Assessment of the trophic status of four coastal lagoonsand one estuarine delta, eastern Brazil

Luiz Carlos Cotovicz Junior & Nilva Brandini &Bastiaan Adriaan Knoppers &

Byanka Damian Mizerkowski &José Mauro Sterza &

Alvaro Ramon Coelho Ovalle &

Paulo Ricardo Petter Medeiros

Received: 9 February 2012 /Accepted: 5 July 2012 /Published online: 22 July 2012# Springer Science+Business Media B.V. 2012

Abstract Anthropogenic eutrophication of aquaticecosystems continues to be one of the major environ-mental issues worldwide and also of Brazil. Over thelast five decades, several approaches have been pro-posed to discern the trophic state and the natural andcultural processes involved in eutrophication, includ-ing the multi-parameter Assessment of Estuarine

Trophic Status (ASSETS) index model. This studyapplies ASSETS to four Brazilian lagoons (Mundaú,Manguaba, Guarapina, and Piratininga) and one estu-arine delta (Paraíba do Sul River), set along the easternBrazilian coast. The model combines three indicesbased on the pressure–state–response (PSR) approachto rank the trophic status and forecast the potentialeutrophication of a system, to which a final ASSETSgrade is established. The lagoons were classified asbeing eutrophic and highly susceptible to eutrophica-tion, due primarily to their longer residence times butalso their high nutrient input index. ASSETS classifiedthe estuary of the Paraíba do Sul river with a low tomoderate trophic state (e.g., largely mesotrophic) andlow susceptibility to eutrophication. Its nutrient inputindex was high, but the natural high dilution andflushing potential driven by river flow mitigated thesusceptibility to eutrophication. Eutrophication fore-casting provided more favorable trends for theMundaú and Manguaba lagoons and the Paraíba doSul estuary, in view of the larger investments in waste-water treatment and remediation plans. The finalASSETS ranking system established the lagoons ofMundaú as “moderate,”Manguaba as “bad,” Guarapinaas “poor,” and Piratininga as “bad,”whereas the Paraíbado Sul River Estuary was “good.”

Keywords Trophic state . Eutrophication . ASSETSmodel . Estuaries . Eastern Brazil

Environ Monit Assess (2013) 185:3297–3311DOI 10.1007/s10661-012-2791-x

L. C. Cotovicz Junior (*) :N. Brandini :B. A. KnoppersDepartamento de Geoquímica, Instituto de Química,Universidade Federal Fluminense (UFF),Outeiro de São João Batista, s/n°,Niterói, Rio de Janeiro CEP 24.020-141, Brazile-mail: lcc.junior@gmail.com

B. D. MizerkowskiCentro de Estudos do Mar (CEM),Universidade Federal do Paraná (UFPR),Avenida Beira-Mar, s/n°,Pontal do Sul, Paraná, Brazil

J. M. Sterza :A. R. C. OvalleCentro de Biociências e Biotecnologia,Universidade Estadual do Norte Fluminense (UENF),Avenida Albeto Lamego,2000 Campo dos Goytacazes, Rio de Janeiro, Brazil

P. R. P. MedeirosDepartamento de Geografia e Meio Ambiente,Centro de Ciências Exatas e Naturais,Universidade Federal de Alagoas (UFAL),Campus A. C. Simões s/n, Tabuleiro do Martins,Maceió, Alagoas, Brazil

Introduction

Over the last five decades, many fresh, estuarine, andcoastal waters developed into the most fertilized envi-ronments of the world. Eutrophication, which refers tothe enrichment of nutrients, organic matter, and theassociated enhancement of primary production, hasbecome a widespread water quality issue acceleratedby the anthropogenic activities in the watersheds(Golterman and Oude 1991; Nixon 1995; Cloern2001). For example, evaluation of historical changes innutrient loading revealed that estuarine systems haveexperienced a six to 50 times increase in the nitrogen(N) load and an 18–180 times in the phosphorous (P)load as compared to pristine conditions (Conley 2000).Among some of the multiple drivers of eutrophicationare agriculture and associated fertilizer usage, popula-tion growth with untreated effluent discharge, industrialdevelopment, and the increase of combustion of fossilfuels (Likens 1972; Boesch 2002). The development ofexcessive algal and/or harmful algal blooms (HABs),shifts from benthic to pelagic dominated productivity,loss of submerged aquatic vegetation (SAV), lowdissolved oxygen (DO) (hypoxia and anoxia), alterationof foods webs, and loss of biodiversity are considered assome of the main multiple symptoms (Bricker et al.1999; Anderson et al. 2002; Cloern 2001; Ferreira etal. 2005; Glibert et al. 2010).

Over time, many methods and conceptualapproaches have been developed to assess the trophicstate and eutrophication of aquatic water bodies, alsoin support for management purposes (Carlson 1977;Lambou et al. 1983; Vollenweider et al. 1992; Knopperset al. 1991; Nixon 1995; Bricker et al. 1999; Conley2000; Nobre et al. 2005; Scavia and Bricker 2006; BorjaandDauer 2008; Paerl 2009; Primpas and Karydis 2010;Devlin et al. 2011; Ferreira et al. 2011). In addition to theestablishment of standard variables to monitor eutrophi-cation, it has become necessary to adopt indices whichcombine quantitative and qualitative indicators forassessing the trophic conditions (Izzo et al. 1997).Selecting key indicators is required to adequatelydescribe the trophic status of the environment. Suchparameters must reflect a gradient of the levels ofhuman-induced impacts, in which an increase in nutrientloads leads to a decrease of water quality (Ferreira et al.2011).

Furthermore, a wide discussion has also emergedfrom the issue of nitrogen and phosphorous co-

limitation in aquatic systems, which entails the neces-sity of certain site-specific modeling adaptations(Nixon 1995; Cloern 2001; Howarth and Marino2006; Elser et al. 2007; Conley et al. 2009; Paerl2009; Ferreira et al. 2011). Most of the earlierconcepts developed for temperate systems adoptedphosphorous as the limiting nutrient in freshwaterswhereas nitrogen in estuarine and coastal waters.Observations in tropical coastal lagoons of the state ofRio de Janeiro (Brazil) indicated phosphorus limitationin short periods during the dry season (Knoppers et al.1999). It must be borne in mind that tropical estuarinesystems are generally subject to a continuous growthperiod, and seasonal variability is governed by changesin precipitation, temperature, and tidal exchange, incontrast to temperate systems prone to seasonal lightlimitation of growth.

This study applies the ASSETS model to five tropicalcoastal estuarine systems of the east coast of Brazil, alllimited by nitrogen and characterized by different degreesof human impacts and residence times of water. ASSETSwas developed by a group of specialists following theNOAA’s Estuarine Eutrophication Survey (Bricker et al.1999, 2003) and used to rank the eutrophication status ofestuaries and coastal areas of USA. This methodologyhas been also applied for diverse European and Asiaticestuaries (Bricker et al. 1999, 2003; Ferreira et al. 2007;Xiao et al. 2007; Scavia and Bricker 2006; Whitall et al.2007; Bricker et al. 2008) and lately also to two systemsin southeast Brazil (Mizerkowki 2011). The experiencesusing the ASSETSmethodology appear to be sufficientlyrobust to allow its application to a range of different typesof coastal systems (Ferreira et al. 2007).

Materials and methods

The study areas

The geographical location, physiographic features,and population densities of the study areas are sum-marized in Table 1, and Fig. 1 depicts the systemsthemselves. Further details are described below.

The Mundaú–Manguaba lagoon–estuarine system

Mundaú–Manguaba lagoon–estuarine system (MMELS)is located in the state of Alagoas at the northern premisesof the eastern coast of Brazil (latitude 9°35′ and 9°46′S;

3298 Environ Monit Assess (2013) 185:3297–3311

longitude 34°44′ and 35°58′W). MMELS falls into thecategory of a choked estuarine–lagoon system, with longresidence times of water, a large potential for materialrecycling and retention, and exhibits eutrophic conditions(EC). MMELS consists of three distinct compartments(Table 1), the larger Manguaba and the smaller Mundaúlagoons and a maze of narrow channels connected via asingle 250-m-wide tidal inlet to the sea, which dissipatesaround 90 % of the tidal energy before reaching thelagoons. Residence times of water are longer in MALthan in MUL (Table 1). A distinct seasonal cycle isobserved with a dry summer (November to March) anda wet winter (May to August) period and the climate is ofKöppen Type As. Sugarcane waste effluents are trans-ported by the rivers, and untreated urban sewage is intro-duced directly into MUL from the large City of Maceióand from several smaller cities into MAL. According toIBGE (2008), less than 10 % of the total urban sewage istreated (primary and secondary treatments). Crop burningactivities have been affecting the entire lower drainagebasin and also Maceió city (Oliveira and Kjerfve 1993).

Guarapina lagoon

The eastern Fluminense coastline between the cities ofNiterói and Cabo Frio, state of Rio de Janeiro, Brazil

harbors a series of choked lagoons. Guarapina lagoon(GL) (longitude 22°56′S, latitude 42°42′W) formspart of the Maricá lagoon system. The small watershedis bordered by a relative pristine mountainous ridge.The lagoon is fed by three rivulets with a combinedfreshwater discharge of 0.5 m3 s−1. The lagoon is usedfor fishing and recreation (Machado and Knoppers1988) and still maintains its traditional land use oflow-density cattle pastures and urban conglomerationat the seaward end of the lagoon and sand barriers(Bitton et al. 1999). The population growth accordingto the last census of IBGE (2010) was 5 % year−1 andthe system harbors 3,525 households, of which only31 have sewage treatment representing 8 % of the totalpopulation (IBGE 2008).

The Piratininga lagoon

Piratininga lagoon (PL) (latitude 22°56′S, longitude43°00′W) is located near the city of Niterói, state ofRio de Janeiro, and represents a small internal lagooncell of the Piratininga–Itaipu system (Table 1). Thedrainage basin is fed by the Jacaré and Arrozal streamsand other undefined diffuse sources (Wasserman et al.1999). PL has been under a gradual increase of cul-tural eutrophication due to the combined effect of low

Table 1 Summary of physical characteristics and watershed population density for each estuary

Features MUL MAL GL PL PSE

Location Latitude S 9°35′a 9°46′a 22°56′b 22°56′b 21°37′c

Longitude W 35°44′a 35°58′a 42°42′b 43°00′b 41°01′c

Surface area (km2) 24a 43a 6.38b 2.9b 21.5c

Volume (106 m3) 69.8a 97.7a 6.5b 2b 43.1

Average depth (m) 1.5a 2.1a 1b 0.7b 2c

Tidal range (m) 0.2a 0.03a 0.03b 0.04b 0.85c

Tidal prism (106 m3) 17.3a 6.1a 0.38b 0,11b 18.3c

Average freshwater discharge (m3 s−1) Rainy 65.9a 57.2a – – 1,000c

Dry 14.1a 15.9a – – 450c

Annual 3a 28a 0.46b 0.1b 725c

Watershed population (×106 hab) 0.9d 0.3d 0.1d 0.2d 4.9d

Residence time (days) 16a 36a 14b 30b 0.75

MUL Mundaú lagoon, MAL Manguaba lagoon, GL Guarapina lagoon, PL Piratininga lagoon, PSE Paraíba do Sul estuarya Oliveira and Kjerfve (1993)b Knoppers et al. (1991)c Sterza and Fernandes (2006)d IBGE (2010)

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tidal flushing and uncontrolled domestic sewage dis-charge (Knoppers et al. 1991, 1999). The benthicmacroalgae Chara sp. began to proliferate in the1960s and occupies more than 60 % of the lagoon’sarea (Carneiro et al. 1994). The demographic expan-sion rate has been 11 % year−1 (Bitton et al. 1999;IBGE 2010), and the wastewater treatment attends lessthan 9 % of the households (IBGE 2008).

The Paraíba do Sul estuary

The Paraíba do Sul estuary (PSE) is located at thenorthern premises of the state of Rio de Janeiro (latitude21°37′S, longitude 41°01′W) and is composed of amain river channel and a minor secondary channel.The latter harbors a mangrove forest of approximately8 km2 (Sterza and Fernandes 2006). The coast is

a,b

cde

00900600300

300

600

Atlantic Ocean

Guarapina Lagoon

0 200 400

22°5

7' S

0 0.5 1 km

22°5

6' S

42°42' W42°43' W42°44' W

PR & CR

0 300 600 900 12000

300

600

Piratininga Lagoon

AtlanticOcean

0 200 400

22°5

6' S

22°5

7' S

43°05' W 43°04' W 43°04' W 43°03' W

0 0.5 1 km

Niterói City

-35.980144 -35.930144 -35.880144 -35.830144 -35.780144-9.7500309

-9.7000309

-9.6500309

-9.6000309

9°36

' S9°

41' S

35°58' W 35°52' W 35°46' W

0 0.03 0.060 4 8 km

Manguaba Lagoon

AtlanticOcean

MundaúLagoon

Maceió City

PDMR

SR

MR

00900600300

300

600

Atlantic Ocean

São João da Barra City

21°3

5' S

21°3

7' S

41°04' W 41°02' W 41°00' W

0 200 4000 1.25 2.5 km

Paraiba do Sul River Estuary

Fig. 1 Map location of the systems analyzed. a, b Mundaú and Manguaba lagoons; c Paraíba do Sul River Estuary; d Guarapinalagoon; e Piratininga lagoon

3300 Environ Monit Assess (2013) 185:3297–3311

characterized by high wave energy regime and micro-tides (Table 1). The summer season (November toJanuary) is humid and the winter season (July toAugust) dry, with a climate of Köppen type Aw. Theriver is an example of highly impacted system. It drainsone of the most populated and industrialized regions ofBrazil, receiving nutrient loads from upstream sourcesalong its river course. The Paraíba do Sul River fulfills awide range of economic services to the inhabitants of thestates of São Paulo, Minas Gerais, and Rio de Janeiro,Brazil. It receives industrial, agricultural, and domesticeffluents; provides potable water for most of the citieslocated along its course; generates energy from hydro-electrical dams; and maintains a substantial local fisheryin its coastal waters. The percentage of the populationwith access to sewage collection varies along the courseof the Paraíba do Sul River. The effluent treatmentcovers 10.2% of the population in the state of São Paulowhile only 1.2 % in the state of Minas Gerais and 2 % inthe state of Rio de Janeiro (ANA 2006a).

Sampling strategies

Sampling in all systems covered the estuarine mixingzone between the fresh and marine end members. Ineach of the compartments of MMELS, 07 samplingcampaigns were performed covering the wet and dryseasons between 2006 and 2008. MUL was coveredby 16 stations set along longitudinal transects, MALby 20 stations, and the tidal channels by 10 stationsper campaign. Additional water samples were taken atthe critical effluent point sources (B. Knoppers,personal communication). The lagoon proper of GLwas sampled at bi-weekly intervals at three samplingstations over an annual cycle, with three additionalstations set in the rivulets and one off the lagoon’smouth (Knoppers et al. 1999). The lagoon proper ofPL was sampled along a transect with seven stations atmonthly intervals during an annual cycle, includingalso its two main rivulets (Carneiro et al. 1994;Knoppers et al. 1999). The estuarine gradient of PSEwas sampled at monthly intervals at five stations inaccordance to the unimodal seasonal pattern of riverflow (Sterza and Fernandes 2006). Additional sampleswere collected at Campos City 30 km upstream (e.g.,the freshwater end-member) and also in its coastalwaters (i.e., marine end-member). More informationon the physical and biogeochemical features and sam-pling strategies of the GL and PL systems are

encountered in Knoppers and Kjerfve (1999) andKnoppers et al. (1999) and for PSE in Carvalho andTorres (2002), Sterza and Fernandes (2006), andJennerjahn et al. (2010). Information on the overallphysical setting andwater quality ofMMELS is restrictedto Oliveira and Kjerfve (1993), and the present data usedfor the ASSETS model have as yet been unpublished.

All systems were assessed by a congruent set ofphysical and chemical parameters and were measuredas follows: Temperature, salinity, pH, and dissolvedoxygen were measured in situ with either WTW-50(Germany) or YSI 6600 (USA) multi-probes; dissolvedinorganic nitrogen (ammonia, nitrite, and nitrate) andphosphate (orthophosphate) were quantified as inGrasshof et al. (1983) and chlorophyll-a (Chl-a) as inStrickland and Parsons (1972). Whatman GF/F filterswere used for the chlorophyll-a analyses and the filtratefor the nutrient analyses. All water samples were kept inthe dark and on ice during transport to the respectivelaboratories, and nutrient samples and chlorophyll-afilters kept at −18 °C in a freezer prior to analyses.

Information on the distribution and biomass ofmacroalgae, frequency, and species composition ofphytoplankton blooms, including HABs when present,was obtained for MMELS from Melo-Magalhães et al.(2008), for GL as in Knoppers et al. (1999), and for PLfrom Carneiro et al. (1994). Macroalgae have onlybeen reported for PL and harmful algal blooms havebeen scant.

The ASSETS model

The ASSETS model was developed for the US NationalEstuarine Eutrophication Assessment (Bricker et al.1999) and adopts the conceptual pressure–state–response (PSR) approach. ASSETS works with quanti-tative and semi-quantitative components, using fielddata, models, and expert knowledge to provide PSRindicators (Bricker et al. 2003). The three indices(pressure–state–response) are briefly described below;for a full description, see Bricker et al. (1999, 2003) andFerreira et al. (2007).

Pressure—influencing factors

Influencing factors (IF) help to establish a link be-tween a system’s natural susceptibility to eutrophica-tion as a function of the dilution and flushing potentialand the specific nutrient nitrogen loading (N) (Bricker

Environ Monit Assess (2013) 185:3297–3311 3301

et al. 2008). Physical and hydrologic data are usedseparately to define the dilution and flushing potential(i.e., rates) which are combined to give a susceptibilityrating. For example, the dilution potential is charac-terized by the degree of mixing of the water column(i.e., homogeneous or stratified) and the freshwater orsaline volume fraction of the estuary. The flushingpotential considers the combined effect of the tidalrange and the ratio between the freshwater inflowand the estuaries’ volume. The final classification ofsusceptibility is a combination of the “dilution andflushing potentials,” as shown in the matrix of Table 2from Bricker et al. (1999). The matrix exemplifies thathigher dilution and flushing rates lead to lower reten-tion times for nutrients (i.e., low susceptibility), andthe opposite situation can lead to enhanced eutrophi-cation (i.e., high susceptibility).

The N loading susceptibility model, initially devel-oped for estuaries with regular river flow (Bricker et al.2003), has been further adapted for other estuarine–coastal systems (Ferreira et al. 2007). The model definesthe variation of nitrogen mass as DIN in the estuary as aratio between the anthropogenic load and the total massof nutrient loading considering also the freshwater inputand the nutrient discharged by advection and exchangewith the ocean.

Considering the hypothetic situation that there is nohuman input, the background levels can be describedas (Ferreira et al. 2007):

Mb ¼ " Tp Msea

� �" Tp þ Q T� ��1

where ε is the fraction of water leaving the bay at ebbtides does not return in the flood (proxy for re-entrainment), Tp is the tidal prism (in cubic meters),Msea is the N concentration offshore (in kilograms percubic meter), Q is the freshwater input (in cubic metersper second), and T is the tidal period (seconds).

Under the assumption that there is no oceanic inputof N, the anthropogenic influence (Mh) is considered asthe N load from the rivers (Min in kilograms per cubicmeter) and the effluent discharge (Mef in kilograms persecond) as follows:

Mh ¼ T QMin þMef½ �ð Þ Q T þ " Tp� ��1

The nutrient input, regarded as a human influence(HI), is henceforth defined by:

Nutrient input ¼ Mh Mh þMbð Þ�1

Nutrient input scores are framed into three classes aslow (0–0.4), moderate (0.4–0.8), and high (0.8–1).The susceptibility rating is combined in a matrix witha rating for nitrogen loads to determine the final influ-encing factor rating.

State—eutrophic conditions

The EC is a rating based on five indicators or symptomsthat are determined according to the salinity zones—freshwater (S00–0.5), mixing (0.5–25), and seawater(>25 psu). Ratings for the primary symptoms Chl-aand macroalgae are averaged for each salinity zone.The secondary symptoms used are DO, changes in thecoverage of SAV, and the occurrence of nuisance and/orharmful algal blooms (HABs) (Devlin et al. 2011).Bricker et al. (2003) presented detailed information onthe logical decision process for the determination of thelevel of expression and respective scores of the primaryand secondary symptoms. EC is then calculated byaggregating primary and secondary symptoms, using acombination matrix (Bricker et al. 2003).

Where possible, ASSETS employs data rather than“expert knowledge,” for instance by using statisticalcriteria for determination of the status for Chl-a (90thpercentile) and for DO (10th percentile) of average

Table 2 Matrix for the determination of the estuarine susceptibility to eutrophication

Dilution potential

High Moderate Low

Flushing potential High Low susceptibility Low susceptibility Moderate susceptibility

Moderate Low susceptibility Moderate susceptibility High susceptibility

Low Moderate susceptibility High susceptibility High susceptibility

Source: Bricker et al. (1999)

3302 Environ Monit Assess (2013) 185:3297–3311

annual data values. The application of the percentile-based approach is illustrated for Chl-a (Fig. 2) and forDO (Fig. 3) with data from the Mundaú lagoon as anexample. The percentile value approach is being usedwithin the European Water Framework Directive(WFD; see Ferreira et al. 2011) for evaluating theecological and chemical status for all European waterbodies until 2015 (Beliaeff and Pelletier 2011).

Response—future outlook

An analysis of the future outlook (FO) is performed todetermine whether the present conditions of nutrientpressure in an estuary will worsen, improve, or remainsimilar at a medium time scale (e.g., over the next twodecades). The assessment of expected changes in nu-trient pressure is based on a variety of drivers, includ-ing demographic trends, wastewater treatment, andremediation plans, together with expected changes inagricultural practices and watershed uses, and finallycomplemented by expert knowledge. The susceptibil-ity component is combined with a projection of thefuture outlook. The foreseeable evolution is gradedinto five classes from better to worse (Bricker et al.2003; Nobre et al. 2005; Xiao et al. 2007).

Synthesis—the overall ASSETS grade

The final stage of the ASSETS determination synthe-sizes the three scores of PSR to provide an overall

description of the system status in terms of eutrophica-tion. The combination of the PSR results in a matrix ofcombinations leads to the classification of the aquaticsystem into five categories: high (better), good, moder-ate, poor, or bad (worse). These categories are color-coded following the convention of the WFD and pro-vide a scale for setting reference conditions for differenttypes of transitional waters with regard to eutrophication(Bricker et al. 2003).

Results

Salinity zones

The salinity zones of the study areas are shown inTable 3. The calculations were carried out by averagingvalues for an annual cycle. MUL and MAL are domi-nated by a freshwater zone at its upper to central areas,while the mixing pattern was observed from their centralto lower regions. MAL is governed by a higher fresh-water fraction than MUL, but the seawater percentage issmall for both. GL showed a predominance of mixedwaters, with the freshwater zone restricted to an insig-nificant small portion of the rivulets mouth. The PL areawas classified presenting about 83.5 % of mixed watersand 16.5 % of seawater. PSE being a typical deltaicestuary presented a more evenly distributed estuarinegradient and distinct seasonal shifts between dry–wetseasonal patterns (Sterza and Fernandes 2006), with oneperiod of more pronounced intrusion of seawater (dryperiod) and the other (rainy period) more dominated by

Mundaú Lagoon

0

4

8

12

16

5 15 25 35 45 55 65 75 85

Mor

e

Chlorophyll-a (µg.L -1)

Fre

qu

ency

0%

20%

40%

60%

80%

100%

Frequency % cumulative

Fig. 2 Percentile 90 value for chlorophyll-a (dashed lines in-tersection) in the mixing zone of the Mundaú lagoon

Mundaú Lagoon

0

2

4

6

8

1 2 3 4 5 6 7 8 9 10 11 12M

ore

Dissolved Oxygen (mg.L-1)

Fre

qu

ency

0%

20%

40%

60%

80%

100%

Frequency % cumulative

Fig. 3 Percentile 10 value for dissolved oxygen (dashed linesintersection) in the mixing zone of the Mundaú lagoon

Environ Monit Assess (2013) 185:3297–3311 3303

freshwater. Over an annual cycle, PSE was divided intoaround 46% of freshwater, 33% of mixing, and 21% ofseawater zones.

Susceptibility

Under annual average conditions of the volume ofestuarine waters and the tidal range, the results yieldeda low dilution and flushing potential for the lagoonsand a moderate dilution and high flushing potential forthe river estuary. Hence, the estuarine susceptibility isclassified as high for the lagoons and moderate to lowfor the Paraiba do Sul River estuary (Table 4).

Nutrient input

The results of the model calculations for the nutrientinputs for the five systems are presented in Table 5. Theconcentrations of DIN in rivers (Min) were higher in PLwith 28.5 μM (3.2×10−3 kg m−3) and in PSE with22.1 μM (3.1×10−4 kg m−3). Offshore surface concen-trations were 3.1 μM (4.4×10−5 kg m−3) for the Mun-daú–Manguaba system, 2.5 μM (3.5×10−5 kg m−3) for

GL and PL, and 13.5 μM (1.9×10−4 kg m−3) for PSE(Jennerjahn et al. 2010).

The anthropogenic input to the systems derived fromeffluent discharge (Mef) was estimated by adopting theaverage N release per capita considered as 9.04 gN day−1 (FEEMA 1987; Meybeck and Helmer 1989;Meybeck et al. 1989). The watershed of the PSE is theone that receives the highest input of nutrients followedbyMUL,MAL, PL, and GL. The calculation of the PSEanthropogenic input by per capita release (17,308TN year−1) is corroborated by other river flux studiesalong the eastern Brazil coast, with an estimate of18,672 TN year−1 in 1998 (unpublished data) and19,200 TN year−1 in 2010 (C. Gonçalves, personalcommunication).

For the Mundaú–Manguaba lagoon system, the con-tribution of effluents related to the sugar cane practiceswas estimated, yielding fluxes of around 2.4×10−2 and1.6×10−2 N kg s−1 for MUL and MAL, respectively,with 21,700 ha of the cultivated area being in the MALand 29,480 ha in the MUL watersheds. The emissionfactors adopted in this study were taken from Lacerda etal. (2008). The calculated background concentrationswere higher in MAL and PL. The calculated anthropo-genic influence (Mh) varied in according to the estuaries,with high values in MUL and PL, while the final nutri-ent input was determined for all systems.

Influencing factors—pressure

Susceptibility and nutrient inputs are combined to deter-mine the IF. Higher susceptibility combined with highnutrient input results in a high score for IF, whereas theopposite holds for better conditions (low score). Theclassification of IF was high for all lagoons, whereas forPSE the classification was moderate to low.

Table 3 Average percentage area of the salinity zones for theestuarine systems

Salinity zoneclassification

MUL MAL GL PL PSE

Annual Dry Rainy

Freshwater(0–0.5)

28 41 0 0 46.1 16.0 75.0

Mixing(0.5–25)

70 54.4 100 83.5 33.2 50.0 18.8

Seawater(>25)

2 4.6 0 16.5 20.7 33.3 6.3

Table 4 Determination of theestuarine susceptibility accord-ing to the dilution and flushingpotentials of the systems

aThe classification and calcula-tion of this variables are welldescribed in Bricker et al. (1999)

MUL MAL GL PL PSE

Volume (106 m3) 69.8 97.7 6.5 2 43.1

Dilution volumea 1.10−2 1.10−2 1.10−1 5.10−1 2.10−2

Dilution potentiala Low Low Low Low Low

Tide rangea Micro Micro Micro Micro Micro

Daily river input (106 m3) 3 2.4 3.10−2 7.10−3 62.6

River input/estuary volumea 4×10−2 2×10−2 4×10−3 3×10−3 1.4

Export potentiala Moderate Moderate Low Low High

Estuarine susceptibilitya High High High High Moderate low

3304 Environ Monit Assess (2013) 185:3297–3311

Eutrophic conditions—state

The eutrophic conditions of the systems are presentedin Table 6. With the exception of PSE, all the systemspresented high primary symptoms. In PL, the majorproblem is the large spatial coverage of macroalgaewhich attains more than 60 % of the surface areathroughout the year (Knoppers et al. 1999), whereasthe other systems were dominated by phytoplankton.Maximum Chl-a levels were indicative of hypereutro-phic conditions (>60 μg Chl-aL−1) for MUL, MAL,and GL, with a high spatial coverage (>50 %) andperiodic frequency of occurrence (seasonal pattern) inthe freshwater and mixing salinity zones. Moreover,the seawater domain of MUL and MAL was classifiedas medium eutrophic (>5≤20 μgChl-aL−1), also com-monly regarded as mesotrophic (Vollenweider et al.1992). For PSE, medium conditions were classifiedfor the entire estuary and throughout the seasonalcycle based on Chl-a (>5≤20 μg Chl-aL−1).

As for the primary symptoms, the classification wasalso variable for the secondary symptoms. No informa-tion was found for SAV, but low concentrations of DOand HABs have been documented. MUL did not exhibitvalues indicating biologically stressful conditions relat-ed to the dissolved oxygen content. PSE also was

exempt of biological stress, except for the seawater zone(i.e., 4.3 mg L−1). On the other hand, the 10th percentilevalue of GL was 3.38 mg L−1, being prone to thecategory of biologically stressful conditions. In thesethree systems, the final classification for secondarysymptoms was low. For PL and MAL, the secondarysymptoms for eutrophic conditions are more critical. InPL, the DO value for the mixing zone was 2.5 mg L−1

(i.e., biological stress) and in seawater as low as1.28 mg L−1 (i.e., hypoxia), with a high periodicfrequency of occurrence. MAL exhibited the worstconditions with respect to the secondary symptomsdue to frequent occurrence of HABs in the freshwaterand mixing salinity zones. These HABs occur moreduring the dry period (Melo-Magalhães et al. 2008).

Future outlook—response

The assessment of the expected future outlook incorpo-rates both quantitative and qualitative information. Itincludes computations of the population growth trendsobtained from the National Brazilian Census (BrazilianInstitute of Geography and Statistics; IBGE 2010) mul-tiplied by the per capita nitrogen load (e.g., 9.04gN day−1; FEEMA 1987; Meybeck and Helmer 1989;Meybeck et al. 1989), as well as the prognosis ofplanned remediation actions by local and/or federalauthorities and the industries, with respect to wastewatertreatment and fertilizer usage in agricultural practicesand watershed uses, complemented by expert knowl-edge. The susceptibility component is combined withina matrix with the projections of the future outlook of thenutrient load scenarios (Bricker et al. 2003). Table 7summarizes the future outlook for all the systems. Theforeseeable development and associated socioeconomicand environmental actions are henceforth described foreach system.

Table 5 Average DIN concen-trations in rivers and offshorewaters and estimated loads fromanthropogenic effluents to sys-tems and the respective nutrientinput scores and classificationsfor each system

MUL MAL GL PL PSE

Min (kg m−3) 2.3×10−4 1.6×10−4 7.7×10−5 3.2×10−3 3.1×10−4

Msea (kg m−3) 4.4×10−5 4.4×10−5 3.5×10−5 3.5×10−5 1.9×10−4

Mef (kg s−1) 7.2×10−2 2.6×10−2 2.8×10−4 1.6×10−3 0.4×10−1

Mb (kg m−3) 1.8×10−5 4.1×10−6 2.5×10−5 7.4×10−6 8.6×10−5

Mh (kg m−3) 1.36×10−3 9.9×10−4 6.7×10−4 1.5×10−2 5.3×10−4

Mh/(Mb+Mh) 0.99 1 0.88 1 0.86

Nutrient input High High High High High

Table 6 Determination of eutrophic conditions (EC) by the com-bination of primary and secondary symptoms for the systems

Estuary Primarysymptoms

Secondarysymptoms

EC

MUL High Low Moderate

MAL High High High

GL High Low Moderate

PL High Moderate Moderate high

PSE Moderate Low Moderate low

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The Mundaú–Manguaba estuarine–lagoon systemASSETS considered the future outlook for the MULand MAL lagoons as apt for improvement but at a lowlevel. MUL and MAL are, currently, being subject tomanagement actions, particularly with respect to theimpacts of the sugarcane and chlor-alkali industryeffluents, environmental urban and rural sanitation,and protection of water and natural resources (ANA2006b). The management plan is driven by the partic-ipation of several governmental committees, NGOs,and the public itself. The intention is to spend approx-imately of $550 million with the action plan. IBGE(2010) data also estimated a maximum populationgrowth rate of 5 % year−1. As such, a decrease innutrient inputs to these lagoons can be forecasted.

The Gaurapina and Piratininga lagoons According tothe ASSETS outlook, GL and PL’s future outlook willworsen at a high level. For GL and PL, no direct man-agement actions have been established, apart from theconstruction of one local sewage treatment plant at PL,which has now been completed. Further uncontrolledhousing construction and diffuse effluent dischargeshould deteriorate the ground water of both lagoons.These systems are also located close to Rio de Janeirocity, and they are being subject to a high populationgrowth of about 10 % year−1 (IBGE 2010).

The Paraíba do Sul estuary As expected, the ASSETSoutlook considered that PSE should improve at a highlevel. This is naturally brought about by the high

dilution and flushing potential of the river and the estu-ary itself. A consortium implemented by the states ofSão Paulo, Minas Gerais, and Rio de Janeiro has beendealing with several remedial actions (ANA 2006a).The main objectives entail the reduction of pollutantloads, exploitation and rational use of water resources,urban drainage and flood control, coordinated action onwater resources management and sustainable land use,and building tools of participative management by thelocal municipalities, considering also the impact fromtransboundary issues. The project was estimated at251.6 millions of dollars for the lower river sectionand its estuary, and for the entire drainage basin, theinvestments reach $1.5 billion.

The final overall ASSETS grade

The combined PSR index is presented in Table 8. PSEhad the best indices, with a good final trophic status.MUL was classified with moderate eutrophic condi-tions, with a future outlook of low improvement and amoderate final classification. MAL and PL had theworst or highest eutrophic conditions for which a badfinal ASSETS grade was discerned. GL presented mod-erate eutrophic conditions, but its future outlook is toworsen and the final ASSETS grade is poor.

Seasonality

The results obtained by the ASSETS model corre-spond to the average annual condition of the systems.

Table 7 Determination of future outlook by the combination of the susceptibility and future nutrient trend pressure for the systems

MUL MAL GL PL PSE

Susceptibility High High High High Low

Future nutrient pressures Decrease Decrease Increase Increase Decrease

Future outlook Improve low Improve low Worsen high Worsen high Improve high

Table 8 Combination of the three PSR indices providing the final ASSETS for each system

MUL MAL GL PL PSE

IF High High High High Moderate low

EC Moderate High Moderate Moderate high Moderate low

FO Improve low Improve low Worsen high Worsen high Improve high

ASSETS Moderate Bad Poor Bad Good

IF influencing factors, EC eutrophic conditions, FO future outlook, ASSETS Assessment of Estuarine Trophic Status

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However, one should consider that seasonal shifts inthe degree of eutrophication may occur in all systemsdue to the unimodal pattern of freshwater inflow andassociated nutrients, as well as multiple land use prac-tices, especially of agriculture. The ASSETS modelwas tested for the systems with the highest seasonalvariability, the Mundaú–Manguaba lagoons and theParaíba do Sul estuary. The data were treated as abovebut separated for the governing dry and wet periods.Table 9 summarizes all the PSR indices and also thefinal ASSETS grade.

PSE presented an improvement of the trophic statusfrom the dry to the rainy period, whereas for MUL andMAL, no significant differences between the dry andwet seasons were discerned by ASSETS. The seasonalASSETS classification in MUL and MAL were thesame as obtained from the average annual data set,which was poor and bad, respectively. PSE, whichreceived a good ASSETS grade based on the averageannual data set, now received a moderate grade for thedry season and a high grade for the wet season. Thedifferences in the seasonal expression of the trophicstatus in PSE are related to the marked unimodalseasonal pattern of river flow.

Discussion

The final ASSETS grade assigned to MUL was poor,to MAL as bad, to GL as poor, to PL as bad, and toPSE as good. However, the individual pressure–state–response indices differed between the systems notonly due to differences in nutrient inputs and algalbiomass but also due to the natural typology of thewatersheds and the hydrological–geomorphologicalconfiguration of the systems.

The ASSETS methodology indicated that thelagoon systems addressed are naturally highly suscep-tible to eutrophication, as also indicated on a qualita-tive basis by studies from other lagoons of SE Brazil(Knoppers and Kjerfve 1999; Knoppers et al. 1999).All of the lagoons addressed fall into the category ofchoked lagoons with a high degree of enclosure fromthe sea and high residence times of water due to theefficient dissipation of tidal energy by more than 90 %in the tidal channels. This leads to efficient retentionand also recycling of biogenic matter in the systems(Knoppers et al. 1999). All of these are naturallysubject to eutrophication and the degree of differencesin nutrient inputs versus residence times of water asdealt with the ASSETS model seems to have givenacceptable results, when compared to earlier defini-tions of the trophic state (Knoppers et al. 1991, 1999).

On the other hand, the low susceptibility of PSE toeutrophication is a result both of its open access to thesea, tidal pumping, and the high freshwater flow lead-ing to its high potential of dilution and flushing.During the wet season, the nutrients are rapidlyflushed to the sea, diluted during plume dispersal,and primary production remains low within the estu-ary. Under these conditions, primary production mayincrease at the inner shelf after the gradual sedimenta-tion of suspended particles (Balzer and Knoppers1996). In contrast, during the dry season, the nutrientsreside longer within the estuary, being more availableto the biota and the primary production is favored.

The higher nutrient N inputs of PSE, MUL, andMAL were not only due to the much larger watershedsof these systems in comparison to those of GL and PLbut also due to their multiple anthropogenic uses in-volving nitrogen. PSE, by far the largest system,receives nitrogen from intense urban and industrial

Table 9 Summary of the all indices of the ASSETS classification for the seasonal periods for MAL, MUL, and PSE

System Period Sus N Inp IF P Symp S Symp EC FO ASSETS

MUL Dry H H H H L M IL P

Rainy MH H H H L M IL M

MAL Dry H H H H H H IL B

Rainy MH H H H L M IL M

PSE Dry M H MH ML L ML IH M

Rainy L H ML L L L IH H

Sus susceptibility, NInp nutrient input, IF influencing factors, P Symp primary symptoms, S Symp secondary symptoms, EC eutrophicconditions, FO future outlook

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point sources and agricultural uses (fertilizers) alongits long river course. The smaller Mundaú–Manguabalagoon system also receives relatively high nutrient Nloads, but essential features distinguish both from eachother.

The MUL and MAL watersheds deliver N fromdiffuse urban sources and nutrient fluxes from sugar-cane production. But MUL is drastically affected bythe N input of one fourth of the total population ofabout one million of Maceió City; MAL only receivesdomestic effluents from a population of about 60,000.On the other hand, the average annual residence timeof water of MUL is in the order of 2 weeks, while ofMAL 6 weeks (Oliveira and Kjerfve 1993). It seemsthat higher flushing times of MUL as compared toMAL compensate for the higher nutrient inputs bydilution. ASSETS discerned a bad state for MAL andonly a poor state for MUL, mainly due to differencesbetween the systems secondary symptoms, which inMAL corresponds to the frequent occurrence ofcyanobacterial blooms of Anabaeana spiroides andMicrocystis aeruginosa in alternation with the diatomsCyclotella meneghiniana and Skeletonema cf. costatum.The blooms and their chlorophyll a biomass valuesclearly induced eutrophic conditions and occasionallyHABs (Melo-Magalhães et al. 2008).

The final ASSETS grade calculated to GLwas equiv-alent to MUL, despite that nutrient loading to GL wassmaller. However, both exhibited similar residencetimes of water (i.e., 2 weeks). GL is also characterizedby a succession of phytoplankton species fromCyanobacteria in summer to a mixed population ofdiatoms and dinoflagellates in winter (Knoppers et al.1999). But both systems differ considerably with respectto the area ratio between the watershed and lagoonsurfaces, with GL also harboring a higher relief water-shed with more preserved forests and MUL a larger butlower relief watershed with more human impacts. Thesedifferences did not affect the final ASSETS ranking.

In PL, low levels of DO are related to the massiveproliferation of the macroalgae Chara hornemannii.Stagnation and light limitation of bottom waters with-in the algal banks lead to the degradation of organicmatter produced at the top of the banks and henceforthto hypoxic or even anoxic conditions at the bottom. PLdoes not exhibit any direct riverine input of materialsbut is connected to another lagoon by a channel whichhas direct access to the sea (Carneiro et al. 1994).Urbanization in the entire area has induced eutrophication

over time, but sewage treatment plants are only nowbeing implemented.

The eutrophication symptoms varied within andacross the system types. For instance, the phytoplank-ton species composition in transitional waters has beenshown to be linked to the flushing time of waters(Bettencourt et al. 2003; Ferreira et al. 2005), includ-ing the lagoons from Rio de Janeiro (Knoppers et al.1999). This can also be observed comparing the PSEand the GL systems. The watershed of PSE supplies400 times more N than the watershed of GL, but theinfluencing factor of PSE is minor due to its highfreshwater discharge and flushing potentials. For ex-ample, similar patterns are also found between SanFrancisco Bay and Chesapeake Bay, USA. The formerreceives a higher N and P loading than the latter, butSan Francisco Bay has lower standing stocks of phy-toplankton and little or no hypoxia as a result of itsvigorous tidal mixing and light limitation caused bysediment resuspension (Boesch 2002). According toSharp (2010), in the Delaware Estuary (USA), andprobably many other urbanized estuaries, high nutrientinputs do not necessarily lead to adverse eutrophica-tion responses that are controlled more by the aquaticecology and physical dynamics, rather than anthropo-genic inputs.

The definition of future outlook was variablebetween the systems because the watersheds of theBrazilian rivers and estuaries are managed by munici-palities which do not commonly interact to cover theentire watershed under a single managing concept. Eachcommittee of a determined sub-watershed is responsiblefor its management, but some are more articulated,organized, and established than others. The committeesare responsible for the elaboration of the water resourcesplan of the areas. Committees which will in the futuremanage entire watersheds as a single functional unit arenow being implemented for three of the systems (PSE,MUL, and MAL) (ANA 2006a, b).

The seasonal variability of system functioning isalso an important feature to be considered for theapplication of the ASSETS model in tropical andsubtropical estuaries and in management actions, asalso evidenced by the exercise for PSE. The naturalsusceptibility was largely related to the seasonal vari-ation of the residence times of water or as such thefreshwater inflow controlled by precipitation. Thisdirectly affected the pressure component of the model.The eutrophic condition improves when freshwater

3308 Environ Monit Assess (2013) 185:3297–3311

flow is larger and nutrients bypass the system resultingin a lower uptake potential by primary producers.These conditions are especially evident in systems thathave marked seasonal patterns, like in PSE. In theMUL and MAL, the river flow has different conditionsbetween the seasons, but this difference is not suffi-cient to shift the ASSETS classification, indicatingthat in these lagoons, the eutrophication is persistentthroughout the year due to, primarily, their longerresidence times of water. In all, it seems that thehydrodynamic component of the ASSETS model, in-cluding the dilution and flushing potential, plays themajor role in determining the degree of the trophicstate rather than only the nutrient load itself.

Despite the fact that Brazil has a comprehensiveand rigorous environmental legislation, Law enforce-ment is the caveat. Law 6938/1981 establishes theNational Policy of the Environment, aimed to pre-serve, improve, and restore environmental quality.Law 9605/1998, known as Environmental CrimesLaw, provides for criminal and administrative sanc-tions from harmful activities to the environment. The357/2005 CONAMA Resolution provides for the clas-sification and environmental guidelines for the frame-work of surface water bodies, as well as establishes theconditions and effluent discharge standards. However,laws and specific incentives dealing with the eutrophi-cation problem (e.g., NEEA, WFD) for Brazilian wa-ter bodies have as yet to be implemented.

Conclusions

The differences established by ASSETS corroboratedthat the natural susceptibility in well-flushed systemswas lower than in poor-flushed systems, such as thelagoons. As such, it becomes obvious that the typologyand water residence times together with robust knowl-edge of the land uses and nutrient inputs of a system arethe key factors for the understanding of the establish-ment of environmental status and its management.

Using the ASSETS, multi-parameter methodologyto determine the trophic state of the addressed Brazil-ian systems highlighted the importance and utility ofusing systematic methods for coastal management. Itwas applied to rank eutrophication status of someBrazilian estuaries and provides one of the first workscontaining the status of eutrophication in Braziliansystems. Improvements to the ASSETS model are

suggested in the pressure component, like insertaspects of nutrient co-limitation (N and P) for phyto-plankton growth and add studies of ground waterdischarge. The evaluation exercise of the trophic statuswith ASSETS for PSE with distinct wet and dry sea-sons also yielded useful results and should be consid-ered as a relevant factor in systems with greatvariations in climate and river run-off.

Acknowledgments The authors thank all the students in-volved in the acquisition of samples and laboratory assistance.Manoel Messias dos Santos of UFAL performed the nutrientanalyses for Mundaú–Manguaba and Wilson Machado (UFF)provided valuable criticism and suggestions. L.C. CotoviczJunior is a Ph.D. Scholar of CNPq and N. Brandini a Post-Docfrom CAPES. B. Knoppers is a Senior Researcher from CNPq(Proc. Nr. 301572/2010-0). Funding was obtained from CNPq(POLCAMAR-Project proc. nr. 590002/2005-8 and INCT-TMOcean proc. no. 573601/2008-9). The authors also thankSuzanne B. Bricker and João G. Ferreira for their help inunderstanding and application of ASSETS. We are highly grate-ful to the two anonymous reviewers for their time consuminginput and valuable remarks.

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