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Ecological Indicators 75 (2017) 145–154

Contents lists available at ScienceDirect

Ecological Indicators

journa l homepage: www.e lsev ier .com/ locate /eco l ind

riginal Articles

evelopment of submerged macrophyte and epiphyton in aow-through system: Assessment and modelling predictions in

nterconnected reservoirs

aria Spoljar a, Chen Zhang b,∗, Tvrtko Drazina a, Guixia Zhao b, Jasna Lajtner a,oran Radonic c

Department of Biology, Zoology, Faculty of Science, University of Zagreb, Rooseveltov Trg 6, HR-10000 Zagreb, CroatiaState Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, ChinaPapuk Nature Park, Trg Gospe Vocinske bb, HR-33522, Vocin, Croatia

r t i c l e i n f o

rticle history:eceived 26 May 2016eceived in revised form 8 November 2016ccepted 21 December 2016

eywords:ubmerged macrophyte modellow velocityooepiphytonhallow reservoirsarstapuk Nature Park (Croatia)

a b s t r a c t

Every approach to lake restoration requires the reestablishment of submerged macrophytes. However,macrophyte overgrowth in shallow lakes may lead to deterioration and a consequent necessity forrestoration treatments. We assumed that a major threat to the increased trophic level in the Janko-vac flow-through system arises from the sediment, where the accumulation of deciduous leaf litter anddecayed macrophyte fragments could generate anoxic conditions. The integrated Water Quality Model(WQM) and the Submerged Aquatic Vegetation Model (SAVM) were combined in the Jankovac Model(JanM) and applied during the vegetated season in 2008 and 2014, with the aim to offer a possibleapproach to the maintenance of good water quality. The impacts of flow velocity and epiphyton growthon submerged macrophyte coverage and biomass were simulated. Biocenotic analyses suggested thatepiphyton growth was more extensive in 2014 in comparison to 2008. The results of JanM indicatedthat increased flow velocities enhanced macrophyte growth and dissolved oxygen concentrations con-

currently with the decline of epiphyton biomass. Furthermore, results suggested that epiphyton growthrate of 0.4 d−1 maintained macrophyte coverage and biomass at a satisfactory level of 70% reservoir cov-erage. Considering the proposed scenarios hydraulic treatment could be applied to regulate submergedmacrophytes in shallow reservoirs, as an efficient and less invasive approach than sediment removal,especially in sensitive karst areas.

© 2016 Elsevier Ltd. All rights reserved.

. Introduction

Ratio among primary producers, macrophytes (i.e. charophytes,ryophytes and angiosperms): phytoplankton: periphytic algae,

s crucial in maintaining a favourable transparent state in lakesScheffer, 1998). Macrophyte stands have exceptional abilityo alter environmental conditions, nutrient cycling, biocoenosisssemblages and biotic interactions. Their impact on ecosystem

unctioning is related to the complexity of macrophyte stemsnd their physiology (Kuczynska-Kippen and Nagengast, 2006;haparro et al., 2014). Complex submerged macrophytes achieve

∗ Corresponding author.E-mail addresses: maria.spoljar@biol.pmf.hr (M. Spoljar), emil@tju.edu.cn

C. Zhang), tvrtko.drazina@biol.pmf.hr (T. Drazina), zhaoxiaoxue1119@163.comG. Zhao), jasna.lajtner@biol.pmf.hr (J. Lajtner), radonic.goran1@gmail.comG. Radonic).

ttp://dx.doi.org/10.1016/j.ecolind.2016.12.038470-160X/© 2016 Elsevier Ltd. All rights reserved.

their best results in the suppression of algal bloom through thecompetition for nutrient uptake (Jeppesen et al., 1997; Lau andLane, 2002) or by the production of allelopathic substances tomitigate algal growth (van Donk and van de Bund, 2002). Floating-leaved macrophytes increase shading, reduce algal photosyntheticoxygen production and reject zooplankters (Compte et al., 2011),whilst emergent macrophytes prevent coastal erosion (Horppilaand Nurminen, 2005). Besides numerous zooplankters (Kuczynska-Kippen and Nagengast, 2006; Spoljar et al., 2012b), macrophytestands host many epiphytic organisms, i.e., algae, protozoans andmeiofauna (Kralj et al., 2006; Spoljar et al., 2012c; Drazina et al.,2013). Epiphytic biomass and diversity depend on multiple abiotic(light supplies, nutrients, flow velocity, water residence time) and

biotic (macrophyte architecture, abundance of grazers) factors.

Interactions among macrophytes, illumination, epiphyton, graz-ers and fish may reflect the trophic state of the hydrosystem(Beresford and Jones, 2010; Spoljar et al., 2011). Epiphyton biomass

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46 M. Spoljar et al. / Ecologica

s generally higher in eutrophic lakes, but also, due to better illu-ination, its ratio can be higher in oligotrophic lakes (Laugaste

nd Reunanen, 2005). The same authors studied epiphyton on2 macrophyte species during the summer in the hypertrophictratified Verevi Lake (Estonia), and concluded that substrateomplexity may affect epiphyton biomass. For instance, chloro-hyll a amounted to 117–200 �g g DM−1 on floating-leaved plants,30–360 �g g DM−1 on emergent plants, and the highest values,20–920 �g g DM−1 on submerged plants. From biotic components,piphyton-feeding snails as known grazers, have a significantmpact on the biomass and species composition in the epiphyton,y reducing and removing old and recovering new epiphyton strataBrönmark, 1989; Zebek and Szymanska, 2014).

A shift between a transparent vs. turbid state is largely dueo macrophyte presence vs. absence. For instance, Scharmützelseeake (SE of Berlin, Germany) was characterized by turbid waterntil 2003. Thereafter, increased water transparency together with

rapid submerged macrophyte colonization, up to 5 m depth cor-esponded to the light supply of 3 E m−2 d−1 (Hilt et al., 2010).he authors recorded that an upgrowth of submerged macrophytetands to approximately 24% coverage in 2005–2006, dominatedy rootless Nitellopsis obtusa and Ceratophyllum demersum, con-ributed to the stabilization of the water transparency. Dense

acrophyte stands may also cause low bottom oxygen concen-ration, release P from the sediment and suppress mineralisationStephen et al., 1997; Søndergaard et al., 2003). These conditionsndicate a higher trophic level and may transform the lake from

transparent to a turbid state, in accordance with the knownhemical process clearly described by Søndergaard et al. (2003): Inxidised conditions, phosphorus is sorbed to iron (III) compounds,hile in anoxia iron (III) is reduced to iron (II) and subsequently

oth iron and sorbed phosphate returned into solution. In twoeservoirs of the Parana basin (South America) Chiba de Castro et al.2013) observed the negative effects of dense macrophyte stands80–100% coverage) where a decline in the redox potential wasaused by oxygen depletion. In the study of Caraco and Cole (2002)t was established that in the River Hudson (the stretch from Nework to Albany, USA) the alien aquatic macrophyte (Trapa natans)ay extremely decrease dissolved oxygen concentration to values

elow 2.5 mg l−1, while within macrophyte stands dominated by native species (Vallisneria americana) dissolved oxygen did notecrease below 5 mg l−1 during the summer growing season. In theestoration of overgrown lakes important ecological goals are toreate diverse macrophyte stands with an open water and mosaicf different, preferably submerged, macrophytes (Moss et al., 1997).

mosaic community of macrophytes will increase habitat het-rogeneity between macrophyte stands and the open water andnhance biocoenotic diversity and life styles (food preferences,igrations, nesting, moulting), facilitate succession of organisms

nd remove water pollutants and nutrients (Björk, 1994; Wangt al., 2009). Macrophyte diversity provides stands less sensitiveo physical disturbances, i.e.waves, bioturbations and herbivores,uppress algal production and reduce losses of total phosphorusEngelhardt and Ritchie, 2001; Hilt et al., 2006).

Predictions of ecosystem functioning are often requested andan prove to be of great value in protected areas with pecu-iar karst phenomenon, as in the Papuk Nature Park (Croatia).fter sediment-drainage of the Jankovac reservoirs (Papuk Natureark) in 2003 we analysed invertebrates in plankton, epiphytonnd benthos as well as macrophyte coverage, and environmentalarameters in 2008 and 2014. According to obtained data (Spoljart al., 2012a,b,d, 2015) macrophytes tend to overwhelm both reser-

oirs and thus the eutrophication process could be triggered. Wessumed that the increased trophic level in the Jankovac reser-oirs originated from the sediment, where the accumulation ofeciduous leaf litter and decayed macrophyte fragments proba-

ators 75 (2017) 145–154

bly generate anoxic conditions. In such cases aeration methodsfor water column (Verner, 1994) and sediment (Hilt et al., 2006)are frequently applied in lake restorations. Flow velocity also playsan important role in flow-through systems affecting macrophytestands (Wilby et al., 1998), epiphyton (Spoljar et al., 2012a), plank-tonic (Spoljar et al., 2012b) and benthic (Sertic-Peric et al., 2011)organisms. For instance, low to medium flow velocities sustain thediversity and density of macrophyte stands (Madsen et al., 2001;Franklin et al., 2008). The same authors recorded that higher flowvelocities negatively impact macrophyte stands, while Asaeda andSon (2000) and Horner et al. (2011) noted an increased epiphytonflushing rate. Recently, many modelling efforts have offered solu-tions for eutrophication reduction (Jin and Ji, 2015; Zhang et al.,2015, 2016). In the present study we considered flow velocity anddissolved oxygen concentrations as the main drivers in the balancebetween macrophyte coverage and epiphyton biomass and con-ducted them through a modelling design. The main objectives ofthis study were: (1) using a model simulation to analyse the influ-ence of the flow velocity and epiphyton on macrophyte coverageand biomass; (2) to analyse environmental properties for sustain-able growth of macrophytes and (3) to present an assemblage ofzooepiphyton, protozoans and meiofauna, under impact of envi-ronmental conditions in the Jankovac flow-through system. Theoverall aim of this study is to present a hydraulic control strat-egy in the regulation of submerged macrophytes within shallowreservoirs.

2. Material and methods

2.1. Study area

Jankovac Stream (45◦31′07′′N, 17◦41′11′′E, Fig. 1, Table 1) is asmall approximately 700 m long hydrosystem, in a submountainarea at 475 m asl., situated on sedimentary karst rocks in the PapukNature Park, NE Croatia, and is described in detail in our previousstudies (Spoljar et al., 2012a,b,d). Most of the stream was anthro-pogenically modified in two reservoirs (lentic parts), while loticparts occur as rheocrene spring (JS) and the Skakavac Waterfallover the tufa barrier (JW). The two reservoirs (R1 and R2) exist asan interconnected flow-through system separated by a bank, andwater flows through a connection between reservoirs. Across thelongitudinal profile, the stream is mostly surrounded by deciduousforest, dominated by beech (Fagus sylvatica L.), followed by com-mon ash (Fraxinus excelsior L.), maple (Acer pseudoplatanus L., A.obtusatum (Waldst. et Kit. ex Willd.)) and wych elm (Ulmus glabraHuds.). The reservoir banks are slightly inclined. The bottom is cov-ered with organic mud, which consists of a thick layer (0.5 m) in thelittoral zone of mostly fine particulated organic matter, originatingfrom macrophyte decay and deciduous leaf litter.

Both reservoirs were subjected to the sediment-drainagemethod in September of 2003 in an attempt to increase the waterlevel. Water is transparent through the whole column and thusfavours the growth of submerged macrophytes, Hippuris vulgarisas dominant and accompanying Potamogeton natans. Emergentmacrophytes, Carex sp., Scirpus sp., Iris pseudacorus and Typha latifo-lia, constitute a discontinuous narrow belt around both reservoirs.

2.2. Assessment of zooepiphyton, environmental parameters andtheir interactions

Samples were collected in triplicate in July and the first half

of September of 2008 and 2014 (Fig. 1). Within both reservoirstwo habitats were identified: nonvegetated habitats, with pelagial(R1N, R2N), inflow (R1I) and outflow (R1O, R2O) parts of reser-voirs; and vegetated habitats with H. vulgaris (R1H, R2H). Epiphyton

M. Spoljar et al. / Ecological Indicators 75 (2017) 145–154 147

Fig. 1. Bathymetric map of interconnected reservoirs with marked sampling points in reservoirs R1 and R2. Abbreviation follow downstream direction: JS – Jankovac Spring;R1I – hypocrenal inflow into R1, R1N – nonvegetated pelagial in R1, R1H – Hippuris stands in R1; R1O – outflow from R1, R2N – nonvegetated pelagial in R2, R2H – Hippurisstands in R2; R2O – outflow from R2, JW – Skakavac Waterfall.

Table 1Main hydromorphological and environmental features of the Jankovac Stream, Papuk Nature Park.

Localities JS R1 R2 JW

Area (m2) 9240 5317Lenghtmax (m) 61 168 130Widthmax (m) 3 52 51zmax (m) 0.25 1.9 1.95 0.7Height (m) 32Total volume (m3) 8.8 × 104 6.8 × 104

Main reservoirstations

R1N R1H R2N R2H

Habitatspecification

Lotic Lentic Lentic Lentic Lentic Lotic

Flow velocity(m s−1)

0.36–0.57 0.07–0.15 Stagnant 0.06–0.13 Stagnant 1.01–1.40

WRT* (day) 4.4 3.4Bottomgranulometry

Tufa, detritus Mud Mud Mud Mud Boulders, tufa

Bed anddominantmacrophytecoverage

Thin layer ofsediment,hypocrenalcovered withdense mosses

Nonvegetated Hippurisvulgaris,Potamogetonnatans

Nonvegetated Hippurisvulgaris,Potamogetonnatans

Thin layer ofcompact tufasediment, patchymosses

A ovac Wn l. (201

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bbreviations: JS – Jankovac Spring, R1 – Reservoir 1, R2 – Reservoir 2, JW – Jankonvegetated pelagial in R2, R2H – Hippuris stands in R2, *According to Spoljar et a

as sampled from submerged and branched Hippuris. This specieseaches its maximum growth activity in July. For epiphyton analy-is, shoots of both macrophytes (each sample contained a shoot of

single plant) were sampled with a plexiglas core sampler (30 cmigh, � 8 cm, 26 �m mesh) according to Kornijów and Kairesalo1994). Macrophyte shoots ranging between 10–15 cm in lengthere cut and epiphyton was scraped off using a small brush andashed into plastic bottles after which they were transported to the

aboratory and the living material was identified ≤48 h of collection.Epiphyton, protozoans and meiofauna (benthic or periphytic

eterogeneous groups of metazoans: rotifers, nematodes, gas-rotrichs, cladocerans, copepods, ostracods; defined as organismshat can pass through a 1000 �m sieve and retained on a 44 �m

ieve; Giere, 2009) were identified and counted in three subsam-les under an Opton-Axiovert 35 inverted microscope (125×–400×agnification). For species determination, the following litera-

ure was consulted: Voigt and Koste (1978), Ogden and Hedley

aterfall, R1N – nonvegetated pelagial in R1, R1H – Hippuris stands in R1; R2N –2b).

(1980), Amoros (1984), Einsle (1993), Foissner and Berger (1996),and Rundle et al. (2002). Bdelloidea and Nematoda were countedbut not identified. Microfaunal biomass in epiphyton, presentedin dry weight, was calculated by assuming a biovolume based ontheir geometric shapes, and converted to dry mass for protozoans(Gilbert et al., 1998), rotifers, cladocerans and copepods (Dumontet al., 1975; Malley et al., 1989). All shoots were dried and weighedand epiphytic biomass was estimated as �g g−1 DM (epiphyton drymass per gram dry mass of macrophyte).

At each sampling point, in parallel with biocoenoses samples,field measurements and samples for laboratory analyses weretaken. Temperature, dissolved oxygen concentration, pH (HatchHQ30d), conductivity (HACH sensION 5) and flow velocity (P600

flow meter, DOSTMANN electronic GmbH) were determined inthe field. All nutrients, orthophosphates, total phosphorus (TP),nitrates and Kjeldahl total nitrogen (TN) were determined accord-ing to APHA (1995). Nitrites and ammonium were measured using

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on chromatography (Dionex ICS-3000). Dissolved organic mat-er (DOM, mg O2Mn l−1) was measured through the estimation ofhemical oxygen demand, CODMn, (Spoljar et al., 2011). Algae, mea-ured as chlorophyll a (Chl a) according to Nusch (1980), in planktonPChl-a) and epiphyton (EChl-a), and concentration of particulaterganic matter (POM) were considered as food resources. POM val-es, were measured as ash-free dry mass (AFDM) according to therocedure described in Spoljar et al. (2012b). Macrophyte dry massDM) was measured after epiphyton removal and weighed afterrying in a thermostat at 104 ◦C for 24 h.

Before the statistical analysis, all the data were logarithmi-ally transformed [log (x + 1)] and their normality was checkedsing Shapiro-Wilk’s test. Results of this test showed that data didot follow normal distribution, and then a non-parametric Mann-hitney U test (comparison between two independent samples for

ooepiphyton biomass between two years) was used. Relationshipsetween environmental and biotic parameters were correlatedsing Spearman rank.

.3. The JanM

Jankovac Water Quality and the Macrophyte Model (JanM)omposed the water quality model coupled with the sub-model M-AVM (Modified-Submerged Aquatic Vegetation Model). The JanMas developed under the framework of the Environmental Fluidynamics Code (EFDC, Hamrick, 1992), model to simulate hydro-ynamics and water quality in the Jankovac Reservoirs. Based onhe Submerged aquatic vegetation Model, SAVM (Cerco et al., 2002;in et al., 2007), the submodel M-SAVM (Zhang et al., 2015) waseveloped by modification of the light attenuation equation. The

anM structure accompanying the embedded subroutine for nutri-nts (ortho-phosphates and nitrates) and dissolved oxygen (DO)ycles has been described previously (Zhang et al., 2016), and theoverning hydrodynamics and mass-balance equations togetherith the numerical solution algorithm (Zhang et al., 2013; Jin and

i, 2015) are attached in the Supplementary Material. The kineticass balance equations for shoot, root, and epiphyton have also

een described previously (Ji, 2008; Jin and Ji, 2013; Zhang et al.,015). The main biomass-balance equations of the JanM and theumerical solution algorithm can be found in the Supplementaryaterial.

The growth limiting function for light intensity, f2(I), wasescribed as Eq. (1) in the M-SAVM. The �e was determined by theater transparency (Secchi depth) and epiphyton in the M-SAVM

Zhang et al., 2015). The effect of epiphyton was included in theight attenuation equation, which is the main difference between

-SAVM and SAVM.

2(I) = 2.718�e · Hs

(exp(−˛) − exp(−ˇ)

)(1)

e = �0 + KeBeCChle

(1a)

here �e is the light attenuation coefficient (m−1); Hs is the aver-ge shoot height above the bed (m); the coefficients and areescribed in detail in Ji (2008); �0 is the background light attenu-tion coefficient (m−1), which reflects the water transparency; Bere the epiphyton biomass (g C m−2); Ke is the coefficient for EChl am−1 mg−1 m2); and CChle is the carbon/EChl a ratio for epiphytong C: mg EChl a).

.4. Model application

.4.1. Framework of the simulationsThe horizontal plane of reservoirs was divided into 278 grid cells

DX 1.57 − 13.8m, DY 3.57 − 16.7m) with two layers in JanM. The

ators 75 (2017) 145–154

hydrodynamic time step was 1 s, water quality and macrophytemodel were 0.4 s.

The semi-monthly averaged data for hydraulic and meteorolog-ical boundary conditions were used and water quality and loads,also on a semi-monthly basis. Both initial shoot and root carbonbiomass values were assumed to be 5 g C m−2 in the bottom layer.

2.4.2. Calibration and validationJanM was calibrated and verified to a hydrodynamic with

the water depth (z) and flow velocity (FV), using two datasets,07/01–09/30, 2008 and 07/01–09/30, 2014. The model simulationsof constituents were good with RMSE of depth (0.17 m). Hydrody-namic model calibration was carried out by changing the roughness(calibrated from 0.025 to 0.035). RMSE of velocity is 0.36 cm s−1. Thecalibration and validation results of z and FV at R1H and R2H arepresented in the Supplementary Material (Fig. S1).

JanM was calibrated and verified with the five water qualityparameters, DO, DOM, TP, TN, chlorophyll-a (EChl-a and PChl-a),using two datasets, 07/01–07/31, 2014 and 09/01–09/30, 2014. Thecalibrated values of the major coefficients in JanM are presentedin the Supplementary Material (Table S1 in Supplementary mate-rial). The results of the main limnological parameters at R1H andR2H are presented in the Supplementary Material (Figs. S2 and S3in Supplementary material). The model simulations of main waterproperties showed a good fit with RMSE, R-RMSE, and the absoluteerror values were <30% (Table S2 in Supplementary material).

JanM was calibrated and verified respectively with macrophytebiomass in two datasets, 07/01–10/10, 2008 and 07/01–10/10,2014. The values of the major coefficients for calibration in M-SAVMare given in Table 2. The model simulations are acceptable, basedon RMSE, R-RMSE, and the absolute error values (Table 3).

2.4.3. Sensitivity analysisA sensitivity analysis was conducted to elucidate how the uncer-

tainty of the model outputs can be apportioned to the parameters(Arhonditsis and Brett, 2005). The sensitivity analyses for lightattenuation coefficient and maximum growth rate of plant shootswere carried out in M-SAVM as part of a previous study (Zhanget al., 2015). The epiphyton maximum growth rate (PMe) for thisstudy was chosen because the impact of epiphyton in mitigation ofmacrophytes growth is focused.

3. Results

3.1. The coverage and biomass of macrophytes influenced by flowvelocity

Simulated macrophyte coverage is consistent with the trends ofmeasured data in reservoirs R1 and R2 (Fig. 2, Table 3). Three sce-narios were simulated by the JanM with the purpose of establishingthe effect of FV on macrophyte growth, measured as coverageand biomass, dissolved oxygen, light attenuation and epiphytonbiomass.

The original scenario (OS) was the calibration from 2008. Three,five, and ten times higher FV were assumed in the scenarios. Themodelled macrophyte coverage in the OS reached maximums of73% in R1 and 90% in R2 (Fig. 3a). Results suggested that macro-phyte coverage and biomass both increased with higher FV in thesimulated scenarios. By applying the FV10 scenario, results indi-cated an extension of macrophyte coverage up to 78% and 92%,in R1 and R2, respectively. Similarly, macrophyte biomass also

amounted to higher values in the FV10 scenario, with a maximumof 167.5 g DM m−2 at R1H and 132.4 g DM m−2 at R2H (Fig. 3b).

Significant oscillations for DO were observed in the FV10 sce-nario at R1H (p = 0.01). The concentrations of DO by FV10 varied

M. Spoljar et al. / Ecological Indicators 75 (2017) 145–154 149

Fig. 2. Modelled coverage and biomass of macrophytes for calibration (a, b) and validation (c, d) period.

Fig. 3. Modelled macrophyte coverage and biomass, DO, light attenuation f2(I), and epiphyton biomass in three different flow velocity scenarios (FV3, FV5, FV10).

150 M. Spoljar et al. / Ecological Indicators 75 (2017) 145–154

Table 2Major M-SAVM coefficients and constants of the calibrated model a.

Parameter Description Value Reported in literature Unit

fPr fraction of production directlytransferred to the root

0.15 0.15 Ji (2008) –

Ls ,Lr ,Le non-respiration loss rate for plantshoots, roots, and epiphytes

0.01 0.01 Ji (2008) d−1

PMs maximum growth rate under optimalconditions for plant shoots

0.15 0.1 Cerco and Moore (2001)0.2 Ji (2008)0.2–0.3, Janse et al. (2010)0.144 van Nes et al. (2002)0.17 Zhang et al. (2015)

d−1

*PMe maximum growth rate under optimalconditions for epiphytes

0.2 0.065 Zhang et al. (2015) d−1

*KNhw ,KNhb half-saturation constant for nitrogenuptake from water and bed

0.1 0.13 Thursby and Harlin (1982)0.19 Cerco and Moore (2001)

g N m−3

*KPhw ,KPhb half-saturation constant forphosphorus uptake from water and bed

0.03 0.02 Madden and Kemp (1996)0.028 Cerco and Moore (2001)

g P m−3

Iso maximum value for optimum lightintensity for plant growth

90 20–100 Ji (2008) W m−2 d−1

*KTP1 effect of temperature below optimallow temperature on shoot production

0.001 0.001 Ji (2008) ◦C−2

*KTP2 effect of temperature above optimalhigh temperature on shoot production

0.001 0.001 Ji (2008) ◦C−2

*KD attenuation due to shoots self-shading 0.02 0.045 Cerco and Moore (2001)0.0143 Ji (2008)

m2 g−1

*RMs maximum respiration rate for plantshoots at reference temperature

0.04 0.019 Madsen et al. (1991)0.022 Cerco and Moore (2001)0.02 Zhang et al. (2015)

d−1

*RMr maximum respiration rate for plantroots at reference temperature

0.015 0.022 Cerco and Moore (2001)0.01 Ji (2008); Zhang et al. (2015)

d−1

*RMe maximum respiration rate forepiphytes at reference temperature

0.025 0.0005 Zhang et al. (2015) d−1

*KTRS ,KTRr effect of temperature on plant shootsand roots respiration

0.001 0.001 Ji (2008) ◦C−1

*Krs root-to-shoot transfer rate for lightdependence

0.35 0.35 Zhang et al. (2015) d−1

*Ihss half-saturation light at shoot surface 120 120 Zhang et al. (2015) W m−2 d−1

�0 the background light attenuationcoefficient

0.6 0.5 van Nes et al. (2002); Janse et al.(2010)

m−1

Ke coefficient for epiphyte chlorophyll 0.04 0.04 Zhang et al. (2015) m−1 mg−1 m2

Hs the average shoot height above the bed 0.3 – manc nitrogen to carbon ratio for plant

shoots, roots, and epiphytes0.167 0.167 Cerco and Cole (1994) g N: g C

apc phosphorus to carbon ratio for plantshoots, roots, and epiphytes

0.007 0.007 Cerco et al. (2004) g P: g C

CChle carbon to chlorophyll ratio forepiphytes

0.12 0.15 Mao et al. (2009)0.12 Zhang et al. (2015)

g C: mg EChl a

a The parameters with the symbol ‘*’ are in the equations for f1(N), f3(T), f5(D), Pe , Rs , Rr , Re , and Jrs , which are detailed elsewhere (Ji, 2008).

Table 3Statistical error quantification analysis results of calibration and validation for biomass a.

Parameter July September

R1 R2 R1 R2

i. Calibration periodMeasured coverage (%) 75 60 75 60Modeled coverage (%) 68 84 68 52Absolute error 11.5RMSE 13.6R-RMSE (%) 20.1

ii. Validation periodCoverage of Macrophytes (%) 87 97 97 94Modeled coverage (%) 86 97 97 94Absolute error 0.3RMSE 0.5

btog

R-RMSE (%) 0.5

a R-RMSE = RMSE/Mean.

etween 7.0 and 20.2 mg O2 l−1 in both reservoirs (Fig. 3c). In par-

icular, some trends of a slight decline during the establishmentf macrophytes were observed after which a rapid increase in therowth period was exhibited.

According to the original scenario of JanM, the light intensity

limitation coefficient among macrophytes reached an average of0.537 ± 0.158 at R1H and 0.357 ± 0.173 at R2H in OS (Fig. 3d). TheFV10 scenario resulted in the highest averages among the threescenarios, with 0.627 ± 0.132 (R1H) and 0.373 ± 0.180 (R2H). The

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M. Spoljar et al. / Ecologica

ight intensity limitation coefficient was slightly lower (∼0.007) at2H in comparison to R1H by FV10 during macrophyte decay, butas not indicative of a significant decline of biomass.

Epiphyton biomass decreased with increased FV in the scenar-os. The modelled epiphyton biomass in the OS achieved maximumalues of 28.9 g DM m−2 in R1H and 19.9 g DM m−2 in R2H (Fig. 3e).he FV10 scenario indicated a meaningful decline of epiphytoniomass in comparison with the OS, 63.1% and 40.2%, in R1H and2H, respectively.

.2. The impact of epiphyton in mitigation of macrophytes growth

A sensitivity analysis was performed to test the influence of aide spectrum of parameter values for the epiphyton maximum

rowth rate (PMe). In Jankovac Reservoir, macrophyte coveragehould be reduced and remain at a max of 70% of the lake area.herefore, we designed a test to simulate the increase of epiphytonrowth rates in the M-SAVM, i.e, 0.25, 0.3, and 0.4 d−1.

The modelled macrophyte coverage and biomass bothecreased with increased epiphyton growth (PMe) in sensitivitynalysis scenarios. The results show that macrophyte coverages restricted at 61.0% in R1 and 51% in R2 comprising the highestpiphyton growth rate scenario, PMe0.4 (Fig. 4a). Similarly, theacrophyte biomass declined in PMe0.4, with maximum values of

9.5 g DM m−2 at R1H and 59.8 g DM m−2 at R2H (Fig. 4b). Resultsf PMe0.3 and PMe0.4 scenarios suggested that the maximumacrophyte coverage could be undermined and coverage could be

elow ∼70% of the lake area.

.3. Zooepiphyton assemblage and interactions withnvironmental parameters

The diversity of meiofauna remained similar, 30 and 25 taxa,n 2008 and 2014 respectively, with rotifers as the most diverseroup. Biomass of total zooepiphyton notably increased from 2008o 2014. Ciliates and rotifers made a prominent contribution in008 and nematodes and copepods in 2014 (Fig. 5). Instead ofistinctive variations in zooepiphyton biomass, temporal as wells spatial (between reservoirs) oscillations were not statisticallyifferent (Mann-Whitney, p < 0.05).

Zooepiphyton was significantly and negatively affected by flowelocity. Macrophyte coverage, substrate size (considered throughacrophyte DM) and biomass of epiphytic algae enhanced the

iomass of zooepiphyton dominant groups (Table 4). Copepods alsohowed similar trends of interactions with environmental param-ters, but a significantly positive relationship was revealed withissolved oxygen concentrations among macrophytes (r = 0.425).Chl-a was significantly (p < 0.001) positively impacted by sub-trate size (0.760) and coverage (0.815).

. Discussion

.1. Medium–term alterations in studied reservoirs

The results of this modelling reveal possibilities for the reg-lation of submerged macrophyte growth in small and shalloweservoirs of the temperate zone. Any treatments in an ecosystemequest prior preparation and selection, peculiarly in a hydrosys-em situated in a karst area, known worldwide for its habitats,pecies diversity and sensitivity to anthropogenic disturbanceWilliams, 2008; Buzan and Pallavicini, 2014). In spite of being a

rotected area, Jankovac reservoirs were subjected to sediment-rainage restoration in 2003, which resulted in a decline ofacrophyte diversity. According to Razlog-Grlica and Grlica (2004),

0 macrophyte species were recorded before treatment but by the

ators 75 (2017) 145–154 151

following year there were 10 fewer species, suggesting that sedi-ment removal eliminated propagules (Hilt et al., 2006). During 2008and 2014, we conducted comprehensive ecological research ofenvironmental parameters and aquatic biocoenosis, thus we wereable to observe and record the possible signs of an increased trophiclevel (Spoljar et al., 2012a,b,d, 2014). Firstly, a notable increasein phytoplankton biomass (2.18 ± 0.57 �g l−1 Chl a in 2008 and4.91 ± 2.01 �g l−1 Chl a in 2014) indicating a transition from anoligotrophic to a mesotrophic level. Secondly, uniform macrophytestands dominated by Hippuris and Potamogeton, which successivelyincreased their infestation and by 2014 occupied almost the wholereservoir bed. According to Perrow et al. (1994) and Hilt et al. (2006)monocultures of macrophyte stands indicate a higher trophic level,while a diverse macrophyte assemblage is highly preferred and bet-ter sustains the balance between biocoenosis and nutrient. Thirdly,macroinvertebrate assemblages were present in 2008, indicatingclean and not significantly altered water quality, while in 2014 pol-lution and a deterioration in water quality had become apparent(Spoljar et al., 2014, 2015). We presumed that in aquatic bio-coenosis macroinvertebrates were initially negatively impacted bydecreased oxygen, probably due to the dissolved organic matterdecomposition in the sediment (Bianchini et al., 2008). Namely,hypoxic conditions in the bottom water layer as well as in sediment,could be explained by the presence of the surrounding deciduousforest which contributes to a higher accumulation of leaf litterand decayed macrophyte fragments. Both lead to anoxic condi-tions, confirmed by a slight increase of phosphates and sulphatesabove the permissible concentrations in the sediment (Spoljar et al.,2014). Similarly, Kuczynska-Kippen and Joniak (2010) in a study ofmid-field and mid-forest ponds in NW Poland, also pointed out thesignificant impact of the catchment area on limnological parame-ters and aquatic biocenoses.

4.2. Interactions among flow velocity, macrophytes andepiphyton

The main intention of this study was to invent and sug-gest a treatment against macrophyte overgrowth and anoxicconditions that is less invasive than sediment removal, and to pre-vent the occurrence of eutrophication processes in a particularkarst situated flow-through system. Simultaneously, we combinedan interpretation of ecological interactions from the results ofepiphyton biocoenotic analysis and modelling simulations. Theapplication of such modelling can offer solutions as well as pre-dictions for lake restoration. Numerous approaches have beendeveloped to reduce eutrophication in water bodies, i.e. EFDC(Hamrick, 1992), WASP (Wool et al., 2002) together with modelsdesigned to predict and manage macrophyte growth, i.e., SAVM(Cerco and Moore, 2001; Jin and Ji, 2013) and the modified SAVMby Zhang et al. (2015, 2016).

In the JanM simulation we included flow velocity with the aimto obtain data anticipated in the regulation of macrophyte coverageand biomass. Commonly, the diversity and density of macrophytesare promoted at low to medium and suppressed by increased flowvelocities (Madsen et al., 2001; Franklin et al., 2008). Recently,hydrological treatments in lake restoration based on macrophyteregulation, have been presented as a result of water level fluctua-tions (Moss et al., 1997; Beklioglu et al., 2006; Zhang et al., 2015),hypolimnetic withdrawal of nutrient rich water (McComas, 2003),or dilution of high nutrient concentration, by adding nutrient-poorwater, reducing algal growth by flushing faster than they can repro-duce (Cooke et al., 1993). The modelled results of interactions

among macrophytes, flow velocity, epiphyton and environmen-tal parameters may be explained as follows: firstly, higher flowvelocity probably flushes epiphyton, thus enables light supplyand increases macrophyte coverage and biomass; secondly, oxy-

152 M. Spoljar et al. / Ecological Indicators 75 (2017) 145–154

Fig. 4. Modelled macrophyte coverage and biomass in sensitivity analysis with different scenarios of epiphyton growth (PMe: PMe0.25, PMe0.3, PMe0.4).

Table 4Spearman rank correlations (r; p < 0.05) among main groups and total zooepiphyton against environmental parameters.

�g g−1 DM

Ciliophora Rotifera Nematoda Gastrotricha Copepoda Total Zooepiphyton

Macrophytes coverage 0.659*** 0.696** 0.227 0.353 0.024 0.641*

EChl a (�g g−1 DM) 0.748*** 0.898*** 0.210 0.549* 0.235 0.797***

Macrophyte DM (g) 0.679** 0.771*** 0.335 0.491* 0.383 0.813***

* p < 0.05.** p < 0.001.

*** p < 0.0001.

Ft

goflatameaetsbeniRip

ig. 5. Spatio-temporal oscillations of dominant groups and total zooepiphyton onhe studied sampling points.

en concentrations are increased by the photosynthetic activityf macrophytes and mixing is enhanced as a result of higherow velocity and the inflow of highly oxygenated water; thirdly,eration enhances the mineralisation of organic matter and con-ributes to phosphorous precipitation, its uptake by macrophytesnd prevention of algal bloom. Asaeda and Son (2000) experi-entally established flow velocity as a key factor in epiphyton

rosion, and Wilby et al. (1998), further investigating this inter-ction, concluded that higher flow velocities limit epiphyton andnhance macrophyte growth. Moreover, the resilience of Hippuriso higher flow velocity could be explained by their flexible buttrong stem, and it is likely that this species is more restrictedy a low trophic level and higher pH than by flow velocity. Thextent of submerged macrophyte coverage is also important inutrient reduction efforts and evaluating the success of water qual-

ty management (Jin and Ji, 2013; Zhang et al., 2016). In the Yuqiaoeservoir, NE China, Zhang et al. (2015) suggested that the decline

n nutrient concentrations was due to uptake of Potamogeton cris-us growth during periods of exponential growth. Simulations

with increased flow velocity reinforce mixing and dissolved oxy-gen concentrations through the whole water column in shallowreservoirs, as previously confirmed by Chu and Jirka (2003) andDemars and Manson (2013). The turbulence caused by macrophytestands could positively impact oxygen supplies and mineralisa-tion in the bottom water layer and sediment (Huai et al., 2010).In laboratory conditions it was confirmed that reaeration rates arealso enhanced by macrophyte complexity (Moog and Jirka, 1999).Moreover, the relationship between flow velocity and epiphyticbiomass implies inverse interactions, i.e., non-filamentous algaewere markedly and negatively affected in comparison to filamen-tous algae at higher flow velocity (Asaeda and Son, 2000), andthere is an increase in epiphyton biomass at lower flow velocity(Rovira et al., 2016). Both effects are pronounced through time,and are in compliance with our results, where modelled and fieldassessment indicated water movement as the main stressor to havea significant impact on biomass decrease of algae, small proto-zoans and epiphytic meiofauna. Different epiphytic protozoan andmeiofaunal groups responded differently to the oscillation of flowvelocity. Due to higher flow velocities, observed in 2008, small-bodied and r-strategist organisms (protozoans, rotifers) developedhigher abundances (Spoljar et al., 2012a,b). Additionally, most ofthe rotifers present were microfilter-feeders that can consume thelarge amounts of suspended organic matter transported in thewater of higher flow velocity (Duggan, 2001; Drazina et al., 2013),which brings them a greater amount of that food type. Nematodesprefer long periods of habitat stability, which prevailed in 2014(Majdi et al., 2012). They are a heterogeneous trophic group (preda-tors, bacterivores, algivores and omnivores) and thus, in a thickepiphyton layer they can utilize different food sources. Overall,results collected in Jankovac reservoirs indicated that the biomassof ciliates and rotifers, as small-bodied attached organisms highlydependent on microhabitat properties, was strongly and signifi-

cantly affected by macrophyte coverage and substrate complexity(Spoljar et al., 2012c; Kuczynska-Kippen and Basinska, 2014).

l Indic

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.3. Interactions among light, macrophytes and epiphyton

Macrophyte coverage and growth can be controlled by lightntensity, water turbidity, epiphytic biofilm as well as snail grazerspon epiphyton on macrophyte stems (Köhler et al., 2010; Zebeknd Szymanska, 2014). Submersed macrophyte stands retaineduspended particles, increased light attenuation and improvedownstream transparency, i.e. light supply (Köhler et al., 2010).imulations in our study reveal a significant relationship betweenhe biomass of macrophytes and epiphyton (Zhang et al., 2015).igher epiphyton growth implies a negative effect on macrophytesue to the restriction of light availability and macrophyte photo-ynthesis (Franklin et al., 2008). Rich epiphyton could result higherutrient concentrations, as confirmed in standing water bodiesHill and Harvey, 1990). In the lentic part of running waters, shortater residence time promotes nutrient increase and the growth

f benthic and epiphytic algae, while long residence time leads tohytoplankton turbidity (Hilton et al., 2006).

. Conclusions

The results of this modelling demonstrated that hydraulic simu-ations could be effective in the alteration of transparent and turbidtates i.e. in the balance between macrophytes and epiphyton,specially in small and shallow water bodies. The model for Janko-ac reservoirs (JanM) is the result of a combination of the integrated

ater Quality Model (WQM) and the Submerged Aquatic Vegeta-ion Model (SAVM). These reservoirs are small hydrosystems in ansolated karst and protected area, so common hydrological restora-ion methods, i.e. water pumps, should be avoided. The adjusted

ethods should be able to achieve the most sustainable option,t within the scope of esthetical value of this landscape and pro-

ected area. Increased flow velocity could have a positive impactn macrophytes and accompanying epiphyton assemblages. Thus,e are suggesting some less invasive and debilitating restora-

ion methods: cutting macrophytes to form a mosaic communityf macrophytes and open water would increase flow velocity.

ncreased flow velocity, habitat complexity and biodiversity wouldnable better oxygen supply and mineralization in the sedimenthrough the constant horizontal and vertical mixing of these smallnd shallow reservoirs. The presented results offer encouragementor the application of hydraulic management in lake restoration,nd such application would achieve a favourable quality of sedi-ent, water column and aquatic biocenosis.

cknowledgements

This study was granted by the Papuk Nature Park project. Wehank the personnel of Papuk Nature Park for administrative andeld support, especially Vlatka Dumbovic and Marijana Kesic. Were especially grateful to Robert Kippen for English improvement.

e thank Ivica Lajtner for help in field transport and photodoc-mentation and Svjetlana Vidovic for contribution in laboratorynalyses. The modelling in this study was supported by the Nationalatural Science Foundation of China (No. 51679160) and the Sci-nce Fund for Creative Research Groups of the National Naturalcience Foundation of China (No. 51321065).

ppendix A. Supplementary data

Supplementary data associated with this article can be found,n the online version, at http://dx.doi.org/10.1016/j.ecolind.2016.2.038.

ators 75 (2017) 145–154 153

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