Knowledge and Management of Aquatic Ecosystems (2016) 417 15ccopy R Stancheva and RG Sheath published by EDP Sciences 2016

DOI 101051kmae2016002

wwwkmae-journalorg

Knowledge ampManagement ofAquaticEcosystems

Journal fully supported by Onema

Review Open Access

Benthic soft-bodied algae as bioindicators of stream water quality

R Stancheva and RG Sheath

Department of Biological Sciences California State University San Marcos San Marcos 333 S Twin Oaks Valley RdCalifornia 92096-0001 USA

Received December 13 2015 ndash Revised January 21 2016 ndash Accepted January 25 2016

Abstract ndash This review presents the state-of-the-art of benthic soft-bodied algae as biondicators of stream and riverwater quality with emphasis on bioassessments set by the legislation (eg European Water Framework Directive USAClean Water Act) to promote the restoration and ensure ecological sustainability of water resources The advantagesand shortcomings of a variety of bioassessment field and laboratory methods for algae are discussed The increasing useof soft-bodied algae in biotic indices to assess individual anthropogenic stressors and in multimetric indices of bioticintegrity to evaluate ecological condition in streams is summarized Rapid microscopic and molecular approaches forinferring nutrient supply with heterocystous cyanobacteria and other sensitive algae are proposed The need of betterunderstanding of soft-bodied algae as bioindicators is discussed and suggestions are made for obtaining meaningfulbioassessment information with cost-efficient efforts

Key-words Bioassessment water quality benthic soft-bodied algae stream river

Reacutesumeacute ndash Les algues benthiques agrave corps mou comme bioindicateurs de la qualiteacute de lrsquoeau en riviegravere Cetterevue preacutesente lrsquoeacutetat de lrsquoart des algues benthiques agrave corps mou comme bioindicateurs de la qualiteacute de lrsquoeau en riviegravereavec un accent sur lrsquoeacutevaluation biologique fixeacutee par la leacutegislation (par exemple la directive europeacuteenne cadre sur lrsquoeaule Clean Water Act USA) pour promouvoir la restauration et assurer la durabiliteacute eacutecologique des ressources en eauLes avantages et les inconveacutenients de diverses meacutethodes de bioeacutevaluation de terrain et de laboratoire pour les alguessont discuteacutes Lrsquoutilisation croissante des algues agrave corps mou dans les indices biotiques pour eacutevaluer les facteurs destress anthropiques et les indices multimeacutetriques drsquointeacutegriteacute biotique pour eacutevaluer lrsquoeacutetat eacutecologique des cours drsquoeauest preacutesenteacutee Les approches rapides microscopiques et moleacuteculaires avec des cyanobacteacuteries heacuteteacuterocysteacutees et drsquoautresalgues sensibles pour deacuteduire lrsquoapport de nutriments sont proposeacutees La neacutecessiteacute drsquoune meilleure compreacutehension desalgues agrave corps mou comme bioindicateurs est discuteacutee et des suggestions sont faites pour obtenir de bonnes donneacutees debioeacutevaluation drsquoun bon rapport coucirct-efficaciteacute

Mots-cleacutes eacutevaluation biologique qualiteacute de lrsquoeau algues benthiques agrave corps mou courant riviegravere

1 Introduction

In streams benthic algae are one of the most species-richorganism groups (Meyer 2007) and the rationale for their usein bioassessments has been summarized in previous reviews(see Whitton and Kelly 1995 Lowe and Pan 1996 Stevensonand Smol 2003 Stevenson 2014) The most important advan-tages of benthic algae over other stream organisms as bioindi-cators are outlined as follows (a) benthic algae are sessile orhave limited movement and they cannot avoid potential pol-lution through migration or other means and thus they musteither tolerate the ambient environment or perish (b) the gen-eration time ranges from a few days for unicellular organ-isms to several months for larger multicellular filamentousand colonial soft-bodied algae (belonging to all non-diatomalgal taxonomic groups including cyanobacteria) and thusshort- and long-term shifts in environmental conditions canbe observed (Jarlman 1996 Whitton 2012) (c) algae have

Corresponding author rhristovcsusmedu

species-specific environmental tolerances and preferences anddirectly respond to water chemistry (such as nutrient levelssalinity pH organic pollution herbicides etc) (d) benthic al-gal communities are typically species-rich and spatially com-pact so a few square centimeters of substratum may supportover a hundred species each one with specific environmentalrequirements and thus represents an information-rich systemfor environmental monitoring (modified from Lowe and Pan1996) Compared to macroinvertebrates and fish algae are bet-ter suited for local-scale or upstream-downstream studies andbetter indicate water chemistry and land use that alters waterquality because of their position at the base of food webs andrestricted motility (Johnson 2006 Resh 2008) Due to theirdesiccation tolerance algae could be the only water qualitybioindicator in intermittent streams in more arid areas

Ecological indicators which are measurable structural orfunctional characteristics of the ecosystems including biolog-ical conditions (USEPA 2002) are central to bioassessmentwith their primary role being to evaluate ecosystem responses

This is an Open Access article distributed under the terms of the Creative Commons Attribution License CC-BY-ND (httpcreativecommonsorglicensesby-nd40) which permits unrestricted use distributionand reproduction in any medium provided the original work is properly cited If you remix transform or build upon the material you may not distribute the modified material

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

to anthropogenic stress (ie deviation from ecological in-tegrity Niemi and McDonald 2004) Algae are bioindica-tors of both structural components of ecological integrity(taxonomic composition) and functional integrity (biomassrates pattern and relative importance of processes) (Doleacutedecand Statzner 2010) The water-quality criteria in countriesaround the world are established by legislation and large-scalebioassessment projects are designed to evaluate the streamhealth and to support water resource management decisionsThe goal of the USA Clean Water Act (CWA 1972) is to re-store and maintain the physical chemical and biological in-tegrity of water resources and to have surface waters with bi-ological integrity defined as ldquothe capability to support andmaintain a balanced integrated adaptive community of organ-isms having species composition diversity and functional or-ganization comparable to that of natural habitat of the regionrdquo(Frey 1977) Biological condition is usually measured in termsof deviation from a natural or minimally disturbed conditionand reference conditions for biological integrity refers to theldquonaturalnessrdquo of the structure and function of the biota in theabsence of significant human disturbance or alteration (Stod-dard et al 2006) Similar water-quality governmental policiesand guidance are developed in Australia and New Zealand(ANZECC 2000) Recent European Union (EU) legislationinstituted the Water Framework Directive (WFD EC 2000) inwhich key components are a general requirement for ecolog-ical protection and a sustainable water use that is applicableto all surface waters ndash rivers and streams among others TheWFD requires all surface water bodies to achieve ldquogood eco-logical statusrdquo by 2015 defined as having a biota consistentwith only slight alterations from that expected in the absenceof human impact (reference conditions) This goal is similar tothe concept for biological integrity in the US (Stevenson et al2010) Each member state in the European Union has had toestablish methods for assessing ecological status for a range ofbiological quality elements one of which is ldquomacrophytes andphytobenthosrdquo

Despite the equal treatment of diatoms and soft-bodied (ienon-diatom) algae in the ldquosaprobic systemrdquo of Kolkwitz andMarsson (1908) diatoms have received increasing attentionin the past century due to their easy use as bioindicators (re-viewed by Stevenson et al 2010 Whitton 2013) The currentstate-of-art in algae-based river and stream bioassessment inthe EU shows that the diatoms are developed and intercali-brated as proxies for phytobenthos gradually narrowed to anapplication of a few diatom indices (Poikane 2015) The soft-bodied algae supplement either phytobentos or macrophytestream assessment systems in several states and the abundanceof the phytobentos is not evaluated (Kelly 2013 Poikane2015) The only exception is Norway whose stream bioassess-ment is based completely on soft-bodied algae (Schneiderand Lindstroslashm 2009 2011) The US national bioassessmentsare largely based on diatom community composition supple-mented by total algal biomass data and proportional abundanceof all algal taxonomic groups Ecological integrity and ecolog-ical status are holistic concepts not confined to any single tax-onomic group and require understanding of both the state of aparticular indicator group and its interaction with other organ-isms and the catchment (Kelly 2013) In theory information

gained from the entire benthic algal community can providea more comprehensive indication of environmental conditions(Kelly 2006) The broader understanding of the conditions ofthe benthic algal communities is important especially in situ-ations where different pressures have resulted in shifts in thebalance between algal taxonomic groups (Kelly 2013)

The merit of soft-bodied algae as bioindicators has beennoted by researchers which conducted small usually single-watershed bioassessment studies worldwide for instance inSpain (Fernandez-Pintildeas et al 1991 Douterelo et al 2004)Russia (Rusanov et al 2012) Canada (Vis et al 1998)Brazil (Rodrigues and Bicudo 2001) Argentina (Loez andTopaliaacuten 1997) New Zealand (Winterbourn 1990) In Asiamany countries need capacity building programs to developaquatic bioassessment techniques commonly used in EuropeUS Japan and South Korea (Goulden 2011) Currently soft-bodied algae metrics (Hill et al 2000 Griffith et al 2002Porter et al 2008 Danielson et al 2011 Potapova andCarlisle 2011) and indices based solely on soft-bodied algae(Gutowski et al 2004 Schaumburg et al 2004 Schneiderand Lindstroslashm 2009 2011 Fetscher et al 2014) have beendeveloped for large-scale stream bioassessments in Europe andthe US

However surprisingly little has been published addressingthe performance of diatoms compared to soft-bodied algae asbioindicators (Lavoie et al 2004 Kelly 2006 Kelly et al2008 Schneider et al 20122013 Stancheva et al 2013b) oron the relative strength of indices derived from a single assem-blage vs combined assemblages (Potapova and Carlisle 2011Fetscher et al 2014) Some of these studies (eg Lavoie et al2004 Kelly et al 2008 Potapova and Carlisle 2011) con-tribute to the impression that soft-bodied algae did not im-prove stressor responsiveness of diatoms alone but they werebased on taxonomy methods that allowed mainly genus-levelor coarser identifications of soft-bodied algae which may ac-count for the conclusions In contrast studies designed toexplore the full potential of soft-bodied algae demonstratedthat they enhance bioassessment power along the followinglines of consideration (1) multimetric indices based on entirealgal communities created in southern Californian streamsshowed better responsiveness to anthropogenic stress over in-dices based either on diatoms or soft-bodied algae assemblagesalone (Fetscher et al 2014) (2) the best performing soft-bodied algal index exhibited greater discriminatory power thanits diatom counterpart near the higher end of the range of an-thropogenic disturbance (Fetscher et al 2014) (3) differencesin diatom and soft-bodied algal biotic indices were detected inecosystems which are subject to changing environmental con-ditions these differences could provide indications related toecosystem stability (Schneider et al 2012) (4) diatom andsoft-bodied algal communities respond to nutrient supply andpH differently with diatom taxon richness generally increasingwith nutrient availability in contrast to decreasing soft-bodiedalgae richness (Schneider et al 2013) (5) diatoms in con-junction with soft-bodied algae provide a more robust assess-ment of nutrient conditions inferring nitrogen (N) limitation in20 more sites than monitoring with either algal group alone(Stancheva et al 2013b)

15 page 2 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

While the diatom analytical bioassessment methods arefocused on species composition and the data are easy tocalibrate large variability exists among the soft-bodied al-gae methodologies which target different parameters of al-gal community The goal of this review was to comparethe currently applied analytical methods for soft-bodied al-gae in large-scale bioassessments to discuss their consand pros efforts level and resulting contributioninput tostream water quality evaluation Better understanding of thevalue of soft-bodied algae as bioindicators and the appro-priate methods for their analysis according to the bioassess-ment goal can help an informed decision-making for waterquality management In addition algal-nutrient interactionsare discussed in the light of their bioindicator potentialExamples are included from our research experience in-corporating soft-bodied algae in stream bioassessment inCalifornia as part of the Surface Water Ambient Monitor-ing Program of the California State Water Resources Con-trol Board (SWAMP httpwwwwaterboardscagovwater_issuesprogramsswamp) (Stancheva et al 2012ab 2013ab2014 2015 Fetscher et al 2013ndash2015 Wehr et al 2013)

2 Field and laboratory bioassessmentmethods for soft-bodied algae

The less frequent use of soft-bodied algae in bioassessmentrelative to diatoms is likely due in part to challenges associ-ated with soft-algal species-level identification and quantifica-tion of specimens which have contributed to the impressionthat they are less measurable and not cost-effective (Lavoieet al 2004) The major obstacle for soft-bodied algae eval-uation consists in their naturally broad variation of thallus sizeand associated morphological diversity of vegetative and re-productive structures which are taxonomically fundamentalFor practical reasons soft-bodied algae are often separatedbased on their size to macroalgae and microalgae (Sheath andCole 1992) requiring different methodological treatment ei-ther during the sample collection or during the subsequentsample processing and species identification

The second hurdle is the stream heterogeneity (Palmer andPoff 1997) and patchy distribution of macroalgae in streams(Sheath and Cole 1992) which may cause bias for algal col-lection if quantitative random sampling is employed Luceet al (2010) showed that the highest benthic algal biomass isaccumulated in a transition refuge zone away from the thal-weg across bed-rock rivers due to geomorphic factors Manylong-living macroalgae such as Chara Cladophora Batra-chospermum Lemanea Stigeoclonium reflect water chemistryover long periods of time and are important indicators ofhighly variable nutrient levels (Whitton 2012) However themacroalgae differ in their preferences to stream physical habi-tat conditions Consequently several sampling approaches areused to overcome the heterogeneity of benthic soft-bodiedalgae distribution and to improve the macroalgal detectionLarger macroalgae such as Lemanea Chara Cladophora andVaucheria are included in macrophyte bioassessment surveysof WFD (Kelly 2013) For habitats with great spatial and tem-poral variation qualitative targeted sampling of algae is highlyrecommended option to the random quantitative sampling in

the US national surveys (Stevenson and Smol 2003) Freshqualitative samples with stream macroalgae are collected ad-ditionally to the quantitative sampling in California (Fetscheret al 2009) capturing many indicator macroalgae species(Table 1) Similar to the variety of sampling techniques nu-merous corresponding laboratory methods for algae exists Se-lecting the appropriate methodology for collecting and labora-tory processing of benthic soft-algae is a crucial first step forobtaining reliable data and meaningful bioassessment results

In this section we will discuss the methodology for stan-dardized large-scale bioassessment programs which surveythe general patterns of algal composition and biomass tempo-rally and spatially Such data can be used for water resource as-sessments in discussions of possible changes to water qualityland-use management regimes or the classification of streamsaccording to degree or type of anthropogenic impact

21 Field sampling of soft-bodied algae

Sampling design and techniques vary with monitoringneeds study dataset scale stream types targeted habitats fac-tors affecting algae distribution and budget (see for detailsStevenson and Smol 2003 Lowe and Pan 2006) Currentlythere are two main soft-bodied algae sampling approachesused in large-scale stream bioassessment programs worldwide

A semi-quantitative sampling approach for soft-bodied al-gae is employed in the EU This method has been devel-oped in Norway (Jarlman et al 1996) but become a stan-dard method in large-scale biomonitoring surveys of streamsand rivers and as part of the European Project Standard-ization of River Classifications protocol (STAR httpwwweu-staratframesethtm) in Germany (Pipp and Rott 1996) andAustria (Pfister and Pipp 2013) The method had been de-signed to evaluate algal species composition and to providesemi-quantitative estimates of species abundance on a 5-pointscale or directly as percent cover in the field In summarymacroscopic algae are surveyed along a stream bottom of ap-proximately 10 m using an aquascope to identify the percent-age of the bottom surface covered by differently appearingalgal elements which are collected and stored separately invials Microscopic algae are brushed from an area of about8 times 8 cm on the upper side of each of ten stones with diame-ters ranging between 10 and 20 cm taken from each samplingsite according to Kelly et al (1998) Semi-quantitative algalsampling allows for the separate collection of well-preservedalgal thalli which is important for species identification ofmacroalgae Three to ten replicates are collected from eachsubstratum sampled and data obtained with this method hasbeen successfully used for indicator species optima calcula-tions and development of algal indices (Rott et al 19971999Schneider and Lindstroslashm 2009 2011 Schneider et al 2013Rott and Schneider 2014) Generally the results obtained bythis approach are comparable to diatoms targeting the taxo-nomic composition and structure of soft-bodied algae com-munities The main disadvantage of this method is the lackof algal biomass estimate which may limit its application inharmful algal blooms monitoring and managing

Quantitative algal sampling is preferred technique in theUS bioassessment Two quantitative sampling approaches

15 page 3 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

While the diatom analytical bioassessment methods arefocused on species composition and the data are easy tocalibrate large variability exists among the soft-bodied al-gae methodologies which target different parameters of al-gal community The goal of this review was to comparethe currently applied analytical methods for soft-bodied al-gae in large-scale bioassessments to discuss their consand pros efforts level and resulting contributioninput tostream water quality evaluation Better understanding of thevalue of soft-bodied algae as bioindicators and the appro-priate methods for their analysis according to the bioassess-ment goal can help an informed decision-making for waterquality management In addition algal-nutrient interactionsare discussed in the light of their bioindicator potentialExamples are included from our research experience in-corporating soft-bodied algae in stream bioassessment inCalifornia as part of the Surface Water Ambient Monitor-ing Program of the California State Water Resources Con-trol Board (SWAMP httpwwwwaterboardscagovwater_issuesprogramsswamp) (Stancheva et al 2012ab 2013ab2014 2015 Fetscher et al 2013ndash2015 Wehr et al 2013)

2 Field and laboratory bioassessmentmethods for soft-bodied algae

The less frequent use of soft-bodied algae in bioassessmentrelative to diatoms is likely due in part to challenges associ-ated with soft-algal species-level identification and quantifica-tion of specimens which have contributed to the impressionthat they are less measurable and not cost-effective (Lavoieet al 2004) The major obstacle for soft-bodied algae eval-uation consists in their naturally broad variation of thallus sizeand associated morphological diversity of vegetative and re-productive structures which are taxonomically fundamentalFor practical reasons soft-bodied algae are often separatedbased on their size to macroalgae and microalgae (Sheath andCole 1992) requiring different methodological treatment ei-ther during the sample collection or during the subsequentsample processing and species identification

The second hurdle is the stream heterogeneity (Palmer andPoff 1997) and patchy distribution of macroalgae in streams(Sheath and Cole 1992) which may cause bias for algal col-lection if quantitative random sampling is employed Luceet al (2010) showed that the highest benthic algal biomass isaccumulated in a transition refuge zone away from the thal-weg across bed-rock rivers due to geomorphic factors Manylong-living macroalgae such as Chara Cladophora Batra-chospermum Lemanea Stigeoclonium reflect water chemistryover long periods of time and are important indicators ofhighly variable nutrient levels (Whitton 2012) However themacroalgae differ in their preferences to stream physical habi-tat conditions Consequently several sampling approaches areused to overcome the heterogeneity of benthic soft-bodiedalgae distribution and to improve the macroalgal detectionLarger macroalgae such as Lemanea Chara Cladophora andVaucheria are included in macrophyte bioassessment surveysof WFD (Kelly 2013) For habitats with great spatial and tem-poral variation qualitative targeted sampling of algae is highlyrecommended option to the random quantitative sampling in

the US national surveys (Stevenson and Smol 2003) Freshqualitative samples with stream macroalgae are collected ad-ditionally to the quantitative sampling in California (Fetscheret al 2009) capturing many indicator macroalgae species(Table 1) Similar to the variety of sampling techniques nu-merous corresponding laboratory methods for algae exists Se-lecting the appropriate methodology for collecting and labora-tory processing of benthic soft-algae is a crucial first step forobtaining reliable data and meaningful bioassessment results

In this section we will discuss the methodology for stan-dardized large-scale bioassessment programs which surveythe general patterns of algal composition and biomass tempo-rally and spatially Such data can be used for water resource as-sessments in discussions of possible changes to water qualityland-use management regimes or the classification of streamsaccording to degree or type of anthropogenic impact

21 Field sampling of soft-bodied algae

Sampling design and techniques vary with monitoringneeds study dataset scale stream types targeted habitats fac-tors affecting algae distribution and budget (see for detailsStevenson and Smol 2003 Lowe and Pan 2006) Currentlythere are two main soft-bodied algae sampling approachesused in large-scale stream bioassessment programs worldwide

A semi-quantitative sampling approach for soft-bodied al-gae is employed in the EU This method has been devel-oped in Norway (Jarlman et al 1996) but become a stan-dard method in large-scale biomonitoring surveys of streamsand rivers and as part of the European Project Standard-ization of River Classifications protocol (STAR httpwwweu-staratframesethtm) in Germany (Pipp and Rott 1996) andAustria (Pfister and Pipp 2013) The method had been de-signed to evaluate algal species composition and to providesemi-quantitative estimates of species abundance on a 5-pointscale or directly as percent cover in the field In summarymacroscopic algae are surveyed along a stream bottom of ap-proximately 10 m using an aquascope to identify the percent-age of the bottom surface covered by differently appearingalgal elements which are collected and stored separately invials Microscopic algae are brushed from an area of about8 times 8 cm on the upper side of each of ten stones with diame-ters ranging between 10 and 20 cm taken from each samplingsite according to Kelly et al (1998) Semi-quantitative algalsampling allows for the separate collection of well-preservedalgal thalli which is important for species identification ofmacroalgae Three to ten replicates are collected from eachsubstratum sampled and data obtained with this method hasbeen successfully used for indicator species optima calcula-tions and development of algal indices (Rott et al 19971999Schneider and Lindstroslashm 2009 2011 Schneider et al 2013Rott and Schneider 2014) Generally the results obtained bythis approach are comparable to diatoms targeting the taxo-nomic composition and structure of soft-bodied algae com-munities The main disadvantage of this method is the lackof algal biomass estimate which may limit its application inharmful algal blooms monitoring and managing

Quantitative algal sampling is preferred technique in theUS bioassessment Two quantitative sampling approaches

15 page 3 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

Table 1 Macroalgal indicator species and non-reproducing ldquomorphospeciesrdquo evaluated using indicator species analysis for stream bioassess-ment in California which require qualitative sampling and large amount of material for species identification Indicator classes are definedfor total dissolved phosphorus (TP low lt10 microgmiddotLminus1 high gt100 microgmiddotLminus1) total dissolved nitrogen (TN low lt02 mgmiddotLminus1 high gt3 mgmiddotLminus1) dis-solved organic carbon (DOC low lt16 mgmiddotLminus1 high gt83 mgmiddotLminus1) dissolved copper (Cu low lt03 microgmiddotLminus1 high gt17 microgmiddotLminus1) and ldquoreferencerdquoconditions (algal taxa selected from Fetscher et al 2014)

Taxon Indicator class

TP TN DOC Cu ldquoReferencerdquo

Calothrix fusca (Kuumltz) Bornet and Flahault low

Calothrix parietina (Naumlgeli) Thuret ref

Cladophora glomerata (L) Kuumltz high high high high non-ref

Mougeotia calcarea (Cleve) Wittr low

Mougeotia sp 1 (d 9ndash15 microm) low

Mougeotia sp 2 (d 22ndash30 microm) low

Mougeotia sp 3 (d 18ndash22 microm) low ref

Nostoc verrucosum Vaucher ex Bornet and Flahault low low ref

Nostochopsis lobatus HCWood em Geitler low

Oedogonium sp 1 (d 35ndash45 microm) high non-ref

Oedogonium sp 3 (d 10ndash16 microm) non-ref

Oedogonium sp 5 (d 4ndash6 microm) high

Paralemanea catenata (Kuumltz) M LVis and Sheath low

Rhizoclonium hieroglyphicum (C Agardh) Kuumltz high high high non-ref

Rivularia minutula (Kuumltz) Bornet et Flahault low

Sheathia involuta (Vis and Sheath) Salomaki and Vis low

Spirogyra borgeana Transeau low

Spirogyra majuscula Kuumltz low

Spirogyra varians (Hassall) Kuumltz low

Spirogyra weberi Kuumltz low

Spirogyra sp 1 (d 33ndash40 microm plane w 1 chl) low

Spirogyra sp 2 (d 25ndash32 microm plane w 1 chl) low

Spirogyra sp 4 (d 60ndash105 microm plane w 5ndash8 chl) high

Spirogyra sp 12 (d 110ndash145 microm plane w 5ndash8 chl) high

Tolypothrix distorta Kuumltz ex Bornet and Flahault low ref

Ulothrix zonata (Weber and Mohr) Kuumltz low ref

Ulva flexuosa Wulfen high non-ref

Zygnema sterile Transeau low

Zygnema sp 1 (d 26ndash31 microm) low

Abbreviations d ndash filament diameter w ndash transverse wall chl ndash chloroplast ref ndash ldquoreferencerdquo

are applied in the US national stream bioassessments(1) multihabitat sampling used by the EnvironmentalProtection Agencys (USEPA) Environmental Monitoringand Assessment Program (EMAP httpwwwepagovemapprotocols by Lazorchak et al 1998 2000 Stevensonand Bahls 1999) and the National Rivers and StreamsAssessment program (NRSA httpwaterepagovtyperslmonitoringriverssurvey USEPA 2007 protocol) and (2) sin-gle targeted-habitat sampling used by the United States Geo-logical Surveys (USGS) National Water-Quality AssessmentProgram (NAWQA httpwaterusgsgovnawqa protocol byAcker 2002 Moulton et al 2002) Modification of the mul-tihabitat quantitative sampling of algae is also adopted by theSWAMP program in California (Fetscher et al 2009) Ben-thic soft-bodied algae are collected at 11 objectively selected

locations spaced evenly across a 150 m or 250 m long streamreach (depending upon whether the average wetted width ofthe stream is less or greater than 10 m) The sampling lo-cations alternate between the points defined at 25 50and 75 of the wetted width in high-gradient systems andat ldquomargin-center-marginrdquo positions in low-gradient systemsWithin each reach samples are obtained from whatever sub-strata (eg cobble siltsand gravel bedrock wood concrete)are present at a single location across each of the 11 tran-sects and combined into a well-mixed composite sample fromwhich four aliquots are drawn for analysis of soft-bodied al-gae diatoms chlorophyll aand ash-free dry mass (Fetscheret al 2009) The total surface area sampled for each streamreach is recorded and typically does not exceed 150 cm2 Themodification of the method in California consists of collecting

15 page 4 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

of additional qualitative fresh sample containing all visiblemacroalgae within the stream reach (Fetscher et al 2009)This sample compensates the possible bias of the randomquantitative algae sampling and allows for additional informa-tion such as reproductive structure observation and moleculardata collection

Multihabitat quantitative sampling is a cost-effectivemethod which provides consistent and repeatable samplingof algae in conjunction with diatoms macroinvertebrates andphysical habitat (Hughes and Peck 2008) A similar multi-habitat sampling technique is employed in the stream biomon-itoring in the New Zealand with consideration that it enablestesting for statistical significance of differences among sitesand for diagnosis of impacts (Biggs and Kilroy 2000) Accord-ing to Stevenson and Bahls (1999) this method best character-izes the benthic algae in the stream reach However our expe-rience showed that the objectively selected sampling locationsare not always representative for the entire algal diversity in thesurveyed stream reach and many macroalgal taxa are recordedonly qualitatively possibly collected from the marginal transi-tion refuge zones (Hughes and Peck 2008 Luce et al 2010)

The quantitative algal sampling may target a single-sampling habitat (Moulton et al 2002) Algal samples are col-lected across five transects from richest targeted habitat wheremaximum taxa richness is likely to be observed along a 150to 300 m stream reach A single habitat type is sampled acrossall monitored streams for a comparability of results as habi-tat selection is based on the following priority (1) epilithichabitat ndash riffles in shallow streams with coarse-grained sub-strates (2) epidendric habitat ndash woody snags in streams withfine-grained substrates and (3) epiphytic habitat ndash macrophytebeds in streams where riffles and woody snags are absentThe sampled substratum area is recorded Additional quanti-tative samples are collected from depositional-targeted habi-tats and qualitative multihabitat algal samples are electiveShorter lengths of stream reaches may be sampled for singlehabitat samples because the chosen single habitat (eg rif-fles) is usually common within the study streams (Stevensonand Bahls 1999) Species composition of assemblages froma single microhabitat is expected to reflect water quality dif-ferences among streams more precisely than multihabitat sam-pling but impacts in other habitats in the reach may be missed(Stevenson and Bahls 1999) A modification of the singletargeted-habitat method is implemented in algal bioassessmentby the Ontario Ministry of the Environment (2011) and is pre-ferred in small-scale studies when biomass of benthic algaeis assessed (eg OlsquoBrien and Wehr 2010) or species com-position associations with environmental variables is explored(Brown et al 2008 Rusanov et al 2012)

All quantitative sampling protocols include replicate sam-pling of a subset of 10 of sites in order to register the errorvariation associated with random sampling in large surveys asa measure of the precision of assessment at all sites

22 Taxonomic analysis and quantificationof soft-bodied algae

Once the preserved and fresh algal samples arrive in thelaboratory their analysis has two objectives The first objec-

tive is to adequately characterize the species composition ofthe algal community which sets the scope for interpretationand evaluation in any resource or pollution monitoring inves-tigation (Biggs and Kilroy 2000) The second objective is toquantify the algal community which is the basis of statisti-cally valid data interpretation calculation of diversity indicesoptima and tolerances for indicator species (after ter Braakand van Dam 1989 Dufrecircne and Legendre 1997) and algalbiomass Algal quantification can be either absolute by obtain-ing species-specific cell densities or biovolumes or based onrelative abundance of taxa The soft-bodied algal identificationprocess which requires detailed observation of all taxonomi-cally relevant morphological features might interfere with bio-volume quantification of algal taxa and as a result differenttaxonomic approaches exist with emphasis on either objective

The European standard semi-quantitative method (Jarlmanet al 1996) is best suited for taxonomic identification of al-gae but does not yield an estimate of algal biovolume withinthe stream reach Macroalgae are identified from many sep-arately collected samples and often fresh samples are avail-able Dissecting and compound light microscopes are usedfor sorting the material and species identifications are donein counting chambers or microscope slides Percent cover foreach macroalgal species measured in the field is converted toa 5-point scale or is used directly Relative abundance of mi-croalgae is estimated on the same scale from additionally col-lected samples excluding diatoms

In contrast laboratory procedures which follow quanti-tative algal sampling in the US prioritize the objective toprecisely estimate the density or biovolume of benthic al-gae by counting algal cells in a known number of micro-scopic fields in a subsample of known volume (Stevensonand Bahls 1999 Biggs and Kilroy 2000 Acker 2002) Thecomposite algal sample is blended mechanically to break uplarge filaments and colonies and the small mixed subsam-ple is suspended in Palmer-Maloney counting chambers forspecies identification and biovolume estimates A quantity of300 algal ldquocell unitsrdquo or ldquonatural counting unitsrdquo includingthe ldquolivingrdquo diatoms with intact chloroplasts (Stevenson andBahls 1999 Biggs and Kilroy 2000 Acker 2002) are iden-tified and counted In this way often more than 50 of theestimated total algal biovolume is attributed to living diatoms(Potapova and Charles 2005) which limits soft-bodied al-gal analysis due to the low number of specimens observedMore current laboratory methods associated with multihabi-tat quantitative sampling improves the macroalgal treatmentby its separate evaluation in Sedwick-Rafter chamber and ex-tends microalgal counts to 300 soft-bodied algal entities af-ter initial blending of the sample (USEPA 2008) Accordingto Biggs (1987) and Biggs and Kilroy (2000) thorough sam-ple blending minimizes subsampling error without damagingthalli In contrast we argue that this sample processing maylower the resolution of taxonomic analysis especially in re-gards to macroalgal component characterized by high diver-sity of vegetative and reproductive morphology which needto be observed during the identification process (review byStancheva et al 2012a) Simultaneous analysis of diatoms andsoft-bodied algae provides valuable quantitative informationfor biovolume proportions among taxonomic groups which is

15 page 5 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

important in determination of potential shift in dominant al-gal groups However only diatoms are subject to further de-tailed taxonomic evaluation by specific methods (Stevensonand Bahls 1999 Acker 2002) while soft-bodied algae com-position remains underinvestigated

The best approach to obtain detailed taxonomic datafor soft-bodied algal community from preserved quantitativecomposite samples is a separate processing of macroalgaland microalgal fractions preferably by analyzing abundantmacroalgal material in conjunction with observing reproduc-tive morphology from fresh samples A novel quantificationmethod for stream soft-bodied algae collected by multihabi-tat quantitative sampling for the SWAMP program in Califor-nia was developed in an attempt to increase taxonomic resolu-tion of the data and to produce precise biovolume information(Stancheva et al 2012a 2015) Sample blending is avoided bygentle removal of macroalgae which preserves their integrityThen macroalgae are processed separately in a gridded petridish and identified microscopically Microalgae excluding di-atoms are counted on microscope slides with a single layer ofcells for a better observation of morphological features Quali-tative analysis of additional fresh samples is an important stepfor identifying macroalgae because large amount of algal ma-terial is observed including reproductive structures Fresh sam-ples allow isolation culturing and molecular studies on speciesof interest such as taxonomically problematic genera (egZygnema and Spirogyra (Stancheva et al 2012c 2013a) raresensitive and potentially endemic species (Wehr et al 2013)or nuisance algae and harmful cyanobacteria (Fetscher et al2015) This methodology although time-consuming enhancesthe power of water-quality assessments by better knowledge oflocal algal flora (Porter et al 2008)

According to Stevenson et al (1996) quantitative meth-ods for algae estimate accurately assesses algal biomassand taxonomic shifts but is time-consuming and mayhave high error variances Quality assurance techniquesregister the error variance of laboratory sample process-ing and algae identification by requiring that 10 of thesamples are counted by two taxonomists for large-scalebioassessment projects Consistency in taxonomic identifica-tions within a laboratory and in a program is very impor-tant and is maintained by development of online identifica-tion tools which illustrate soft-bodied algal flora recordedfrom the sampling area of the project such as Gutowskiand Foerster (2009) Benthische Algen ohne Diatomeenund Characeen (httpwwwlanuvnrwdeveroeffentlichungenarbeitsblattarbla9arbla9starthtm) Stancheva et al (2014)Soft-Bodied Stream Algae of California (httpdbmusebladecoloradoeduDiatomTwosbsac_siteindexphp) ANSP AlgaeImage Database from the Phycology Section Patrick Centerfor Environmental Research Academy of Natural Sciences(httpdiatomacnatsciorgAlgaeImage)

3 Approaches to apply soft-bodied algaeas bioindicators

The oldest approach to stream bioassessment is based onan indicator species concept where known environmental tol-

erances of algal species are used to evaluate the water qual-ity Tolerances of algal species to environmental variables aredetermined by a non-quantitative ranking of the water qual-ity characteristics of habitats in which taxa have been re-ported in extensive literature sources For example Palmer(1969) ranked algal species genera and phyla according theirtolerance to high organic pollution VanLandingham (1982)provided autecological data for 161 cyanobacterial speciesin eight categories or ldquospectrardquo (eg pH saprobien nutrienthalobion temperature general and specific habitat and sea-sonality) Schmedtje et al (1998) classified 138 soft-bodiedbenthic algal taxa in regards to trophic state

The concept of ldquosaprobien systemrdquo (Sladecek 1973) andthe weighted average equation of Zelinka and Marvan (1961)are a cornerstone for the development of biotic indices to as-sess a single stressor that are largely used in WFD of the EU(see for review Kelly 2013 Poikane et al 2014) but notadopted in the US large-scale bioassessment Soft-bodied al-gal biotic indices are derived from a semi-quantitative dataset with fine taxonomic resolution and relative quantificationof the taxa In contrast multimetric indices of biotic integritywhich include several structural and functional measures ofalgal communities assess the overall ecological condition areused in the US (Doleacutedec and Statzner 2010) Soft-bodied al-gal metrics for multimetric indices of biotic integrity are con-structed from a quantitative data set with absolute biovolumequantification of the taxa but with variable taxonomic resolu-tion due to the differences among the laboratory methods

In this section we present both types of bioassessment in-dices in more detail because they are the final step in thestream bioassessment and highly depend on the quality of thedata obtained by the methods outlined in the preceding section

31 Biotic indices (BI)

Rott et al (1997 1999) developed the first weighted av-erage BIs for assessment of saprobic and trophic status ofstreams and rivers in Austria based on algae from all taxo-nomic groups The index utilises numerical data from morethan 1100 stream sites in Austria combined with informationfrom the literature with special attention to results relevant tothe situations in Austrian running waters (Rott et al 1999)These numerical models used species indicator values (relatedto species optima) ranging from 0 to 5 as predictors of waterquality parameters Lists with more than 500 soft-bodied algaespecies with species specific saprobic or trophic values (totalphosphorus (TP) nitrate (NO3) andor ammonium (NH4) con-centration as proxy for nutrients) and indicator weight weredeveloped (Rott et al 19971999) To calculate the indices fora sampling site the species relevant indicator value and weightare used weighted additionally by the frequency informationfrom the microscopic analysis (Sladecek 1973 Rott et al1997 1999) although the calculation procedure allows for theuse of presence-absence data for the whole algal community(Rott et al 1997) In this way ecological status of streams andrivers is evaluated according to five classes (high good mod-erate poor bad) based on three saprobic and five trophic con-dition classes (Rott et al 1997 1999 Pfister and Pipp 2013)Potapova et al (2004) noted that the underlying assumption of

15 page 6 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

important in determination of potential shift in dominant al-gal groups However only diatoms are subject to further de-tailed taxonomic evaluation by specific methods (Stevensonand Bahls 1999 Acker 2002) while soft-bodied algae com-position remains underinvestigated

The best approach to obtain detailed taxonomic datafor soft-bodied algal community from preserved quantitativecomposite samples is a separate processing of macroalgaland microalgal fractions preferably by analyzing abundantmacroalgal material in conjunction with observing reproduc-tive morphology from fresh samples A novel quantificationmethod for stream soft-bodied algae collected by multihabi-tat quantitative sampling for the SWAMP program in Califor-nia was developed in an attempt to increase taxonomic resolu-tion of the data and to produce precise biovolume information(Stancheva et al 2012a 2015) Sample blending is avoided bygentle removal of macroalgae which preserves their integrityThen macroalgae are processed separately in a gridded petridish and identified microscopically Microalgae excluding di-atoms are counted on microscope slides with a single layer ofcells for a better observation of morphological features Quali-tative analysis of additional fresh samples is an important stepfor identifying macroalgae because large amount of algal ma-terial is observed including reproductive structures Fresh sam-ples allow isolation culturing and molecular studies on speciesof interest such as taxonomically problematic genera (egZygnema and Spirogyra (Stancheva et al 2012c 2013a) raresensitive and potentially endemic species (Wehr et al 2013)or nuisance algae and harmful cyanobacteria (Fetscher et al2015) This methodology although time-consuming enhancesthe power of water-quality assessments by better knowledge oflocal algal flora (Porter et al 2008)

According to Stevenson et al (1996) quantitative meth-ods for algae estimate accurately assesses algal biomassand taxonomic shifts but is time-consuming and mayhave high error variances Quality assurance techniquesregister the error variance of laboratory sample process-ing and algae identification by requiring that 10 of thesamples are counted by two taxonomists for large-scalebioassessment projects Consistency in taxonomic identifica-tions within a laboratory and in a program is very impor-tant and is maintained by development of online identifica-tion tools which illustrate soft-bodied algal flora recordedfrom the sampling area of the project such as Gutowskiand Foerster (2009) Benthische Algen ohne Diatomeenund Characeen (httpwwwlanuvnrwdeveroeffentlichungenarbeitsblattarbla9arbla9starthtm) Stancheva et al (2014)Soft-Bodied Stream Algae of California (httpdbmusebladecoloradoeduDiatomTwosbsac_siteindexphp) ANSP AlgaeImage Database from the Phycology Section Patrick Centerfor Environmental Research Academy of Natural Sciences(httpdiatomacnatsciorgAlgaeImage)

3 Approaches to apply soft-bodied algaeas bioindicators

The oldest approach to stream bioassessment is based onan indicator species concept where known environmental tol-

erances of algal species are used to evaluate the water qual-ity Tolerances of algal species to environmental variables aredetermined by a non-quantitative ranking of the water qual-ity characteristics of habitats in which taxa have been re-ported in extensive literature sources For example Palmer(1969) ranked algal species genera and phyla according theirtolerance to high organic pollution VanLandingham (1982)provided autecological data for 161 cyanobacterial speciesin eight categories or ldquospectrardquo (eg pH saprobien nutrienthalobion temperature general and specific habitat and sea-sonality) Schmedtje et al (1998) classified 138 soft-bodiedbenthic algal taxa in regards to trophic state

The concept of ldquosaprobien systemrdquo (Sladecek 1973) andthe weighted average equation of Zelinka and Marvan (1961)are a cornerstone for the development of biotic indices to as-sess a single stressor that are largely used in WFD of the EU(see for review Kelly 2013 Poikane et al 2014) but notadopted in the US large-scale bioassessment Soft-bodied al-gal biotic indices are derived from a semi-quantitative dataset with fine taxonomic resolution and relative quantificationof the taxa In contrast multimetric indices of biotic integritywhich include several structural and functional measures ofalgal communities assess the overall ecological condition areused in the US (Doleacutedec and Statzner 2010) Soft-bodied al-gal metrics for multimetric indices of biotic integrity are con-structed from a quantitative data set with absolute biovolumequantification of the taxa but with variable taxonomic resolu-tion due to the differences among the laboratory methods

In this section we present both types of bioassessment in-dices in more detail because they are the final step in thestream bioassessment and highly depend on the quality of thedata obtained by the methods outlined in the preceding section

31 Biotic indices (BI)

Rott et al (1997 1999) developed the first weighted av-erage BIs for assessment of saprobic and trophic status ofstreams and rivers in Austria based on algae from all taxo-nomic groups The index utilises numerical data from morethan 1100 stream sites in Austria combined with informationfrom the literature with special attention to results relevant tothe situations in Austrian running waters (Rott et al 1999)These numerical models used species indicator values (relatedto species optima) ranging from 0 to 5 as predictors of waterquality parameters Lists with more than 500 soft-bodied algaespecies with species specific saprobic or trophic values (totalphosphorus (TP) nitrate (NO3) andor ammonium (NH4) con-centration as proxy for nutrients) and indicator weight weredeveloped (Rott et al 19971999) To calculate the indices fora sampling site the species relevant indicator value and weightare used weighted additionally by the frequency informationfrom the microscopic analysis (Sladecek 1973 Rott et al1997 1999) although the calculation procedure allows for theuse of presence-absence data for the whole algal community(Rott et al 1997) In this way ecological status of streams andrivers is evaluated according to five classes (high good mod-erate poor bad) based on three saprobic and five trophic con-dition classes (Rott et al 1997 1999 Pfister and Pipp 2013)Potapova et al (2004) noted that the underlying assumption of

15 page 6 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

inference indices based on the weighted averaging of speciesindicator values is that the shapes of species response curvesalong the environmental gradient are unimodal and symmet-rical However Sladecek (1973) and Rott et al (1997) havealso recognized that algal species do not necessarily followunimodal or symmetrical environmental distribution patternsand have estimated the relative probability of species occur-rence across several saprobic zones Nevertheless to simplifythe calculation and representation of results they based theirindices on a single indicator value for each species (Potapovaet al 2004) These indices include all taxonomic groups butevaluation based only on diatoms although possible has lowerpredictive power (Rott et al 1999) Using a similar approacha long list with diatoms and soft-bodied algae characteristicsfor reference conditions in different bioregions in Austria hadbeen developed (Pfister and Pipp 2013) in order to assessdeviations of trophic and saprobic states from the respectivebioregion-specific reference conditions

Both saprobic and trophic indices of Rott et al (19971999) are successfully used in the stream ecological classi-fication in Germany but they are not applicable in Norwaybecause many local benthic algae are not available in the indi-cator lists (Schneider and Lindstroslashm 2011) One explanationfor this variation is the predominance of soft waters in Norwayand hard waters in central Europe but in Scandinavia otherfactors are probably also important such as that much of theP may be organic especially where water drains from peat-lands (Whitton 2013) Furthermore the species optima andtolerances for pH conductivity TP and NO3 of common soft-bodied algal species in Norway and Austria are significantlydifferent with generally higher values for Austria (Rott andSchneider 2014)

Consequently Schneider and Lindstroslashm (2011) developednew periphyton index of trophic status (PIT) for Norway de-rived from 556 samples (over 350 river sites) and indicatorvalues for nutrient optima for 153 soft-bodied algal speciesconsidering TP as a proxy for trophic status A long historyof acidification impairment of surface waters in Scandinaviacaused by sulfur and nitrogen emissions established soft-bodied algae as early warning indicators in regular monitor-ing programs in Norway (Knutzen et al 1980) Schneiderand Lindstroslashm (2009) created the acidification index periphy-ton (AIP) for Norway based on 608 samples (318 river sites)and indicator values for pH-optima for 108 soft-bodied algaspecies are calculated ranging from pH 513 to 750 The dataobtained between 1976 and 2010 in Norway are used for thedevelopment and testing of the new soft-bodied algae indices(Lindstroslashm et al 2004 Schneider and Lindstroslashm 20092011Schneider 2011 Schneider et al 2013)

Taxa optima for both of these indices are calculated frompresence-absence datasets by averaging pH and log10-transformed TP at the sites where particular taxa occur This methodis a modification for qualitative datasets of the weightedaveraging method (ter Braak and van Dam 1989) whichis considered a practical and robust approach for quantify-ing species responses to environmental parameters (Ponaderet al 2007) Authors initially calculated weighted optimaincluding species relative abundance estimated on a 5-pointscale or as a percent bottom cover but concluded that semi-

quantitative data provided no better fit with TP concentrationthan presence-absence data (Schneider and Lindstroslashm 2011)The difference between a weighted averaging inference modeland the indices mentioned above is essentially the numericalscale on which species indicator values are expressed and esti-mations are made In inference models species optima are ab-solute values of the parameter that is estimated in contrast totheir expression on a convenient scale ranging in value from 0to 5 (Potapova et al 2004) The final values of the AIP andPIT indices are absolute values since they are calculated as asum of the indicator values of all indicator species recorded ina given sample divided by the number of indicator species

Regardless of the fact that the statistical power of weightedaveraging might be lowered by the presence-absence data setSchneider et al (2013) demonstrated that both soft-bodied in-dices (AIP and PIT) are significantly correlated to five diatom-based indices for pH trophic and pollution states widely usedin Europe and to corresponding environmental parameters (pHand TP) tested in 52 rivers in Norway These studies suggestthat indices based on the presence or absence of soft-bodiedalgae are excellent for broad surveys involving a large num-ber of sites (Whitton 2013) Furthermore Schneider and Lind-stroslashm (2011) provided evidence that use of ldquomorphospeciesrdquocategories for some filamentous genera which require repro-ductive structures for species identification (ie MougeotiaSpirogyra Zygnema and Oedogonium) although of poor tax-onomic value (Drummond et al 2005) might be useful andpractical eutrophication indicators Finally soft-algal indica-tor lists of Schneider and Lindstroslashm (20092011) demonstratethe importance of species-level identification because only ina few algal genera do all species have similar optima in respectto TP (eg desmids Gongrosira Draparnaldia) UnivariateBIs infer individual stressor conditions but indices inferringnutrients and pH should be particularly useful because theseenvironmental constituents are highly variable due to weatherand diurnal variation of metabolic processes (Stevenson et al2010 Whitton 2013) According to Stevenson (2010) nutri-ent and pH BIs can be used to refine stressor-response rela-tionships to resolve threshold levels and to establish criteriafor stressors Schneider and Lindstroslashm (2011) reported a ma-jor threshold of 10 microgmiddotLminus1 TP for the relationship between PITand TP concentrations

If the soft-bodied algal weighted average IBs are usedin isolation only three stressors can be evaluated (eg or-ganic pollution nutrient load pH) among multiple potentialstressors and natural causes of community variation (Cairnsand Pratt 1993) This problem could be overcome by indicesbased on the actual species expected in a particular stream site(Kelly 2013) A good example is the approach developed inGermany Based on results from multivariate and univariateanalysis of the local algal flora and environmental variables232 soft-bodied algal species are classified into four assess-ment categories according to their sensitivity to trophy sapro-bity and contaminants in conjunction with to their distributionpattern among variable geomorphology (Foerster et al 2004Gutowski et al 2004 and Schaumburg et al 2004 2012)This method can avoid the problems with single-stressor IBswhich can not detect taxonomic change due to other factorsthan those for which the index has been calibrated but requires

15 page 7 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

good understanding of algal communities from different geo-graphic areas and water types

32 Multimetric indices of biotic integrity (IBI)

Several diatom IBIs have been developed in the pastdecade and serve as a main tool together with macroinver-tebrate IBIs in stream bioassessment programs in the UnitedStates Similarly the requirements of the European WFD foran integrative assessment of ecological condition of streamsand rivers are frequently achieved through diatom multimet-ric indices one of which includes algal biomass (chloro-phyll a) as community metric (Delgardo et al 2010) Reg-ulatory methodology for development and application of thisbioassessment tool are suggested (Hering et al 2006) Thestandard approach in the construction of diatom IBIs are out-lined by Stevenson et al (2010) and literature cited thereinThe most critical step in any IBI development is the selectionof the metrics ndash the ultimate goal is to choose metrics that rep-resent as many levels of ecological organization as possiblefollowing the original concept of Karr (1981) The soft-bodiedalgal community attributes that have been used to assess eco-logical conditions in streams are both structural and functionalthe latter together with chlorophyll a and ash-free dry massmeasurements are representative for the entire benthic commu-nity including diatoms bacteria and fungi (Stevenson et al2010) Structural taxonomic characteristics of soft-bodied al-gal communities indicator species and indicator guilds whichcombine a subset taxa with similar physiologies and ecosystemfunction are most often applied as biotic indices and as metricsin multimetric indices (Table 2) The value of IBIs is that theytend to be more linear than univariate BIs (Fore et al 1994)and help to provide a summary index which simplifies com-munication of results by a convenient scoring scale eg 0 to100 (Stevenson et al 2010) However the meaning of IBIs hasbeen questioned in regards to predictability diagnostic powerlack of reason for high or low index values the validity of sum-ming heterogeneous metrics into a single measure of streamcondition blurring effects on one metric by effects on othermetrics etc (see review by Doleacutedec and Statzner 2010)

The exploration of soft-bodied algae community character-istics as supplemental metrics in diatom IBIs began with workby Hill et al (2000 2003) which include non-taxonomic andfunctional measures of entire benthic algal communities iechlorophyll a ash-free dry mass and alkaline phosphatase ac-tivity in two studies of streams in the eastern US (as part ofEMAP) each comprised of nearly 300 samples In additiontwo taxonomic metrics containing soft-bodied algae (relativeabundance of cyanobacteria and relative genera richness) wereevaluated (Hill et al 2000) Despite the noted relationship be-tween both taxonomic metrics and some environmental vari-ables they were not responsive to water-quality constituents(Hill et al 2000)

Porter (2008) and Porter et al (2008) tested the efficacyof algal-community metrics calculated from 976 stream andriver samples collected across the United States (as part ofNAWQA) and their national and regional relations with waterchemistry Several metrics showed one or more significant cor-relations to nutrient and suspended-sediment concentrations

including soft-bodied algal species richness and relative abun-dance of eutrophic sestonic and motile algae determined fromliterature sources A promising metric of trophic condition isthe relative abundance of N2-fixing heterocystous cyanobac-teria combined with diatoms containing cyanobacterial en-dosymbionts Epithemia Rhopalodia and Denticula whichshowed a negative correlation with N concentration (Porteret al 2008) However the presence of endosymbionts inDenticula has not been confirmed for North American species(Lowe 2003)

The current development of soft-bodied algal metrics con-sists of empirical evaluation of indicator species from studieddata sets in contrast to autecological guild metrics based onliterature data from distant geographical locations Danielsonet al (2011) in a survey of 193 wadeable streams in Maineused the weighted-average approach to compute species op-tima for watershed disturbances (eg TP total nitrogen (TN)conductivity land use that is no longer forest or wetland)and to categorize the algal species based on their sensitiv-ity and tolerance to disturbance Optima for 41 soft-bodiedalgal taxa are calculated separately from diatoms based onlog10-transformed density to avoid distortion of relative abun-dances by large densities of cyanobacteria In this way au-thors distinguished many sensitive algal taxa (such as speciesbelonging to Audouinella Batrachospermum Calothrix Toly-pothrix Mougeotia Zygnema Ulothrix) but failed to deter-mine disturbance tolerant soft-bodied algal species Howevermetrics using proportion sensitive algal species including di-atoms and those based on soft-bodied algae alone showed sig-nificant correlation with developed land cover in contrastto biomass and some taxonomic metrics (such as total speciesrichness richness and relative abundance of green algae redalgae and cyanobacteria) which were not correlated with an-thropogenic stressors (Table 2)

Potapova and Carlisle (2011) developed diatom IBIs forover 1000 NAWQA Program sites in five geographical regionsacross conterminous US They used Indicator species analy-sis (Dufrecircne and Legendre 1997) to identify diatom and soft-bodied algal species associated with reference and disturbedsites which are a priory classified based on watershed dis-turbance As result only 34 soft-bodied algal taxa (or mor-phological groups) were determined to be possible indicatorsof reference or disturbed sites and their inclusion as metricdid not improve the classification accuracy of diatoms IBIsPotapova and Carlisle (2011) attributed the poor performanceof soft-bodied algal metrics to the taxonomic method whichprecludes from species level identification and recommendeddevelopment of new methods that better characterize the soft-bodied algal communities

Fetscher et al (2014) constructed the first IBIs based onsoft-bodied algae alone derived from more than 451 streamsamples collected predominantly in southern California(SWAMP modified field method by Fetscher et al 2009and novel taxonomic method by Stancheva et al 2012a)Soft-bodied algal metrics were taxonomic ndash algal phyla in-dicator species and indicator guilds and were expressed intwo ways proportion of total biovolume (relative biovolume)and proportion of total species number (relative species rich-ness) Indicator species had been evaluated empirically from

15 page 8 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

Table 2 Structural and functional attributes of the stream benthic soft-bodied algae community used as metrics in IBIs and reported rela-tionships with environmental variables Positive relationships are in regular font negative relationships are italicized () indicates that metricis calculated as proportion from the entire assemblage including ldquolivingrdquo diatom cells ldquoAlgaerdquo refers to entire algal assemblage includingdiatoms ldquoSBArdquo refers to soft-bodied (non-diatom) algae only

Soft-bodied algal IBI metric relationship Referencescommunity attribute with environmental variables

Biomass categoryTotal biovolume a mTotal biovolume NO2 + NOe

3 TSSe a eCell density aCell density TSSe e fAsh-free dry mass (AFDM) urban and suburban landc sand and fine sedimentsc

TSSc canopyd sloped Cld SOd4 TNd

a c d j o

Chlorophyll a(Chl a) urban and suburban landc colorc Fec canopyd Cld can-nel widthd riparian disturbanced

a c d f k o

Autotrophic index (AFDMChl a) j oTaxonomic composition categoryIndicator guilds category Indicator species categoryNutrient stoichiometry Metabolic ratesSpecies richness NHe

4 TNe TPe POe4 TSSe agriculture lande forested

landea e

Relative genera richness Clc Fec Mnc a cGenera richness fDivision richness fShannon index g oCyanobacteria (RA) SiOc

2 agriculture+all human disturbance in riparian zonec a c fCyanobacteria non-heterocystous (RB RSR) mChlorophyta (RA) a fChlorophyta (RB) land useb bChlorophyta excl Zygnemataceae (RB RSR) mZygnemataceae (RB RSR) mRhodophyta (RA) a fRhodophyta (RB RSR) m

Indicator guilds categoryN2-fixing heterocystous m ncyanobacteria (RB RSR)N2-fixing algae (RA) forested lande NO2+NOe

3 TNe agriculture+urban lande

e

CRUS (RB) land useb bZHR (RR) land useb bSestonic algae (RA) NHe

4 TNe TPe POe4 TSSe agriculture+urban lande

forested landee

Motile algae (RA) NHe4 NO2+NOe

3 TNe TPe POe4 TSSe agriculture

lande forested landee

Indicator species categorySensitive SBA (RB) developed land covera aSensitive algae (RB) developed land covera aEutrophic SBA (RA) TNe TPe POe

4 agriculture lande forested lande eEutrophic algae (RA) NO2+NOe

3 TNe TPe POe4 TSSe agriculture+urban

lande forested landee

Low TP SBA indicators (RSR) land useb bHigh DOC SBA indicators (RB RSR) land useb bHigh Cu SBA indicators (RSR) land useb bNon-reference conditions land useb bSBA indicators (RB RSR)TP algal indicators (RA) gConductivity algal indicators (RA) iDIN algal indicators (RA) i

15 page 9 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

Table 2 Continued

Soft-bodied algal IBI metric relationship Referencescommunity attribute with environmental variables

Nutrient contentAlgal CSA NSA PSA j

Nutrient stoichiometryCNSA jNPSA j o

Metabolic ratesAlkaline phosphatase activity agriculture in riparian zonec TPd canopyd all disturbance

in riparian zonec channel substrate width and depthdc d f

References Danielson et al 2011 (a) Fetscher et al 2014 (b) Hill et al 2000 (c) Hill et al 2003 (d) Porter et al 2008 (e) Griffith et al2002 (f) Leland and Porter 2001 (g) Munn et al 2002 (i) OlsquoBrien and Wehr 2010 (j) Pan et al 1999 (k) Stancheva et al 2012a (m)Stancheva et al 2013b (n) Vis et al 1998 (o) Abbreviations IBI ndash multimetric indices of biotic integrity RB ndash relative biovolume RA ndashrelative abundance based on cell numbers RSR ndash relative species richness SA ndash surface area CRUS ndash Cladophora glomerata + Rhizocloniumhieroglyphicum + Ulva flexuosa + Stigeoclonium spp ZHR ndash Zygnemataceae + heterocystous cyanobacteria + Rhodophyta DIN ndash dissolvedinorganic nitrogen TN-total nitrogen TP ndash total phosphorus DOC ndash dissolved organic carbon TSS ndash total suspended solids WT ndash watertemperature

the validation dataset because literature sources do not pro-vide sufficient autecological data Indicator species analysis(Dufrecircne and Legendre 1997) was performed on species abso-lute biovolume data There were 81 soft-bodied algal speciesidentified to correlate significantly with either low or highconcentrations of TP TN dissolved organic carbon (DOC)or dissolved copper (Cu) (see Table 1 for values of wa-ter chemistry parameters) Several soft-bodied algal metricspassed the screening process for IBI development includ-ing two indicator guilds with contrasting responses to localstressors each based on a subset of taxa with similar func-tion in the ecosystem The guild metric with negative re-sponse to increasing levels of generalized stressor combineda proportion of Zygnemataceae heterocystous cyanobacteriaand red algae in agreement with previous observations thateach group is sensitive to particular nutrient or other waterchemistry constituents (Stancheva et al 2012a) The oppositemetric consists of proportions of Cladophora glomerata LRhizoclonium hieroglyphicum (C Agardh) Kuumltz Ulva flexu-osa Wulfen and Stigeoclonium spp which have been evalu-ated as the strongest indicators of high levels of TN TP DOCCu and non-reference conditions (Tables 1 and 2 Figure 1)except for Stigeoclonium which did not fulfill statistical crite-ria because of its rare distribution in the study area

Selected soft-bodied algal metrics were incorporated in17 hybrid IBIs containing diatom metrics also and in 3 soft-bodied algal IBIs Some of the soft-bodied algal metrics in-cluded in the hybrid IBIs were designed to reduce laboratoryefforts such as species level taxonomy resolution without bio-volume estimate vs genus level identification with biovolumedata In addition 5 diatom IBIs were constructed from thesame data set The best performing IBI in regards to the dis-criminatory power among the three site disturbance classesand responsiveness to anthropogenic stress signal-to-noiseratio metric redundancy and degree of indifference to naturalgradients contains five diatom and three soft-bodied algal met-rics (species indicators of low TP high Cu and high DOC ex-

Fig 1 Diagram visualizing the opposite distributional trends of twoguild algal metrics along the generalized land use gradient used instream IBIs in California by Fetscher et al 2014 Legend Lower-lefttriangle indicates the ZHR guild metric consisting of Zygnemataceaeheterocystous cyanobacteria and red algae Upper-right triangle in-dicates the CRUS guild metric consisting of Cladophora glomerataL Rhizoclonium hieroglyphicum (C Agardh) Kuumltz Ulva flexuosaWulfen and Stigeoclonium spp Abbreviations see Table 1

pressed as relative species richness) The comparison betweenboth types of single-algal IBIs showed that the soft-bodied al-gal IBIs separate best the disturbed and intermediate sites andrespond negatively to canopy cover and slope while diatomIBIs discriminate better intermediate and reference sites butare responsive to more natural gradients such as stream or-der watershed area and percent fine substrate (Fetscher et al2014)

In summary the structural soft-bodied algal metrics cur-rently applied in stream IBIs are variable Depending onthe taxonomic method they can be expressed as relativebiovolume (Fetscher et al 2014) or relative abundance (basedon cell density Danielson et al 2011 Potapova and Carlisle2011) with live diatom cells included or not in the counts Itseems that empirically evaluated local soft-bodied algal indi-cator species and guild metrics best respond to anthropogenicstress Furthermore Fetscher et al (2014) demonstrated thatspecies level or lower taxonomic resolution is needed for

15 page 10 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

meaningful algal IBIs because they rely on soft-bodied in-dicator species not genera Hill et al (2003) suggested thatregardless of the approach taken the resulting index should becomposed of biological metrics that have clear relationship tospecific environmental stressors in consideration of their vari-ability at different spatial scales (reach stream river basin)

4 Soft-bodied algae as bioindicatorsof nutrients

Nutrients are a high-priority water quality concern be-cause they are a common cause of stream impairment Theyare typically monitored by discrete sampling of ambient con-centrations which can be highly variable even over a shortduration and these data are rarely indicative of the potentialfor ecosystem impacts (Whitton and Kelly 1995) Historicallytwo approaches have been taken with regards to biologicalmonitoring of nutrients an ecosystem approach in which algalbiomass and productivity are used to infer nutrient impact andan autecological approach in which indicator species and BIsare used as nutrient assessment tools (Borchardt 1996) In-deed functional algal attributes are less commonly used al-though they are informative for ecosystem condition (Kelly2013)

Nutrient enrichment typically stimulates algal growth inflowing waters and many studies demonstrate threshold algalresponse of approximately 30 microgmiddotLminus1 TP and 40 microgmiddotLminus1 TNabove which chlorophyll values are substantially higher (for areview see Dodds et al 1997 Stevenson et al 2012) Benthicchlorophyll values above 100 mgmiddotmminus2 have been consideredexcessive representing a critical level for an aesthetic nui-sance (Welch et al 1988) As system becomes more produc-tive different species of algae become more competitive in-cluding toxin-producing cyanobacteria (Fetscher et al 2015)and species composition shifts occur Usually nuisance algalgrowths in streams and rivers are monitored by quantitativesampling of algal biomass However algal-nutrient interac-tions should be interpreted with care because many studieshave shown that factors other than nutrients (eg light temper-ature substratum type and availability etc) could be more im-portant in determining algal biomass species composition andstructure (reviewed by Borchardt 1996) According to Biggs(1996) biomass loss in streams is a function of algal commu-nity age periodic sloughing losses of the mats large losses dueto disturbance events such as floods and grazing from inverte-brates and fish during prolonged periods of hydrological stabil-ity Therefore attempts to generate dissolved nutrient-benthicalgal biomass models should be considered carefully (for re-view see Biggs 2010)

On the other hand algal growth can be limited by scarcityof macronutrients and micronutrients but the most frequentlimiting factors are nitrogen (N) and phosphorus (P) becausedemand is high relative to their availability The concept ofsingle-nutrient limitation which postulates that an algal speciescan be limited by only one nutrient at a time does not usuallyapply to algal communities where diverse species may be lim-ited by different nutrients simultaneously (Borchardt 1996)Francoeur et al (1999) and Dodds and Welch (2000) showed

that N P or other nutrients can be colimiting for stream pe-riphyton Furthermore the availability of both nutrients mayvary geographically for instance P is in short supply in thenorth part of the US N in the Pacific Southwest and both nu-trients in the Pacific Northwest (Borchardt 1996 and literaturetherein)

Nutrient limitation both by P and N in streams is read-ily accessible by the functional responses of the benthic al-gal community such as alkaline phosphatase activity (APA)and atmospheric N fixation which are expected to decreasewith nutrient enrichment (Hill et al 2000 Stancheva et al2013b) Indeed APA measurements of entire periphyton inlarge-scale stream bioassessments showed contradicting re-sults (Hill et al 2000 2003 Griffith et al 2002 Table 2)which could be explained by multiple ecological processesoperating at different spatial and temporal scales in com-plex ecological systems (Pan et al 1999) According toMulholland and Rosemond (1992) APA is a valuable indi-cator of P limitation affecting algal species composition butdoes not consistently affect algal biomass (chlorophyll a totalbiovolume) and productivity (carbon fixation rate chlorophyll-specific carbon fixation rate)

Under conditions of moderate P limitation some freshwa-ter green algae such as Draparnaldia Chaetophora Stigeo-clonium (Gibson and Whitton 1987) and red algae eg Ba-trachospermum Sheathia Sirodotia (Sheath and Hambrook1990) form different types of ldquosurfacerdquo phosphatases (Whittonet al 1998) In addition they develop prominent hairs wherethe phosphatase is located functioning to increase the surfacearea of phosphorus uptake (Whitton 1988) This activity iseasy to assay for practical monitoring purposes by use of sub-strates such as p-nitrophenyl phosphate upon whose hydroly-sis releases the colored p-nitrophenol (Whitton 1991 Whittonet al 2002) Similarly conditions of inorganic phosphatedeficiency influence the trichome morphology of cyanobac-teria belonging to the Rivulariaceae by inducing formationof long colorless multicellular hairs which are the sites ofphosphomonoesterase activity for utilizing organic phosphates(Whitton and Mateo 2012) The members of Rivulariaceaealso possess heterocysts and are able to fix atmospheric ni-trogen during periods of high inorganic P supply (Whitton andMateo 2012) Mateo et al (2010) observed that in Pyreneescalcareous streams P limitation is the main chemical factor toinfluence benthic cyanobacterial communities including sev-eral heterocystous taxa of which Rivularia was the most abun-dant The authors proposed rapid methods for assessing long-term nutrient changes in a catchment combining observationson macroscopically visible cyanobacteria with assays of sur-face phosphatase activity (Mateo et al 2010)

N limitation of benthic algal communities from largestream data sets in southern California had been clearly indi-cated by the presence of N2-fixing heterocystous cyanobacteriaand coccoid cyanobaterial endosymbionts in diatoms Rhopalo-dia and Epithemia (Stancheva et al 2013b) Responsethresholds in N2-fixers biovolume and nitrogenase gene ex-pression obtained by real-time reverse transcriptase PCR were0075 mgmiddotLminus1 NO3-N 004 mgmiddotLminus1 NH4-N and an NP ra-tio (by weight) of 151 (Stancheva et al 2013b) Thus rapidquantitative microscopic and molecular methods for nutrient

15 page 11 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

monitoring can be based on N2-fixing cyanobacteria andendosymbiont-containing diatoms (Stancheva et al 2013b)If these rapid and simple approaches proposed by Whitton(1991) Mateo et al (2010) and Stancheva et al (2013b) are in-corporated in standard bioassessment of stream nutrient condi-tions they could be beneficial also in monitoring air pollution-related atmospheric nitrogen deposition which is a recognizedthreat to plant diversity in temperate and northern parts of Eu-rope and North America (Bobbink et al 2010) but its impacton stream ecosystems is largely unexplored

5 Concluding remarks

This review shows that soft-bodied algae are valuable in-dicators of stream and river water quality but holistic stud-ies including all algal taxonomic groups are not yet com-mon The structural taxonomic attributes of soft-bodied algalcommunities are good measures of anthropogenic stress butbetter understanding of the nature of this organism groupis needed to make it meaningful and easy-to-use standardbioassessment tools For instance Stevenson and Smol (2003)suggested that the precision of algal indicators is improvedwhen they are refined with regional datasets It is particu-larly important for soft-bodied algae which exhibit strongergeographical specialization than diatoms which makes theirapplicability more locally restricted (Potapova and Carlisle2011 Schneider et al 2012 Schneider and Rott 2013)

Another important consideration in soft-bodied algaebioassessment application is the quality of taxonomic identi-fications which is central to biological assessment The impactgenerated by taxonomical uncertainty and incompleteness usu-ally transcends the limits of ecology and environmental man-agement (Bortolus 2008) Large-scale bioassessment surveysare designed with the objective to produce statistically validassessments of biological conditions in streams (Hughes andPeck 2008) but the fundamental key piece of biological in-formation is a species of algae or any other organism selectedas an indicator Therefore field sampling and taxonomic anal-ysis should follow the best practices to provide a detailed listof microalgae and macroalgae identified to species level Theoptimal level of taxonomic resolution for stream biomonitor-ing is still debated (reviewed by Rimet and Bouchez 2012)Species level determination is considered the gold standardeven if there are some disadvantages of using precise taxo-nomic resolution mostly associated with high cost time andthe expertise demanded and the possibility for more errors inidentification (Konar and Iken 2009) Biovolume quantifica-tion of soft-bodied algae is important during the initial accrualof data for development of algal IBIs but metrics based onrelative rather than absolute values have stronger relationshipsto water quality and enable statistical significant evaluation ofecological tolerances (Danielson et al 2011 Fetscher et al2014)

Once the algal attributes such as an indicator species orstressor responsive ecological guilds are determined to be sta-tistically valid and included in IBIs as metrics reducing thetaxonomic efforts and cost for continuing routine monitoringmight be appropriate similarly to microinvertebrate bioasess-ment (Gartzia De Bikuntildea et al 2015) For example one of

the best performing hybrid IBIs for southern California in-cludes three soft-bodied algal metrics which do not requirebiovolume data but species level identification (Fetscher et al2014) thus the reduction of taxonomic analysis efforts is pos-sible by semi-quantitative estimate All successfully appliedBIs in European stream and river biomonitoring are based onalgal presence-absence species level data which confirmed theimportance of fine taxonomic resolution Further reduction oftaxonomy efforts is feasible for causal assessments such as ofnutrient condition which can be evaluated rapidly by micro-scopic or molecular methods based on ecological guilds suchas N2-fixing cyanobacteria alone or in combination with redalgae and Zygnemataceae (after Fetscher et al 2014) Devel-oping molecular methods for algal ecological guilds could bemore realistic option then the molecular bioassessment of al-gae community composition which is promising approach butnot applicable at this point (Manoylov 2014)

Acknowledgements Part of the discussed research was funded by theconsolidated grants and the SWAMP Program of the California StateWater Resources Control Board We thank both anonymous review-ers for their valuable comments which improved the quality of themanuscript

References

Acker F 2002 Analysis of Soft Algae and Enumeration of TotalNumber of Diatoms in USGS NAWQA Program QuantitativeTargeted-Habitat (RTH and DTH) Samples Protocol P-1363 InCharles DF Knowles C and Davis RS (eds) Protocols for theanalysis of algal samples collected as part of the US GeologicalSurvey National Water-Quality Assessment Program Report 02-06 Patrick Center for Environmental Research The Academy ofNatural Sciences Philadelphia

ANZECC 2000 National Water Quality Management StrategyThe Australian and New Zealand Guidelines for Fresh andMarine Water Quality Australian and New Zealand Environmentand Conservation Council and Agriculture and ResourseManagement Council of Australia and New Zealand CanberraAustralia

Biggs BJF 1987 Effects of sample storage and mechanical blend-ing on the quantitative analysis of river periphyton FreshwaterBiol 18 197ndash203

Biggs BJF 1996 Patterns in benthic algae of streams In StevensonRJ Bothwell ML and Lowe RL (eds) Algal EcologyFreshwater Benthic Ecosystems Academic Press San Diego31ndash56

Biggs BJF 2010 Eutrophication of streams and rivers dissolvednutrient-chlorophyll relationships for benthic algae J N AmBenthol Soc 19 17ndash31

Biggs BJF and Kilroy C 2000 Stream periphyton monitoringmanual National Institute of Water and Atmospheric Researchfor the New Zealand Ministry for the Environment viewed19 November 2013 available at httpwwwsmfgovtnzresults5092_periphytonmanualpdf

Bobbink R Hicks K Galloway J Spranger T Alkemade RAshmore M Bustamante M Cinderby S Davidson EDentener F Emmett B Erisman JW Fenn M Gilliam FNordin A Pardo L and De Vries W 2010 Global assessmentof nitrogen deposition effects on terrestrial plant diversity a syn-thesis Ecol Appl 20 30ndash59

15 page 12 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

good understanding of algal communities from different geo-graphic areas and water types

32 Multimetric indices of biotic integrity (IBI)

Several diatom IBIs have been developed in the pastdecade and serve as a main tool together with macroinver-tebrate IBIs in stream bioassessment programs in the UnitedStates Similarly the requirements of the European WFD foran integrative assessment of ecological condition of streamsand rivers are frequently achieved through diatom multimet-ric indices one of which includes algal biomass (chloro-phyll a) as community metric (Delgardo et al 2010) Reg-ulatory methodology for development and application of thisbioassessment tool are suggested (Hering et al 2006) Thestandard approach in the construction of diatom IBIs are out-lined by Stevenson et al (2010) and literature cited thereinThe most critical step in any IBI development is the selectionof the metrics ndash the ultimate goal is to choose metrics that rep-resent as many levels of ecological organization as possiblefollowing the original concept of Karr (1981) The soft-bodiedalgal community attributes that have been used to assess eco-logical conditions in streams are both structural and functionalthe latter together with chlorophyll a and ash-free dry massmeasurements are representative for the entire benthic commu-nity including diatoms bacteria and fungi (Stevenson et al2010) Structural taxonomic characteristics of soft-bodied al-gal communities indicator species and indicator guilds whichcombine a subset taxa with similar physiologies and ecosystemfunction are most often applied as biotic indices and as metricsin multimetric indices (Table 2) The value of IBIs is that theytend to be more linear than univariate BIs (Fore et al 1994)and help to provide a summary index which simplifies com-munication of results by a convenient scoring scale eg 0 to100 (Stevenson et al 2010) However the meaning of IBIs hasbeen questioned in regards to predictability diagnostic powerlack of reason for high or low index values the validity of sum-ming heterogeneous metrics into a single measure of streamcondition blurring effects on one metric by effects on othermetrics etc (see review by Doleacutedec and Statzner 2010)

The exploration of soft-bodied algae community character-istics as supplemental metrics in diatom IBIs began with workby Hill et al (2000 2003) which include non-taxonomic andfunctional measures of entire benthic algal communities iechlorophyll a ash-free dry mass and alkaline phosphatase ac-tivity in two studies of streams in the eastern US (as part ofEMAP) each comprised of nearly 300 samples In additiontwo taxonomic metrics containing soft-bodied algae (relativeabundance of cyanobacteria and relative genera richness) wereevaluated (Hill et al 2000) Despite the noted relationship be-tween both taxonomic metrics and some environmental vari-ables they were not responsive to water-quality constituents(Hill et al 2000)

Porter (2008) and Porter et al (2008) tested the efficacyof algal-community metrics calculated from 976 stream andriver samples collected across the United States (as part ofNAWQA) and their national and regional relations with waterchemistry Several metrics showed one or more significant cor-relations to nutrient and suspended-sediment concentrations

including soft-bodied algal species richness and relative abun-dance of eutrophic sestonic and motile algae determined fromliterature sources A promising metric of trophic condition isthe relative abundance of N2-fixing heterocystous cyanobac-teria combined with diatoms containing cyanobacterial en-dosymbionts Epithemia Rhopalodia and Denticula whichshowed a negative correlation with N concentration (Porteret al 2008) However the presence of endosymbionts inDenticula has not been confirmed for North American species(Lowe 2003)

The current development of soft-bodied algal metrics con-sists of empirical evaluation of indicator species from studieddata sets in contrast to autecological guild metrics based onliterature data from distant geographical locations Danielsonet al (2011) in a survey of 193 wadeable streams in Maineused the weighted-average approach to compute species op-tima for watershed disturbances (eg TP total nitrogen (TN)conductivity land use that is no longer forest or wetland)and to categorize the algal species based on their sensitiv-ity and tolerance to disturbance Optima for 41 soft-bodiedalgal taxa are calculated separately from diatoms based onlog10-transformed density to avoid distortion of relative abun-dances by large densities of cyanobacteria In this way au-thors distinguished many sensitive algal taxa (such as speciesbelonging to Audouinella Batrachospermum Calothrix Toly-pothrix Mougeotia Zygnema Ulothrix) but failed to deter-mine disturbance tolerant soft-bodied algal species Howevermetrics using proportion sensitive algal species including di-atoms and those based on soft-bodied algae alone showed sig-nificant correlation with developed land cover in contrastto biomass and some taxonomic metrics (such as total speciesrichness richness and relative abundance of green algae redalgae and cyanobacteria) which were not correlated with an-thropogenic stressors (Table 2)

Potapova and Carlisle (2011) developed diatom IBIs forover 1000 NAWQA Program sites in five geographical regionsacross conterminous US They used Indicator species analy-sis (Dufrecircne and Legendre 1997) to identify diatom and soft-bodied algal species associated with reference and disturbedsites which are a priory classified based on watershed dis-turbance As result only 34 soft-bodied algal taxa (or mor-phological groups) were determined to be possible indicatorsof reference or disturbed sites and their inclusion as metricdid not improve the classification accuracy of diatoms IBIsPotapova and Carlisle (2011) attributed the poor performanceof soft-bodied algal metrics to the taxonomic method whichprecludes from species level identification and recommendeddevelopment of new methods that better characterize the soft-bodied algal communities

Fetscher et al (2014) constructed the first IBIs based onsoft-bodied algae alone derived from more than 451 streamsamples collected predominantly in southern California(SWAMP modified field method by Fetscher et al 2009and novel taxonomic method by Stancheva et al 2012a)Soft-bodied algal metrics were taxonomic ndash algal phyla in-dicator species and indicator guilds and were expressed intwo ways proportion of total biovolume (relative biovolume)and proportion of total species number (relative species rich-ness) Indicator species had been evaluated empirically from

15 page 8 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

Table 2 Structural and functional attributes of the stream benthic soft-bodied algae community used as metrics in IBIs and reported rela-tionships with environmental variables Positive relationships are in regular font negative relationships are italicized () indicates that metricis calculated as proportion from the entire assemblage including ldquolivingrdquo diatom cells ldquoAlgaerdquo refers to entire algal assemblage includingdiatoms ldquoSBArdquo refers to soft-bodied (non-diatom) algae only

Soft-bodied algal IBI metric relationship Referencescommunity attribute with environmental variables

Biomass categoryTotal biovolume a mTotal biovolume NO2 + NOe

3 TSSe a eCell density aCell density TSSe e fAsh-free dry mass (AFDM) urban and suburban landc sand and fine sedimentsc

TSSc canopyd sloped Cld SOd4 TNd

a c d j o

Chlorophyll a(Chl a) urban and suburban landc colorc Fec canopyd Cld can-nel widthd riparian disturbanced

a c d f k o

Autotrophic index (AFDMChl a) j oTaxonomic composition categoryIndicator guilds category Indicator species categoryNutrient stoichiometry Metabolic ratesSpecies richness NHe

4 TNe TPe POe4 TSSe agriculture lande forested

landea e

Relative genera richness Clc Fec Mnc a cGenera richness fDivision richness fShannon index g oCyanobacteria (RA) SiOc

2 agriculture+all human disturbance in riparian zonec a c fCyanobacteria non-heterocystous (RB RSR) mChlorophyta (RA) a fChlorophyta (RB) land useb bChlorophyta excl Zygnemataceae (RB RSR) mZygnemataceae (RB RSR) mRhodophyta (RA) a fRhodophyta (RB RSR) m

Indicator guilds categoryN2-fixing heterocystous m ncyanobacteria (RB RSR)N2-fixing algae (RA) forested lande NO2+NOe

3 TNe agriculture+urban lande

e

CRUS (RB) land useb bZHR (RR) land useb bSestonic algae (RA) NHe

4 TNe TPe POe4 TSSe agriculture+urban lande

forested landee

Motile algae (RA) NHe4 NO2+NOe

3 TNe TPe POe4 TSSe agriculture

lande forested landee

Indicator species categorySensitive SBA (RB) developed land covera aSensitive algae (RB) developed land covera aEutrophic SBA (RA) TNe TPe POe

4 agriculture lande forested lande eEutrophic algae (RA) NO2+NOe

3 TNe TPe POe4 TSSe agriculture+urban

lande forested landee

Low TP SBA indicators (RSR) land useb bHigh DOC SBA indicators (RB RSR) land useb bHigh Cu SBA indicators (RSR) land useb bNon-reference conditions land useb bSBA indicators (RB RSR)TP algal indicators (RA) gConductivity algal indicators (RA) iDIN algal indicators (RA) i

15 page 9 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

Table 2 Continued

Soft-bodied algal IBI metric relationship Referencescommunity attribute with environmental variables

Nutrient contentAlgal CSA NSA PSA j

Nutrient stoichiometryCNSA jNPSA j o

Metabolic ratesAlkaline phosphatase activity agriculture in riparian zonec TPd canopyd all disturbance

in riparian zonec channel substrate width and depthdc d f

References Danielson et al 2011 (a) Fetscher et al 2014 (b) Hill et al 2000 (c) Hill et al 2003 (d) Porter et al 2008 (e) Griffith et al2002 (f) Leland and Porter 2001 (g) Munn et al 2002 (i) OlsquoBrien and Wehr 2010 (j) Pan et al 1999 (k) Stancheva et al 2012a (m)Stancheva et al 2013b (n) Vis et al 1998 (o) Abbreviations IBI ndash multimetric indices of biotic integrity RB ndash relative biovolume RA ndashrelative abundance based on cell numbers RSR ndash relative species richness SA ndash surface area CRUS ndash Cladophora glomerata + Rhizocloniumhieroglyphicum + Ulva flexuosa + Stigeoclonium spp ZHR ndash Zygnemataceae + heterocystous cyanobacteria + Rhodophyta DIN ndash dissolvedinorganic nitrogen TN-total nitrogen TP ndash total phosphorus DOC ndash dissolved organic carbon TSS ndash total suspended solids WT ndash watertemperature

the validation dataset because literature sources do not pro-vide sufficient autecological data Indicator species analysis(Dufrecircne and Legendre 1997) was performed on species abso-lute biovolume data There were 81 soft-bodied algal speciesidentified to correlate significantly with either low or highconcentrations of TP TN dissolved organic carbon (DOC)or dissolved copper (Cu) (see Table 1 for values of wa-ter chemistry parameters) Several soft-bodied algal metricspassed the screening process for IBI development includ-ing two indicator guilds with contrasting responses to localstressors each based on a subset of taxa with similar func-tion in the ecosystem The guild metric with negative re-sponse to increasing levels of generalized stressor combineda proportion of Zygnemataceae heterocystous cyanobacteriaand red algae in agreement with previous observations thateach group is sensitive to particular nutrient or other waterchemistry constituents (Stancheva et al 2012a) The oppositemetric consists of proportions of Cladophora glomerata LRhizoclonium hieroglyphicum (C Agardh) Kuumltz Ulva flexu-osa Wulfen and Stigeoclonium spp which have been evalu-ated as the strongest indicators of high levels of TN TP DOCCu and non-reference conditions (Tables 1 and 2 Figure 1)except for Stigeoclonium which did not fulfill statistical crite-ria because of its rare distribution in the study area

Selected soft-bodied algal metrics were incorporated in17 hybrid IBIs containing diatom metrics also and in 3 soft-bodied algal IBIs Some of the soft-bodied algal metrics in-cluded in the hybrid IBIs were designed to reduce laboratoryefforts such as species level taxonomy resolution without bio-volume estimate vs genus level identification with biovolumedata In addition 5 diatom IBIs were constructed from thesame data set The best performing IBI in regards to the dis-criminatory power among the three site disturbance classesand responsiveness to anthropogenic stress signal-to-noiseratio metric redundancy and degree of indifference to naturalgradients contains five diatom and three soft-bodied algal met-rics (species indicators of low TP high Cu and high DOC ex-

Fig 1 Diagram visualizing the opposite distributional trends of twoguild algal metrics along the generalized land use gradient used instream IBIs in California by Fetscher et al 2014 Legend Lower-lefttriangle indicates the ZHR guild metric consisting of Zygnemataceaeheterocystous cyanobacteria and red algae Upper-right triangle in-dicates the CRUS guild metric consisting of Cladophora glomerataL Rhizoclonium hieroglyphicum (C Agardh) Kuumltz Ulva flexuosaWulfen and Stigeoclonium spp Abbreviations see Table 1

pressed as relative species richness) The comparison betweenboth types of single-algal IBIs showed that the soft-bodied al-gal IBIs separate best the disturbed and intermediate sites andrespond negatively to canopy cover and slope while diatomIBIs discriminate better intermediate and reference sites butare responsive to more natural gradients such as stream or-der watershed area and percent fine substrate (Fetscher et al2014)

In summary the structural soft-bodied algal metrics cur-rently applied in stream IBIs are variable Depending onthe taxonomic method they can be expressed as relativebiovolume (Fetscher et al 2014) or relative abundance (basedon cell density Danielson et al 2011 Potapova and Carlisle2011) with live diatom cells included or not in the counts Itseems that empirically evaluated local soft-bodied algal indi-cator species and guild metrics best respond to anthropogenicstress Furthermore Fetscher et al (2014) demonstrated thatspecies level or lower taxonomic resolution is needed for

15 page 10 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

meaningful algal IBIs because they rely on soft-bodied in-dicator species not genera Hill et al (2003) suggested thatregardless of the approach taken the resulting index should becomposed of biological metrics that have clear relationship tospecific environmental stressors in consideration of their vari-ability at different spatial scales (reach stream river basin)

4 Soft-bodied algae as bioindicatorsof nutrients

Nutrients are a high-priority water quality concern be-cause they are a common cause of stream impairment Theyare typically monitored by discrete sampling of ambient con-centrations which can be highly variable even over a shortduration and these data are rarely indicative of the potentialfor ecosystem impacts (Whitton and Kelly 1995) Historicallytwo approaches have been taken with regards to biologicalmonitoring of nutrients an ecosystem approach in which algalbiomass and productivity are used to infer nutrient impact andan autecological approach in which indicator species and BIsare used as nutrient assessment tools (Borchardt 1996) In-deed functional algal attributes are less commonly used al-though they are informative for ecosystem condition (Kelly2013)

Nutrient enrichment typically stimulates algal growth inflowing waters and many studies demonstrate threshold algalresponse of approximately 30 microgmiddotLminus1 TP and 40 microgmiddotLminus1 TNabove which chlorophyll values are substantially higher (for areview see Dodds et al 1997 Stevenson et al 2012) Benthicchlorophyll values above 100 mgmiddotmminus2 have been consideredexcessive representing a critical level for an aesthetic nui-sance (Welch et al 1988) As system becomes more produc-tive different species of algae become more competitive in-cluding toxin-producing cyanobacteria (Fetscher et al 2015)and species composition shifts occur Usually nuisance algalgrowths in streams and rivers are monitored by quantitativesampling of algal biomass However algal-nutrient interac-tions should be interpreted with care because many studieshave shown that factors other than nutrients (eg light temper-ature substratum type and availability etc) could be more im-portant in determining algal biomass species composition andstructure (reviewed by Borchardt 1996) According to Biggs(1996) biomass loss in streams is a function of algal commu-nity age periodic sloughing losses of the mats large losses dueto disturbance events such as floods and grazing from inverte-brates and fish during prolonged periods of hydrological stabil-ity Therefore attempts to generate dissolved nutrient-benthicalgal biomass models should be considered carefully (for re-view see Biggs 2010)

On the other hand algal growth can be limited by scarcityof macronutrients and micronutrients but the most frequentlimiting factors are nitrogen (N) and phosphorus (P) becausedemand is high relative to their availability The concept ofsingle-nutrient limitation which postulates that an algal speciescan be limited by only one nutrient at a time does not usuallyapply to algal communities where diverse species may be lim-ited by different nutrients simultaneously (Borchardt 1996)Francoeur et al (1999) and Dodds and Welch (2000) showed

that N P or other nutrients can be colimiting for stream pe-riphyton Furthermore the availability of both nutrients mayvary geographically for instance P is in short supply in thenorth part of the US N in the Pacific Southwest and both nu-trients in the Pacific Northwest (Borchardt 1996 and literaturetherein)

Nutrient limitation both by P and N in streams is read-ily accessible by the functional responses of the benthic al-gal community such as alkaline phosphatase activity (APA)and atmospheric N fixation which are expected to decreasewith nutrient enrichment (Hill et al 2000 Stancheva et al2013b) Indeed APA measurements of entire periphyton inlarge-scale stream bioassessments showed contradicting re-sults (Hill et al 2000 2003 Griffith et al 2002 Table 2)which could be explained by multiple ecological processesoperating at different spatial and temporal scales in com-plex ecological systems (Pan et al 1999) According toMulholland and Rosemond (1992) APA is a valuable indi-cator of P limitation affecting algal species composition butdoes not consistently affect algal biomass (chlorophyll a totalbiovolume) and productivity (carbon fixation rate chlorophyll-specific carbon fixation rate)

Under conditions of moderate P limitation some freshwa-ter green algae such as Draparnaldia Chaetophora Stigeo-clonium (Gibson and Whitton 1987) and red algae eg Ba-trachospermum Sheathia Sirodotia (Sheath and Hambrook1990) form different types of ldquosurfacerdquo phosphatases (Whittonet al 1998) In addition they develop prominent hairs wherethe phosphatase is located functioning to increase the surfacearea of phosphorus uptake (Whitton 1988) This activity iseasy to assay for practical monitoring purposes by use of sub-strates such as p-nitrophenyl phosphate upon whose hydroly-sis releases the colored p-nitrophenol (Whitton 1991 Whittonet al 2002) Similarly conditions of inorganic phosphatedeficiency influence the trichome morphology of cyanobac-teria belonging to the Rivulariaceae by inducing formationof long colorless multicellular hairs which are the sites ofphosphomonoesterase activity for utilizing organic phosphates(Whitton and Mateo 2012) The members of Rivulariaceaealso possess heterocysts and are able to fix atmospheric ni-trogen during periods of high inorganic P supply (Whitton andMateo 2012) Mateo et al (2010) observed that in Pyreneescalcareous streams P limitation is the main chemical factor toinfluence benthic cyanobacterial communities including sev-eral heterocystous taxa of which Rivularia was the most abun-dant The authors proposed rapid methods for assessing long-term nutrient changes in a catchment combining observationson macroscopically visible cyanobacteria with assays of sur-face phosphatase activity (Mateo et al 2010)

N limitation of benthic algal communities from largestream data sets in southern California had been clearly indi-cated by the presence of N2-fixing heterocystous cyanobacteriaand coccoid cyanobaterial endosymbionts in diatoms Rhopalo-dia and Epithemia (Stancheva et al 2013b) Responsethresholds in N2-fixers biovolume and nitrogenase gene ex-pression obtained by real-time reverse transcriptase PCR were0075 mgmiddotLminus1 NO3-N 004 mgmiddotLminus1 NH4-N and an NP ra-tio (by weight) of 151 (Stancheva et al 2013b) Thus rapidquantitative microscopic and molecular methods for nutrient

15 page 11 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

monitoring can be based on N2-fixing cyanobacteria andendosymbiont-containing diatoms (Stancheva et al 2013b)If these rapid and simple approaches proposed by Whitton(1991) Mateo et al (2010) and Stancheva et al (2013b) are in-corporated in standard bioassessment of stream nutrient condi-tions they could be beneficial also in monitoring air pollution-related atmospheric nitrogen deposition which is a recognizedthreat to plant diversity in temperate and northern parts of Eu-rope and North America (Bobbink et al 2010) but its impacton stream ecosystems is largely unexplored

5 Concluding remarks

This review shows that soft-bodied algae are valuable in-dicators of stream and river water quality but holistic stud-ies including all algal taxonomic groups are not yet com-mon The structural taxonomic attributes of soft-bodied algalcommunities are good measures of anthropogenic stress butbetter understanding of the nature of this organism groupis needed to make it meaningful and easy-to-use standardbioassessment tools For instance Stevenson and Smol (2003)suggested that the precision of algal indicators is improvedwhen they are refined with regional datasets It is particu-larly important for soft-bodied algae which exhibit strongergeographical specialization than diatoms which makes theirapplicability more locally restricted (Potapova and Carlisle2011 Schneider et al 2012 Schneider and Rott 2013)

Another important consideration in soft-bodied algaebioassessment application is the quality of taxonomic identi-fications which is central to biological assessment The impactgenerated by taxonomical uncertainty and incompleteness usu-ally transcends the limits of ecology and environmental man-agement (Bortolus 2008) Large-scale bioassessment surveysare designed with the objective to produce statistically validassessments of biological conditions in streams (Hughes andPeck 2008) but the fundamental key piece of biological in-formation is a species of algae or any other organism selectedas an indicator Therefore field sampling and taxonomic anal-ysis should follow the best practices to provide a detailed listof microalgae and macroalgae identified to species level Theoptimal level of taxonomic resolution for stream biomonitor-ing is still debated (reviewed by Rimet and Bouchez 2012)Species level determination is considered the gold standardeven if there are some disadvantages of using precise taxo-nomic resolution mostly associated with high cost time andthe expertise demanded and the possibility for more errors inidentification (Konar and Iken 2009) Biovolume quantifica-tion of soft-bodied algae is important during the initial accrualof data for development of algal IBIs but metrics based onrelative rather than absolute values have stronger relationshipsto water quality and enable statistical significant evaluation ofecological tolerances (Danielson et al 2011 Fetscher et al2014)

Once the algal attributes such as an indicator species orstressor responsive ecological guilds are determined to be sta-tistically valid and included in IBIs as metrics reducing thetaxonomic efforts and cost for continuing routine monitoringmight be appropriate similarly to microinvertebrate bioasess-ment (Gartzia De Bikuntildea et al 2015) For example one of

the best performing hybrid IBIs for southern California in-cludes three soft-bodied algal metrics which do not requirebiovolume data but species level identification (Fetscher et al2014) thus the reduction of taxonomic analysis efforts is pos-sible by semi-quantitative estimate All successfully appliedBIs in European stream and river biomonitoring are based onalgal presence-absence species level data which confirmed theimportance of fine taxonomic resolution Further reduction oftaxonomy efforts is feasible for causal assessments such as ofnutrient condition which can be evaluated rapidly by micro-scopic or molecular methods based on ecological guilds suchas N2-fixing cyanobacteria alone or in combination with redalgae and Zygnemataceae (after Fetscher et al 2014) Devel-oping molecular methods for algal ecological guilds could bemore realistic option then the molecular bioassessment of al-gae community composition which is promising approach butnot applicable at this point (Manoylov 2014)

Acknowledgements Part of the discussed research was funded by theconsolidated grants and the SWAMP Program of the California StateWater Resources Control Board We thank both anonymous review-ers for their valuable comments which improved the quality of themanuscript

References

Acker F 2002 Analysis of Soft Algae and Enumeration of TotalNumber of Diatoms in USGS NAWQA Program QuantitativeTargeted-Habitat (RTH and DTH) Samples Protocol P-1363 InCharles DF Knowles C and Davis RS (eds) Protocols for theanalysis of algal samples collected as part of the US GeologicalSurvey National Water-Quality Assessment Program Report 02-06 Patrick Center for Environmental Research The Academy ofNatural Sciences Philadelphia

ANZECC 2000 National Water Quality Management StrategyThe Australian and New Zealand Guidelines for Fresh andMarine Water Quality Australian and New Zealand Environmentand Conservation Council and Agriculture and ResourseManagement Council of Australia and New Zealand CanberraAustralia

Biggs BJF 1987 Effects of sample storage and mechanical blend-ing on the quantitative analysis of river periphyton FreshwaterBiol 18 197ndash203

Biggs BJF 1996 Patterns in benthic algae of streams In StevensonRJ Bothwell ML and Lowe RL (eds) Algal EcologyFreshwater Benthic Ecosystems Academic Press San Diego31ndash56

Biggs BJF 2010 Eutrophication of streams and rivers dissolvednutrient-chlorophyll relationships for benthic algae J N AmBenthol Soc 19 17ndash31

Biggs BJF and Kilroy C 2000 Stream periphyton monitoringmanual National Institute of Water and Atmospheric Researchfor the New Zealand Ministry for the Environment viewed19 November 2013 available at httpwwwsmfgovtnzresults5092_periphytonmanualpdf

Bobbink R Hicks K Galloway J Spranger T Alkemade RAshmore M Bustamante M Cinderby S Davidson EDentener F Emmett B Erisman JW Fenn M Gilliam FNordin A Pardo L and De Vries W 2010 Global assessmentof nitrogen deposition effects on terrestrial plant diversity a syn-thesis Ecol Appl 20 30ndash59

15 page 12 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

Table 2 Structural and functional attributes of the stream benthic soft-bodied algae community used as metrics in IBIs and reported rela-tionships with environmental variables Positive relationships are in regular font negative relationships are italicized () indicates that metricis calculated as proportion from the entire assemblage including ldquolivingrdquo diatom cells ldquoAlgaerdquo refers to entire algal assemblage includingdiatoms ldquoSBArdquo refers to soft-bodied (non-diatom) algae only

Soft-bodied algal IBI metric relationship Referencescommunity attribute with environmental variables

Biomass categoryTotal biovolume a mTotal biovolume NO2 + NOe

3 TSSe a eCell density aCell density TSSe e fAsh-free dry mass (AFDM) urban and suburban landc sand and fine sedimentsc

TSSc canopyd sloped Cld SOd4 TNd

a c d j o

Chlorophyll a(Chl a) urban and suburban landc colorc Fec canopyd Cld can-nel widthd riparian disturbanced

a c d f k o

Autotrophic index (AFDMChl a) j oTaxonomic composition categoryIndicator guilds category Indicator species categoryNutrient stoichiometry Metabolic ratesSpecies richness NHe

4 TNe TPe POe4 TSSe agriculture lande forested

landea e

Relative genera richness Clc Fec Mnc a cGenera richness fDivision richness fShannon index g oCyanobacteria (RA) SiOc

2 agriculture+all human disturbance in riparian zonec a c fCyanobacteria non-heterocystous (RB RSR) mChlorophyta (RA) a fChlorophyta (RB) land useb bChlorophyta excl Zygnemataceae (RB RSR) mZygnemataceae (RB RSR) mRhodophyta (RA) a fRhodophyta (RB RSR) m

Indicator guilds categoryN2-fixing heterocystous m ncyanobacteria (RB RSR)N2-fixing algae (RA) forested lande NO2+NOe

3 TNe agriculture+urban lande

e

CRUS (RB) land useb bZHR (RR) land useb bSestonic algae (RA) NHe

4 TNe TPe POe4 TSSe agriculture+urban lande

forested landee

Motile algae (RA) NHe4 NO2+NOe

3 TNe TPe POe4 TSSe agriculture

lande forested landee

Indicator species categorySensitive SBA (RB) developed land covera aSensitive algae (RB) developed land covera aEutrophic SBA (RA) TNe TPe POe

4 agriculture lande forested lande eEutrophic algae (RA) NO2+NOe

3 TNe TPe POe4 TSSe agriculture+urban

lande forested landee

Low TP SBA indicators (RSR) land useb bHigh DOC SBA indicators (RB RSR) land useb bHigh Cu SBA indicators (RSR) land useb bNon-reference conditions land useb bSBA indicators (RB RSR)TP algal indicators (RA) gConductivity algal indicators (RA) iDIN algal indicators (RA) i

15 page 9 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

Table 2 Continued

Soft-bodied algal IBI metric relationship Referencescommunity attribute with environmental variables

Nutrient contentAlgal CSA NSA PSA j

Nutrient stoichiometryCNSA jNPSA j o

Metabolic ratesAlkaline phosphatase activity agriculture in riparian zonec TPd canopyd all disturbance

in riparian zonec channel substrate width and depthdc d f

References Danielson et al 2011 (a) Fetscher et al 2014 (b) Hill et al 2000 (c) Hill et al 2003 (d) Porter et al 2008 (e) Griffith et al2002 (f) Leland and Porter 2001 (g) Munn et al 2002 (i) OlsquoBrien and Wehr 2010 (j) Pan et al 1999 (k) Stancheva et al 2012a (m)Stancheva et al 2013b (n) Vis et al 1998 (o) Abbreviations IBI ndash multimetric indices of biotic integrity RB ndash relative biovolume RA ndashrelative abundance based on cell numbers RSR ndash relative species richness SA ndash surface area CRUS ndash Cladophora glomerata + Rhizocloniumhieroglyphicum + Ulva flexuosa + Stigeoclonium spp ZHR ndash Zygnemataceae + heterocystous cyanobacteria + Rhodophyta DIN ndash dissolvedinorganic nitrogen TN-total nitrogen TP ndash total phosphorus DOC ndash dissolved organic carbon TSS ndash total suspended solids WT ndash watertemperature

the validation dataset because literature sources do not pro-vide sufficient autecological data Indicator species analysis(Dufrecircne and Legendre 1997) was performed on species abso-lute biovolume data There were 81 soft-bodied algal speciesidentified to correlate significantly with either low or highconcentrations of TP TN dissolved organic carbon (DOC)or dissolved copper (Cu) (see Table 1 for values of wa-ter chemistry parameters) Several soft-bodied algal metricspassed the screening process for IBI development includ-ing two indicator guilds with contrasting responses to localstressors each based on a subset of taxa with similar func-tion in the ecosystem The guild metric with negative re-sponse to increasing levels of generalized stressor combineda proportion of Zygnemataceae heterocystous cyanobacteriaand red algae in agreement with previous observations thateach group is sensitive to particular nutrient or other waterchemistry constituents (Stancheva et al 2012a) The oppositemetric consists of proportions of Cladophora glomerata LRhizoclonium hieroglyphicum (C Agardh) Kuumltz Ulva flexu-osa Wulfen and Stigeoclonium spp which have been evalu-ated as the strongest indicators of high levels of TN TP DOCCu and non-reference conditions (Tables 1 and 2 Figure 1)except for Stigeoclonium which did not fulfill statistical crite-ria because of its rare distribution in the study area

Selected soft-bodied algal metrics were incorporated in17 hybrid IBIs containing diatom metrics also and in 3 soft-bodied algal IBIs Some of the soft-bodied algal metrics in-cluded in the hybrid IBIs were designed to reduce laboratoryefforts such as species level taxonomy resolution without bio-volume estimate vs genus level identification with biovolumedata In addition 5 diatom IBIs were constructed from thesame data set The best performing IBI in regards to the dis-criminatory power among the three site disturbance classesand responsiveness to anthropogenic stress signal-to-noiseratio metric redundancy and degree of indifference to naturalgradients contains five diatom and three soft-bodied algal met-rics (species indicators of low TP high Cu and high DOC ex-

Fig 1 Diagram visualizing the opposite distributional trends of twoguild algal metrics along the generalized land use gradient used instream IBIs in California by Fetscher et al 2014 Legend Lower-lefttriangle indicates the ZHR guild metric consisting of Zygnemataceaeheterocystous cyanobacteria and red algae Upper-right triangle in-dicates the CRUS guild metric consisting of Cladophora glomerataL Rhizoclonium hieroglyphicum (C Agardh) Kuumltz Ulva flexuosaWulfen and Stigeoclonium spp Abbreviations see Table 1

pressed as relative species richness) The comparison betweenboth types of single-algal IBIs showed that the soft-bodied al-gal IBIs separate best the disturbed and intermediate sites andrespond negatively to canopy cover and slope while diatomIBIs discriminate better intermediate and reference sites butare responsive to more natural gradients such as stream or-der watershed area and percent fine substrate (Fetscher et al2014)

In summary the structural soft-bodied algal metrics cur-rently applied in stream IBIs are variable Depending onthe taxonomic method they can be expressed as relativebiovolume (Fetscher et al 2014) or relative abundance (basedon cell density Danielson et al 2011 Potapova and Carlisle2011) with live diatom cells included or not in the counts Itseems that empirically evaluated local soft-bodied algal indi-cator species and guild metrics best respond to anthropogenicstress Furthermore Fetscher et al (2014) demonstrated thatspecies level or lower taxonomic resolution is needed for

15 page 10 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

meaningful algal IBIs because they rely on soft-bodied in-dicator species not genera Hill et al (2003) suggested thatregardless of the approach taken the resulting index should becomposed of biological metrics that have clear relationship tospecific environmental stressors in consideration of their vari-ability at different spatial scales (reach stream river basin)

4 Soft-bodied algae as bioindicatorsof nutrients

Nutrients are a high-priority water quality concern be-cause they are a common cause of stream impairment Theyare typically monitored by discrete sampling of ambient con-centrations which can be highly variable even over a shortduration and these data are rarely indicative of the potentialfor ecosystem impacts (Whitton and Kelly 1995) Historicallytwo approaches have been taken with regards to biologicalmonitoring of nutrients an ecosystem approach in which algalbiomass and productivity are used to infer nutrient impact andan autecological approach in which indicator species and BIsare used as nutrient assessment tools (Borchardt 1996) In-deed functional algal attributes are less commonly used al-though they are informative for ecosystem condition (Kelly2013)

Nutrient enrichment typically stimulates algal growth inflowing waters and many studies demonstrate threshold algalresponse of approximately 30 microgmiddotLminus1 TP and 40 microgmiddotLminus1 TNabove which chlorophyll values are substantially higher (for areview see Dodds et al 1997 Stevenson et al 2012) Benthicchlorophyll values above 100 mgmiddotmminus2 have been consideredexcessive representing a critical level for an aesthetic nui-sance (Welch et al 1988) As system becomes more produc-tive different species of algae become more competitive in-cluding toxin-producing cyanobacteria (Fetscher et al 2015)and species composition shifts occur Usually nuisance algalgrowths in streams and rivers are monitored by quantitativesampling of algal biomass However algal-nutrient interac-tions should be interpreted with care because many studieshave shown that factors other than nutrients (eg light temper-ature substratum type and availability etc) could be more im-portant in determining algal biomass species composition andstructure (reviewed by Borchardt 1996) According to Biggs(1996) biomass loss in streams is a function of algal commu-nity age periodic sloughing losses of the mats large losses dueto disturbance events such as floods and grazing from inverte-brates and fish during prolonged periods of hydrological stabil-ity Therefore attempts to generate dissolved nutrient-benthicalgal biomass models should be considered carefully (for re-view see Biggs 2010)

On the other hand algal growth can be limited by scarcityof macronutrients and micronutrients but the most frequentlimiting factors are nitrogen (N) and phosphorus (P) becausedemand is high relative to their availability The concept ofsingle-nutrient limitation which postulates that an algal speciescan be limited by only one nutrient at a time does not usuallyapply to algal communities where diverse species may be lim-ited by different nutrients simultaneously (Borchardt 1996)Francoeur et al (1999) and Dodds and Welch (2000) showed

that N P or other nutrients can be colimiting for stream pe-riphyton Furthermore the availability of both nutrients mayvary geographically for instance P is in short supply in thenorth part of the US N in the Pacific Southwest and both nu-trients in the Pacific Northwest (Borchardt 1996 and literaturetherein)

Nutrient limitation both by P and N in streams is read-ily accessible by the functional responses of the benthic al-gal community such as alkaline phosphatase activity (APA)and atmospheric N fixation which are expected to decreasewith nutrient enrichment (Hill et al 2000 Stancheva et al2013b) Indeed APA measurements of entire periphyton inlarge-scale stream bioassessments showed contradicting re-sults (Hill et al 2000 2003 Griffith et al 2002 Table 2)which could be explained by multiple ecological processesoperating at different spatial and temporal scales in com-plex ecological systems (Pan et al 1999) According toMulholland and Rosemond (1992) APA is a valuable indi-cator of P limitation affecting algal species composition butdoes not consistently affect algal biomass (chlorophyll a totalbiovolume) and productivity (carbon fixation rate chlorophyll-specific carbon fixation rate)

Under conditions of moderate P limitation some freshwa-ter green algae such as Draparnaldia Chaetophora Stigeo-clonium (Gibson and Whitton 1987) and red algae eg Ba-trachospermum Sheathia Sirodotia (Sheath and Hambrook1990) form different types of ldquosurfacerdquo phosphatases (Whittonet al 1998) In addition they develop prominent hairs wherethe phosphatase is located functioning to increase the surfacearea of phosphorus uptake (Whitton 1988) This activity iseasy to assay for practical monitoring purposes by use of sub-strates such as p-nitrophenyl phosphate upon whose hydroly-sis releases the colored p-nitrophenol (Whitton 1991 Whittonet al 2002) Similarly conditions of inorganic phosphatedeficiency influence the trichome morphology of cyanobac-teria belonging to the Rivulariaceae by inducing formationof long colorless multicellular hairs which are the sites ofphosphomonoesterase activity for utilizing organic phosphates(Whitton and Mateo 2012) The members of Rivulariaceaealso possess heterocysts and are able to fix atmospheric ni-trogen during periods of high inorganic P supply (Whitton andMateo 2012) Mateo et al (2010) observed that in Pyreneescalcareous streams P limitation is the main chemical factor toinfluence benthic cyanobacterial communities including sev-eral heterocystous taxa of which Rivularia was the most abun-dant The authors proposed rapid methods for assessing long-term nutrient changes in a catchment combining observationson macroscopically visible cyanobacteria with assays of sur-face phosphatase activity (Mateo et al 2010)

N limitation of benthic algal communities from largestream data sets in southern California had been clearly indi-cated by the presence of N2-fixing heterocystous cyanobacteriaand coccoid cyanobaterial endosymbionts in diatoms Rhopalo-dia and Epithemia (Stancheva et al 2013b) Responsethresholds in N2-fixers biovolume and nitrogenase gene ex-pression obtained by real-time reverse transcriptase PCR were0075 mgmiddotLminus1 NO3-N 004 mgmiddotLminus1 NH4-N and an NP ra-tio (by weight) of 151 (Stancheva et al 2013b) Thus rapidquantitative microscopic and molecular methods for nutrient

15 page 11 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

monitoring can be based on N2-fixing cyanobacteria andendosymbiont-containing diatoms (Stancheva et al 2013b)If these rapid and simple approaches proposed by Whitton(1991) Mateo et al (2010) and Stancheva et al (2013b) are in-corporated in standard bioassessment of stream nutrient condi-tions they could be beneficial also in monitoring air pollution-related atmospheric nitrogen deposition which is a recognizedthreat to plant diversity in temperate and northern parts of Eu-rope and North America (Bobbink et al 2010) but its impacton stream ecosystems is largely unexplored

5 Concluding remarks

This review shows that soft-bodied algae are valuable in-dicators of stream and river water quality but holistic stud-ies including all algal taxonomic groups are not yet com-mon The structural taxonomic attributes of soft-bodied algalcommunities are good measures of anthropogenic stress butbetter understanding of the nature of this organism groupis needed to make it meaningful and easy-to-use standardbioassessment tools For instance Stevenson and Smol (2003)suggested that the precision of algal indicators is improvedwhen they are refined with regional datasets It is particu-larly important for soft-bodied algae which exhibit strongergeographical specialization than diatoms which makes theirapplicability more locally restricted (Potapova and Carlisle2011 Schneider et al 2012 Schneider and Rott 2013)

Another important consideration in soft-bodied algaebioassessment application is the quality of taxonomic identi-fications which is central to biological assessment The impactgenerated by taxonomical uncertainty and incompleteness usu-ally transcends the limits of ecology and environmental man-agement (Bortolus 2008) Large-scale bioassessment surveysare designed with the objective to produce statistically validassessments of biological conditions in streams (Hughes andPeck 2008) but the fundamental key piece of biological in-formation is a species of algae or any other organism selectedas an indicator Therefore field sampling and taxonomic anal-ysis should follow the best practices to provide a detailed listof microalgae and macroalgae identified to species level Theoptimal level of taxonomic resolution for stream biomonitor-ing is still debated (reviewed by Rimet and Bouchez 2012)Species level determination is considered the gold standardeven if there are some disadvantages of using precise taxo-nomic resolution mostly associated with high cost time andthe expertise demanded and the possibility for more errors inidentification (Konar and Iken 2009) Biovolume quantifica-tion of soft-bodied algae is important during the initial accrualof data for development of algal IBIs but metrics based onrelative rather than absolute values have stronger relationshipsto water quality and enable statistical significant evaluation ofecological tolerances (Danielson et al 2011 Fetscher et al2014)

Once the algal attributes such as an indicator species orstressor responsive ecological guilds are determined to be sta-tistically valid and included in IBIs as metrics reducing thetaxonomic efforts and cost for continuing routine monitoringmight be appropriate similarly to microinvertebrate bioasess-ment (Gartzia De Bikuntildea et al 2015) For example one of

the best performing hybrid IBIs for southern California in-cludes three soft-bodied algal metrics which do not requirebiovolume data but species level identification (Fetscher et al2014) thus the reduction of taxonomic analysis efforts is pos-sible by semi-quantitative estimate All successfully appliedBIs in European stream and river biomonitoring are based onalgal presence-absence species level data which confirmed theimportance of fine taxonomic resolution Further reduction oftaxonomy efforts is feasible for causal assessments such as ofnutrient condition which can be evaluated rapidly by micro-scopic or molecular methods based on ecological guilds suchas N2-fixing cyanobacteria alone or in combination with redalgae and Zygnemataceae (after Fetscher et al 2014) Devel-oping molecular methods for algal ecological guilds could bemore realistic option then the molecular bioassessment of al-gae community composition which is promising approach butnot applicable at this point (Manoylov 2014)

Acknowledgements Part of the discussed research was funded by theconsolidated grants and the SWAMP Program of the California StateWater Resources Control Board We thank both anonymous review-ers for their valuable comments which improved the quality of themanuscript

References

Acker F 2002 Analysis of Soft Algae and Enumeration of TotalNumber of Diatoms in USGS NAWQA Program QuantitativeTargeted-Habitat (RTH and DTH) Samples Protocol P-1363 InCharles DF Knowles C and Davis RS (eds) Protocols for theanalysis of algal samples collected as part of the US GeologicalSurvey National Water-Quality Assessment Program Report 02-06 Patrick Center for Environmental Research The Academy ofNatural Sciences Philadelphia

ANZECC 2000 National Water Quality Management StrategyThe Australian and New Zealand Guidelines for Fresh andMarine Water Quality Australian and New Zealand Environmentand Conservation Council and Agriculture and ResourseManagement Council of Australia and New Zealand CanberraAustralia

Biggs BJF 1987 Effects of sample storage and mechanical blend-ing on the quantitative analysis of river periphyton FreshwaterBiol 18 197ndash203

Biggs BJF 1996 Patterns in benthic algae of streams In StevensonRJ Bothwell ML and Lowe RL (eds) Algal EcologyFreshwater Benthic Ecosystems Academic Press San Diego31ndash56

Biggs BJF 2010 Eutrophication of streams and rivers dissolvednutrient-chlorophyll relationships for benthic algae J N AmBenthol Soc 19 17ndash31

Biggs BJF and Kilroy C 2000 Stream periphyton monitoringmanual National Institute of Water and Atmospheric Researchfor the New Zealand Ministry for the Environment viewed19 November 2013 available at httpwwwsmfgovtnzresults5092_periphytonmanualpdf

Bobbink R Hicks K Galloway J Spranger T Alkemade RAshmore M Bustamante M Cinderby S Davidson EDentener F Emmett B Erisman JW Fenn M Gilliam FNordin A Pardo L and De Vries W 2010 Global assessmentof nitrogen deposition effects on terrestrial plant diversity a syn-thesis Ecol Appl 20 30ndash59

15 page 12 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

Table 2 Continued

Soft-bodied algal IBI metric relationship Referencescommunity attribute with environmental variables

Nutrient contentAlgal CSA NSA PSA j

Nutrient stoichiometryCNSA jNPSA j o

Metabolic ratesAlkaline phosphatase activity agriculture in riparian zonec TPd canopyd all disturbance

in riparian zonec channel substrate width and depthdc d f

References Danielson et al 2011 (a) Fetscher et al 2014 (b) Hill et al 2000 (c) Hill et al 2003 (d) Porter et al 2008 (e) Griffith et al2002 (f) Leland and Porter 2001 (g) Munn et al 2002 (i) OlsquoBrien and Wehr 2010 (j) Pan et al 1999 (k) Stancheva et al 2012a (m)Stancheva et al 2013b (n) Vis et al 1998 (o) Abbreviations IBI ndash multimetric indices of biotic integrity RB ndash relative biovolume RA ndashrelative abundance based on cell numbers RSR ndash relative species richness SA ndash surface area CRUS ndash Cladophora glomerata + Rhizocloniumhieroglyphicum + Ulva flexuosa + Stigeoclonium spp ZHR ndash Zygnemataceae + heterocystous cyanobacteria + Rhodophyta DIN ndash dissolvedinorganic nitrogen TN-total nitrogen TP ndash total phosphorus DOC ndash dissolved organic carbon TSS ndash total suspended solids WT ndash watertemperature

the validation dataset because literature sources do not pro-vide sufficient autecological data Indicator species analysis(Dufrecircne and Legendre 1997) was performed on species abso-lute biovolume data There were 81 soft-bodied algal speciesidentified to correlate significantly with either low or highconcentrations of TP TN dissolved organic carbon (DOC)or dissolved copper (Cu) (see Table 1 for values of wa-ter chemistry parameters) Several soft-bodied algal metricspassed the screening process for IBI development includ-ing two indicator guilds with contrasting responses to localstressors each based on a subset of taxa with similar func-tion in the ecosystem The guild metric with negative re-sponse to increasing levels of generalized stressor combineda proportion of Zygnemataceae heterocystous cyanobacteriaand red algae in agreement with previous observations thateach group is sensitive to particular nutrient or other waterchemistry constituents (Stancheva et al 2012a) The oppositemetric consists of proportions of Cladophora glomerata LRhizoclonium hieroglyphicum (C Agardh) Kuumltz Ulva flexu-osa Wulfen and Stigeoclonium spp which have been evalu-ated as the strongest indicators of high levels of TN TP DOCCu and non-reference conditions (Tables 1 and 2 Figure 1)except for Stigeoclonium which did not fulfill statistical crite-ria because of its rare distribution in the study area

Selected soft-bodied algal metrics were incorporated in17 hybrid IBIs containing diatom metrics also and in 3 soft-bodied algal IBIs Some of the soft-bodied algal metrics in-cluded in the hybrid IBIs were designed to reduce laboratoryefforts such as species level taxonomy resolution without bio-volume estimate vs genus level identification with biovolumedata In addition 5 diatom IBIs were constructed from thesame data set The best performing IBI in regards to the dis-criminatory power among the three site disturbance classesand responsiveness to anthropogenic stress signal-to-noiseratio metric redundancy and degree of indifference to naturalgradients contains five diatom and three soft-bodied algal met-rics (species indicators of low TP high Cu and high DOC ex-

Fig 1 Diagram visualizing the opposite distributional trends of twoguild algal metrics along the generalized land use gradient used instream IBIs in California by Fetscher et al 2014 Legend Lower-lefttriangle indicates the ZHR guild metric consisting of Zygnemataceaeheterocystous cyanobacteria and red algae Upper-right triangle in-dicates the CRUS guild metric consisting of Cladophora glomerataL Rhizoclonium hieroglyphicum (C Agardh) Kuumltz Ulva flexuosaWulfen and Stigeoclonium spp Abbreviations see Table 1

pressed as relative species richness) The comparison betweenboth types of single-algal IBIs showed that the soft-bodied al-gal IBIs separate best the disturbed and intermediate sites andrespond negatively to canopy cover and slope while diatomIBIs discriminate better intermediate and reference sites butare responsive to more natural gradients such as stream or-der watershed area and percent fine substrate (Fetscher et al2014)

In summary the structural soft-bodied algal metrics cur-rently applied in stream IBIs are variable Depending onthe taxonomic method they can be expressed as relativebiovolume (Fetscher et al 2014) or relative abundance (basedon cell density Danielson et al 2011 Potapova and Carlisle2011) with live diatom cells included or not in the counts Itseems that empirically evaluated local soft-bodied algal indi-cator species and guild metrics best respond to anthropogenicstress Furthermore Fetscher et al (2014) demonstrated thatspecies level or lower taxonomic resolution is needed for

15 page 10 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

meaningful algal IBIs because they rely on soft-bodied in-dicator species not genera Hill et al (2003) suggested thatregardless of the approach taken the resulting index should becomposed of biological metrics that have clear relationship tospecific environmental stressors in consideration of their vari-ability at different spatial scales (reach stream river basin)

4 Soft-bodied algae as bioindicatorsof nutrients

Nutrients are a high-priority water quality concern be-cause they are a common cause of stream impairment Theyare typically monitored by discrete sampling of ambient con-centrations which can be highly variable even over a shortduration and these data are rarely indicative of the potentialfor ecosystem impacts (Whitton and Kelly 1995) Historicallytwo approaches have been taken with regards to biologicalmonitoring of nutrients an ecosystem approach in which algalbiomass and productivity are used to infer nutrient impact andan autecological approach in which indicator species and BIsare used as nutrient assessment tools (Borchardt 1996) In-deed functional algal attributes are less commonly used al-though they are informative for ecosystem condition (Kelly2013)

Nutrient enrichment typically stimulates algal growth inflowing waters and many studies demonstrate threshold algalresponse of approximately 30 microgmiddotLminus1 TP and 40 microgmiddotLminus1 TNabove which chlorophyll values are substantially higher (for areview see Dodds et al 1997 Stevenson et al 2012) Benthicchlorophyll values above 100 mgmiddotmminus2 have been consideredexcessive representing a critical level for an aesthetic nui-sance (Welch et al 1988) As system becomes more produc-tive different species of algae become more competitive in-cluding toxin-producing cyanobacteria (Fetscher et al 2015)and species composition shifts occur Usually nuisance algalgrowths in streams and rivers are monitored by quantitativesampling of algal biomass However algal-nutrient interac-tions should be interpreted with care because many studieshave shown that factors other than nutrients (eg light temper-ature substratum type and availability etc) could be more im-portant in determining algal biomass species composition andstructure (reviewed by Borchardt 1996) According to Biggs(1996) biomass loss in streams is a function of algal commu-nity age periodic sloughing losses of the mats large losses dueto disturbance events such as floods and grazing from inverte-brates and fish during prolonged periods of hydrological stabil-ity Therefore attempts to generate dissolved nutrient-benthicalgal biomass models should be considered carefully (for re-view see Biggs 2010)

On the other hand algal growth can be limited by scarcityof macronutrients and micronutrients but the most frequentlimiting factors are nitrogen (N) and phosphorus (P) becausedemand is high relative to their availability The concept ofsingle-nutrient limitation which postulates that an algal speciescan be limited by only one nutrient at a time does not usuallyapply to algal communities where diverse species may be lim-ited by different nutrients simultaneously (Borchardt 1996)Francoeur et al (1999) and Dodds and Welch (2000) showed

that N P or other nutrients can be colimiting for stream pe-riphyton Furthermore the availability of both nutrients mayvary geographically for instance P is in short supply in thenorth part of the US N in the Pacific Southwest and both nu-trients in the Pacific Northwest (Borchardt 1996 and literaturetherein)

Nutrient limitation both by P and N in streams is read-ily accessible by the functional responses of the benthic al-gal community such as alkaline phosphatase activity (APA)and atmospheric N fixation which are expected to decreasewith nutrient enrichment (Hill et al 2000 Stancheva et al2013b) Indeed APA measurements of entire periphyton inlarge-scale stream bioassessments showed contradicting re-sults (Hill et al 2000 2003 Griffith et al 2002 Table 2)which could be explained by multiple ecological processesoperating at different spatial and temporal scales in com-plex ecological systems (Pan et al 1999) According toMulholland and Rosemond (1992) APA is a valuable indi-cator of P limitation affecting algal species composition butdoes not consistently affect algal biomass (chlorophyll a totalbiovolume) and productivity (carbon fixation rate chlorophyll-specific carbon fixation rate)

Under conditions of moderate P limitation some freshwa-ter green algae such as Draparnaldia Chaetophora Stigeo-clonium (Gibson and Whitton 1987) and red algae eg Ba-trachospermum Sheathia Sirodotia (Sheath and Hambrook1990) form different types of ldquosurfacerdquo phosphatases (Whittonet al 1998) In addition they develop prominent hairs wherethe phosphatase is located functioning to increase the surfacearea of phosphorus uptake (Whitton 1988) This activity iseasy to assay for practical monitoring purposes by use of sub-strates such as p-nitrophenyl phosphate upon whose hydroly-sis releases the colored p-nitrophenol (Whitton 1991 Whittonet al 2002) Similarly conditions of inorganic phosphatedeficiency influence the trichome morphology of cyanobac-teria belonging to the Rivulariaceae by inducing formationof long colorless multicellular hairs which are the sites ofphosphomonoesterase activity for utilizing organic phosphates(Whitton and Mateo 2012) The members of Rivulariaceaealso possess heterocysts and are able to fix atmospheric ni-trogen during periods of high inorganic P supply (Whitton andMateo 2012) Mateo et al (2010) observed that in Pyreneescalcareous streams P limitation is the main chemical factor toinfluence benthic cyanobacterial communities including sev-eral heterocystous taxa of which Rivularia was the most abun-dant The authors proposed rapid methods for assessing long-term nutrient changes in a catchment combining observationson macroscopically visible cyanobacteria with assays of sur-face phosphatase activity (Mateo et al 2010)

N limitation of benthic algal communities from largestream data sets in southern California had been clearly indi-cated by the presence of N2-fixing heterocystous cyanobacteriaand coccoid cyanobaterial endosymbionts in diatoms Rhopalo-dia and Epithemia (Stancheva et al 2013b) Responsethresholds in N2-fixers biovolume and nitrogenase gene ex-pression obtained by real-time reverse transcriptase PCR were0075 mgmiddotLminus1 NO3-N 004 mgmiddotLminus1 NH4-N and an NP ra-tio (by weight) of 151 (Stancheva et al 2013b) Thus rapidquantitative microscopic and molecular methods for nutrient

15 page 11 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

monitoring can be based on N2-fixing cyanobacteria andendosymbiont-containing diatoms (Stancheva et al 2013b)If these rapid and simple approaches proposed by Whitton(1991) Mateo et al (2010) and Stancheva et al (2013b) are in-corporated in standard bioassessment of stream nutrient condi-tions they could be beneficial also in monitoring air pollution-related atmospheric nitrogen deposition which is a recognizedthreat to plant diversity in temperate and northern parts of Eu-rope and North America (Bobbink et al 2010) but its impacton stream ecosystems is largely unexplored

5 Concluding remarks

This review shows that soft-bodied algae are valuable in-dicators of stream and river water quality but holistic stud-ies including all algal taxonomic groups are not yet com-mon The structural taxonomic attributes of soft-bodied algalcommunities are good measures of anthropogenic stress butbetter understanding of the nature of this organism groupis needed to make it meaningful and easy-to-use standardbioassessment tools For instance Stevenson and Smol (2003)suggested that the precision of algal indicators is improvedwhen they are refined with regional datasets It is particu-larly important for soft-bodied algae which exhibit strongergeographical specialization than diatoms which makes theirapplicability more locally restricted (Potapova and Carlisle2011 Schneider et al 2012 Schneider and Rott 2013)

Another important consideration in soft-bodied algaebioassessment application is the quality of taxonomic identi-fications which is central to biological assessment The impactgenerated by taxonomical uncertainty and incompleteness usu-ally transcends the limits of ecology and environmental man-agement (Bortolus 2008) Large-scale bioassessment surveysare designed with the objective to produce statistically validassessments of biological conditions in streams (Hughes andPeck 2008) but the fundamental key piece of biological in-formation is a species of algae or any other organism selectedas an indicator Therefore field sampling and taxonomic anal-ysis should follow the best practices to provide a detailed listof microalgae and macroalgae identified to species level Theoptimal level of taxonomic resolution for stream biomonitor-ing is still debated (reviewed by Rimet and Bouchez 2012)Species level determination is considered the gold standardeven if there are some disadvantages of using precise taxo-nomic resolution mostly associated with high cost time andthe expertise demanded and the possibility for more errors inidentification (Konar and Iken 2009) Biovolume quantifica-tion of soft-bodied algae is important during the initial accrualof data for development of algal IBIs but metrics based onrelative rather than absolute values have stronger relationshipsto water quality and enable statistical significant evaluation ofecological tolerances (Danielson et al 2011 Fetscher et al2014)

Once the algal attributes such as an indicator species orstressor responsive ecological guilds are determined to be sta-tistically valid and included in IBIs as metrics reducing thetaxonomic efforts and cost for continuing routine monitoringmight be appropriate similarly to microinvertebrate bioasess-ment (Gartzia De Bikuntildea et al 2015) For example one of

the best performing hybrid IBIs for southern California in-cludes three soft-bodied algal metrics which do not requirebiovolume data but species level identification (Fetscher et al2014) thus the reduction of taxonomic analysis efforts is pos-sible by semi-quantitative estimate All successfully appliedBIs in European stream and river biomonitoring are based onalgal presence-absence species level data which confirmed theimportance of fine taxonomic resolution Further reduction oftaxonomy efforts is feasible for causal assessments such as ofnutrient condition which can be evaluated rapidly by micro-scopic or molecular methods based on ecological guilds suchas N2-fixing cyanobacteria alone or in combination with redalgae and Zygnemataceae (after Fetscher et al 2014) Devel-oping molecular methods for algal ecological guilds could bemore realistic option then the molecular bioassessment of al-gae community composition which is promising approach butnot applicable at this point (Manoylov 2014)

Acknowledgements Part of the discussed research was funded by theconsolidated grants and the SWAMP Program of the California StateWater Resources Control Board We thank both anonymous review-ers for their valuable comments which improved the quality of themanuscript

References

Acker F 2002 Analysis of Soft Algae and Enumeration of TotalNumber of Diatoms in USGS NAWQA Program QuantitativeTargeted-Habitat (RTH and DTH) Samples Protocol P-1363 InCharles DF Knowles C and Davis RS (eds) Protocols for theanalysis of algal samples collected as part of the US GeologicalSurvey National Water-Quality Assessment Program Report 02-06 Patrick Center for Environmental Research The Academy ofNatural Sciences Philadelphia

ANZECC 2000 National Water Quality Management StrategyThe Australian and New Zealand Guidelines for Fresh andMarine Water Quality Australian and New Zealand Environmentand Conservation Council and Agriculture and ResourseManagement Council of Australia and New Zealand CanberraAustralia

Biggs BJF 1987 Effects of sample storage and mechanical blend-ing on the quantitative analysis of river periphyton FreshwaterBiol 18 197ndash203

Biggs BJF 1996 Patterns in benthic algae of streams In StevensonRJ Bothwell ML and Lowe RL (eds) Algal EcologyFreshwater Benthic Ecosystems Academic Press San Diego31ndash56

Biggs BJF 2010 Eutrophication of streams and rivers dissolvednutrient-chlorophyll relationships for benthic algae J N AmBenthol Soc 19 17ndash31

Biggs BJF and Kilroy C 2000 Stream periphyton monitoringmanual National Institute of Water and Atmospheric Researchfor the New Zealand Ministry for the Environment viewed19 November 2013 available at httpwwwsmfgovtnzresults5092_periphytonmanualpdf

Bobbink R Hicks K Galloway J Spranger T Alkemade RAshmore M Bustamante M Cinderby S Davidson EDentener F Emmett B Erisman JW Fenn M Gilliam FNordin A Pardo L and De Vries W 2010 Global assessmentof nitrogen deposition effects on terrestrial plant diversity a syn-thesis Ecol Appl 20 30ndash59

15 page 12 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

meaningful algal IBIs because they rely on soft-bodied in-dicator species not genera Hill et al (2003) suggested thatregardless of the approach taken the resulting index should becomposed of biological metrics that have clear relationship tospecific environmental stressors in consideration of their vari-ability at different spatial scales (reach stream river basin)

4 Soft-bodied algae as bioindicatorsof nutrients

Nutrients are a high-priority water quality concern be-cause they are a common cause of stream impairment Theyare typically monitored by discrete sampling of ambient con-centrations which can be highly variable even over a shortduration and these data are rarely indicative of the potentialfor ecosystem impacts (Whitton and Kelly 1995) Historicallytwo approaches have been taken with regards to biologicalmonitoring of nutrients an ecosystem approach in which algalbiomass and productivity are used to infer nutrient impact andan autecological approach in which indicator species and BIsare used as nutrient assessment tools (Borchardt 1996) In-deed functional algal attributes are less commonly used al-though they are informative for ecosystem condition (Kelly2013)

Nutrient enrichment typically stimulates algal growth inflowing waters and many studies demonstrate threshold algalresponse of approximately 30 microgmiddotLminus1 TP and 40 microgmiddotLminus1 TNabove which chlorophyll values are substantially higher (for areview see Dodds et al 1997 Stevenson et al 2012) Benthicchlorophyll values above 100 mgmiddotmminus2 have been consideredexcessive representing a critical level for an aesthetic nui-sance (Welch et al 1988) As system becomes more produc-tive different species of algae become more competitive in-cluding toxin-producing cyanobacteria (Fetscher et al 2015)and species composition shifts occur Usually nuisance algalgrowths in streams and rivers are monitored by quantitativesampling of algal biomass However algal-nutrient interac-tions should be interpreted with care because many studieshave shown that factors other than nutrients (eg light temper-ature substratum type and availability etc) could be more im-portant in determining algal biomass species composition andstructure (reviewed by Borchardt 1996) According to Biggs(1996) biomass loss in streams is a function of algal commu-nity age periodic sloughing losses of the mats large losses dueto disturbance events such as floods and grazing from inverte-brates and fish during prolonged periods of hydrological stabil-ity Therefore attempts to generate dissolved nutrient-benthicalgal biomass models should be considered carefully (for re-view see Biggs 2010)

On the other hand algal growth can be limited by scarcityof macronutrients and micronutrients but the most frequentlimiting factors are nitrogen (N) and phosphorus (P) becausedemand is high relative to their availability The concept ofsingle-nutrient limitation which postulates that an algal speciescan be limited by only one nutrient at a time does not usuallyapply to algal communities where diverse species may be lim-ited by different nutrients simultaneously (Borchardt 1996)Francoeur et al (1999) and Dodds and Welch (2000) showed

that N P or other nutrients can be colimiting for stream pe-riphyton Furthermore the availability of both nutrients mayvary geographically for instance P is in short supply in thenorth part of the US N in the Pacific Southwest and both nu-trients in the Pacific Northwest (Borchardt 1996 and literaturetherein)

Nutrient limitation both by P and N in streams is read-ily accessible by the functional responses of the benthic al-gal community such as alkaline phosphatase activity (APA)and atmospheric N fixation which are expected to decreasewith nutrient enrichment (Hill et al 2000 Stancheva et al2013b) Indeed APA measurements of entire periphyton inlarge-scale stream bioassessments showed contradicting re-sults (Hill et al 2000 2003 Griffith et al 2002 Table 2)which could be explained by multiple ecological processesoperating at different spatial and temporal scales in com-plex ecological systems (Pan et al 1999) According toMulholland and Rosemond (1992) APA is a valuable indi-cator of P limitation affecting algal species composition butdoes not consistently affect algal biomass (chlorophyll a totalbiovolume) and productivity (carbon fixation rate chlorophyll-specific carbon fixation rate)

Under conditions of moderate P limitation some freshwa-ter green algae such as Draparnaldia Chaetophora Stigeo-clonium (Gibson and Whitton 1987) and red algae eg Ba-trachospermum Sheathia Sirodotia (Sheath and Hambrook1990) form different types of ldquosurfacerdquo phosphatases (Whittonet al 1998) In addition they develop prominent hairs wherethe phosphatase is located functioning to increase the surfacearea of phosphorus uptake (Whitton 1988) This activity iseasy to assay for practical monitoring purposes by use of sub-strates such as p-nitrophenyl phosphate upon whose hydroly-sis releases the colored p-nitrophenol (Whitton 1991 Whittonet al 2002) Similarly conditions of inorganic phosphatedeficiency influence the trichome morphology of cyanobac-teria belonging to the Rivulariaceae by inducing formationof long colorless multicellular hairs which are the sites ofphosphomonoesterase activity for utilizing organic phosphates(Whitton and Mateo 2012) The members of Rivulariaceaealso possess heterocysts and are able to fix atmospheric ni-trogen during periods of high inorganic P supply (Whitton andMateo 2012) Mateo et al (2010) observed that in Pyreneescalcareous streams P limitation is the main chemical factor toinfluence benthic cyanobacterial communities including sev-eral heterocystous taxa of which Rivularia was the most abun-dant The authors proposed rapid methods for assessing long-term nutrient changes in a catchment combining observationson macroscopically visible cyanobacteria with assays of sur-face phosphatase activity (Mateo et al 2010)

N limitation of benthic algal communities from largestream data sets in southern California had been clearly indi-cated by the presence of N2-fixing heterocystous cyanobacteriaand coccoid cyanobaterial endosymbionts in diatoms Rhopalo-dia and Epithemia (Stancheva et al 2013b) Responsethresholds in N2-fixers biovolume and nitrogenase gene ex-pression obtained by real-time reverse transcriptase PCR were0075 mgmiddotLminus1 NO3-N 004 mgmiddotLminus1 NH4-N and an NP ra-tio (by weight) of 151 (Stancheva et al 2013b) Thus rapidquantitative microscopic and molecular methods for nutrient

15 page 11 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

monitoring can be based on N2-fixing cyanobacteria andendosymbiont-containing diatoms (Stancheva et al 2013b)If these rapid and simple approaches proposed by Whitton(1991) Mateo et al (2010) and Stancheva et al (2013b) are in-corporated in standard bioassessment of stream nutrient condi-tions they could be beneficial also in monitoring air pollution-related atmospheric nitrogen deposition which is a recognizedthreat to plant diversity in temperate and northern parts of Eu-rope and North America (Bobbink et al 2010) but its impacton stream ecosystems is largely unexplored

5 Concluding remarks

This review shows that soft-bodied algae are valuable in-dicators of stream and river water quality but holistic stud-ies including all algal taxonomic groups are not yet com-mon The structural taxonomic attributes of soft-bodied algalcommunities are good measures of anthropogenic stress butbetter understanding of the nature of this organism groupis needed to make it meaningful and easy-to-use standardbioassessment tools For instance Stevenson and Smol (2003)suggested that the precision of algal indicators is improvedwhen they are refined with regional datasets It is particu-larly important for soft-bodied algae which exhibit strongergeographical specialization than diatoms which makes theirapplicability more locally restricted (Potapova and Carlisle2011 Schneider et al 2012 Schneider and Rott 2013)

Another important consideration in soft-bodied algaebioassessment application is the quality of taxonomic identi-fications which is central to biological assessment The impactgenerated by taxonomical uncertainty and incompleteness usu-ally transcends the limits of ecology and environmental man-agement (Bortolus 2008) Large-scale bioassessment surveysare designed with the objective to produce statistically validassessments of biological conditions in streams (Hughes andPeck 2008) but the fundamental key piece of biological in-formation is a species of algae or any other organism selectedas an indicator Therefore field sampling and taxonomic anal-ysis should follow the best practices to provide a detailed listof microalgae and macroalgae identified to species level Theoptimal level of taxonomic resolution for stream biomonitor-ing is still debated (reviewed by Rimet and Bouchez 2012)Species level determination is considered the gold standardeven if there are some disadvantages of using precise taxo-nomic resolution mostly associated with high cost time andthe expertise demanded and the possibility for more errors inidentification (Konar and Iken 2009) Biovolume quantifica-tion of soft-bodied algae is important during the initial accrualof data for development of algal IBIs but metrics based onrelative rather than absolute values have stronger relationshipsto water quality and enable statistical significant evaluation ofecological tolerances (Danielson et al 2011 Fetscher et al2014)

Once the algal attributes such as an indicator species orstressor responsive ecological guilds are determined to be sta-tistically valid and included in IBIs as metrics reducing thetaxonomic efforts and cost for continuing routine monitoringmight be appropriate similarly to microinvertebrate bioasess-ment (Gartzia De Bikuntildea et al 2015) For example one of

the best performing hybrid IBIs for southern California in-cludes three soft-bodied algal metrics which do not requirebiovolume data but species level identification (Fetscher et al2014) thus the reduction of taxonomic analysis efforts is pos-sible by semi-quantitative estimate All successfully appliedBIs in European stream and river biomonitoring are based onalgal presence-absence species level data which confirmed theimportance of fine taxonomic resolution Further reduction oftaxonomy efforts is feasible for causal assessments such as ofnutrient condition which can be evaluated rapidly by micro-scopic or molecular methods based on ecological guilds suchas N2-fixing cyanobacteria alone or in combination with redalgae and Zygnemataceae (after Fetscher et al 2014) Devel-oping molecular methods for algal ecological guilds could bemore realistic option then the molecular bioassessment of al-gae community composition which is promising approach butnot applicable at this point (Manoylov 2014)

Acknowledgements Part of the discussed research was funded by theconsolidated grants and the SWAMP Program of the California StateWater Resources Control Board We thank both anonymous review-ers for their valuable comments which improved the quality of themanuscript

References

Acker F 2002 Analysis of Soft Algae and Enumeration of TotalNumber of Diatoms in USGS NAWQA Program QuantitativeTargeted-Habitat (RTH and DTH) Samples Protocol P-1363 InCharles DF Knowles C and Davis RS (eds) Protocols for theanalysis of algal samples collected as part of the US GeologicalSurvey National Water-Quality Assessment Program Report 02-06 Patrick Center for Environmental Research The Academy ofNatural Sciences Philadelphia

ANZECC 2000 National Water Quality Management StrategyThe Australian and New Zealand Guidelines for Fresh andMarine Water Quality Australian and New Zealand Environmentand Conservation Council and Agriculture and ResourseManagement Council of Australia and New Zealand CanberraAustralia

Biggs BJF 1987 Effects of sample storage and mechanical blend-ing on the quantitative analysis of river periphyton FreshwaterBiol 18 197ndash203

Biggs BJF 1996 Patterns in benthic algae of streams In StevensonRJ Bothwell ML and Lowe RL (eds) Algal EcologyFreshwater Benthic Ecosystems Academic Press San Diego31ndash56

Biggs BJF 2010 Eutrophication of streams and rivers dissolvednutrient-chlorophyll relationships for benthic algae J N AmBenthol Soc 19 17ndash31

Biggs BJF and Kilroy C 2000 Stream periphyton monitoringmanual National Institute of Water and Atmospheric Researchfor the New Zealand Ministry for the Environment viewed19 November 2013 available at httpwwwsmfgovtnzresults5092_periphytonmanualpdf

Bobbink R Hicks K Galloway J Spranger T Alkemade RAshmore M Bustamante M Cinderby S Davidson EDentener F Emmett B Erisman JW Fenn M Gilliam FNordin A Pardo L and De Vries W 2010 Global assessmentof nitrogen deposition effects on terrestrial plant diversity a syn-thesis Ecol Appl 20 30ndash59

15 page 12 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

monitoring can be based on N2-fixing cyanobacteria andendosymbiont-containing diatoms (Stancheva et al 2013b)If these rapid and simple approaches proposed by Whitton(1991) Mateo et al (2010) and Stancheva et al (2013b) are in-corporated in standard bioassessment of stream nutrient condi-tions they could be beneficial also in monitoring air pollution-related atmospheric nitrogen deposition which is a recognizedthreat to plant diversity in temperate and northern parts of Eu-rope and North America (Bobbink et al 2010) but its impacton stream ecosystems is largely unexplored

5 Concluding remarks

This review shows that soft-bodied algae are valuable in-dicators of stream and river water quality but holistic stud-ies including all algal taxonomic groups are not yet com-mon The structural taxonomic attributes of soft-bodied algalcommunities are good measures of anthropogenic stress butbetter understanding of the nature of this organism groupis needed to make it meaningful and easy-to-use standardbioassessment tools For instance Stevenson and Smol (2003)suggested that the precision of algal indicators is improvedwhen they are refined with regional datasets It is particu-larly important for soft-bodied algae which exhibit strongergeographical specialization than diatoms which makes theirapplicability more locally restricted (Potapova and Carlisle2011 Schneider et al 2012 Schneider and Rott 2013)

Another important consideration in soft-bodied algaebioassessment application is the quality of taxonomic identi-fications which is central to biological assessment The impactgenerated by taxonomical uncertainty and incompleteness usu-ally transcends the limits of ecology and environmental man-agement (Bortolus 2008) Large-scale bioassessment surveysare designed with the objective to produce statistically validassessments of biological conditions in streams (Hughes andPeck 2008) but the fundamental key piece of biological in-formation is a species of algae or any other organism selectedas an indicator Therefore field sampling and taxonomic anal-ysis should follow the best practices to provide a detailed listof microalgae and macroalgae identified to species level Theoptimal level of taxonomic resolution for stream biomonitor-ing is still debated (reviewed by Rimet and Bouchez 2012)Species level determination is considered the gold standardeven if there are some disadvantages of using precise taxo-nomic resolution mostly associated with high cost time andthe expertise demanded and the possibility for more errors inidentification (Konar and Iken 2009) Biovolume quantifica-tion of soft-bodied algae is important during the initial accrualof data for development of algal IBIs but metrics based onrelative rather than absolute values have stronger relationshipsto water quality and enable statistical significant evaluation ofecological tolerances (Danielson et al 2011 Fetscher et al2014)

Once the algal attributes such as an indicator species orstressor responsive ecological guilds are determined to be sta-tistically valid and included in IBIs as metrics reducing thetaxonomic efforts and cost for continuing routine monitoringmight be appropriate similarly to microinvertebrate bioasess-ment (Gartzia De Bikuntildea et al 2015) For example one of

the best performing hybrid IBIs for southern California in-cludes three soft-bodied algal metrics which do not requirebiovolume data but species level identification (Fetscher et al2014) thus the reduction of taxonomic analysis efforts is pos-sible by semi-quantitative estimate All successfully appliedBIs in European stream and river biomonitoring are based onalgal presence-absence species level data which confirmed theimportance of fine taxonomic resolution Further reduction oftaxonomy efforts is feasible for causal assessments such as ofnutrient condition which can be evaluated rapidly by micro-scopic or molecular methods based on ecological guilds suchas N2-fixing cyanobacteria alone or in combination with redalgae and Zygnemataceae (after Fetscher et al 2014) Devel-oping molecular methods for algal ecological guilds could bemore realistic option then the molecular bioassessment of al-gae community composition which is promising approach butnot applicable at this point (Manoylov 2014)

Acknowledgements Part of the discussed research was funded by theconsolidated grants and the SWAMP Program of the California StateWater Resources Control Board We thank both anonymous review-ers for their valuable comments which improved the quality of themanuscript

References

Acker F 2002 Analysis of Soft Algae and Enumeration of TotalNumber of Diatoms in USGS NAWQA Program QuantitativeTargeted-Habitat (RTH and DTH) Samples Protocol P-1363 InCharles DF Knowles C and Davis RS (eds) Protocols for theanalysis of algal samples collected as part of the US GeologicalSurvey National Water-Quality Assessment Program Report 02-06 Patrick Center for Environmental Research The Academy ofNatural Sciences Philadelphia

ANZECC 2000 National Water Quality Management StrategyThe Australian and New Zealand Guidelines for Fresh andMarine Water Quality Australian and New Zealand Environmentand Conservation Council and Agriculture and ResourseManagement Council of Australia and New Zealand CanberraAustralia

Biggs BJF 1987 Effects of sample storage and mechanical blend-ing on the quantitative analysis of river periphyton FreshwaterBiol 18 197ndash203

Biggs BJF 1996 Patterns in benthic algae of streams In StevensonRJ Bothwell ML and Lowe RL (eds) Algal EcologyFreshwater Benthic Ecosystems Academic Press San Diego31ndash56

Biggs BJF 2010 Eutrophication of streams and rivers dissolvednutrient-chlorophyll relationships for benthic algae J N AmBenthol Soc 19 17ndash31

Biggs BJF and Kilroy C 2000 Stream periphyton monitoringmanual National Institute of Water and Atmospheric Researchfor the New Zealand Ministry for the Environment viewed19 November 2013 available at httpwwwsmfgovtnzresults5092_periphytonmanualpdf

Bobbink R Hicks K Galloway J Spranger T Alkemade RAshmore M Bustamante M Cinderby S Davidson EDentener F Emmett B Erisman JW Fenn M Gilliam FNordin A Pardo L and De Vries W 2010 Global assessmentof nitrogen deposition effects on terrestrial plant diversity a syn-thesis Ecol Appl 20 30ndash59

15 page 12 of 16

R Stancheva and RG Sheath Knowl Manag Aquat Ecosyst (2016) 417 15

Borchardt MA 1996 Nutrients In Stevenson RJ BothwellML and Lowe RL (eds) Algal Ecology Freshwater BenthicEcosystems Academic Press San Diego 184ndash228

Bortolus A 2008 Error cascades in the biological sciences the un-wanted consequences of using bad taxonomy in ecology Ambio37 114ndash118

Brown LR May JT and Hunsaker CT 2008 Species compo-sition and habitat associations of benthic algal assemblages inheadwater streams of the Sierra Nevada California West N AmNaturalist 68 194ndash209

Cairns JJ and Pratt JR 1993 A history of biological monitoringusing benthic macroinvertebrates In Rosenberg DM and ReshVH (eds) Freshwater biomonitoring and benthic macroinverte-brates Chapman and Hall New York 10ndash28

Clean Water Act 1972 Federal Water Pollution Control Act ndashAmendments of 1972 Public Law 92-50033USC1251

Danielson TJ Loftin CS Tsomides L DiFranco JL and ConnorsB 2011 Algal bioassessment metrics for wadeable streams andrivers of Maine USA J N Am Benthol Soc 30 1033ndash1048

Delgardo C Pardo I and Liliana G 2010 A multimetric diatom in-dex to assess the ecological status of coastal Galician rivers (NWSpain) Hydrobiologia 644 371ndash384

Dodds WK and Welch EB 2000 Establishing nutrient criteria instreams J N Am Benthol Soc 19 186ndash196

Dodds WK Smith VH and Zander B 1997 Developing nutrienttargets to control benthic chlorophyll levels in streams a casestudy of the Clark Fork River Water Res 31 1738ndash1750

Doleacutedec S and Statzner B 2010 Responses of freshwater biotato human disturbances contribution of J-NABS to developmentsin ecological integrity assessments J N Am Benthol Soc 29286ndash311

Douterelo I Perona E and Mateo P 2004 Use of cyanobacteriato assess water quality in running waters Environ Pollut 127377ndash384

Drummond CS Hall JD Karol KG Delwiche CF andMcCourt RM 2005 Phylogeny of Spirogyra and Sirogonium(Zygnematophyceae) based on rbcL sequence data J Phycol41 1055ndash1064

Dufrecircne M and Legendre P 1997 Species assemblages and indica-tor species the need for a flexible asymmetrical approach EcolMonogr 67 345ndash366

European Commission 2000 Directive 200060EC of the EuropeanParlament and Council establishing a framework for Communityaction in the field of water policy Official Journal of theEuropean Community 327 1ndash72

Fernandez-Pintildeas F Leganeacutes F Mateo P and Bonilla I 1991 Blue-green algae (cyanobacteria) as indicators of water quality intwo Spanish rivers In Whitton BA Rott E and Friedrich G(eds) Use of algae for monitoring rivers Institut fuumlr BotanikUniversitaumlt Innsbruck Innsbruck 151ndash156

Fetscher AE Busse LB and Ode PR 2009 Standard operat-ing procedure for collecting stream algae samples and associ-ated physical habitat and chemical data for ambient bioassess-ments in California California State Water Resources ControlBoard Surface Water Ambient Monitoring Program (SWAMP)Bioassessment SOP 002

Fetscher AE Sutula MA Busse LB and Stein ED 2013Condition of California perennial wadeable streams based onalgal indicators California State Water Resources Control BoardSurface Water Ambient Monitoring Program (SWAMP) FinalTechnical Report

Fetscher AE Stancheva R Kociolek JP Sheath RG Stein EDMazor RD Ode PR and Busse LB 2014 Development and

comparison of stream indices of biotic integrity using diatoms vsnon-diatom algae vs a combination J Appl Phycol 26 433ndash450

Fetscher AE Howard MDA Stancheva R Kudela RM SteinED Sutula MA Busse LB Sheath RG 2015 Wadeablestreams as widespread sources of benthic cyanotoxin productionin California USA Harmful Algae 49 105ndash116

Foerster J Gutowski Aand Schaumburg J 2004 Defining types ofrunning waters in Germany using benthic algae a prerequisite formonitoring according to the Water Framework Directive J ApplPhycol 16 407ndash418

Fore LS Karr JR and Conquest LL 1994 Statistical properties ofan index of biotic integrity used to evaluate water resources CanJ Fish Aquat Sci 51 1077ndash1087

Francoeur SN Biggs BJF Smith RA and Lowe RL 1999Nutrient limitation of algal biomass accrual in streams seasonalpatterns and a comparison of methods J N Am Benthol Soc18 242ndash260

Frey DG 1977 Biological integrity of water a historical ap-proach In Ballentine RK and Guarraia LJ (eds) The integrityof water a symposium US Environmental Protection AgencyWashington DC

Gartzia De Bikuntildea B Loacutepez E Leonardo JM Arrate J MartiacutenezA Agirre A and Manzanos A 2015 Reduction of sampling ef-fort assessing macroinvertebrate assemblages for biomonitoringof rivers Knowl Manag Aquat Ecosyst 416 08

Gibson MT and Whitton BA 1987 Hair phosphatase activ-ity and environmental chemistry in freshwater StigeocloniumChaetophora and Draparnaldia (Chaetophorales) Brit PhycolJ 22 11ndash22

Goulden CE 2011 The need for capacity building for biomonitoringof lakes and streams in Asia Lakes amp Reservoirs Research ampManagement 16 159ndash163

Griffith MB Hill BH Herlihy AT and Kaufmann PR 2002Multivariate analysis of periphyton assemblages in relation to en-vironmental gradients in Colorado Rocky Mountain streams JPhycol 38 83ndash95

Gutowski A and Foerster J 2009 Benthische Algen ohneDiatomeen und Characeen Landesamt fuumlr Natur Umweltund Verbraucherschutz Nordrhein-Westfalen viewed 3 April2014 httpwwwlanuvnrwdeveroeffentlichungenarbeitsblattarbla9arbla9starthtm

Gutowski A Foerster J and Schaumburg J 2004 The use of benthicalgae excluding diatoms and Charales for the assessment of theecological status of running waters a case history from GermanyOceanol Hydrobiol Stud 33 3ndash15

Hering D Feld CK Moog O and Ofenboumlck T 2006 Cook book forthe development of a Multimetric Index for biological conditionof aquatic ecosystems experiences from the European AQEMand STAR projects and related initiatives Hydrobiologia 566311ndash 324

Hill BH Herlihy AT Kaufmann PR Stevenson RJ McCormickFH and Burch Johnson C 2000 Use of periphyton assemblagedata as an index of biotic integrity J N Am Benthol Soc 1950ndash67

Hill BH Herlihy AT Kaufmann PR DeCelles SJ and BorghMAV 2003 Assessment of streams of the eastern United Statesusing a periphyton index of biotic integrity Ecol Indic 2 325ndash338

Hughes RM and Peck DV 2008 Acquiring data for large aquaticresource surveys the art of compromise among science logisticsand reality J N Am Benthol Soc 27 837ndash859

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Kelly MG 2006 A comparison of diatoms with other phyto-benthos as indicators of ecological status in streams in north-ern England Proceedings of the 18th International DiatomSymposium Biopress Bristol

Kelly MG 2013 Data rich information poor Phytobenthos assess-ment and the Water Framework Directive Eur J Phycol 48437ndash450

Kelly MG Cazaubon A Coring E DelUomo A Ector LGoldsmith B Guasch H Huumlrlimann J Jarlman A Kaweka BKwandrans J Laugaste R Lindstroslashm EA Leitao M MarvanP Padisak J Pipp E Prygiel J Rott E Sabater S van Dam Hand Vizinet J 1998 Recommendations for routine sampling ofdiatoms for water quality assessments in Europe J Appl Phycol10 215ndash224

Kelly MG King L Jones RI Barker PA and Jamieson BJ 2008Validation of diatoms as proxies for phytobenthos when assessingecological status in lakes Hydrobiologia 610 125ndash129

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Kolkwitz R and Marsson M 1908 Oumlkologie der pflanzlichenSaprobien Ber Dtsch bot Ges 26 505ndash519

Konar B and Iken K 2009 Influence of taxonomic resolutionand morphological functional groups in multivariate analyses ofmacroalgal assemblages Phycologia 48 24ndash31

Lavoie I Vincent WF Pienitz R and Painchaud J 2004 Benthicalgae as bioindicators of agricultural pollution in the streamsand rivers of southern Queacutebec (Canada) Aquat Ecosyst HealthManag 7 43ndash58

Lazorchak JM Klemm DJ and Peck DV 1998 EnvironmentalMonitoring and Assessment Program-Surface Waters FieldOperations and Methods for Measuring the Ecological Conditionof Wadeable Streams EPA620R-94004F US EnvironmentalProtection Agency Washington DC

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Lindstroslashm EA Johansen SW and Saloranta T 2004 Periphytonin running waters ndash long-term studies of natural variationHydrobiologia 521 63ndash86

Loez C and Topaliaacuten ML 1997 Use of algae for monitoringrivers in Argentina with a speciel emphasis for the Reconquistariver (region of Buenos Aires) In Prygiel J Whitton BA andBukowska J (eds) Use of algae for monitoring rivers Institutfuumlr Botanik Universitaumlt Innsbruck Innsbruck 72ndash83

Lowe RL 2003 Keeled and canaled diatoms In Wehr JD andSheath RG (eds) Freshwater Algae of North America Ecologyand Classification Academic Press San Diego CA 669ndash684

Lowe RL and Pan Y 1996 Benthic algal communities as bio-logical monitors In Stevenson RJ Bothwell ML and LoweRL (eds) Algal Ecology Freshwater Benthic EcosystemsAcademic Press San Diego 705ndash740

Luce JJ Cattaneo A and Lapointe MF 2010 Spatial patterns inperiphyton biomass after low-magnitude flow spates geomorphicfactors affecting patchiness across gravel-cobble riffles J N AmBenthol Soc 29 614ndash626

Manoylov KM 2014 Taxonomic identification of algae (morpho-logical and molecular) species concepts methodologies andtheir implication for ecological bioassessment J Phycol 50409ndash424

Mateo P Berrendero E Perona E Loza V and Whitton BA 2010Phosphatase activities of cyanobacteria as indicators of nutrientstatus in a Pyrenees river Hydrobiologia 652 255ndash268

Meyer JL Strayer DL Wallace JB Eggert SL Helfman GSand Leonard NE 2007 The contribution of headwater streamsto biodiversity in river networks J Am Water Resour Assoc 4386ndash103

Moulton SR Kennen JG Goldstein RM and Hambrook JA2002 Revised Protocols for Sampling Algal Invertebrateand Fish Communities as Part of the National Water-QualityAssessment Program US Geological Survey Open File Report02-150 Reston VA

Mulholland PJ and Rosemond AD 1992 Periphyton response tolongitudinal nutrient depletion in a woodland stream evidence ofupstream-downstream linkage J N Am Benthol Soc 11 405ndash419

Munn MD Black RW and Gruber SJ 2002 Response of benthicalgae to environmental gradients in an agriculturally dominatedlandscape J N Am Benthol Soc 21 221ndash237

Niemi GJ and McDonald ME 2004 Application of ecological in-dicators Annu Rev Ecol Evol Syst 35 89ndash111

OrsquoBrien PJ and Wehr JD 2010 Periphyton biomass and ecolog-ical stoichiometry in streams within an urban to rural land-usegradient Hydrobiologia 657 89ndash105

Ontario Ministry of the Environment 2011 An Algal BioassessmentProtocol for use in Ontario Rivers viewed 20 November2013 httpwwwenegovoncaenvironmentenresourcesSTDPROD_101254html

Palmer CM 1969 A composite rating of algae tolerating organicpollution J Phycol 5 78ndash82

Palmer MA and Poff NL 1997 The influence of environmentalheterogeneity on patterns and processes in streams J N AmBenthol Soc 16 169ndash173

Pan Y Stevenson RJ Hill BH Kaufmann PR and Herlihy AT1999 Spatial patterns and ecological determinants of benthic al-gal assemblages in Mid- Atlantic Highland streams J Phycol35 460ndash468

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Poikane S 2015 Current state-of-art and future needs in algae-basedmonitoring from the perspective of the EU In Cantonati MKelly MG Rott E Sabater S Stevenson RJ Whitton BASchneider S Shubert EL Van de Vijever B Vis ML andAngeli N (eds) Use of algae for monitoring rivers and com-parable habitats Abstract Book Trento Italy 23

Poikane S Zapoukas N Borja S Davies SP van de Bund W andBirk S 2014 Intercalibration of aquatic ecological assessmentmethods in the European Union Lessons learned and way for-ward Environ Sci Policy 44 237ndash246

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Porter SD 2008 Algal Attributes An Autecological Classificationof Algal Taxa Collected by the National Water-QualityAssessment Program US Geological Survey Data Series 329Viewed 25 November 2013 httppubsusgsgovdsds329

Porter SD Mueller DK Spahr NE Munn MD and DubrovskyNM 2008 Efficacy of algal metrics for assessing nutrient andorganic enrichment in flowing water Freshwater Biol 53 1036ndash1054

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Potapova MG and Charles DF 2005 Choice of substrate in algae-based water-quality assessment J N Am Benthol Soc 24415minus427

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Rodrigues L and Bicudo DC 2001 Similarity among periphytonalgal communities in a lentic-lotic gradi ent of the upper Paranariver floodplain Brazil Revista Brasileira de Botacircnica 24 235ndash248

Rott E and Schneider SC 2014 A comparison of ecological optimaof soft-bodied benthic algae in Norwegian and Austrian riversand consequences for river monitoring in Europe Sci TotalEnviron 475 180ndash186

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Rott E Pipp E Pfister P Van Dam H Ortler K Binder Nand Pall K 1999 Indikationslisten fuumlr Aufwuchsalgen inOumlsterreichischen Flieszliggewaumlssern Teil 2 TrophieindicationBundesministerium f Land- und Forstwirtschaft Zahl4103408- IVA 197 Wien

Rusanov AG Stanislavskaya EV and Aacutecs Eacute 2012 Periphytic al-gal assemblages along environmental gradients in the rivers ofthe Lake Ladoga basin Northwestern Russia implication for thewater quality assessment Hydrobiologia 695 305ndash327

Schaumburg J Schranz C Foerster J Gutowski A HofmannG Meilinger P Schneider S and Schmedtje U 2004Ecological classification of macrophytes and phytobenthos forrivers in Germany according to the Water Framework DirectiveLimnologica 34 283ndash301

Schaumburg J Schranz C Stelzer C Vogel A and Gutowski A2012 Instruction Manual for the Assessment of Running WaterEcological Status in Accordance with the Requirements of theEG-Water Framework Directive Macrophytes and PhytobenthosBavarian Environment Agency Augsburg

Schmedtje U Gutowski A Hofmann G Leukart P MelzerA Mollenhauer D Schneider S and Tremp H 1998Trophie kartierung von aufwuchs- und makrophytendo-minierten Fliesgewassern Informationsberichte des BayerischenLandesamtes fur Wasserwirtschaft 498

Schneider S 2011 Impact of calcium and TOC on biological acidi-fication assessment in Norwegian rivers Sci Total Environ 4091164ndash1171

Schneider SC and Lindstroslashm EA 2009 Bioindication inNorwegian rivers using non-diatomaceous benthic algae theacidification index periphyton (AIP) Ecol Indic 9 1206ndash1211

Schneider SC and Lindstroslashm EA 2011 The periphyton index oftrophic status PIT a new eutrophication metric based on non-diatomaceous benthic algae in Nordic rivers Hydrobiologia 665143ndash155

Schneider SC Lawniczak AE Picintildeska-Faltynowicz J andSzoszkiewicz K 2012 Do macrophytes diatoms and non-diatom benthic algae give redundant information Results froma case study in Poland Limnologica 42 204ndash211

Schneider SC Kahlert M and Kelly MG 2013 Interactions be-tween pH and nutrients on benthic algae in streams and conse-quences for ecological status assessment and species richness pat-terns Sci Total Environ 444 73ndash84

Sheath RG and Hambrook JA 1990 Freshwater ecology InCole KM and Sheath RG (eds) Biology of the Red AlgaeCambridge University Press New York 423ndash454

Sheath RG and Cole KM 1992 Biogeography of stream macroal-gae in North America J Phycol 28 448ndash460

Slaacutedecek V 1973 System of water quality from the biological pointof view Arch HydrobiolndashBeih Ergebn Limnol 7 1ndash218

Stancheva R Fetscher AE and Sheath RG 2012a A novel quan-tification method for stream-inhabiting non-diatom benthic al-gae and its application in bioassessment Hydrobiologia 684225ndash239

Stancheva R Hall JD and Sheath RG 2012b Systematicsof the genus Zygnema (Zygnematophyceae Charophyta) fromCalifornian watersheds J Phycol 48 409ndash422

Stancheva R Hall JD McCourt RM and Sheath RG 2013aIdentity and phylogenetic placement of Spirogyra species(Zygnematophyceae Charophyta) from California streams andelsewhere J Phycol 49 588ndash607

Stancheva R Sheath RG Read BA McArthur KD SchroepferC Kociolek JP and Fetscher AE 2013b Nitrogen-fixingcyanobacteria (free-living and diatom endosymbionts) their usein southern California stream bioassessment Hydrobiologia 720111ndash127

Stancheva R Fuller C and Sheath RG 2014 Soft-bodied streamalgae of California viewed 9 January 2015 httpdbmusebladecoloradoeduDiatomTwosbsac_siteindexphp

Stancheva R Busse L Kociolek JP and Sheath RG 2015Standard Operating Procedures for Laboratory Processingand Identification of Stream Algae in California CaliforniaState Water Resources Control Board Surface Water AmbientMonitoring Program (SWAMP) Bioassessment SOP 0003

Stevenson RJ 2014 Ecological assessments with algae a reviewand synthesis J Phycol 50 437ndash461

Stevenson RJ and Bahls LL 1999 Periphyton protocols InBarbour MT Gerritsen J and Snyder BD (eds) RapidBioassessment Protocols for Use in Wadeable Streams andRivers Periphyton Benthic Macroinvertebrates and Fish EPA841-B-99-002 United States Environmental Protection AgencyWashington DC

Stevenson RJ Bothwell ML and Lowe RL 1996 Algal EcologyFreshwater Benthic Ecosystems Academic Press San DiegoCA

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Stevenson RJ Pan Y and van Dam H 2010 Assessing envi-ronmental conditions in rivers and streams with diatoms InSmol JP and Stoermer EF (eds) The Diatoms Applicationsfor the Environmental and Earth Sciences 2nd edn CambridgeUniversity Press Cambridge MA 2nd edition

Stevenson RJ Bennett BJ Jordan DN and French RD 2012Phosphorus regulates stream injury by filamentous green algaeDO and pH with threshold in responses Hydrobiologia 695 25ndash42

Stoddard JL Larsen DP Hawkins CP Johnson RK and NorrisRH 2006 Setting expectations for the ecological conditionof streams the concept of reference condition Ecol Appl 161267ndash1276

ter Braak CJF and van Dam H 1989 Inferring pH from diatoms acomparison of old and new calibration methods Hydrobiologia178 209ndash223

USEPA 2002 A SAB report a framework for assessing and re-porting on ecological condition EPASAB-EPEC-02ndash009 USEnvironmental Protection Agency Washington DC

USEPA 2007 National Rivers and Streams Assessment FieldOperations Manual EPA-841-B-07009 US EnvironmentalProtection Agency Washington DC

USEPA 2008 National Rivers and Streams Assessment LaboratoryMethods Manual EPA-841-B07-010 US EnvironmentalProtection Agency Office of Water and Office of Research andDevelopment Washington DC

VanLandingham SL 1982 Guide to the identification environ-mental requirements and pollution tolerance of bluegreen algae(Cyanophyta) EPA-6003-82-07

Vis C Hudon C Cattaneo A and Pinel-Alloul B 1998 Periphytonas an indicator of water quality in the St Lawrence River (QueacutebecCanada) Environ Pollut 101 13ndash24

Wehr JD Stancheva R Truhn K and Sheath RG 2013Discovery of the rare freshwater brown alga Pleurocladia lacus-tris (Ectocarpales Phaeophyceae) in California streams West NAm Naturalist 73 148ndash157

Welch EB Jacoby JM Horner RR and Seeley MR 1988Nuisance biomass levels of periphytic algae in streamsHydrobiologia 157 161ndash168

Whitton BA 1988 Hairs in eukaryotic algae In Round FE (ed)Algae and the Aquatic Environment Contributions in Honour ofJWG Lund Biopress Bristol UK 226ndash460

Whitton BA 1991 Use of phosphatase assays with algae to as-sess phosphorus status of aquatic environments In JeffreyDW and Madden B (eds) Bioindicators and EnvironmentalManagement Academic Press London 295ndash310

Whitton BA and Kelly MG 1995 Use of algae and other plants formonitoring rivers Aust J Ecol 20 45ndash56

Whitton BA and Mateo P 2012 Rivulariaceae In Whitton BA(ed) Ecology of Cyanobacteria II Their Diversity in Space andTime Springer London UK 561ndash592

Whitton BA 2012 Changing approaches to monitoring during theperiod of the Use of Algae for Monitoring Rivers symposiaHydrobiologia 695 7ndash16

Whitton BA 2013 Use of Benthic Algae and Bryophytes forMonitoring Rivers J Ecol Environ 36 95ndash100

Whitton BA Yelloly JM Christmas M and Hernaacutendez I 1998Surface phosphatase activity of benthic algal communities in astream with highly variable ambient phosphate concentrationsVerh Int Ver Theoret Angew Limnol 26 967ndash972

Whitton BA Clegg E Christmas M Gemmell JJ and RobinsonPJ 2002 Development of Phosphastase Assay for MonitoringNutrients in Rivers ndash Methodology Manual for Measurement ofPhosphatase Activity in Mosses and Green Algae EnvironmentAgency of England and Wales STRE106-E-P

Winterbourn MJ 1990 Interactions among nutrients algae and in-vertebrates in a New-Zealand mountain stream Freshwater Biol23 463ndash4

Zelinka M and Marvan P 1961 Zur Praumlzisierung der biologischenKlassifikation der Reinheit flieszligender Gewaumlsse Arch Hydrobiol57 389ndash407

Cite this article as R Stancheva and RG Sheath 2016 Benthic soft-bodied algae as bioindicators of stream water quality Knowl ManagAquat Ecosyst 417 15

15 page 16 of 16

• Introduction
• Field and laboratory bioassessment methods for soft-bodied algae
• • Field sampling of soft-bodied algae
  • Taxonomic analysis and quantification of soft-bodied algae
  • • Approaches to apply soft-bodied algae as bioindicators
    • • Biotic indices (BI)
      • Multimetric indices of biotic integrity (IBI)
      • • Soft-bodied algae as bioindicators of nutrients
        • Concluding remarks
        • References