was quite uniform and dominated by cobble (5–20 cm) and gravel (0.2–5 cm) except for site V1 where it was primarily made of mud and gravel. Benthic macroinvertebrates were collected by removing and thoroughly scrubbing the substrate with a soft bristle brush. The collected material was placed in plastic

bottles and fixed with 96% alcohol on-site. The biomass of benthic macroinvertebrates was measured by analytical balance AE 163 (Mettler-Toledo International Inc., Switzerland), having a precision of 0.0001 g, within a day after collection, so the potential weight loss due to extraction of body lipids by ethanol was minimized. Insect larvae and other collected macroinvertebrates were identified to genus or species level with the aid of pertinent literature (Brinkhurst & Jamieson, 1971; Rozkosˇny, 1980; Gloër et al., 1985; Waringer & Graf, 1997; Jacob, 2003; Vallenduuk & Pillot, 2007; Timm, 2009; Pillot, 1984a, b, 2009) in the laboratory of the Institute of Zoology, Faculty of Biology, where the material is stored.

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The concentration of dissolved oxygen (DO), dissolved oxygen saturation (DOS), conductivity (c), water temperature, and pH were measured with a MULTI 340i/SET from WTW (Germany) between 12:00 and 1:00 p.m. at all localities by immersing the corresponding electrodes 0.05 m below the water surface. Water flow rates (Q) were calculated from the cross-sectional area and longitudinal velocity data for every sampling site. The cross-sectional area was first determined by depth measurements and then divided into vertical sections where river velocity was measured using a ‘‘GEOPACKS Stream Flowmeter’’ (Geopacks, UK). Total flow was computed summing the flow increments for all the vertical sections. Water samples for chemical analysis were taken at the same time as benthic macroinvertebrate samples by holding a 400 ml polyethylene bottle below water surface in the opposite direction to that of the current. Anions (PO43-, NO2-, NO3-,Cl-, Br-, and acetate), cations (Ca2?, Mg2?, Sr2?, Ba2?, and NH4?), and trace metals (Pb2?, Cu?, Cd2?, Co2?, Zn2?, Ni2?, Mn2?, and Fe2?) in water were determined with a DIONEX 4000i ion chromatograph (Thermo Fisher Scientific Inc., USA), in the Water Laboratory of the Institute of General and Physical Chemistry in Belgrade, using standard in EPA methods (Pfaff, 1993). Concentrations of some ions below the detection limits were excluded from further analysis. Total water hardness (TWH, mg l-1 CaCO3) was calculated according to formula: TWH ¼ Ca2þ 2:497 þ Mg2þ 4:115 þ Fe2þ 1:792 þ Mn2þ 1:822; with ion concentrations expressed in mg l-1. Sample handling and analyses for total suspended solids (TSS) and biochemical oxygen demand (BOD5) were performed in accordance with APHA (1998).

Data analysis All data were expressed as mean ± 1standard deviation. The samples were compared statistically using unpaired t test or Mann–Whitney Rank Sum test and paired t test at the 5% level of significance (P \ 0.05). In order to measure the strength of the association among pairs of variables, the Pearson product moment correlation was used, with a P \ 0.05 level of

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significance. Relationships between average water temperature and different community metrics and indices were statistically analyzed by fitting linear or piecewise functions to the data. Piecewise regression was used as a tool for quantitative identification of ecological thresholds (Ficetola & Denoe¨l, 2009 and references therein). All statistical tests were performed with Sigma Plot 11 software (Systat Software Inc., San Jose, CA, USA). Eleven measures were used to quantify the effects of temperature change on different metrics of benthic macroinvertebrate community structure and composition. First, we analyzed whether temperature has a direct effect on benthic macroinvertebrate community composition. If it does, dissimilarity of species assemblages should be higher at sites with larger temperature differences than at sites with lower temperature differences. Therefore, we calculated Sørensen similarity index (Sørensen, 1948) for all combinations of sites. We also calculated the differences in the corresponding temperatures (Dtav) and tested for correlation of similarity and Dtav with a normalized Mantel test (Fortin & Gurevitch, 1993). Euclidean distances were used in order to determine strength of association between sites with respect to Sørensen similarity index. Sørensen similarity index was calculated, Mantel test was performed, and strength of association was determined by statistical software package Brodgar Ver. 2.7.2, Highland Statistics Ltd., Newsburgh, UK. For the same purpose, we used a weighted longitudinal river zonation index (RLZI) with known sensitivity to both species composition and water temperature (Moog, 2002). Effects on alpha diversity were quantified with the Simpson dominance index (Sim) (Simpson, 1949), and species richness (spr). We used five taxonomic indices to quantify thermal effects on benthic macroinvertebrate groups with known sensitivity to water temperature change. Thermal effects on number of Ephemeroptera, Plecoptera, and Trichoptera species were measured by EPT richness (EPTr). Further, percentage of Chironomidae abundance (Chi%), and Gastropoda abundance (Gas%) within total abundance were used as metrics. Since Chironomidae were the most diverse group in the examined part of Kudosˇki stream, two more taxonomic indices were used to discriminate the effects of water temperature increase on most abundant and diverse Chironomidae subfamilies and tribes:

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percentages of Orthocladiinae (Ort/Chi), and Chironomini (Chii/Chi) within total Chironomidae abundance. The environmental data were analyzed together with the community metrics data using co-inertia analysis (CIA) (Dole´dec & Chessel, 1994). The CIA allows for simultaneous ordination of two data matrices sharing the same set of rows. Co-inertia axes were calculated maximizing the covariance of the factorial scores generated in the separate ordinations of the two input tables (in this study normed PCA of the environmental variables and normed PCA of the community metrics data). CIA was a method of choice since application of other ordination methods such as RDA or CCA cannot handle low numbers of sites (in our case 8) associated with a relatively large number of environmental variables (here 19). CIA does not suffer from such constraint since it is based on partial least-squares regression instead on multivariate regression like RDA and CCA (Dray et al., 2004). In addition, the CIA method is unique due to its ability to clearly illustrate the strength of the co-structure between biotic and environmental data for every locality by plotting together standardized scores of environmental and community metrics for all localities. Pairs belonging to the same locality are linked by an arrow with its length reversely proportional to the strength of the co-structure. This ability is very useful in tracking ecological thresholds defined as the critical value of an environmental driver for which small changes can produce an unproportionally large change in community structure. A Monte-Carlo permutation test was used to check the significance of the costructure between the two data sets as revealed by CIA. All multivariate analyses were computed using the ADE-4 software (Thioulouse et al., 1997). The proportion of variability in community structure explained by each environmental variable was evaluated by the coefficient of determination in percentages (100*r2) of linear regression between standardized community scores along co-inertia F1 axis and the environmental variable (Durance & Ormerod, 2007).

Results The co-structure between the environmental and community data sets revealed by CIA was very strong as confirmed by the high value of the correlation coefficient along the F1 axis (0.90) and statistically

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Fig. 2 CIA triplot showing 19 environmental variables and 10 community metrics (white squares, see Table 2 for codes) from 8 sampling sites. Ordination diagram of 19 normalized environmental variables in the CIA (see ‘‘Materials and methods’’ section for codes) is represented with arrows starting from the origin and projected on the F1 9 F2 factorial map. Standardized co-inertia scores of environmental data and community metrics for each sampling site are also projected onto the F1 9 F2 factorial map. The circle locates the site as ordinated by environmental variables, and the arrowhead locates it as ordinated by the community metrics

significant (Monte-Carlo permutation test, P = 0.028) (Fig. 2). The common structure was almost onedimensional with the F1 axis explaining 92.3% of the co-structure and F2 axis contributing only marginally with 5.1%. Environmental variables Environmental variables with the longest orthogonal projection on co-inertia F1 axis have the strongest influence on longitudinal changes in benthic macroinvertebrate community structure, as shown for three components of water temperature regime: average (tav), minimal (tmin), and maximal (tmax) water temperature (Fig. 2). Analysis of water temperature regime showed several key features: it was almost identical between the reference sites (V1, V2, and D1) (Fig. 3). After the abrupt increase of water temperature due to geothermal water inflow at V3, tav decreased monotonously. Results of paired t test showed that statistically higher water temperature in respect to V2 was maintained up to site


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Fig. 3 Longitudinal changes of mean water temperature (tav) ± 1SD along the investigated sites at the Kudosˇki stream. Data points within a plot sharing a common superscript letter are significantly different (P \ 0.05)

K2 (P = 0.004) thus defining the extent of geothermal influence. Linear regression between tav and standardized community scores along F1 axis showed that tav explains 87.7% of variability in community structure along F1 co-inertia axis (Table 1). Further, water velocity, DO, and TWH showed significant association with F1 co-inertia axis (Fig. 2). However, average values of these parameters explained much smaller part of variability in community structure along F1 co-inertia axis compared to water temperature (Table 1). Remaining environmental variables showed much weaker association with F1 co-inertia axis (Fig. 2) and were not significantly correlated with standardized community scores. Macroinvertebrate communities Influence of water temperature on community metrics with the exception of beta diversity was examined

with CIA. In contrast to environmental variables, most of community metrics showed a very tight association with co-inertia F1 axis indicating a profound change in community structure along the water temperature gradient (Fig. 2). Species richness, evenness, and EPTr were decreasing, while total abundance, biomass, RLZI, Chi% Gas%, and Chii/Chi were increasing with water temperature increase. The location of each study site is marked with an arrow starting at the position defined by standardized scores of environmental data and ending at the position defined by standardized scores of community data (Fig. 2). Short arrows confirmed the strong co-structure between environmental and community data sets as already shown by the high value of the correlation coefficient along the F1 axis. The exceptions were sites V3 and V5 whose arrows were the longest and oppositely directed. Therefore, environmental scores of V3 and V5 sites were grouped with those of V4 site, but community scores of V5 site were considerably shifted and grouped with those of K1 site (Fig. 2). Such a discrepancy indicates that changes in community structure at V5 site were much greater than expected from environmental factors change, which is the exact definition of ecological threshold (Andersen et al., 2008). Standardized scores of community data for K2 and reference sites were strongly aligned along F1 axis forming a third group of sites. Keeping in mind the extent of similarity in community structure and composition between thermally uninfluenced sites shown by Sørensen similarity index (Fig. 4, inset) and CIA (Fig. 2), we have chosen V2 site (closest to geothermal water inflow) as a reference site used for comparison with geothermally influenced sites further on. In order to examine the influence of water temperature changes on macroinvertebrate beta diversity,

Table 1 Regression relationships (y = a ? bx) between standardized community scores along F1 axis (dependent variable) and environmental variables showing the greatest association with F1 co-inertia axis (independent variables) Independent variables

a (±SE)

b (±SE)

100*r2 (%)

F

P

tav

0.204 (0.031)

-3.29 (0.52)

87.7

46.64

\0.001

tmin

0.216 (0.036)

-2.17 (0.40)

85.6

35.59

\0.001

tmax

0.204 (0.030)

-4.18 (0.64)

88.4

45.67

\0.001

Water velocity

4.114 (1.449)

-2.67 (0.98)

57.3

8.07

0.030

DO

-0.537 (0.205)

5.87 (2.25)

53.4

6.88

0.039

TWH

-0.008 (0.002)

6.03 (1.72)

67.6

12.51

0.012

tav Mean water temperature, tmin minimal water temperature, tmax maximal water temperature, DO dissolved oxygen concentration, TWH total water hardness

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Fig. 4 Linear regression of differences in mean water temperature (Dtav) versus Sørensen similarity index for all sites. Inset strength of association between sites with respect to Sørensen similarity index measured by Euclidean distances

values of the Sørensen similarity index were plotted for each site as function of differences in water temperature (Fig. 4). Sørensen similarity between sites decreased and hence beta diversity increased with the increase of water temperature difference. This negative correlation was very strong (Mantel test, r = 0.908) and highly statistically significant (P = 0.001). Plotting of Euclidean distances showed two distinct groups, one of reference and the other of geothermally influenced sites, with site K2 separated from both (see inset in Fig. 4). Analysis of statistically significant differences in community metrics between the reference site and geothermally influenced sites (V3, V4, V5, K1, and K2)

showed that community metrics were not equally sensitive to water temperature increase (Dtav, Table 2). The most sensitive were RLZI, EPTr, and Gas% and the least sensitive were biomass and total abundance. Species richness showed greater sensitivity than evenness. Chironomidae-based indices (Chi%, Chii/ Chi, and Ort/Chi) were quite insensitive, showing statistically significant change at Dtav = 10.1°C. In addition Chii/Chi and Ort/Chi showed an opposite response to water temperature increase (Fig. 5e, f). We detected an abrupt increase in the number of significantly changed metrics (from four to eight) between sites V5 and V4 (Table 2). This indicates that sites V3 and V4 and sites V5 and K1, respectively, comprise two different groups with a markedly different community composition and structure, as in the case of CIA. Indeed, there were no statistical differences in community parameters within those groups while seven community metrics were statistically different between groups themselves, namely, localities V4 and V5 (Table 2). These results underline that an ecological threshold may be reached at Dtav = 8.3°C, causing significant shift in benthic macroinvertebrate community structure. The relationships between the Simpson index, total abundance, Chii/Chi, Ort/Chi, and biomass and average temperature as the environmental driving force (tav) were excellently described by piecewise regression (Fig. 5; Table 3). Break-point temperatures for the Simpson index, total abundance, and Chii/Chi were placed near tav at site V5 and for biomass and Ort/Chi between sites K1 and K2 (Fig. 5; Table 3). Species richness, EPTr and

Table 2 P values determined by unpaired t test or Mann–Whitney Rank Sum test for community metrics showing statistically significant differences between the reference site (V2) and thermally influenced sites (V3–V5, K1, and K2) Sites

Dtav (°C)

bm

ab*

Chii/Chi*

Ort/Chi*

V3

10.9

0.004

0.023

0.012

0.002

0.007

0.013

V4

10.1

V5 K1

8.3 6.4

K2

2.9

Chi%*

0.041

Sim*

spr*

EPTr

Gas%

RLZI*

0.01

\0.001

\0.001

0.002

\0.001

0.04

\0.001

0.004

0.002

\0.001

0.047 0.026

0.001 \0.001

0.002 0.002

\0.001 \0.001

0.027

0.002

0.001

Dtav is a difference in mean water temperature between the reference site and thermally influenced sites Insignia of the community metrics are: bm biomas, ab total abundance, Chii/Chi percentage of Chironomini within total Chironomidae abundance, Ort/Chi percentage of Orthocladiinae within total Chironomidae abundance, Chi% percentage of Chironomidae abundance within total abundance, Sim Simpson index, spr species richness, EPTr Ephemeroptera, Plecoptera, and Trichoptera richness, Gas% percentage of Gastropoda abundance within total abundance, RLZI weighted longitudinal river zonation index *Community metrics showing statistically significant differences between sites V4 and V5

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a

b

c

d

e

f

g

h

Fig. 5 Plots of mean values ± 1SD of eight different community measures (a–h; see Table 2 for codes) in function of mean annual water temperature fitted with piecewise or linear regression. Regarding piecewise regression, borders of gray rectangles are defined by values of standard errors of both break-point coordinates. April abundance of benthic

macroinvertebrates was plotted separately from the average abundance (d) to emphasize its linear decrease with water temperature increase in contrast to steep increase of the average abundance at highest water temperatures. Position of appropriate biocoenotic zones at the RLZI plot (h) is given in different shades of gray

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Table 3 Parameters of piecewise regression fit of selected community metrics in function of mean water temperature Community metrics

Break point ± SE (°C)

r2

F

P

Simpson index

20.51 ± 0.48

0.971

43.97

0.002

Total abundance

19.47 ± 0.47

0.955

28.41

0.004

Chii/Chi

19.70 ± 0.47

0.950

25.21

0.005

Biomass

16.52 ± 0.92

0.988

Ort/Chi

16.84 ± 1.31

0.835

116.9 6.76

\0.001 0.048

RLZI, changed linearly with water temperature increase (Fig. 5). Values of RLZI show that tav increase profoundly changes benthic macroinvertebrate community composition from hyporhithral at the reference site to metapotamal at sites V3 and V4 (Fig. 5h). There was no significant relationship between water temperature and Chi%.

Discussion Our results show large changes in benthic macroinvertebrate community structure with water temperature increase. In order to use these results as predictors of global warming effects, we first proofed that the Kudosˇki Stream is a good model system for studying global warming effects on benthic macroinvertebrate communities in running waters. In our previous study, detailed analysis of environmental parameters has clearly shown that water temperature is the most important environmental determinant of longitudinal changes in benthic macroinvertebrate community composition in the Kudosˇki stream (Zˇivic´ et al., 2013). In this study, we focused on some important components of benthic macroinvertebrate community structure (total abundance, biomass, species richness and evenness, EPT richness, and relative abundances of Gastropoda, Chironomidae, Orthocladiinae, and Chironomini). CIA analysis again distinguished water temperature as dominant environmental variable in determining longitudinal changes of these community structure components. Comparison with long-term studies In order to show that Kudosˇki Stream is a good model system for studying global warming effects, we tested whether the already established effects of global

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warming were among the earliest responses to water temperature rise in our stream system. The main conclusion of long-term studies is that water temperature increase due to global warming causes a decrease in relative abundances of lotic and cold-water taxa versus an increase of lentic and warm-water taxa in streams and rivers (Daufresne et al., 2003, 2007; Durance & Ormerod, 2007, 2009; Chessman, 2009; Feio et al., 2010; Lawrence et al., 2010). In temperate headwaters at Llyn Brianne (UK), the global warming effect had induced significant decrease in total abundance but only in spring season (Durance & Ormerod, 2007). In our study, between sites V2 and K2, where Dtav = 2.9°C corresponds to the recorded effects of global warming on water temperature (1–3°C increase) in long-term studies, two out of four significantly changed metrics (Sørensen index and RLZI) indicated that tav increase induced changes in composition of benthic macroinvertebrate communities. Moreover, the values of RLZI have shown that the direction of change is correct, since upstream increase of tav between K2 and V3 sites gradually shifts composition of their benthic macroinvertebrate communities toward the downstream ones. At the end of the temperature gradient (V3), the benthic macroinvertebrate community structure has metapotamal characteristics, although located only 100 m downstream from the hyporhithral community at reference V2 site. The average total abundance has shown no change up to Dtav = 10.12°C, but in April it decreased linearly with the increase of water temperature, like in temperate headwaters at Llyn Brianne (UK). In this way, our results have completely replicated the effects of global warming recorded so far in long-term studies, thus establishing Kudosˇki Stream as a good model system for studying global warming effects on benthic macroinvertebrate communities in running waters. Biodiversity Results of natural experiments indicate that stream benthic macroinvertebrate alpha diversity will probably decrease in the near future (Friberg et al., 2009; Woodward et al., 2010b). On the other hand, there is no agreement when it comes to the effects on different components of alpha diversity. In a study on Icelandic thermal streams, there was no unidirectional change in species richness, while the decrease in evenness was a very sensitive measure of water temperature increase


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Both biomass and total macroinvertebrate abundance increased with water temperature increase. However, increase in total abundance was not linear like in Hengill studies (Friberg et al., 2009) since it stayed constant up to Dtav = 8.3°C (V5) and abruptly increased afterward (V4). This result, in addition to lack of change in total abundance in Yellowstone and Vrujci spa geothermal streams (Zˇivic´ et al., 2006; Clements et al., 2011), indicates that total abundance is probably not a sensitive measure of global warming effects in continental streams.

Chironomidae in thermal water (Pritchard, 1991). However, in Icelandic thermal streams, Chironomidae were mostly represented by cold-adapted Orthocladiinae, and small Chironomidae diversity and spatial isolation of the island fauna could make colonization of more thermophilic Chironomidae species impossible. Since the Kudosˇki stream is a continental stream situated in an area with a diverse Chironomidae fauna (Milosˇevic´ et al., 2011), colonization of more thermophilic Chironomidae species might occur. However, no statistically significant relationship between Chi% and tav was found due to opposite relationships between tav and the most abundant Chironomidae taxa (Ort/Chi and Chii/Chi). Similarly, abundance of Orthocladiinae decreased and Chironomini increased with water temperature increase in Yellowstone geothermal streams, but the effect on total Chironomidae abundance was opposite to that in our study (Clements et al., 2011). This indicates that, due to their enormous ecological diversity, Chironomidae are not reliable predictors of global warming effects in running waters, and that lower taxonomic levels, subfamily or tribe, are more suitable for that purpose.

Taxonomic indices

Shift in community structure

Analysis of the community structure metrics responses to water temperature increase showed that the decrease in EPT richness and increase in Gas% were most sensitive to tav increase. High sensitivity of EPTr was not a surprise since it is well known that these three insect orders are most sensitive to water temperature increase (Pritchard, 1991; Duggan et al., 2007). Unlike EPT taxa, pulmonate Gastropoda are one of the most abundant inhabitants of thermal streams (Mitchell, 1974; Zˇivic´ et al., 2006; Duggan et al. 2007). In addition, Woodward et al., (2010b) have shown that Radix peregra becomes a dominant constituent of benthic macroinvertebrate communities in Icelandic thermal streams with increase of water temperature. These results confirm our findings that Gastropoda abundance in temperate streams will increase with rising water temperatures, representing one of the earliest responses of benthic macroinvertebrate communities. In Icelandic thermal streams, Chironomidae abundance decreased with water temperature increase (Woodward et al., 2010b). This is unexpected if we consider a rather high abundance and diversity of

Piecewise regression was applied in order to obtain statistically significant relationships of total abundance, biomass, evenness, Ort/Chi and Chii/Chi with tav verifying our last hypothesis that the increase of water temperature can have nonlinear effects on macroinvertebrate community structure. In addition, results of piecewise regression indicated the existence of discontinuities—ecological thresholds (Ficetola & Denoe¨l, 2009) in response of these parameters to tav rise as a driving force. In most cases, the temperature break point was close to the tav at site V5 (19.7°C), thus confirming indications given by CIA that an abrupt shift in community structure occurs after tav rise exceeds 8.3°C. This is an enormous rise of tav, but according to the A2 scenario of global climate change, it may be reached by the end of this century in parts of France and the Iberian Peninsula (Raïsa¨nen et al., 2004). Ecosystem regime shifts as a response to relatively smooth climate changes have already been detected (Walther, 2010), supporting our conclusion that present trends of community responses to changes in climatic conditions should not be linearly extrapolated to future warming.

(Friberg et al., 2009). In our study, and similar to the results of two other studies on continental geothermal streams (Zˇivic´ et al., 2006; Clements et al., 2011), both components of alpha diversity decreased with water temperature increase. This discrepancy is probably a consequence of Island fauna specificity regarding its low diversity (only 36 species found in 15 streams) compared to much more diverse fauna of a temperate continental stream like Kudosˇki Stream (143 species). Total abundance and biomass

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Conclusions Additional investigations are needed to verify our obtained results and gain new insights into the effects of global warming on small running water ecosystems. First, heated sites in our study are not independent of each other thereby reducing the possibility for broad generalization of our findings. Therefore, future investigations require the inclusion of similar thermal springs in this area. Although geothermal streams are potentially good model systems for studying the effects of global warming, several problems need to be considered. Most of geothermal springs are enriched with a range of solutes influencing benthic macroinvertebrate communities differently from elevated water temperature (e.g., Clements et al., 2011). Further, the issue of high algal abundance, characteristic for geothermal streams, with a profound influence on food webs and energy flow through the ecosystem has to be taken into account. Thus, future studies should focus on (1) The inclusion of other relevant organism groups like phytobenthos, fish and macrophytes, and (2) the upscaling of the investigation level by analyzing temperature effects on process rates, nutrient and energy cycling on the whole ecosystem level. There is a growing body of evidence that, at the present state of global warming, strong effects may arise through species interactions and resource availability (e.g., Durance & Ormerod, 2010; Cahill et al., 2012). The geothermal system of the Kudosˇki stream may contribute to the understanding of these problems when experimental design is focused on monitoring the effects of elevated water temperature at the species level, and on sampling sites at the lower end of elevated temperature gradient (K2 site) capturing fine changes in species composition induced by small water temperature increase, comparable to those recorded thus far in long-term studies. Acknowledgments The present study was supported by the Serbian Ministry of Education, Science and Technological Development (Project No. TR 31075 and 173040).

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