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An ecohydrology model of the Guadiana Estuary
Estuarine Coastal Shelf Science
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Estuarine, Coastal and Shelf Science xx (2006) 1e12
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www.elsevier.com/locate/ecss
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An ecohydrology model of the Guadiana Estuary (South Portugal)
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Eric Wolanski a,*, Luıs Chicharo b, M. Alexandra Chicharo b, Pedro Morais b
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a
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Australian Institute of Marine Science, PMB No. 3, Townsville MC, Queensland 4810, Australia
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Centro de Ciencias do Mar, Faculdade de Ciencias do Mar e do Ambiente, Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
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Received 30 January 2005; accepted 20 March 2006
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Abstract
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A 1-D ecohydrology model is proposed that integrates physical, chemical and biological processes in the Guadiana Estuary during low flow
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conditions and that predicts the ecosystem health as determined by the following variables: river discharge, nutrients, suspended particulate mat-
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ter, phytoplankton, zooplankton, bivalves, zooplanktivorous fish and carnivorous/omnivorous fish. Low flow conditions prevail now that the Al-
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queva dam has been constructed. The ecological sub-model is based on the non-linear LotkaeVolterra equation. The model is successful in
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capturing the observations of along-river changes in these variables. It suggests that both bottom-up and top-down ecological processes control
the Guadiana Estuary ecosystem health. A number of sensitivity tests show that the model is robust and can be used to predict e within likely
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error bounds provided by the sensitivity tests e the consequences on the estuary ecosystem health of human activities throughout the river catch-
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ment, such as the irrigation farming downstream of the Alqueva dam, reclamation of the salt marshes by urban developments, and flow regu-
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lation by the Alqueva dam. The model suggests that the estuarine ecosystem health requires transient river floods and is compromised by flow
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regulation by the Alqueva dam. Remedial measures are thus necessary.
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Ó 2006 Elsevier Ltd. All rights reserved.
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Keywords: ecohydrology; marine ecology; flushing; modelling; dam; flow regulation; Portugal; Alqueva dam; Guadiana Estuary
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The impact on estuaries is commonly still ignored when
1. Introduction
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dams and irrigation farming are proposed on rivers. In addi-
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1.1. The need for an ecohydrology estuarine model tion, estuaries are often regarded as sites for future develop-
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ment and expansion, and have been increasingly canalized
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Throughout human history, the coastal plains and Lowland and dyked for flood protection, and their wetlands infilled
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River valleys have usually been the most populated areas over for residential areas.
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the world (Wolanski et al., 2004). At present, about 60% of the All these factors impact on the biodiversity and productiv-
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world’s population lives along the estuaries and the coast (Lin- ity and, hence, the overall health of estuaries and the ecosys-
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deboom, 2002). This is degrading estuarine and coastal waters tem services they provide to humans (Nixon, 2003; Erzini,
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through pollution, eutrophication, increased turbidity, overf- 2005). They increasingly lead humans away from the possibil-
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ishing, and habitat destruction. The pollutant supply does ity of ecologically sustainable development of the coastal
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not just include nutrients; it also includes mud from eroded zone. Integrated coastal zone management plans are drawn
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soil, heavy metals, radionuclides, hydrocarbons, and a number up worldwide (e.g., Haward, 1996; Bille and Mermet, 2002;
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of chemicals including new synthetic products. Tagliani et al., 2003; Pickaver et al., 2004; Lau, 2005). How-
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ever, in the presence of significant river input, most are bound
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to fail because they commonly deal only with local, coastal is-
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sues, and do not consider the whole river catchment as the fun-
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damental planning unit. It is as if the land, the river, the
* Corresponding author.
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estuary, and the sea were not part of the same system. When
E-mail address: e.wolanski@aims.gov.au (E. Wolanski).
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0272-7714/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved.
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doi:10.1016/j.ecss.2006.05.029
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dealing with estuaries and coastal waters, in most countries assumed to follow those described by Wolanski et al. (2004)
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land-use managers, water-resources managers, and coastal and are sketched in Fig. 1. These processes are briefly sum-
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and fisheries managers do not cooperate effectively due to marised below.
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administrative, economic and political constraints, and the The ecological health of estuaries is determined by the
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absence of a forum where their ideas and approaches are interaction between organisms and variations in salinity,
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shared and discussed (Wolanski et al., 2004). To help alleviate currents, waves, suspended particulate matter (SPM), bed
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this problem, UNESCO e IHP has launched the ecohydrology sediments, temperature, air exposure, hypoxia, wetland
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program. In this program, the concept of ecohydrology is contaminants and biodiversity. Like the health of a living
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introduced as a holistic approach to the management of rivers, organism, the health of an estuary or a coastal water body, can-
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estuaries and coastal zones within entire river catchments, by not be measured by one single variable, indeed a number of
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adopting science-based solutions to management issues that variables are important (Balls, 1994). Well-flushed estuaries
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restore or enhance natural processes as well as the use of tech- are intrinsically more robust than poorly flushed systems. As
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nological solutions (Zalewski, 2002). a result, environmental degradation is most often apparent dur-
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This science-based management requires the use of a holis- ing periods of reduced freshwater inflows, e.g. during drought
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tic model to quantify the human impact on the ecosystem or when human activities reduce the freshwater flow. There-
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health of estuaries and to enable the exchange of information fore, this ecohydrology model focuses on low flow conditions
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between oceanographers, biologists, ecologists, engineers, so- when vertically well-mixed conditions often prevail.
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ciologists, economists and water-resources managers at local Once riverine-derived suspended particulate matter enters the
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and national governmental levels, and the community. estuary, it can be trapped within an estuarine turbidity maximum
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(ETM) zone (Fig. 1). The ETM is commonly located in the
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very low salinity reaches of an estuary. The maximum, depth-
1.2. The science behind the model
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averaged, suspended solid concentration (SSC) at high water
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within an estuary can be predicted semi-empirically as a function
The model is process-based. The dominant physical, chem-
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of the tidal intrusion and the tidal range (Uncles et al., 2002).
ical, biological and human-related processes in an estuary are
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Fig. 1. Sketch of the dominant processes operating in an estuary. Adapted from Wolanski et al. (2004).
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Sediment particles and aggregates within the ETM can give of the food web and influences the fisheries (Chıcharo et al.,
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rise to marked changes in water quality. Fine particles can 2002; Erzini, 2005).
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adsorb metal ions and organic macro-molecules from solution Several pollution sources exist in the Guadiana Estuary
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to such an extent that some metals can be completely removed area, mainly resulting from urbanisation, agriculture (fertil-
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from solution within a strong ETM (Salomons and Forstner, izers, pesticides, and herbicides), cattle breeding and olive
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1984; Ackroyd et al., 1986). Once nutrients enter an estuary, oil production. The freshwater flow reaching the estuary is
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non-conservative behaviour can be pronounced. Key processes at present regulated by more than 100 dams, including the
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responsible for this non-conservative behaviour include burial Alqueva dam whose construction was completed in 2002
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in sediment reservoirs and desorption processes particularly if and that forms the largest reservoir in Europe (Alveirinho
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the sediment is nutrient-rich. Nutrients are generally mainly in et al., 2004).
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particulate form (i.e. absorbed to the mud particles in suspen-
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sion) in freshwater and can be released in solution in saline 1.4. Aims
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water.
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The salt marshes of Western Europe generally produce This study aimed to develop an ecohydrology model to be
more than 1 kg mÀ2 yrÀ1 of above-ground dry matter (Boor-
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applied to the low flow conditions in the Guadiana Estuary. It
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man et al., 1994a,b; Lefeuvre, 1996). Salt marshes export describes such a model designed specifically for vertically
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some of this organic matter. Salt marshes and their tidal creeks well-mixed estuaries. The ecological sub-model is also simple,
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are also an important nursery ground, and a refuge, for larvae though still realistic. It incorporates the seven state variables:
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and post-larvae of bivalve, carnivorous/omnivorous fish and nutrients, suspended particulate matter, phytoplankton, zoo-
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zooplankton. plankton, bivalves, zooplanktivorous fish and carnivorous/om-
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The estuary is modelled as a converter of living phyto- nivorous fish in the estuary and it predicts the ecosystem
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plankton to detrital particles; it is also a conveyor of detrital health.
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matter to the sea. Fishes help transfer energy and matter
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from estuarine plants to upper trophic levels. The great bulk 2. Material and methods
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of the organic matter produced (sometimes 90%) is processed
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through the detrital system. Zooplankton, planktivorous fish, 2.1. Field data
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interstitial micro and meiofauna, surface deposit-feeding mol-
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luscs, fishes and polychaeta, and filter-feeding invertebrates Estuarine physical, chemical and biological data were
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consume a much greater proportion of the primary production obtained from the papers of M. Chicharo et al. and P. Morais
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of the phytoplankton and benthic microalgae. Annual plant et al. in this issue and from Pinto (2000), and Esteves et al.
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growth and decay provide continuing large quantities of (2000). Data from river inflow were obtained online from
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organic detritus. In addition, there is often a considerable input Water National Institute (INAG), National System of Hydro-
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of detritus from river inflow. Detrital particles and their asso- logical Resources (http://snirh.inag.pt/) from the hydrometric
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ciated microorganisms provide the basic food source for station Pulo do Lobo (lat. 37 480 N, long. 7 380 W), located
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primary consumers such as zooplankton, most benthic a few kilometres above the last point of tidal influence
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invertebrates and some fishes. The first trophic level in the ´
(Mertola).
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estuarine ecosystem is therefore best described as a mixed tro-
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phic level of detritus consumers, which in varying degrees are 2.2. The estuarine ecohydrology model
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herbivores, omnivores or primary carnivores (Knox, 1986).
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The prototype is the Guadiana Estuary at low flow
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1.3. Study area conditions e because such low flow conditions prevail now
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that the Alqueva dam exists. For a freshwater flow Qf <
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The Guadiana River is one of the largest in the south of the 50 m3 sÀ1, the Guadiana Estuary is vertically fairly well-
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Iberian Peninsula, crossing extensive rural areas and includes mixed in salinity (Fortunato et al., 2002). In a vertically
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the Iberian Pyritic Belt (Gonzalez, 1995). well-mixed estuary, the distribution of salinity S is determined
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The fluvial regime is characterised by low flows during from the solution of the 1-D advectionediffusion equation
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summer and episodic runoff periods in winter with the result- (Fischer et al., 1979):
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ing discharge of sediments into the estuary and coastal zone.
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The estuary is 60 km long, it has a maximum width of vðSAÞ=vt þ vðQSÞ=vx ¼ vðEA vS=vxÞ=vx ð1Þ
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550 m and the maximum depth varies between 5 and 17 m.
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The tidal regime of the estuary is meso-tidal, with an average where t is the time, Q is the flow rate (driven by tides and
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amplitude of 2 m (Michel, 1980). river flows), E is the longitudinal eddy diffusion coefficient,
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The estuary has an important nursery function for several and A is the cross-sectional area. Eq. (1) is solved for a series
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fish species, such as the anchovy Engraulis encrasicolus sensu of cells of volume V distributed along the length of the estu-
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lato and several Sparidae, and crustacean species such as the ary from the tidal limit to the mouth. The time step dt is set
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brown shrimp Crangon crangon. Moreover, the outwelling to 1 day, thereby averaging over the tides. The open bound-
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from the estuary to the coastal area promotes the development aries are located at the tidal limit and at the mouth. At the
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Fig. 2. Observed and predicted along-channel distributions of salinity in the Guadiana Estuary around the times of (square) high tide and (circle) low tide for
salinity of (a) 2 m3 sÀ1 and (b) 50 m3 sÀ1. Cell # 1 is located at the tidal limit, 60 km upstream of cell # 20 that is located at the mouth.
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tidal limit, the model assumes that the salinity S ¼ 0 and it vðCAÞ=vt þ vðQCÞ=vx ¼ vðEA vC=vxÞ=vx þ DC ð2Þ
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also assumes that Qf is known. At the mouth, the salinity
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is assumed to be 35. Turbulent diffusion is due to tides, where DC is derived from the ecological sub-model described
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wind, and freshwater runoffs and is parameterised by the pa- below.
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rameter E. In the model, this is determined by mixing coef- The ecological sub-model is based on the non-linear
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ficients that quantify the fraction of water in a cell that is LotkaeVolterra equation. It is based on a finite-element model
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exchanged with adjoining cells during the time step (1 with the same cells as those used in the salinity model. A num-
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day). This parameter is varied until the solution fits well ber of modeling equations are possible. In the absence of
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with the observations. This is shown in Fig. 2 for the case excretion and death not due to predation, the predatoreprey
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of the Guadiana Estuary for two values of the freshwater dis- relationship is often calculated by the non-linear equations
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charge Qf (2 and 5 m3 sÀ1). (Brauer and Castillo-Chavez, 2001; Kot, 2001).
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The model enables one to readily calculate the flushing time
vX=vt ¼ bXð1 À X=Xo ÞHðY; Yo1 Þ ð3Þ
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of the estuary. To do that, in the model the freshwater discharge
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is set to be a constant and the estuary is initially filled with uni-
and
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form seawater salinity at t ¼ 0. The system is then allowed to
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evolve, and in the model salt is progressively expelled from vY=vt ¼ ÀbXð1 À X=Xo ÞHðY; Yo1 Þ ð4Þ
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the upper reaches of the estuary until a steady state solution is
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where X is the predator biomass (X ¼ CV) where C is the pred-
reached. This is shown in Fig. 3 for a freshwater discharge
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(Qf) of, respectively, 2 and 50 m3 sÀ1. It is apparent that for ator concentration, Y is the prey biomass, b is the predator
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Qf ¼ 50 m3 sÀ1 the residence time is about 5 days, and that for growth rate, Xo is the predator saturation biomass, Yo1 is the
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Qf ¼ 2 m3 sÀ1 the residence time varies between 14 days in prey starvation biomass, i.e. the biomass at which the predator
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the lower reaches and 37 days in the upper reaches of the estuary. is unable or unwilling to spend energy to find this prey. H is
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the Heavyside function, i.e. H ¼ 0 if Y < Yo1, and H ¼ 1 if
For a non-conservative constituent such as nutrients, plank-
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Y > Yo1. Eq. (2) also applies if Y is a nutrient. Provided starva-
ton, detritus, fish, and bivalve, Eq. (1) is modified by including
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a sinkesource term DC (Thomann, 1980), where C is the tion does not occur, the solution is an S-shaped curve whereby
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concentration: X initially increases exponentially in time. The growth rate is
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Fig. 3. Estimation of the residence time from the time series of salinity distribution in the estuary following intrusion of freshwater for (a) 2 m3 sÀ1 and
(b) 50 m3 sÀ1.
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zero at X ¼ Xo. Because X and Y are related by Eqs. (3) and
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concentration (N ), suspended sediment concentration (SSC),
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(4), Y decreases toward a minimum value. phytoplankton concentration (P), zooplankton concentration
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In the model, freshwater phytoplankton and bacterioplank- (Z ), bivalve concentration (B), detritus concentration (D), zoo-
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ton in the river are subject to salt stress when freshwater mixes planktivorous fish concentration (ZF), and carnivorous/omniv-
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with saltwater; and the freshwater microbial populations die in orous fish concentration (CF). All dying matter becomes
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this zone (Flameling and Kromkamp, 1994; Goosen et al., detritus. Settling is not included in the model, because the an-
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1995). In the model, the salinity also limits the seaward distri- imals (e.g. zooplankton) are mobile and can swim in the water.
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bution of saline water plankton, invertebrates (e.g. bivalves) The model is equally complex at the lowest and highest tro-
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and fishes. phic levels, which increases the model robustness (Jorgensen
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In an estuary, changes in salinity constitute a major stress and Bendoricchio, 2001). Thus the ecosystem model equations
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that can lead to death. There are other stressors, for instance, are:
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small values of the dissolved oxygen concentration. A death-
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excretion rate d must then be added to Eq. (3) that becomes: Nutrients (N; nitrate)
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vX=vt ¼ bXð1 À X=Xo ÞHðY; Yo1 Þ À dX ð5Þ vN=vt¼ÀbNP Pð1ÀP=Po ÞHðN;No1 ÞþaN þgSSCN SSC ð7Þ
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Phytoplankton (P)
The solution of this equation is also an S-shaped curve, the
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maximum value, however, is smaller than in the absence of
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vP=vt ¼ bNP Pð1 À P=Po ÞHðN;No1 Þ À bPZ Zð1 À Z=Zo ÞHðP;Po1 Þ
this death-excretion rate, that is X ¼ Xo(1 À d/b). To remain re-
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alistic the solution requires b > d, i.e. that the growth rate is
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À bPB Bð1 À B=Bo ÞHðP;Po1 Þ
larger than the death-excretion rate.
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À bPCF CFð1 À CF=CFo ÞHðP;Po1 Þ þ aP À dP P ð8Þ
In an estuary, fringing wetlands (mainly salt marshes and
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riparian ecotones, together with the tidal creeks that drain
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Zooplankton (Z )
them) can be an important source of detritus and nutrients,
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as well as a nursery for juveniles and sub-adults as well as
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vZ=vt ¼ bPZ Zð1 À Z=Zo ÞHðP;Po1 Þ þ bDZ Zð1 À Z=Zo ÞHðD;Do1 Þ
a refuge. This is particularly the case for bivalves. Mathemat-
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À bZZF ZFð1 À ZF=ZFo ÞHðZ;Zo1 Þ
ically, this is expressed by adding a source of X to the right-
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À bZCF CFð1 À CF=CFo ÞHðZ;Zo1 Þ þ aZ À dZ Z ð9Þ
hand side of Eq. (5). The final equation becomes:
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vX=vt ¼ bXð1 À X=Xo ÞHðY; Yo1 Þ À dX þ a ð6Þ
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Bivalves (B)
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where a is the import rate from wetlands.
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vB=vt ¼ bPB Bð1ÀB=Bo ÞHðP;Po1 ÞþbDB Bð1ÀB=Bo ÞHðD;Do1 Þ
The ecosystem model represents mathematically through
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ÀbBCF CFð1ÀCF=CFo ÞHðB;Bo1 ÞþaB ÀdB B ð10Þ
Eq. (5) the interactions summarised in Fig. 4 between nutrients
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Fig. 4. Sketch of the estuarine food web in the ecohydrology model.
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Carnivorous/omnivorous fish (CF) SSC ¼ 30 if S < 1
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SSC ¼ 30 þ 7S if 1 < S < 12
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vCF=vt ¼ bBCF CFð1 À CF=CFo ÞHðB;Bo1 Þ SSC ¼ 100 À 3:5ðS À 15Þ if S > 12
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þ bPCF CFð1 À CF=CFo ÞHðP;Po1 Þ
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The model needs the knowledge of all the ecological pa-
þ bZCF CFð1 À CF=CFo ÞHðZ;Zo1 Þ
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rameters. The parameter a varies along-channel to correspond
þ bDCF CFð1 À CF=CFo ÞHðD;Do1 Þ
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to the location of the salt marshes and riparian/terrestrial veg-
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þ aCF À dCF CF ð11Þ etation. The approximate values of the parameters are known
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from a number of studies and from comparison with other es-
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tuaries. The final values were selected as a result of a best-fit
Zooplanktivorous fish (ZF)
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between observed and predicted values. The results of this cal-
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ibration are shown in Fig. 5 for nutrients, zooplankton, bi-
vZF=vt ¼ bZZF ZFð1ÀZF=ZFo ÞHðZ;Zo1 Þ
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valve, and fish, respectively. Table 1 lists the adopted values
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þbDZF ZFð1ÀZF=ZFo ÞHðD;Do1 ÞþaZF ÀdZF ZF ð12Þ
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of the parameters.
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While the calibration appears successful, it is important for
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the user to also judge whether the solution is realistic and sta-
Detritus (D)
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ble (Hilborn and Mangel, 1997). This may be done by under-
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taking a sensitivity test to judge whether the model is
vD=vt ¼ ÀbDB Bð1ÀB=Bo ÞHðD;Do1 Þ
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unrealistically sensitive to a specific parameter, making it po-
ÀbDZF ZFð1ÀZF=ZFo ÞHðD;Do1 Þ
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tentially unstable and unrealistic. A number of sensitivity runs
ÀbDCF CFð1ÀCF=CFo ÞHðD;Do1 Þ
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were carried out, each one involving changing one parameter.
Calculations were performed for Qf ¼ 2 m3 sÀ1, which is the
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ÀbDZ Zð1ÀZ=Zo ÞHðD;Do1 ÞþaD þaD þdB BþdP P
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environmental flow for the Guadiana River, i.e. the post-dam
þdZ Z þdCF CFþdZF ZF ð13Þ
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river discharge during the dry season. The list of sensitivity
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runs is summarised in Table 2.
In these equations the subscripts denote either constituent
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The sensitivity tests show that phytoplankton (Chl a) is
or the interaction between two constituents. For instance,
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most sensitive in cases 2, 4 and 5, i.e. to bNP, bPB and dP
dZF is the death-excretion rate of ZF, and bDZF is the growth
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(Fig. 6a).
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rate of ZF from detritus, i.e. the rate of mass transfer rate
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These results suggest that bivalves play a more important
from detritus to ZF.
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role in filtering phytoplankton than zooplankton. This can re-
In the nutrient equation, a new parameter was introduced,
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sult from the fact that bivalves are benthic and sessile organ-
gSSCN, it denotes the leaching rate of nutrients from the partic-
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isms, being able to resist currents as opposite to zooplankton
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ulate phase (i.e. absorbed on the fine sediment) to the dis-
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populations, although some develop strategies to resist dis-
solved phase.
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placement forces (Simenstad et al., 1994).
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In Eq. (2), because the model is run at a time step of 1 day,
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The most important parameter for zooplankton is dZ (the
Q ¼ Qf. There is thus no need to calculate the tidal dynamics;
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death-excretion rate of zooplankton), and to a lesser degree
these are parameterised by the term E.
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bNP (uptake rate of nutrient by phytoplankton) and bPZ (uptake
When applying Eq. (2) to the zooplanktivorous fish equa-
608 665
rate of phytoplankton by zooplankton). The model zooplankton
tion, Q is modified to incorporate the horizontal swimming
609 666
(Z ) is most sensitive in case 7 and to a lesser degree in cases 2
CO
by the fish as fish swim, by kinesis or taxis following environ-
610 667
and 3 (Fig. 6). As detritus can also be included in zooplankton
diet, if bDZ ¼ 0.1 dayÀ1. In fact, in a situation of low inflow e as
mental clues (Wolanski et al., 1997; Humston et al., 2000).
611 668
This velocity is assumed to be proportional to S. Thus the
612 669
the one tested in the sensitivity runs (Fig. 6c) e the expected de-
fish in the model is able to swim, following taxis or kinesis,
613 670
crease in detritus input caused by the reduction of inflow will
along environmental gradients.
614 671
affect the zooplankton biomass in the estuary, which highlights
UN
615 672
the importance of detritus as food source for estuarine zoo-
616 673
plankton (Edwards, 2001; Kibirige et al., 2002).
3. Results and discussion
617 674
The model also shows that zooplanktivorous fish (ZF) is
618 675
most sensitive to bZZF, bDZF, and dZF (i.e. respectively, the up-
3.1. Application to the Guadiana Estuary
619 676
take rate of zooplankton by zooplanktivorous fish, the uptake
620 677
In the Guadiana Estuary, field data of fine sediment concen- rate of detritus by zooplanktivorous fish, and the death rate of
tration during low flow conditions (Qf < 50 m3 sÀ1) suggest
621 678
the zooplanktivorous fish; cases 6, 11 and 12) (Fig. 6d). In
622 679
the presence of a weak turbidity maximum zone near the salin- fact, salinity changes caused by modification of freshwater/
ity intrusion limit, with a maximum SSC value of 114 mg lÀ1
623 680
seawater balance may affect zooplanktoneprey distribution
at S ¼ 12 while SSC is about 30 mg lÀ1 in the freshwater rea-
624 681
and impact zooplanktivorous fish species distribution. More-
625 682
ches of the estuary (Portela, unpubl. data). Therefore, the over, it suggests that the export of detritus from the salt marsh
626 683
model assumes a suspended sediment concentration (SSC) does not seem to be the most important source of food for
627 684
that is determined as follows: these fish.
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F
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698 755
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PR
703 760
704 761
705 762
706 763
707 764
708 765
ED
709 766
710 767
711 768
712 769
CT
713 770
714 771
715 772
Fig. 5. Along-channel distribution in the Guadiana Estuary of (a) observed (dots) and predicted (line) total fish biomass, (b) observed (dots) and predicted (line)
716 773
bivalve biomass, (c) observed (dots) and predicted (line) nutrients’ (nitrate) mass, and (d) observed (dots) and predicted (line) zooplankton biomass. To convert
E
717 774
À2 À2 À3
biomass to concentration, for fish 2.8e2.87 g cm , for bivalve 1.2e24 m , for nitrate 4e15.5 mM, and for zooplankton 1e54 m .
718 775
RR
719 776
Table 2
720 Model sensitivity runs. All the runs were carried out for a steady, freshwater 777
721 778
discharge Qf ¼ 2 m3 sÀ1. Rates are expressed as dayÀ1
722 779
Run 1: Standard run
Table 1
723 780
bNP decreased from 0.1 to 0.05
Run 2:
CO
Final values of the parameters. Rates are expressed as dayÀ1
724 781
bPZ decreased from 0.1 to 0.05
Run 3:
bPB decreased from 0.1 to 0.05
bNP Run 4:
0.2
725 782
dP decreased from 0.05 to 0.025
bPZ Run 5:
0.1
726 783
bZZF decreased from 0.1 to 0.05
Run 6:
bPB 0.1
727 784
dZ decreased from 0.1 to 0.05
Run 7:
dP 0.05
728 785
bBCF decreased from 0.1 to 0.05
bZZF Run 8:
0.1
UN
729 786
dZ Run 9: decreased from 0.1 to 0.05
0.1
dCF decreased from 0.1 to 0.05
Run 10:
bBCF 0.1
730 787
bDZF decreased from 0.1 to 0.05
Run 11:
dB 0.1
731 788
dZF decreased from 0.1 to 0.05
dCF Run 12:
0.1
732 789
bSSCN decreased from 0.3 to 0.15
bDZF Run 13:
0.1
733 790
bZCF decreased from 0.03 to 0.015
Run 14:
dZF 0.1
734 791
bSSCN Run 15: decreased from 0.03 to 0.015
0.3
bDB decreased from 0.1 to 0.05
bZCF Run 16:
0.03
735 792
aZ and aB decreased from 0.15 to 0.075
Run 17:
bDCF 0.03
736 793
aD in the freshwater zone increased from 0 to 0.05
Run 18
bDB 0.1
737 794
À1 À1
bDZ increased to 0.1 day (run 19) and 0.05 day
bDZ Run 19:
0.05
738 795
aB (run 19a, open circles)
0.15 (¼0 in freshwater reaches)
739 aD increased to 0.15 in the saline region and 0.05 in 796
Run 20:
aD 0.05 (¼0 in freshwater reaches)
the freshwater region
aCF 0.05 (¼0 in freshwater reaches)
740 797
bPCF increased to 0.1; az and aB increased to 0.15
aZ Run 21:
0.05 (¼0 in freshwater reaches)
741 798
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805 862
806 863
807 864
808 865
809 866
F
810 867
811 868
OO
812 869
813 870
814 871
815 872
816 873
PR
817 874
818 875
819 876
820 877
821 878
822 879
ED
823 880
824 881
825 882
826 883
CT
827 884
828 885
829 886
830 887
E
831 888
832 889
RR
833 890
834 891
835 892
836 893
837 894
CO
838 895
839 896
840 897
841 898
842 899
UN
843 900
844 901
845 902
Fig. 6. Along-channel distribution of predicted variables in the Guadiana Estuary for various sensitivity runs shown as numbers (see Table 2). (a) Phytoplankton
biomass (Chl a), (b) zooplankton biomass, (c) zooplankton (cont), (d) zooplanktivorous fish biomass, (e) carnivorous/omnivorous fish biomass, and (f) detritus
846 903
biomass. To convert biomass to concentration, see Fig. 5 and for Chl a 3.5e7.8 mg lÀ1.
847 904
848 905
849 906
850 907
In the model carnivorous/omnivorous fish is measurably reaches of the estuary and the model suggests that this fish
851 908
sensitive only to dCF (the natural death rate of carnivorous/om- is highly vulnerable to a salinity increase, as a result of reduc-
852 909
nivorous fish; case 10, Fig. 6e). The model suggests that no tion in river inflow. The model also suggests that the lower es-
853 910
other parameter than the natural death rate significantly influ- tuary has more detritus than it can consume, thus the
854 911
ences the omnivorous fish. These fishes are mainly freshwater additional detritus from salt marshes is unimportant. In the up-
855 912
Barbus spp. These species are located mostly in the upper per areas, detritus mainly originates from the decomposition of
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913 970
riparian vegetation, this source of detritus seems more impor-
914 971
tant in the middle and lower estuary (Fig. 6f).
915 972
The model sensitivity tests are useful because they show
916 973
that:
917 974
918 975
1. the model appears robust because large, but reasonable,
919 976
changes in the parameters do not lead to instabilities
920 977
such as the destruction of trophic layers;
921 978
2. the biomass of organisms is directly affected by its con-
922 979
sumption of prey or being consumed by predators the
923 980
next level up in the food chain. Indirect effects across
F
924 981
two trophic levels are generally small; for instance if we
925 982
compare ZF from runs 1 and 5, i.e. there is no impact of
OO
926 983
the death rate of phytoplankton on carnivorous fish.
927 984
928 985
929 986
3.2. Examples of management application of the model
930 987
PR
931 988
The ecological sub-model is also simple, though still real-
932 989
istic. It incorporates the dominant six state variables. The
933 990
model integrates physical, chemical and biological processes
934 991
in the estuary; it predicts the ecosystem health as determined Fig. 7. Along-channel distribution of predicted phytoplankton (Chl a) biomass
in the Guadiana Estuary for the standard run (‘as is’), for a doubling of nutrient
935 992
by the following variables: nutrients, suspended particulate
concentration in the river (‘N Â 2’), and for the additional impact of removing
936 993
ED
matter, phytoplankton, zooplankton, bivalves, zooplanktivo-
the salt marshes (‘No marsh, N Â 2’) for a freshwater discharge equal to
937 994
rous fish and carnivorous/omnivorous fish. Thus the model is 2 m3 sÀ1. To convert biomass to concentration for Chl a 3.5e7.8 mg lÀ1.
938 995
simpler than a number of other models (e.g. Flindt and
939 996
Alqueva dam because their renewal and distribution depend
Kamp-Nielsen, 1997 e this comprises 12 state variables)
940 997
on freshets.
that are often too complex and unwieldy for practical applica-
CT
941 998
Moreover, the model can also be used for finding solutions
tions, especially when data are unavailable or insufficient.
942 999
for practical existing environmental problems in the Guadiana
The model can readily be used to test management sce-
943 1000
Estuary such as toxic algal blooms and eutrophication risk. After
narios when querying the impact of developments and
944 1001
the dam construction the estuary reached a man-made quasi-
disturbances to land-use and water-resources in the river
E
945 1002
steady state characterised by poor productivity and low biomass
catchment. For instance, the model predicts (Fig. 7) the impact
946 1003
in all communities (Fig. 8). Indeed, the fluctuations in river dis-
of doubling the nutrient concentration in the Guadiana River
RR
947 1004
charge e as freshets e as occurred historically, increased diver-
as a result of irrigation farming downstream of the Alqueva
948 1005
sity and variability in plankton and nektonic communities
dam. Such farming is indeed planned. The phytoplankton con-
949 1006
(Fig. 8bee), and promoted ecosystem dynamics. This model
centration is predicted to increase, particularly in the phyto-
950 1007
prediction is supported by the observations of Roelke (2000)
plankton maximum zone located in the upper reaches of the
951 1008
in the Nueces Delta, Texas. This ecosystem response to freshwa-
estuary. This suggests that the system is becoming eutrophi-
CO
952 1009
ter discharge pulses can be used as a management solution for
cated and the risk of toxic algae blooms has increased.
953 1010
toxic algal blooms or eutrophication in the Guadiana. In the
The model can also predict the impact of the salt marshes
Guadiana, the model suggests that increasing Qf to 50 m3 sÀ1
954 1011
being destroyed by developments. The model predictions for
955 1012
for 5 days will flush the estuary and promote the development
phytoplankton are shown in Fig. 7. Clearly the risk of eutro-
956 1013
of a diverse phytoplankton and zooplankton communities.
phication and of toxic algae blooms would be further
UN
957 1014
The model is restricted to the estuary. It cannot predict im-
increased.
958 1015
pacts on the coastal zone. Studies are needed to determine if
The model was used to assess the influence on the estuarine
959 1016
longer-duration and possibly higher intensity freshets may
ecosystem health of the Alqueva dam that in 2002e2003 sub-
960 1017
be needed to maintain coastal marine ecosystem health,
stantially decreased the river discharge Qf (Fig. 8a). The pre-
961 1018
˜
as suggested by Doornbos (1982), Quinones and Montes
dictions (Fig. 8b, c) show that without the dam the system was
´
962 1019
(2001), Chıcharo et al. (2002) and Simier et al. (2004).
highly variable during a freshwater pulse, while with the dam
963 1020
Thus the estuarine ecohydrology model is able to provide
the system was at steady state. The predicted influence of the
964 1021
answers to a number of practical questions. These answers
Alqueva dam is particularly dramatic for the carnivorous/om-
965 1022
must always be taken carefully because the model, like any
nivorous fish (Fig. 8d, e) because without the dam the fish was
966 1023
ecosystem model, over-simplifies reality, and the data set is in-
able to spread over much of the estuary for up to a month after
967 1024
adequate for a detailed calibration. In that sense, the model
a freshet, while with the dam the fish is restricted to the upper-
968 1025
predictions are somewhere between quantitative and qualita-
most region of the estuary. Zooplankton and zooplanktivorous
969 1026
tive. Detailed field studies are needed to better understand,
fish also are predicted to decrease in the presence of the
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1032 1089
1033 1090
1034 1091
1035 1092
1036 1093
1037 1094
F
1038 1095
1039 1096
OO
1040 1097
1041 1098
1042 1099
1043 1100
1044 1101
PR
1045 1102
1046 1103
1047 1104
1048 1105
1049 1106
1050 1107
ED
1051 1108
1052 1109
1053 1110
1054 1111
CT
1055 1112
1056 1113
1057 1114
1058 1115
E
1059 1116
1060 1117
RR
1061 1118
1062 1119
1063 1120
1064 1121
1065 1122
CO
1066 1123
1067 1124
1068 1125
1069 1126
Fig. 8. (a) Time series plot of the Guadiana River discharge entering the estuary in the dry season of 2003 in the presence of the Alqueva dam, and the predicted
1070 1127
river discharge if the dam had not been constructed (middle). Time series plot of the predicted distribution of phytoplankton biomass in the Guadiana Estuary in
UN
1071 1128
2003 (b) without and (c) with the Alqueva dam. Time series plot of the predicted distribution of carnivorous/omnivorous fish biomass in the Guadiana Estuary in
2003 (d) without and (e) with the Alqueva dam. To convert biomass to concentration, see Figs. 5 and 6.
1072 1129
1073 1130
1074 1131
and hence better parameterise in the model, the various pro- presently set as a constant, is probably varying seasonally
1075 1132
cesses driving the ecosystem. The model should be seen as and possibly stochastically e data on this are missing and
1076 1133
a living model e it has been written using subroutines that are needed. Also, as the new data become available, the model
1077 1134
are readily edited, so that the new knowledge on individual should be improved by subdividing the phytoplankton com-
1078 1135
processes can readily be incorporated in the model. For the partment into the main classes (Domingues et al., 2005).
1079 1136
model to remain a useful tool, it is suggested that its complex- For science, the model provides a tool to enable the
1080 1137
ity should be increased only as fast as additional physical, exchange of information between oceanographers, biologists,
1081 1138
chemical and biological processes can be quantified through ecologists, engineers, sociologists, economists and water-
1082 1139
new field and laboratory studies. For example, the import resources managers at regional and national government
1083 1140
rate a from salt marshes and riparian ecotones, which is levels, and the community.
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1141 1198
It is hoped that the model can also be useful for manage- References
1142 1199
ment. The model shows that it is possible to predict e within
1143 1200
likely error bounds provided by the sensitivity tests e the con- Ackroyd, D.R., Bale, A.J., Howland, R.J.M., Knox, S., Millward, G.E.,
Morris, A.W., 1986. Distributions and behaviour of dissolved Cu, Zn
1144 1201
sequences on the estuary ecosystem health of human activities
and Mn in the Tamar estuary. Estuarine, Coastal and Shelf Science 23,
1145 1202
throughout the river catchment. The model does show that, to 621e624.
1146 1203
maintain the ecosystem services provided by the estuary, inte- ´
Alveirinho, J.M.A., Gonzalez, R., Ferreira, O., 2004. Natural versus anthropic
1147 1204
grated coastal management needs to take the whole river causes in variations of sand export from river basins: an example from the
1148 1205
catchment as the fundamental planning unit. It is necessary Guadiana river mouth (Southwestern Iberia). Polish Geological Institute
Special Papers 11, 95e102.
1149 1206
to bring together land-use managers, water-resources man-
Balls, P.W., 1994. Nutrient inputs to estuaries from nine Scottish east coast
1150 1207
agers, and coastal and fisheries managers. The model offers rivers: influence of estuarine processes on inputs to the North sea. Estua-
1151 1208
thus a tool for using ecohydrology as a holistic approach to rine, Coastal and Shelf Science 39, 329e352.
F
1152 1209
the management of rivers, estuaries and coastal zones within ´
Bille, R., Mermet, L., 2002. Integrated coastal management at the regional
1153 1210
entire river catchments. level: lessons from Toliary, Madagascar. Ocean and Coastal Management
OO
45, 41e58.
1154 1211
Boorman, L.A., Hazelden, J.H., Loveland, P.J., Wells, J.G., 1994a. Compara-
1155 1212
tive relationships between primary productivity and organic and nutrient
4. Conclusions
1156 1213
fluxes in four salt marshes. In: Mitsch, W.J. (Ed.), Global Wetlands. Old
1157 1214
World and New. Elsevier, Amsterdam, pp. 181e189.
The ecohydrology model is original in that it links physical,
1158 1215
Boorman, L.A., Hazelden, J., Andrews, R., Wells, J.G., 1994b. Organic and
chemical and biological processes over the entire estuary for
PR
nutrient fluxes in four north-west European salt marshes. In: Dyer, K.R.,
1159 1216
the entire food web as a function of catchment output and Orth, R.J. (Eds.), Changes in Fluxes in Estuaries: Implications from Sci-
1160 1217
ence to Management. Olsen and Olsen, Fredensborg, pp. 243e248.
the oceanic open boundary condition. Despite the fact that
1161 1218
Brauer, F., Castillo-Chavez, C., 2001. Mathematical Models in Population Bi-
a number of simplifications are made, the model is encourag-
1162 1219
ology and Epidemiology. Springer, Berlin, 416 pp.
ing in that it reproduces satisfactorily the observations in
1163 1220
´ ´
Chıcharo, L., Chıcharo, M.A., Esteves, E., Andrade, P., Morais, P., 2002. Ef-
2001e2003. These data are still sparse and the model may fects of alterations in fresh water supply on the abundance and distribution
1164 1221
ED
need improvements as additional data become available. of Engraulis encrasicolus in the Guadiana Estuary and adjacent coastal
1165 1222
areas of south Portugal. Journal Ecohydrology and Hydrobiology 1,
The model can readily be used to assess future impact on
1166 1223
195e200.
the Guadiana Estuary ecosystem health caused by urbanisation
1167 1224
Domingues, R.B., Barbosa, A., Galv~o, H., 2005. Nutrients, light and phyto-
a
or other factors that reduce the salt marsh area, by an increase
1168 1225
plankton succession in a temperate estuary (the Guadiana, south-western
CT
in nutrient loads as a result of changes in agriculture practices Iberia). Estuarine, Coastal and Shelf Science 64, 249e260.
1169 1226
in the catchment area due to increase in water availability by Doornbos, G., 1982. Changes in the fish fauna of the former Grevelingen es-
1170 1227
tuary, before and after the closure in 1971. Hydrobiological Bulletin 16,
the Alqueva dam, by extreme high freshwater discharges, e.g.
1171 1228
279e283.
due to release of high volume of water storage in the dam, and
1172 1229
Edwards, A.M., 2001. Adding detritus to a nutrientephytoplanktone
by the introduction of exotic species.
E
1173 1230
zooplankton model: a dynamical-systems approach. Journal of Plankton
The model can also be used to predict the efficiency of re- Research 23, 389e413.
1174 1231
medial measures, such as creating wetlands, creating freshets Erzini, K., 2005. Trends in NE Atlantic landings (southern Portugal): identify-
RR
1175 1232
ing the relative importance of fisheries and environmental variables.
by releasing water from the Alqueva dam, managing bivalve
1176 1233
Fisheries Oceanography 14, 195e209.
species in the freshwater part of the estuary, and removing nu-
1177 1234
Esteves, E., Pina, T., Chicharo, M.A., Andrade, J.P., 2000. The distribution of
trients from the river.
1178 1235
estuarine fish larvae: nutritional condition and co-occurrence with preda-
tors and prey. Acta Oecologica 21 (3), 1e13.
1179 1236
CO
Flameling, I.A., Kromkamp, J., 1994. Responses of respiration and photosyn-
1180 1237
Acknowledgements thesis of Scenedesmus protuberans (Fritsch) to gradual and steep salinity
1181 1238
increases. Journal of Plankton Research 16, 1781e1791.
1182 1239
Flindt, M.R., Kamp-Nielsen, L., 1997. Modelling of an estuarine eutrophica-
It is a pleasure to thank Philippe Pypaert and UNESCO e
1183 1240
tion gradient. Ecological Modeling 102, 143e153.
ROSTE for supporting the development of this model through
Fischer, H.B., List, E.Y., Koh, R.C.Y., Imberger, J., Brooks, N.H., 1979. Mix-
1184 1241
contract No. 875.767.4 in estuarine and coastal zone ecohydrol-
UN
ing in Inland and Coastal Waters. Academic Press, New York, 483 pp.
1185 1242
ogy. Also thanks are due to the University of Algarve for provid- Fortunato, A.B., Oliviera, A., Alves, E.T., 2002. Circulation and salinity intru-
1186 1243
ing logistical support. The collection of the biological data was sion in the Guadiana Estuary. Thalassas 18, 43e65.
1187 1244
´
Gonzalez, J.A.M., 1995. Sedimentologia del estuario del Rio Guadiana (SO
made possible by the financial support of the projects ‘Effects of
1188 1245
´
Portugal). CEP. Biblioteca Universitaria, Universidade de Huelva.
River Flow changes on the fish communities of the Douro, Tejo
Goosen, N.K., van Rijswijk, P., Brockmann, U., 1995. Comparison of hetero-
1189 1246
and Guadiana Estuaries and coastal areas: ecological and socio- trophic bacterial production rates in early spring in the turbid estuaries of
1190 1247
economic predictions (ERIC) (FCT/P/MAR/15263/1999)’, the Scheldt and the Elbe. Hydrobiologia 311, 31e42.
1191 1248
‘General characterisation of the Guadiana Estuary ecosystem Haward, M., 1996. Institutional framework for Australian ocean and coastal
1192 1249
management. Ocean and Coastal Management 33, 19e39.
(FCT/P/15 REG/II/6/96)’, ‘Valorization of Aquatic resources
1193 1250
Hilborn, R., Mangel, M., 1997. The Ecological Detective. Confronting Models
of the Guadiana Estuary (Portugal) (Feder/PPDR/CCRA/ODI-
with Data. Princeton University Press, Princeton, 315 pp.
1194 1251
ANA)’, and the PhD scholarship of P. Morais ‘Engraulis encra- Humston, R., Ault, J.S., Lutcavage, M., Olson, D.B., 2000. Schooling and mi-
1195 1252
sicolus population dynamics in the Guadiana Estuary and gration of large pelagic fishes relative to environmental cues. Fisheries
1196 1253
adjacent coastal area (SFRH/BD/5187/2001)’. Oceanography 9, 136e146.
1197 1254
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12 E. Wolanski et al. / Estuarine, Coastal and Shelf Science xx (2006) 1e12
1255 1289
Jorgensen, S.E., Bendoricchio, G., 2001. Fundamentals of Ecological Model- Roelke, D.L., 2000. Copepod food quality threshold as a mechanism influenc-
1256 1290
ling. Elsevier, 530 pp. ing phytoplankton succession and accumulation of biomass, and secondary
1257 1291
Kibirige, I.R., Perissinotto, R., Nozais, C., 2002. Alternative food sources productivity: a modelling study with management implications. Ecological
of zooplankton in a temporarily-open estuary: evidence from d13C and
1258 1292
Modelling 134, 245e274.
d15N. Journal of Plankton Research 24, 1089e1095.
1259 1293
Salomons, W., Forstner, U., 1984. Metals in the Hydrocycle. Springer-Verlag,
1260 1294
Knox, G.A., 1986. Estuarine Ecosystems: A Systems Approach, vol. II. CRC Berlin, 349 pp.
1261 1295
Press, Florida, 230 pp. Simenstad, C.A., Morgan, C.A., Cordell, J.R., Baross, J.A., 1994. Flux, passive
1262 1296
Kot, M., 2001. Elements of Mathematical Ecology. Cambridge University retention, and active residence of zooplankton in Columbia river estuarine
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Press, Cambridge, 464 pp. turbidity maxima. In: Dyer, J., Orth, M. (Eds.), Changes in Fluxes in
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Lau, M., 2005. Integrated coastal zone management in the People’s Republic Estuaries: Implications from Science to Management. University of
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of China e an assessment of structural impacts on decision-making Plymouth, pp. 473e482 (ECSA22/ERF Symposium).
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processes. Ocean and Coastal Management 48, 115e159. Simier, M., Blanc, L., Aliaume, C., Diouf, P.S., Albaret, J.J., 2004. Spatial and
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Lefeuvre, J.C., 1996. Effects of environmental change on European salt temporal structure of fish assemblages in an ‘‘inverse estuary’’, the Sine
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marshes. In: Structure, Functioning and Exchange Potentialities with Saloum system. Estuarine, Coastal and Shelf Science 59, 69e86.
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Marine Coastal Waters, vols. 1e6. University of Rennes, France. Tagliani, P.R.A., Landazuri, H., Reis, E.G., Tagliani, C.R., Asmus, M.L., San-
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Lindeboom, H., 2002. The coastal zone: an ecosystem under pressure. In: chez-Arcilla, A., 2003. Integrated coastal zone management in the Patos
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Field, J.G., Hempel, G., Summerhayes, C.P. (Eds.), Oceans 2020: Science, Lagoon estuary: perspectives in context of developing country. Ocean
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Trends, and the Challenge of Sustainability. Island Press, Washington, and Coastal Management 46, 807e822.
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pp. 49e84, 365 pp. Thomann, R.V., 1980. Deterministic and statistical models of chemical fate in
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Michel, D., 1980. Synthese des donnes physiques mesures dans le Rio Guadi- aquatic systems. In: Levin, S.A., Hallam, T.G., Gross, L.J. (Eds.), Applied
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ana. Evaluation de l’intrusion saline dans l’estuaire. PhD thesis, Labora- Mathematical Ecology. Springer-Verlag, Berlin, pp. 322e351, 491 pp.
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toire d’oceanographie, Universite de Bruxelles. Uncles, R.J., Stephens, J.A., Smith, R.E., 2002. The dependence of estuarine
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Nixon, S.W., 2003. Replacing the Nile: are anthropogenic nutrients providing turbidity on tidal intrusion length, tidal range and residence time. Conti-
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the fertility once brought to the Mediterranean by a great river? Ambio 32, nental Shelf Research 22, 1835e1856.
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30e39. Wolanski, E., Doherty, P., Carleton, J., 1997. Directional swimming of fish
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Pickaver, A.H., Gilbert, C., Breton, F., 2004. An indicator set to measure the larvae determines connectivity of fish populations on the Great Barrier
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progress in the implementation of integrated coastal zone management in reef. Naturwissenschaften 84, 262e268.
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Europe. Ocean and Coastal Management 47, 449e462. Wolanski, E., Boorman, L.A., Chıcharo, L., Langlois-Saliou, E., Lara, R.,
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Pinto, G.V., 2000. Caracterizac~o Dos Bancos Naturais De Bivalves Com
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¸a Plater, A.J., Uncles, R.J., Zalewski, M., 2004. Ecohydrology as a new
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Interesse Comercial No Estuario Do Guadiana. Tese de licenciatura tool for sustainable management of estuaries and coastal waters. Wetlands
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Biologia Marinha, Universidade do Algarve. Ecology and Management 12, 235e276.
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Quinones, R.A., Montes, R.M., 2001. Relationship between freshwater input Zalewski, M., 2002. Ecohydrology e the use of ecological and hydrological
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to the coastal zone and historical landing of the benthic/demersal fish in processes for sustainable management of water-resources. Hydrological
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Central-South Chile. Fisheries Oceanography 10, 311e328. Sciences Bulletin 47, 823e832.
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Estuarine, Coastal and Shelf Science xx (2006) 1e12
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www.elsevier.com/locate/ecss
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An ecohydrology model of the Guadiana Estuary (South Portugal)
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Eric Wolanski a,*, Luıs Chicharo b, M. Alexandra Chicharo b, Pedro Morais b
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a
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Australian Institute of Marine Science, PMB No. 3, Townsville MC, Queensland 4810, Australia
b
Centro de Ciencias do Mar, Faculdade de Ciencias do Mar e do Ambiente, Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
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Received 30 January 2005; accepted 20 March 2006
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Abstract
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A 1-D ecohydrology model is proposed that integrates physical, chemical and biological processes in the Guadiana Estuary during low flow
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conditions and that predicts the ecosystem health as determined by the following variables: river discharge, nutrients, suspended particulate mat-
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ter, phytoplankton, zooplankton, bivalves, zooplanktivorous fish and carnivorous/omnivorous fish. Low flow conditions prevail now that the Al-
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queva dam has been constructed. The ecological sub-model is based on the non-linear LotkaeVolterra equation. The model is successful in
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capturing the observations of along-river changes in these variables. It suggests that both bottom-up and top-down ecological processes control
the Guadiana Estuary ecosystem health. A number of sensitivity tests show that the model is robust and can be used to predict e within likely
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error bounds provided by the sensitivity tests e the consequences on the estuary ecosystem health of human activities throughout the river catch-
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ment, such as the irrigation farming downstream of the Alqueva dam, reclamation of the salt marshes by urban developments, and flow regu-
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lation by the Alqueva dam. The model suggests that the estuarine ecosystem health requires transient river floods and is compromised by flow
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regulation by the Alqueva dam. Remedial measures are thus necessary.
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Ó 2006 Elsevier Ltd. All rights reserved.
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Keywords: ecohydrology; marine ecology; flushing; modelling; dam; flow regulation; Portugal; Alqueva dam; Guadiana Estuary
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The impact on estuaries is commonly still ignored when
1. Introduction
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dams and irrigation farming are proposed on rivers. In addi-
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1.1. The need for an ecohydrology estuarine model tion, estuaries are often regarded as sites for future develop-
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ment and expansion, and have been increasingly canalized
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Throughout human history, the coastal plains and Lowland and dyked for flood protection, and their wetlands infilled
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River valleys have usually been the most populated areas over for residential areas.
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the world (Wolanski et al., 2004). At present, about 60% of the All these factors impact on the biodiversity and productiv-
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world’s population lives along the estuaries and the coast (Lin- ity and, hence, the overall health of estuaries and the ecosys-
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deboom, 2002). This is degrading estuarine and coastal waters tem services they provide to humans (Nixon, 2003; Erzini,
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through pollution, eutrophication, increased turbidity, overf- 2005). They increasingly lead humans away from the possibil-
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ishing, and habitat destruction. The pollutant supply does ity of ecologically sustainable development of the coastal
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not just include nutrients; it also includes mud from eroded zone. Integrated coastal zone management plans are drawn
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soil, heavy metals, radionuclides, hydrocarbons, and a number up worldwide (e.g., Haward, 1996; Bille and Mermet, 2002;
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of chemicals including new synthetic products. Tagliani et al., 2003; Pickaver et al., 2004; Lau, 2005). How-
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ever, in the presence of significant river input, most are bound
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to fail because they commonly deal only with local, coastal is-
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sues, and do not consider the whole river catchment as the fun-
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damental planning unit. It is as if the land, the river, the
* Corresponding author.
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estuary, and the sea were not part of the same system. When
E-mail address: e.wolanski@aims.gov.au (E. Wolanski).
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0272-7714/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved.
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doi:10.1016/j.ecss.2006.05.029
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dealing with estuaries and coastal waters, in most countries assumed to follow those described by Wolanski et al. (2004)
116 173
land-use managers, water-resources managers, and coastal and are sketched in Fig. 1. These processes are briefly sum-
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and fisheries managers do not cooperate effectively due to marised below.
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administrative, economic and political constraints, and the The ecological health of estuaries is determined by the
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absence of a forum where their ideas and approaches are interaction between organisms and variations in salinity,
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shared and discussed (Wolanski et al., 2004). To help alleviate currents, waves, suspended particulate matter (SPM), bed
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this problem, UNESCO e IHP has launched the ecohydrology sediments, temperature, air exposure, hypoxia, wetland
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program. In this program, the concept of ecohydrology is contaminants and biodiversity. Like the health of a living
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introduced as a holistic approach to the management of rivers, organism, the health of an estuary or a coastal water body, can-
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estuaries and coastal zones within entire river catchments, by not be measured by one single variable, indeed a number of
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adopting science-based solutions to management issues that variables are important (Balls, 1994). Well-flushed estuaries
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restore or enhance natural processes as well as the use of tech- are intrinsically more robust than poorly flushed systems. As
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nological solutions (Zalewski, 2002). a result, environmental degradation is most often apparent dur-
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This science-based management requires the use of a holis- ing periods of reduced freshwater inflows, e.g. during drought
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tic model to quantify the human impact on the ecosystem or when human activities reduce the freshwater flow. There-
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health of estuaries and to enable the exchange of information fore, this ecohydrology model focuses on low flow conditions
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between oceanographers, biologists, ecologists, engineers, so- when vertically well-mixed conditions often prevail.
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ciologists, economists and water-resources managers at local Once riverine-derived suspended particulate matter enters the
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and national governmental levels, and the community. estuary, it can be trapped within an estuarine turbidity maximum
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(ETM) zone (Fig. 1). The ETM is commonly located in the
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very low salinity reaches of an estuary. The maximum, depth-
1.2. The science behind the model
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averaged, suspended solid concentration (SSC) at high water
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within an estuary can be predicted semi-empirically as a function
The model is process-based. The dominant physical, chem-
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of the tidal intrusion and the tidal range (Uncles et al., 2002).
ical, biological and human-related processes in an estuary are
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Fig. 1. Sketch of the dominant processes operating in an estuary. Adapted from Wolanski et al. (2004).
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Sediment particles and aggregates within the ETM can give of the food web and influences the fisheries (Chıcharo et al.,
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rise to marked changes in water quality. Fine particles can 2002; Erzini, 2005).
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adsorb metal ions and organic macro-molecules from solution Several pollution sources exist in the Guadiana Estuary
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to such an extent that some metals can be completely removed area, mainly resulting from urbanisation, agriculture (fertil-
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from solution within a strong ETM (Salomons and Forstner, izers, pesticides, and herbicides), cattle breeding and olive
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1984; Ackroyd et al., 1986). Once nutrients enter an estuary, oil production. The freshwater flow reaching the estuary is
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non-conservative behaviour can be pronounced. Key processes at present regulated by more than 100 dams, including the
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responsible for this non-conservative behaviour include burial Alqueva dam whose construction was completed in 2002
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in sediment reservoirs and desorption processes particularly if and that forms the largest reservoir in Europe (Alveirinho
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the sediment is nutrient-rich. Nutrients are generally mainly in et al., 2004).
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particulate form (i.e. absorbed to the mud particles in suspen-
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sion) in freshwater and can be released in solution in saline 1.4. Aims
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water.
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The salt marshes of Western Europe generally produce This study aimed to develop an ecohydrology model to be
more than 1 kg mÀ2 yrÀ1 of above-ground dry matter (Boor-
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applied to the low flow conditions in the Guadiana Estuary. It
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man et al., 1994a,b; Lefeuvre, 1996). Salt marshes export describes such a model designed specifically for vertically
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some of this organic matter. Salt marshes and their tidal creeks well-mixed estuaries. The ecological sub-model is also simple,
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are also an important nursery ground, and a refuge, for larvae though still realistic. It incorporates the seven state variables:
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and post-larvae of bivalve, carnivorous/omnivorous fish and nutrients, suspended particulate matter, phytoplankton, zoo-
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zooplankton. plankton, bivalves, zooplanktivorous fish and carnivorous/om-
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The estuary is modelled as a converter of living phyto- nivorous fish in the estuary and it predicts the ecosystem
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plankton to detrital particles; it is also a conveyor of detrital health.
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matter to the sea. Fishes help transfer energy and matter
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from estuarine plants to upper trophic levels. The great bulk 2. Material and methods
253 310
of the organic matter produced (sometimes 90%) is processed
254 311
through the detrital system. Zooplankton, planktivorous fish, 2.1. Field data
255 312
interstitial micro and meiofauna, surface deposit-feeding mol-
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luscs, fishes and polychaeta, and filter-feeding invertebrates Estuarine physical, chemical and biological data were
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consume a much greater proportion of the primary production obtained from the papers of M. Chicharo et al. and P. Morais
258 315
of the phytoplankton and benthic microalgae. Annual plant et al. in this issue and from Pinto (2000), and Esteves et al.
259 316
growth and decay provide continuing large quantities of (2000). Data from river inflow were obtained online from
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organic detritus. In addition, there is often a considerable input Water National Institute (INAG), National System of Hydro-
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of detritus from river inflow. Detrital particles and their asso- logical Resources (http://snirh.inag.pt/) from the hydrometric
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ciated microorganisms provide the basic food source for station Pulo do Lobo (lat. 37 480 N, long. 7 380 W), located
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primary consumers such as zooplankton, most benthic a few kilometres above the last point of tidal influence
264 321
invertebrates and some fishes. The first trophic level in the ´
(Mertola).
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estuarine ecosystem is therefore best described as a mixed tro-
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phic level of detritus consumers, which in varying degrees are 2.2. The estuarine ecohydrology model
267 324
herbivores, omnivores or primary carnivores (Knox, 1986).
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The prototype is the Guadiana Estuary at low flow
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1.3. Study area conditions e because such low flow conditions prevail now
270 327
that the Alqueva dam exists. For a freshwater flow Qf <
271 328
The Guadiana River is one of the largest in the south of the 50 m3 sÀ1, the Guadiana Estuary is vertically fairly well-
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Iberian Peninsula, crossing extensive rural areas and includes mixed in salinity (Fortunato et al., 2002). In a vertically
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the Iberian Pyritic Belt (Gonzalez, 1995). well-mixed estuary, the distribution of salinity S is determined
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The fluvial regime is characterised by low flows during from the solution of the 1-D advectionediffusion equation
275 332
summer and episodic runoff periods in winter with the result- (Fischer et al., 1979):
276 333
ing discharge of sediments into the estuary and coastal zone.
277 334
The estuary is 60 km long, it has a maximum width of vðSAÞ=vt þ vðQSÞ=vx ¼ vðEA vS=vxÞ=vx ð1Þ
278 335
550 m and the maximum depth varies between 5 and 17 m.
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The tidal regime of the estuary is meso-tidal, with an average where t is the time, Q is the flow rate (driven by tides and
280 337
amplitude of 2 m (Michel, 1980). river flows), E is the longitudinal eddy diffusion coefficient,
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The estuary has an important nursery function for several and A is the cross-sectional area. Eq. (1) is solved for a series
282 339
fish species, such as the anchovy Engraulis encrasicolus sensu of cells of volume V distributed along the length of the estu-
283 340
lato and several Sparidae, and crustacean species such as the ary from the tidal limit to the mouth. The time step dt is set
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brown shrimp Crangon crangon. Moreover, the outwelling to 1 day, thereby averaging over the tides. The open bound-
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from the estuary to the coastal area promotes the development aries are located at the tidal limit and at the mouth. At the
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Fig. 2. Observed and predicted along-channel distributions of salinity in the Guadiana Estuary around the times of (square) high tide and (circle) low tide for
salinity of (a) 2 m3 sÀ1 and (b) 50 m3 sÀ1. Cell # 1 is located at the tidal limit, 60 km upstream of cell # 20 that is located at the mouth.
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tidal limit, the model assumes that the salinity S ¼ 0 and it vðCAÞ=vt þ vðQCÞ=vx ¼ vðEA vC=vxÞ=vx þ DC ð2Þ
362 419
also assumes that Qf is known. At the mouth, the salinity
363 420
is assumed to be 35. Turbulent diffusion is due to tides, where DC is derived from the ecological sub-model described
364 421
wind, and freshwater runoffs and is parameterised by the pa- below.
365 422
rameter E. In the model, this is determined by mixing coef- The ecological sub-model is based on the non-linear
366 423
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ficients that quantify the fraction of water in a cell that is LotkaeVolterra equation. It is based on a finite-element model
367 424
exchanged with adjoining cells during the time step (1 with the same cells as those used in the salinity model. A num-
368 425
day). This parameter is varied until the solution fits well ber of modeling equations are possible. In the absence of
369 426
with the observations. This is shown in Fig. 2 for the case excretion and death not due to predation, the predatoreprey
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of the Guadiana Estuary for two values of the freshwater dis- relationship is often calculated by the non-linear equations
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charge Qf (2 and 5 m3 sÀ1). (Brauer and Castillo-Chavez, 2001; Kot, 2001).
372 429
The model enables one to readily calculate the flushing time
vX=vt ¼ bXð1 À X=Xo ÞHðY; Yo1 Þ ð3Þ
373 430
of the estuary. To do that, in the model the freshwater discharge
374 431
is set to be a constant and the estuary is initially filled with uni-
and
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form seawater salinity at t ¼ 0. The system is then allowed to
376 433
evolve, and in the model salt is progressively expelled from vY=vt ¼ ÀbXð1 À X=Xo ÞHðY; Yo1 Þ ð4Þ
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the upper reaches of the estuary until a steady state solution is
378 435
where X is the predator biomass (X ¼ CV) where C is the pred-
reached. This is shown in Fig. 3 for a freshwater discharge
379 436
(Qf) of, respectively, 2 and 50 m3 sÀ1. It is apparent that for ator concentration, Y is the prey biomass, b is the predator
380 437
Qf ¼ 50 m3 sÀ1 the residence time is about 5 days, and that for growth rate, Xo is the predator saturation biomass, Yo1 is the
381 438
Qf ¼ 2 m3 sÀ1 the residence time varies between 14 days in prey starvation biomass, i.e. the biomass at which the predator
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the lower reaches and 37 days in the upper reaches of the estuary. is unable or unwilling to spend energy to find this prey. H is
383 440
the Heavyside function, i.e. H ¼ 0 if Y < Yo1, and H ¼ 1 if
For a non-conservative constituent such as nutrients, plank-
384 441
Y > Yo1. Eq. (2) also applies if Y is a nutrient. Provided starva-
ton, detritus, fish, and bivalve, Eq. (1) is modified by including
385 442
a sinkesource term DC (Thomann, 1980), where C is the tion does not occur, the solution is an S-shaped curve whereby
386 443
concentration: X initially increases exponentially in time. The growth rate is
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Fig. 3. Estimation of the residence time from the time series of salinity distribution in the estuary following intrusion of freshwater for (a) 2 m3 sÀ1 and
(b) 50 m3 sÀ1.
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zero at X ¼ Xo. Because X and Y are related by Eqs. (3) and
457 514
concentration (N ), suspended sediment concentration (SSC),
458 515
(4), Y decreases toward a minimum value. phytoplankton concentration (P), zooplankton concentration
459 516
In the model, freshwater phytoplankton and bacterioplank- (Z ), bivalve concentration (B), detritus concentration (D), zoo-
460 517
ton in the river are subject to salt stress when freshwater mixes planktivorous fish concentration (ZF), and carnivorous/omniv-
461 518
with saltwater; and the freshwater microbial populations die in orous fish concentration (CF). All dying matter becomes
462 519
this zone (Flameling and Kromkamp, 1994; Goosen et al., detritus. Settling is not included in the model, because the an-
463 520
1995). In the model, the salinity also limits the seaward distri- imals (e.g. zooplankton) are mobile and can swim in the water.
464 521
bution of saline water plankton, invertebrates (e.g. bivalves) The model is equally complex at the lowest and highest tro-
465 522
and fishes. phic levels, which increases the model robustness (Jorgensen
466 523
In an estuary, changes in salinity constitute a major stress and Bendoricchio, 2001). Thus the ecosystem model equations
467 524
that can lead to death. There are other stressors, for instance, are:
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small values of the dissolved oxygen concentration. A death-
469 526
excretion rate d must then be added to Eq. (3) that becomes: Nutrients (N; nitrate)
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vX=vt ¼ bXð1 À X=Xo ÞHðY; Yo1 Þ À dX ð5Þ vN=vt¼ÀbNP Pð1ÀP=Po ÞHðN;No1 ÞþaN þgSSCN SSC ð7Þ
471 528
472 529
Phytoplankton (P)
The solution of this equation is also an S-shaped curve, the
473 530
maximum value, however, is smaller than in the absence of
474 531
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vP=vt ¼ bNP Pð1 À P=Po ÞHðN;No1 Þ À bPZ Zð1 À Z=Zo ÞHðP;Po1 Þ
this death-excretion rate, that is X ¼ Xo(1 À d/b). To remain re-
475 532
alistic the solution requires b > d, i.e. that the growth rate is
476 533
À bPB Bð1 À B=Bo ÞHðP;Po1 Þ
larger than the death-excretion rate.
477 534
À bPCF CFð1 À CF=CFo ÞHðP;Po1 Þ þ aP À dP P ð8Þ
In an estuary, fringing wetlands (mainly salt marshes and
478 535
riparian ecotones, together with the tidal creeks that drain
479 536
Zooplankton (Z )
them) can be an important source of detritus and nutrients,
480 537
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as well as a nursery for juveniles and sub-adults as well as
481 538
vZ=vt ¼ bPZ Zð1 À Z=Zo ÞHðP;Po1 Þ þ bDZ Zð1 À Z=Zo ÞHðD;Do1 Þ
a refuge. This is particularly the case for bivalves. Mathemat-
482 539
À bZZF ZFð1 À ZF=ZFo ÞHðZ;Zo1 Þ
ically, this is expressed by adding a source of X to the right-
483 540
À bZCF CFð1 À CF=CFo ÞHðZ;Zo1 Þ þ aZ À dZ Z ð9Þ
hand side of Eq. (5). The final equation becomes:
484 541
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485 542
vX=vt ¼ bXð1 À X=Xo ÞHðY; Yo1 Þ À dX þ a ð6Þ
486 543
Bivalves (B)
487 544
where a is the import rate from wetlands.
488 545
vB=vt ¼ bPB Bð1ÀB=Bo ÞHðP;Po1 ÞþbDB Bð1ÀB=Bo ÞHðD;Do1 Þ
The ecosystem model represents mathematically through
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ÀbBCF CFð1ÀCF=CFo ÞHðB;Bo1 ÞþaB ÀdB B ð10Þ
Eq. (5) the interactions summarised in Fig. 4 between nutrients
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Fig. 4. Sketch of the estuarine food web in the ecohydrology model.
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Carnivorous/omnivorous fish (CF) SSC ¼ 30 if S < 1
572 629
SSC ¼ 30 þ 7S if 1 < S < 12
573 630
vCF=vt ¼ bBCF CFð1 À CF=CFo ÞHðB;Bo1 Þ SSC ¼ 100 À 3:5ðS À 15Þ if S > 12
574 631
þ bPCF CFð1 À CF=CFo ÞHðP;Po1 Þ
575 632
The model needs the knowledge of all the ecological pa-
þ bZCF CFð1 À CF=CFo ÞHðZ;Zo1 Þ
576 633
rameters. The parameter a varies along-channel to correspond
þ bDCF CFð1 À CF=CFo ÞHðD;Do1 Þ
577 634
to the location of the salt marshes and riparian/terrestrial veg-
578 635
þ aCF À dCF CF ð11Þ etation. The approximate values of the parameters are known
579 636
from a number of studies and from comparison with other es-
580 637
tuaries. The final values were selected as a result of a best-fit
Zooplanktivorous fish (ZF)
581 638
between observed and predicted values. The results of this cal-
F
582 639
ibration are shown in Fig. 5 for nutrients, zooplankton, bi-
vZF=vt ¼ bZZF ZFð1ÀZF=ZFo ÞHðZ;Zo1 Þ
583 640
valve, and fish, respectively. Table 1 lists the adopted values
OO
þbDZF ZFð1ÀZF=ZFo ÞHðD;Do1 ÞþaZF ÀdZF ZF ð12Þ
584 641
of the parameters.
585 642
While the calibration appears successful, it is important for
586 643
the user to also judge whether the solution is realistic and sta-
Detritus (D)
587 644
ble (Hilborn and Mangel, 1997). This may be done by under-
588 645
taking a sensitivity test to judge whether the model is
vD=vt ¼ ÀbDB Bð1ÀB=Bo ÞHðD;Do1 Þ
PR
589 646
unrealistically sensitive to a specific parameter, making it po-
ÀbDZF ZFð1ÀZF=ZFo ÞHðD;Do1 Þ
590 647
tentially unstable and unrealistic. A number of sensitivity runs
ÀbDCF CFð1ÀCF=CFo ÞHðD;Do1 Þ
591 648
were carried out, each one involving changing one parameter.
Calculations were performed for Qf ¼ 2 m3 sÀ1, which is the
592 649
ÀbDZ Zð1ÀZ=Zo ÞHðD;Do1 ÞþaD þaD þdB BþdP P
593 650
environmental flow for the Guadiana River, i.e. the post-dam
þdZ Z þdCF CFþdZF ZF ð13Þ
594 651
ED
river discharge during the dry season. The list of sensitivity
595 652
runs is summarised in Table 2.
In these equations the subscripts denote either constituent
596 653
The sensitivity tests show that phytoplankton (Chl a) is
or the interaction between two constituents. For instance,
597 654
most sensitive in cases 2, 4 and 5, i.e. to bNP, bPB and dP
dZF is the death-excretion rate of ZF, and bDZF is the growth
598 655
(Fig. 6a).
CT
rate of ZF from detritus, i.e. the rate of mass transfer rate
599 656
These results suggest that bivalves play a more important
from detritus to ZF.
600 657
role in filtering phytoplankton than zooplankton. This can re-
In the nutrient equation, a new parameter was introduced,
601 658
sult from the fact that bivalves are benthic and sessile organ-
gSSCN, it denotes the leaching rate of nutrients from the partic-
602 659
isms, being able to resist currents as opposite to zooplankton
E
ulate phase (i.e. absorbed on the fine sediment) to the dis-
603 660
populations, although some develop strategies to resist dis-
solved phase.
604 661
placement forces (Simenstad et al., 1994).
RR
In Eq. (2), because the model is run at a time step of 1 day,
605 662
The most important parameter for zooplankton is dZ (the
Q ¼ Qf. There is thus no need to calculate the tidal dynamics;
606 663
death-excretion rate of zooplankton), and to a lesser degree
these are parameterised by the term E.
607 664
bNP (uptake rate of nutrient by phytoplankton) and bPZ (uptake
When applying Eq. (2) to the zooplanktivorous fish equa-
608 665
rate of phytoplankton by zooplankton). The model zooplankton
tion, Q is modified to incorporate the horizontal swimming
609 666
(Z ) is most sensitive in case 7 and to a lesser degree in cases 2
CO
by the fish as fish swim, by kinesis or taxis following environ-
610 667
and 3 (Fig. 6). As detritus can also be included in zooplankton
diet, if bDZ ¼ 0.1 dayÀ1. In fact, in a situation of low inflow e as
mental clues (Wolanski et al., 1997; Humston et al., 2000).
611 668
This velocity is assumed to be proportional to S. Thus the
612 669
the one tested in the sensitivity runs (Fig. 6c) e the expected de-
fish in the model is able to swim, following taxis or kinesis,
613 670
crease in detritus input caused by the reduction of inflow will
along environmental gradients.
614 671
affect the zooplankton biomass in the estuary, which highlights
UN
615 672
the importance of detritus as food source for estuarine zoo-
616 673
plankton (Edwards, 2001; Kibirige et al., 2002).
3. Results and discussion
617 674
The model also shows that zooplanktivorous fish (ZF) is
618 675
most sensitive to bZZF, bDZF, and dZF (i.e. respectively, the up-
3.1. Application to the Guadiana Estuary
619 676
take rate of zooplankton by zooplanktivorous fish, the uptake
620 677
In the Guadiana Estuary, field data of fine sediment concen- rate of detritus by zooplanktivorous fish, and the death rate of
tration during low flow conditions (Qf < 50 m3 sÀ1) suggest
621 678
the zooplanktivorous fish; cases 6, 11 and 12) (Fig. 6d). In
622 679
the presence of a weak turbidity maximum zone near the salin- fact, salinity changes caused by modification of freshwater/
ity intrusion limit, with a maximum SSC value of 114 mg lÀ1
623 680
seawater balance may affect zooplanktoneprey distribution
at S ¼ 12 while SSC is about 30 mg lÀ1 in the freshwater rea-
624 681
and impact zooplanktivorous fish species distribution. More-
625 682
ches of the estuary (Portela, unpubl. data). Therefore, the over, it suggests that the export of detritus from the salt marsh
626 683
model assumes a suspended sediment concentration (SSC) does not seem to be the most important source of food for
627 684
that is determined as follows: these fish.
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685 742
686 743
687 744
688 745
689 746
690 747
691 748
692 749
693 750
694 751
695 752
F
696 753
697 754
OO
698 755
699 756
700 757
701 758
702 759
PR
703 760
704 761
705 762
706 763
707 764
708 765
ED
709 766
710 767
711 768
712 769
CT
713 770
714 771
715 772
Fig. 5. Along-channel distribution in the Guadiana Estuary of (a) observed (dots) and predicted (line) total fish biomass, (b) observed (dots) and predicted (line)
716 773
bivalve biomass, (c) observed (dots) and predicted (line) nutrients’ (nitrate) mass, and (d) observed (dots) and predicted (line) zooplankton biomass. To convert
E
717 774
À2 À2 À3
biomass to concentration, for fish 2.8e2.87 g cm , for bivalve 1.2e24 m , for nitrate 4e15.5 mM, and for zooplankton 1e54 m .
718 775
RR
719 776
Table 2
720 Model sensitivity runs. All the runs were carried out for a steady, freshwater 777
721 778
discharge Qf ¼ 2 m3 sÀ1. Rates are expressed as dayÀ1
722 779
Run 1: Standard run
Table 1
723 780
bNP decreased from 0.1 to 0.05
Run 2:
CO
Final values of the parameters. Rates are expressed as dayÀ1
724 781
bPZ decreased from 0.1 to 0.05
Run 3:
bPB decreased from 0.1 to 0.05
bNP Run 4:
0.2
725 782
dP decreased from 0.05 to 0.025
bPZ Run 5:
0.1
726 783
bZZF decreased from 0.1 to 0.05
Run 6:
bPB 0.1
727 784
dZ decreased from 0.1 to 0.05
Run 7:
dP 0.05
728 785
bBCF decreased from 0.1 to 0.05
bZZF Run 8:
0.1
UN
729 786
dZ Run 9: decreased from 0.1 to 0.05
0.1
dCF decreased from 0.1 to 0.05
Run 10:
bBCF 0.1
730 787
bDZF decreased from 0.1 to 0.05
Run 11:
dB 0.1
731 788
dZF decreased from 0.1 to 0.05
dCF Run 12:
0.1
732 789
bSSCN decreased from 0.3 to 0.15
bDZF Run 13:
0.1
733 790
bZCF decreased from 0.03 to 0.015
Run 14:
dZF 0.1
734 791
bSSCN Run 15: decreased from 0.03 to 0.015
0.3
bDB decreased from 0.1 to 0.05
bZCF Run 16:
0.03
735 792
aZ and aB decreased from 0.15 to 0.075
Run 17:
bDCF 0.03
736 793
aD in the freshwater zone increased from 0 to 0.05
Run 18
bDB 0.1
737 794
À1 À1
bDZ increased to 0.1 day (run 19) and 0.05 day
bDZ Run 19:
0.05
738 795
aB (run 19a, open circles)
0.15 (¼0 in freshwater reaches)
739 aD increased to 0.15 in the saline region and 0.05 in 796
Run 20:
aD 0.05 (¼0 in freshwater reaches)
the freshwater region
aCF 0.05 (¼0 in freshwater reaches)
740 797
bPCF increased to 0.1; az and aB increased to 0.15
aZ Run 21:
0.05 (¼0 in freshwater reaches)
741 798
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799 856
800 857
801 858
802 859
803 860
804 861
805 862
806 863
807 864
808 865
809 866
F
810 867
811 868
OO
812 869
813 870
814 871
815 872
816 873
PR
817 874
818 875
819 876
820 877
821 878
822 879
ED
823 880
824 881
825 882
826 883
CT
827 884
828 885
829 886
830 887
E
831 888
832 889
RR
833 890
834 891
835 892
836 893
837 894
CO
838 895
839 896
840 897
841 898
842 899
UN
843 900
844 901
845 902
Fig. 6. Along-channel distribution of predicted variables in the Guadiana Estuary for various sensitivity runs shown as numbers (see Table 2). (a) Phytoplankton
biomass (Chl a), (b) zooplankton biomass, (c) zooplankton (cont), (d) zooplanktivorous fish biomass, (e) carnivorous/omnivorous fish biomass, and (f) detritus
846 903
biomass. To convert biomass to concentration, see Fig. 5 and for Chl a 3.5e7.8 mg lÀ1.
847 904
848 905
849 906
850 907
In the model carnivorous/omnivorous fish is measurably reaches of the estuary and the model suggests that this fish
851 908
sensitive only to dCF (the natural death rate of carnivorous/om- is highly vulnerable to a salinity increase, as a result of reduc-
852 909
nivorous fish; case 10, Fig. 6e). The model suggests that no tion in river inflow. The model also suggests that the lower es-
853 910
other parameter than the natural death rate significantly influ- tuary has more detritus than it can consume, thus the
854 911
ences the omnivorous fish. These fishes are mainly freshwater additional detritus from salt marshes is unimportant. In the up-
855 912
Barbus spp. These species are located mostly in the upper per areas, detritus mainly originates from the decomposition of
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913 970
riparian vegetation, this source of detritus seems more impor-
914 971
tant in the middle and lower estuary (Fig. 6f).
915 972
The model sensitivity tests are useful because they show
916 973
that:
917 974
918 975
1. the model appears robust because large, but reasonable,
919 976
changes in the parameters do not lead to instabilities
920 977
such as the destruction of trophic layers;
921 978
2. the biomass of organisms is directly affected by its con-
922 979
sumption of prey or being consumed by predators the
923 980
next level up in the food chain. Indirect effects across
F
924 981
two trophic levels are generally small; for instance if we
925 982
compare ZF from runs 1 and 5, i.e. there is no impact of
OO
926 983
the death rate of phytoplankton on carnivorous fish.
927 984
928 985
929 986
3.2. Examples of management application of the model
930 987
PR
931 988
The ecological sub-model is also simple, though still real-
932 989
istic. It incorporates the dominant six state variables. The
933 990
model integrates physical, chemical and biological processes
934 991
in the estuary; it predicts the ecosystem health as determined Fig. 7. Along-channel distribution of predicted phytoplankton (Chl a) biomass
in the Guadiana Estuary for the standard run (‘as is’), for a doubling of nutrient
935 992
by the following variables: nutrients, suspended particulate
concentration in the river (‘N Â 2’), and for the additional impact of removing
936 993
ED
matter, phytoplankton, zooplankton, bivalves, zooplanktivo-
the salt marshes (‘No marsh, N Â 2’) for a freshwater discharge equal to
937 994
rous fish and carnivorous/omnivorous fish. Thus the model is 2 m3 sÀ1. To convert biomass to concentration for Chl a 3.5e7.8 mg lÀ1.
938 995
simpler than a number of other models (e.g. Flindt and
939 996
Alqueva dam because their renewal and distribution depend
Kamp-Nielsen, 1997 e this comprises 12 state variables)
940 997
on freshets.
that are often too complex and unwieldy for practical applica-
CT
941 998
Moreover, the model can also be used for finding solutions
tions, especially when data are unavailable or insufficient.
942 999
for practical existing environmental problems in the Guadiana
The model can readily be used to test management sce-
943 1000
Estuary such as toxic algal blooms and eutrophication risk. After
narios when querying the impact of developments and
944 1001
the dam construction the estuary reached a man-made quasi-
disturbances to land-use and water-resources in the river
E
945 1002
steady state characterised by poor productivity and low biomass
catchment. For instance, the model predicts (Fig. 7) the impact
946 1003
in all communities (Fig. 8). Indeed, the fluctuations in river dis-
of doubling the nutrient concentration in the Guadiana River
RR
947 1004
charge e as freshets e as occurred historically, increased diver-
as a result of irrigation farming downstream of the Alqueva
948 1005
sity and variability in plankton and nektonic communities
dam. Such farming is indeed planned. The phytoplankton con-
949 1006
(Fig. 8bee), and promoted ecosystem dynamics. This model
centration is predicted to increase, particularly in the phyto-
950 1007
prediction is supported by the observations of Roelke (2000)
plankton maximum zone located in the upper reaches of the
951 1008
in the Nueces Delta, Texas. This ecosystem response to freshwa-
estuary. This suggests that the system is becoming eutrophi-
CO
952 1009
ter discharge pulses can be used as a management solution for
cated and the risk of toxic algae blooms has increased.
953 1010
toxic algal blooms or eutrophication in the Guadiana. In the
The model can also predict the impact of the salt marshes
Guadiana, the model suggests that increasing Qf to 50 m3 sÀ1
954 1011
being destroyed by developments. The model predictions for
955 1012
for 5 days will flush the estuary and promote the development
phytoplankton are shown in Fig. 7. Clearly the risk of eutro-
956 1013
of a diverse phytoplankton and zooplankton communities.
phication and of toxic algae blooms would be further
UN
957 1014
The model is restricted to the estuary. It cannot predict im-
increased.
958 1015
pacts on the coastal zone. Studies are needed to determine if
The model was used to assess the influence on the estuarine
959 1016
longer-duration and possibly higher intensity freshets may
ecosystem health of the Alqueva dam that in 2002e2003 sub-
960 1017
be needed to maintain coastal marine ecosystem health,
stantially decreased the river discharge Qf (Fig. 8a). The pre-
961 1018
˜
as suggested by Doornbos (1982), Quinones and Montes
dictions (Fig. 8b, c) show that without the dam the system was
´
962 1019
(2001), Chıcharo et al. (2002) and Simier et al. (2004).
highly variable during a freshwater pulse, while with the dam
963 1020
Thus the estuarine ecohydrology model is able to provide
the system was at steady state. The predicted influence of the
964 1021
answers to a number of practical questions. These answers
Alqueva dam is particularly dramatic for the carnivorous/om-
965 1022
must always be taken carefully because the model, like any
nivorous fish (Fig. 8d, e) because without the dam the fish was
966 1023
ecosystem model, over-simplifies reality, and the data set is in-
able to spread over much of the estuary for up to a month after
967 1024
adequate for a detailed calibration. In that sense, the model
a freshet, while with the dam the fish is restricted to the upper-
968 1025
predictions are somewhere between quantitative and qualita-
most region of the estuary. Zooplankton and zooplanktivorous
969 1026
tive. Detailed field studies are needed to better understand,
fish also are predicted to decrease in the presence of the
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1028 1085
1029 1086
1030 1087
1031 1088
1032 1089
1033 1090
1034 1091
1035 1092
1036 1093
1037 1094
F
1038 1095
1039 1096
OO
1040 1097
1041 1098
1042 1099
1043 1100
1044 1101
PR
1045 1102
1046 1103
1047 1104
1048 1105
1049 1106
1050 1107
ED
1051 1108
1052 1109
1053 1110
1054 1111
CT
1055 1112
1056 1113
1057 1114
1058 1115
E
1059 1116
1060 1117
RR
1061 1118
1062 1119
1063 1120
1064 1121
1065 1122
CO
1066 1123
1067 1124
1068 1125
1069 1126
Fig. 8. (a) Time series plot of the Guadiana River discharge entering the estuary in the dry season of 2003 in the presence of the Alqueva dam, and the predicted
1070 1127
river discharge if the dam had not been constructed (middle). Time series plot of the predicted distribution of phytoplankton biomass in the Guadiana Estuary in
UN
1071 1128
2003 (b) without and (c) with the Alqueva dam. Time series plot of the predicted distribution of carnivorous/omnivorous fish biomass in the Guadiana Estuary in
2003 (d) without and (e) with the Alqueva dam. To convert biomass to concentration, see Figs. 5 and 6.
1072 1129
1073 1130
1074 1131
and hence better parameterise in the model, the various pro- presently set as a constant, is probably varying seasonally
1075 1132
cesses driving the ecosystem. The model should be seen as and possibly stochastically e data on this are missing and
1076 1133
a living model e it has been written using subroutines that are needed. Also, as the new data become available, the model
1077 1134
are readily edited, so that the new knowledge on individual should be improved by subdividing the phytoplankton com-
1078 1135
processes can readily be incorporated in the model. For the partment into the main classes (Domingues et al., 2005).
1079 1136
model to remain a useful tool, it is suggested that its complex- For science, the model provides a tool to enable the
1080 1137
ity should be increased only as fast as additional physical, exchange of information between oceanographers, biologists,
1081 1138
chemical and biological processes can be quantified through ecologists, engineers, sociologists, economists and water-
1082 1139
new field and laboratory studies. For example, the import resources managers at regional and national government
1083 1140
rate a from salt marshes and riparian ecotones, which is levels, and the community.
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1141 1198
It is hoped that the model can also be useful for manage- References
1142 1199
ment. The model shows that it is possible to predict e within
1143 1200
likely error bounds provided by the sensitivity tests e the con- Ackroyd, D.R., Bale, A.J., Howland, R.J.M., Knox, S., Millward, G.E.,
Morris, A.W., 1986. Distributions and behaviour of dissolved Cu, Zn
1144 1201
sequences on the estuary ecosystem health of human activities
and Mn in the Tamar estuary. Estuarine, Coastal and Shelf Science 23,
1145 1202
throughout the river catchment. The model does show that, to 621e624.
1146 1203
maintain the ecosystem services provided by the estuary, inte- ´
Alveirinho, J.M.A., Gonzalez, R., Ferreira, O., 2004. Natural versus anthropic
1147 1204
grated coastal management needs to take the whole river causes in variations of sand export from river basins: an example from the
1148 1205
catchment as the fundamental planning unit. It is necessary Guadiana river mouth (Southwestern Iberia). Polish Geological Institute
Special Papers 11, 95e102.
1149 1206
to bring together land-use managers, water-resources man-
Balls, P.W., 1994. Nutrient inputs to estuaries from nine Scottish east coast
1150 1207
agers, and coastal and fisheries managers. The model offers rivers: influence of estuarine processes on inputs to the North sea. Estua-
1151 1208
thus a tool for using ecohydrology as a holistic approach to rine, Coastal and Shelf Science 39, 329e352.
F
1152 1209
the management of rivers, estuaries and coastal zones within ´
Bille, R., Mermet, L., 2002. Integrated coastal management at the regional
1153 1210
entire river catchments. level: lessons from Toliary, Madagascar. Ocean and Coastal Management
OO
45, 41e58.
1154 1211
Boorman, L.A., Hazelden, J.H., Loveland, P.J., Wells, J.G., 1994a. Compara-
1155 1212
tive relationships between primary productivity and organic and nutrient
4. Conclusions
1156 1213
fluxes in four salt marshes. In: Mitsch, W.J. (Ed.), Global Wetlands. Old
1157 1214
World and New. Elsevier, Amsterdam, pp. 181e189.
The ecohydrology model is original in that it links physical,
1158 1215
Boorman, L.A., Hazelden, J., Andrews, R., Wells, J.G., 1994b. Organic and
chemical and biological processes over the entire estuary for
PR
nutrient fluxes in four north-west European salt marshes. In: Dyer, K.R.,
1159 1216
the entire food web as a function of catchment output and Orth, R.J. (Eds.), Changes in Fluxes in Estuaries: Implications from Sci-
1160 1217
ence to Management. Olsen and Olsen, Fredensborg, pp. 243e248.
the oceanic open boundary condition. Despite the fact that
1161 1218
Brauer, F., Castillo-Chavez, C., 2001. Mathematical Models in Population Bi-
a number of simplifications are made, the model is encourag-
1162 1219
ology and Epidemiology. Springer, Berlin, 416 pp.
ing in that it reproduces satisfactorily the observations in
1163 1220
´ ´
Chıcharo, L., Chıcharo, M.A., Esteves, E., Andrade, P., Morais, P., 2002. Ef-
2001e2003. These data are still sparse and the model may fects of alterations in fresh water supply on the abundance and distribution
1164 1221
ED
need improvements as additional data become available. of Engraulis encrasicolus in the Guadiana Estuary and adjacent coastal
1165 1222
areas of south Portugal. Journal Ecohydrology and Hydrobiology 1,
The model can readily be used to assess future impact on
1166 1223
195e200.
the Guadiana Estuary ecosystem health caused by urbanisation
1167 1224
Domingues, R.B., Barbosa, A., Galv~o, H., 2005. Nutrients, light and phyto-
a
or other factors that reduce the salt marsh area, by an increase
1168 1225
plankton succession in a temperate estuary (the Guadiana, south-western
CT
in nutrient loads as a result of changes in agriculture practices Iberia). Estuarine, Coastal and Shelf Science 64, 249e260.
1169 1226
in the catchment area due to increase in water availability by Doornbos, G., 1982. Changes in the fish fauna of the former Grevelingen es-
1170 1227
tuary, before and after the closure in 1971. Hydrobiological Bulletin 16,
the Alqueva dam, by extreme high freshwater discharges, e.g.
1171 1228
279e283.
due to release of high volume of water storage in the dam, and
1172 1229
Edwards, A.M., 2001. Adding detritus to a nutrientephytoplanktone
by the introduction of exotic species.
E
1173 1230
zooplankton model: a dynamical-systems approach. Journal of Plankton
The model can also be used to predict the efficiency of re- Research 23, 389e413.
1174 1231
medial measures, such as creating wetlands, creating freshets Erzini, K., 2005. Trends in NE Atlantic landings (southern Portugal): identify-
RR
1175 1232
ing the relative importance of fisheries and environmental variables.
by releasing water from the Alqueva dam, managing bivalve
1176 1233
Fisheries Oceanography 14, 195e209.
species in the freshwater part of the estuary, and removing nu-
1177 1234
Esteves, E., Pina, T., Chicharo, M.A., Andrade, J.P., 2000. The distribution of
trients from the river.
1178 1235
estuarine fish larvae: nutritional condition and co-occurrence with preda-
tors and prey. Acta Oecologica 21 (3), 1e13.
1179 1236
CO
Flameling, I.A., Kromkamp, J., 1994. Responses of respiration and photosyn-
1180 1237
Acknowledgements thesis of Scenedesmus protuberans (Fritsch) to gradual and steep salinity
1181 1238
increases. Journal of Plankton Research 16, 1781e1791.
1182 1239
Flindt, M.R., Kamp-Nielsen, L., 1997. Modelling of an estuarine eutrophica-
It is a pleasure to thank Philippe Pypaert and UNESCO e
1183 1240
tion gradient. Ecological Modeling 102, 143e153.
ROSTE for supporting the development of this model through
Fischer, H.B., List, E.Y., Koh, R.C.Y., Imberger, J., Brooks, N.H., 1979. Mix-
1184 1241
contract No. 875.767.4 in estuarine and coastal zone ecohydrol-
UN
ing in Inland and Coastal Waters. Academic Press, New York, 483 pp.
1185 1242
ogy. Also thanks are due to the University of Algarve for provid- Fortunato, A.B., Oliviera, A., Alves, E.T., 2002. Circulation and salinity intru-
1186 1243
ing logistical support. The collection of the biological data was sion in the Guadiana Estuary. Thalassas 18, 43e65.
1187 1244
´
Gonzalez, J.A.M., 1995. Sedimentologia del estuario del Rio Guadiana (SO
made possible by the financial support of the projects ‘Effects of
1188 1245
´
Portugal). CEP. Biblioteca Universitaria, Universidade de Huelva.
River Flow changes on the fish communities of the Douro, Tejo
Goosen, N.K., van Rijswijk, P., Brockmann, U., 1995. Comparison of hetero-
1189 1246
and Guadiana Estuaries and coastal areas: ecological and socio- trophic bacterial production rates in early spring in the turbid estuaries of
1190 1247
economic predictions (ERIC) (FCT/P/MAR/15263/1999)’, the Scheldt and the Elbe. Hydrobiologia 311, 31e42.
1191 1248
‘General characterisation of the Guadiana Estuary ecosystem Haward, M., 1996. Institutional framework for Australian ocean and coastal
1192 1249
management. Ocean and Coastal Management 33, 19e39.
(FCT/P/15 REG/II/6/96)’, ‘Valorization of Aquatic resources
1193 1250
Hilborn, R., Mangel, M., 1997. The Ecological Detective. Confronting Models
of the Guadiana Estuary (Portugal) (Feder/PPDR/CCRA/ODI-
with Data. Princeton University Press, Princeton, 315 pp.
1194 1251
ANA)’, and the PhD scholarship of P. Morais ‘Engraulis encra- Humston, R., Ault, J.S., Lutcavage, M., Olson, D.B., 2000. Schooling and mi-
1195 1252
sicolus population dynamics in the Guadiana Estuary and gration of large pelagic fishes relative to environmental cues. Fisheries
1196 1253
adjacent coastal area (SFRH/BD/5187/2001)’. Oceanography 9, 136e146.
1197 1254
YECSS1994_proof 12 July 2006 11/12
ARTICLE IN PRESS
+ MODEL
12 E. Wolanski et al. / Estuarine, Coastal and Shelf Science xx (2006) 1e12
1255 1289
Jorgensen, S.E., Bendoricchio, G., 2001. Fundamentals of Ecological Model- Roelke, D.L., 2000. Copepod food quality threshold as a mechanism influenc-
1256 1290
ling. Elsevier, 530 pp. ing phytoplankton succession and accumulation of biomass, and secondary
1257 1291
Kibirige, I.R., Perissinotto, R., Nozais, C., 2002. Alternative food sources productivity: a modelling study with management implications. Ecological
of zooplankton in a temporarily-open estuary: evidence from d13C and
1258 1292
Modelling 134, 245e274.
d15N. Journal of Plankton Research 24, 1089e1095.
1259 1293
Salomons, W., Forstner, U., 1984. Metals in the Hydrocycle. Springer-Verlag,
1260 1294
Knox, G.A., 1986. Estuarine Ecosystems: A Systems Approach, vol. II. CRC Berlin, 349 pp.
1261 1295
Press, Florida, 230 pp. Simenstad, C.A., Morgan, C.A., Cordell, J.R., Baross, J.A., 1994. Flux, passive
1262 1296
Kot, M., 2001. Elements of Mathematical Ecology. Cambridge University retention, and active residence of zooplankton in Columbia river estuarine
1263 1297
Press, Cambridge, 464 pp. turbidity maxima. In: Dyer, J., Orth, M. (Eds.), Changes in Fluxes in
1264 1298
Lau, M., 2005. Integrated coastal zone management in the People’s Republic Estuaries: Implications from Science to Management. University of
1265 1299
of China e an assessment of structural impacts on decision-making Plymouth, pp. 473e482 (ECSA22/ERF Symposium).
1266 1300
processes. Ocean and Coastal Management 48, 115e159. Simier, M., Blanc, L., Aliaume, C., Diouf, P.S., Albaret, J.J., 2004. Spatial and
1267 1301
Lefeuvre, J.C., 1996. Effects of environmental change on European salt temporal structure of fish assemblages in an ‘‘inverse estuary’’, the Sine
F
1268 1302
marshes. In: Structure, Functioning and Exchange Potentialities with Saloum system. Estuarine, Coastal and Shelf Science 59, 69e86.
´
1269 1303
Marine Coastal Waters, vols. 1e6. University of Rennes, France. Tagliani, P.R.A., Landazuri, H., Reis, E.G., Tagliani, C.R., Asmus, M.L., San-
1270 1304
Lindeboom, H., 2002. The coastal zone: an ecosystem under pressure. In: chez-Arcilla, A., 2003. Integrated coastal zone management in the Patos
OO
1271 1305
Field, J.G., Hempel, G., Summerhayes, C.P. (Eds.), Oceans 2020: Science, Lagoon estuary: perspectives in context of developing country. Ocean
1272 1306
Trends, and the Challenge of Sustainability. Island Press, Washington, and Coastal Management 46, 807e822.
1273 1307
pp. 49e84, 365 pp. Thomann, R.V., 1980. Deterministic and statistical models of chemical fate in
1274 1308
Michel, D., 1980. Synthese des donnes physiques mesures dans le Rio Guadi- aquatic systems. In: Levin, S.A., Hallam, T.G., Gross, L.J. (Eds.), Applied
1275 1309
ana. Evaluation de l’intrusion saline dans l’estuaire. PhD thesis, Labora- Mathematical Ecology. Springer-Verlag, Berlin, pp. 322e351, 491 pp.
´
1276 1310
toire d’oceanographie, Universite de Bruxelles. Uncles, R.J., Stephens, J.A., Smith, R.E., 2002. The dependence of estuarine
PR
1277 1311
Nixon, S.W., 2003. Replacing the Nile: are anthropogenic nutrients providing turbidity on tidal intrusion length, tidal range and residence time. Conti-
1278 1312
the fertility once brought to the Mediterranean by a great river? Ambio 32, nental Shelf Research 22, 1835e1856.
1279 1313
30e39. Wolanski, E., Doherty, P., Carleton, J., 1997. Directional swimming of fish
1280 1314
Pickaver, A.H., Gilbert, C., Breton, F., 2004. An indicator set to measure the larvae determines connectivity of fish populations on the Great Barrier
1281 1315
progress in the implementation of integrated coastal zone management in reef. Naturwissenschaften 84, 262e268.
´
1282 1316
Europe. Ocean and Coastal Management 47, 449e462. Wolanski, E., Boorman, L.A., Chıcharo, L., Langlois-Saliou, E., Lara, R.,
ED
Pinto, G.V., 2000. Caracterizac~o Dos Bancos Naturais De Bivalves Com
1283 1317
¸a Plater, A.J., Uncles, R.J., Zalewski, M., 2004. Ecohydrology as a new
´
1284 1318
Interesse Comercial No Estuario Do Guadiana. Tese de licenciatura tool for sustainable management of estuaries and coastal waters. Wetlands
1285 1319
Biologia Marinha, Universidade do Algarve. Ecology and Management 12, 235e276.
1286 1320
˜
Quinones, R.A., Montes, R.M., 2001. Relationship between freshwater input Zalewski, M., 2002. Ecohydrology e the use of ecological and hydrological
1287 1321
to the coastal zone and historical landing of the benthic/demersal fish in processes for sustainable management of water-resources. Hydrological
CT
1288 1322
Central-South Chile. Fisheries Oceanography 10, 311e328. Sciences Bulletin 47, 823e832.
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