Guy Woodward

Mark O Gessner

Paul S Giller

Vladislav Gulis

Sally Hladyz

Antoine Lecerf

Björn Malmqvist

Brendan G Mckie

‖ Scott

D Tiegs

Helen Cariss

¶ Mike Dobson

Arturo Elosegi

Verónica Ferreira

Manuel A S Graça

Tadeusz Fleituch

Jean O Lacoursière

Marius Nistorescu

Jesús Pozo

Geta Risnoveanu

Markus Schindler

Angheluta Vadineanu

B.-M Vought

Eric Chauvet

Continental-Scale Effects of Nutrient Pollution on Stream Ecosystem Functioning

Excessive nutrient loading is a major threat to aquatic ecosystems worldwide that leads to profound changes in aquatic biodiversity and biogeochemical processes. Systematic quantitative assessment of functional ecosystem measures for river networks is, however, lacking, especially at continental scales. Here, we narrow this gap by means of a pan-European field experiment on a fundamental ecosystem process-leaf-litter breakdown-in 100 streams across a greater than 1000-fold nutrient gradient. Dramatically slowed breakdown at both extremes of the gradient indicated strong nutrient limitation in unaffected systems, potential for strong stimulation in moderately altered systems, and inhibition in highly polluted streams. This large-scale response pattern emphasizes the need to complement established structural approaches (such as water chemistry, hydrogeomorphology, and biological diversity metrics) with functional measures (such as litter-breakdown rate, whole-system metabolism, and nutrient spiraling) for assessing ecosystem health. N utrient enrichment from organic inputs and agricultural run-off is placing the world's vulnerable fresh waters in a precarious position (1)(2)(3)(4). Far-reaching environmental legislation has been introduced to redress human impacts on aquatic communities (5,6), yet the consequences of nutrient loading for stream ecosystem functioning remain poorly understood (4,7,8). This is worrying because key ecosystem services (such as maintenance of viable fisheries as a provisioning service, and organic matter decomposition as a supporting service) ultimately depend on ecosystem processes, such as leaf-litter breakdown and other processes involved in nutrient cycling (3,9).

Many aquatic ecosystems are supported by plant litter inputs (10)(11)(12). This includes streams, where terrestrial leaf breakdown-which is driven by resource quality; the abundance, diversity, and activity of consumers; and environmental factors-is a key ecosystem process (10,13,14). Moderate nutrient enrichment of streams can accelerate breakdown by stimulating microbial con-ditioning and invertebrate consumption (15,16). However, a wide range of responses along nutrient gradients has been reported in field studies, suggesting environmental drivers beyond elevated nutrient supply. For instance, wastewater discharge can induce anoxia, mobilize heavy metals, and physically smother benthic organisms [START_REF] Mason | Biology of Freshwater Pollution[END_REF][START_REF] Bundschuh | [END_REF]. Litter breakdown by invertebrates (19) appears especially sensitive to nutrient pollution relative to that mediated by microbes (20) and, because invertebrates often attain their highest densities in moderately enriched streams, a hump-shaped breakdown rate response might be expected along long nutrient gradients (5).

We hypothesized that breakdown rates are constrained by microbial nutrient limitation at the low end of nutrient pollution gradients and by the effects of environmental degradation on invertebrates at the high end. Most studies, however, have been unable to detect this pattern because they have been conducted over relatively short nutrient gradients and small spatial scales (5,7).

Here, we report a field experiment in 100 European streams spanning 1000-fold differences in nutrient concentrations, as proxy measures of nutrient loading by direct and indirect inputs [START_REF]Materials and methods are available as supplementary materials on Science Online[END_REF]. The validity of this approach is highlighted by the positive relationship between biochemical oxygen demand (BOD 5 ) and nutrient concentrations in more than 8000 European streams, and the comparable frequency distributions of nutrient concentrations between these and our sites (fig.

1 Department of Zoology, Ecology and Plant Science, University College Cork, National University of Ireland, Cork, Enterprise Centre, Distillery Fields, Cork, Ireland. 2 Queen Mary University of London, School of Biological and Chemical Sciences, London E1 4NS, UK. 3 Department of Aquatic Ecology, Eawag: Swiss Federal Institute of Aquatic Science and Technology, 6047 Kastanienbaum, Switzerland. 4 Institute of Integrative Biology (IBZ), ETH Zurich, 8092 Zurich, Switzerland. 5 Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Alte Fischerhütte 2, 16775 Stechlin, Germany. 6 Department of Ecology, Berlin Institute of Technology (TU Berlin), Ernst-Reuter-Platz 1, 10587 Berlin, Germany. 7 S1). We deployed 2400 experimental litter bags made with fine or coarse mesh to determine total, microbially mediated, and invertebrate-driven breakdown rates of litter from two common tree species: slow-decomposing pedunculate oak (Quercus robur L.) and fast-decomposing black alder (Alnus glutinosa [L.] Gaertn.), both widespread across Europe and with closely related species that are common throughout the Holarctic region.

Both litter types exhibited hump-shaped responses for invertebrate-driven breakdown rates as a function of soluble reactive phosphorus (SRP) and dissolved inorganic nitrogen (DIN) concentrations (Fig. 1

and figs. S2 and S3

). Rates were always low at the extremes, but low-to-high at intermediate nutrient concentrations. Within a given range of nutrient concentrations, the spread of breakdown rates was almost equal to the maximum (there was an upper, but not a lower, limit) (figs. S4 and S5), supporting the idea that factors beyond nutrients alone modulated consumer activity (14). Although a similar pattern emerged for total breakdown with highest rates at intermediate enrichment levels, this response was not as clear as for invertebrate-mediated breakdown (fig. S2).

In addition to our Europe-wide measures of breakdown rates, we characterized the structure of invertebrate communities in 10 Irish streams that spanned the entire continental nutrient gradient [START_REF]Materials and methods are available as supplementary materials on Science Online[END_REF]. Condensing the principal gradient of invertebrate primary consumer relative abundance across these sites into a single ordination axis, via detrended canonical correspondence analysis (DCCA) [START_REF] Braak | CANOCO Reference Manual and User's Guide to CANOCO for Windows: Software for Canonical Community Ordination[END_REF], revealed the typical community response to pollution, from indicators of clean water (such as heptageniid mayflies) to those typical of polluted conditions (such as physid snails) (Fig. 2). This enabled us to plot invertebrate community structure against breakdown rate.

The moderately enriched sites exhibited the fastest breakdown and were characterized by the largest consumer taxa (Fig. 2), whose abundance was a strong predictor of breakdown rate (fig. S6). This integrated community gradient yielded clearer unimodal relationships to our functional measure (R 2 all ≥ 0.88, P < 0.001) (Fig. 2) than to either nutrient alone (SRP, R 2 = 0.66 to 0.79, P = 0.04 to 0.004; DIN, not significant).

The rising part of the unimodal curve likely resulted from nutrient stimulation of microbes and subsequent increased consumption of leaf litter by invertebrates. In contrast, the falling portion probably reflects deteriorating environmental conditions suppressing invertebrate-mediated breakdown (for example, chemical and habitat conditions associated with high BOD 5 ) (fig. S1), suggesting that increases in detrimental pollution syndromes (such as oxygen depletion, smothering, or disappearance of sensitive invertebrate taxa) might counteract the stimulating effects of nutrients [START_REF] Lecerf | [END_REF]. Because breakdown at moderately enriched sites was released from constraints of both nutrient limitation and stressors accompanying excess nutrient supply, other drivers, including biological community structure (24,25), clearly assume importance here. This poses challenges-and also provides opportunities-to stream assessment and management because most European streams and rivers lie in this zone of Fig. 1. Rates of invertebratemediated breakdown as a function of SRP and DIN concentrations for oak (Left) and alder (Right) leaves. Each data point represents a temperature-corrected rate [expressed in degree days -1 (dd -1 )] for a single stream. Three-dimensional volume-filling relationships between nutrient gradients and breakdown rates with unimodal Lorentzian surfaces are fitted as bounding envelopes to maxima within categories of nutrient concentrations (per 0.5 log 10 division of SRP and DIN in mg l -1 ); R 2 values of the fits to these maxima are 0.85 for oak and 0.77 for alder, respectively (randomization tests were carried out to rule out any potential influence of different sample sizes setting the bounding envelopes along the nutrient gradients) (figs. S4 and S5) [START_REF]Materials and methods are available as supplementary materials on Science Online[END_REF]. Data points above and below unimodal Lorentzian surfaces are displayed in black and gray, respectively. Fig. 2. Axis I sample scores from a DCCA on communities of primary consumers in alder (circles) and oak (triangles) leaf bags at 10 streams in Ireland, plotted against total (white symbols) and invertebrate-mediated (black symbols) breakdown rate (expressed in degree days -1 ). Unimodal Lorentzian curves have been fitted to the data (alder k total : R 2 = 0.93; P < 0.0001; alder k invertebrate : R 2 = 0.88; P = 0.0006; oak k total : R 2 = 0.97; P < 0.0001; oak k invertebrate : R 2 = 0.96; P = 0.0001). Scores of individual invertebrate taxa depicted as letters at the top of the graph show that the largest litter-consuming detritivores, gammarid shrimps and limnephilid caddisfly larvae, are close to the peak of the curves. An, Ancylidae; As, Asellidae; Ba, Baetidae; El, Elmidae; Ep, Ephemerellidae; Ga, Gammaridae; He, Heptageniidae; Hy, Hydrobiidae; Le, Leuctridae; Li, Limnephilidae; Ly, Lymnaeidae; Ne, Nemouridae; Ol, Oligochaeta; Ph, Physidae; Ti, Tipulidae. maximum uncertainty (Fig. 1 and fig. S1). For example, increased breakdown rates in slightly enriched streams would indicate altered ecosystem functioning, although most managers would consider such streams ecologically intact on the basis of traditional assessment criteria. Conversely, low breakdown rates at moderately enriched sites are no guarantee that streams are unaffected, requiring comprehensive assessments based on a range of indicators in order to draw conclusions about ecosystem impairment.

Axis I DCCA Scores

Our results raise fundamental questions about how to determine ecosystem health. First, naturally low-nutrient conditions are the desired state that water resource managers aspire to, and yet breakdown rates in such systems were indistinguishable from those in heavily polluted streams. This suggests that ensuring both low-nutrient water and effective resource use in stream food webs (from leaf litter to detritivores to fish) coupled with high process rates might be irreconcilable goals in stream management. Second, stream managers currently rely primarily on structural measures to assess stream ecosystem health. In particular, changes in biological community structure (invertebrates, fish, and algae) have long underpinned stream bioassessment schemes because they provide a reliable time-integrated response to stressors such as organic pollution or acidification (5), but biogeographical constraints make this approach difficult to standardize at large scales (10). Litter breakdown can help here because biogeography is a minor issue (for example, black alder or similar species of the genus are common throughout most of Europe and the Holarctic), and marked changes in breakdown rate occurred in the rising portion of the pollution gradient, in which established structural measures (such as water chemistry, hydromorphology, and metrics based on fish, invertebrate, or algal communities) are typically least sensitive. Consequently, litter breakdown-and potentially other functional measures such as whole-ecosystem metabolism, nutrient spiraling, or primary production (26-28)-can be used to complement, not replace, established procedures to assess stream ecosystem health. This highlights the need for differential diagnoses in environmental assessment, as is standard practice in medicine. Importantly, litter breakdown and some other functionally based methods can be implemented at relatively little cost or resource input (29) in order to assess effects of pollution and other ecosystem impacts that are of concern to environmental managers and stakeholders.

Increasing human pressure is accelerating environmental change throughout the world, threatening water security for humans and aquatic biodiversity (2). Large stretches of the landscape in Europe and other parts of the world are characterized today by highly industrialized, intensively managed agriculture and the large-scale application of fertilizers. This, in combination with other nutrient sources such as atmospheric deposition, has resulted in widespread nutrient pol-lution of aquatic ecosystems (2,5,8). Our study reveals that along with biodiversity losses, as fresh waters drift away from their natural conditions, ecosystem processes are profoundly changed, too. Impacts on stream functioning may go beyond the effects on litter breakdown because changing litter dynamics can have strong effects on nutrient retention and transformations (27), invertebrate productivity (12,30), and other functional ecosystem attributes. Given these complexities and large uncertainties surrounding human environmental impacts (5,24), a critical objective for the future will be to improve concepts and implementation tools to simultaneously manage surface waters sustainably and meet the demands of biodiversity conservation and environmental legislation.

  Institute of Marine Research (IMAR) and Department of Life Sciences, University of Coimbra, 3001-401 Coimbra, Portugal. 8 Université de Toulouse; INP, UPS; Laboratoire Ecologie Fonctionnelle et Environnement (EcoLab), 118 Route de Narbonne, 31062 Toulouse, France. 9 CNRS, EcoLab, 31062 Toulouse, France. 10 Department of Ecology and Environmental Science, UmeåUniversity, 90187 Umeå, Sweden. Oakland University, Rochester, MI 48309-4401, USA. 12 Department of Environmental and Geographical Sciences, Manchester Metropolitan University, Chester Street, Manchester M15 6BH, UK. 13 Department of Plant Biology and Ecology, Faculty of Science and Technology, University of the Basque Country, Post Office Box 644, 48080 Bilbao, Spain. 14 Institute of Nature Conservation, Polish Academy of Sciences, Mickiewicza 33, 31-120 Kraków, Poland. 15 School of Education and Environment, Kristianstad University, 29188 Kristianstad, Sweden. 16 Department of Systems Ecology and Sustainability, University of Bucharest, Splaiul Indepedentei 91-95, 050095 Bucharest, Romania.

	*These authors contributed equally to this work.
	†To whom correspondence should be sent. E-mail: g.woodward@
	qmul.ac.uk (G.W.); gessner@igb-berlin.de (M.O.G.); eric.chauvet@
	univ-tlse3.fr (E.C.)
	‡Present address: Department of Biology, Coastal Carolina
	University, Post Office Box 261954 Conway, SC 29528-
	6054, USA.
	§Present address: Monash University, Australian Centre for
	Biodiversity and School of Biological Sciences, Clayton,
	Victoria 3800, Australia.
	‖Present address: Department of Aquatic Sciences and As-
	sessment, Swedish University of Agricultural Sciences, 75007
	Uppsala, Sweden.

11

Department of Biological Sciences, ¶Present address: Forestry Commission Wales, Rhodfa Padarn, Llanbadarn Fawr, Aberystwyth, Ceredigion SY23 3UR, UK. #Present address: Freshwater Biological Association, the Ferry Landing, Far Sawrey, Ambleside, Cumbria LA22 0LP, UK.

Acknowledgments: We thank the European Commission and the Swiss State Secretariat for Research and Education for funding the RivFunction research project (European Union contract EVK1-CT-2001-00088), which was supported under the Fifth Framework Programme. The constructive comments by three anonymous reviewers, which substantially improved the paper, are greatly appreciated. All basic data are available in the supplementary materials. This paper is dedicated to the memory of our colleague Björn Malmqvist, who sadly passed away in 2010.


Pierre Tandeo
email: pierre.tandeo@telecom-bretagne.eu

René Garello

Ronan Fablet

Romain Husson

Fabrice Collard

Bertrand Chapron

Interpolated swell fields from SAR measurements

Synthetic Aperture Radar (SAR) sensors on-board satellites are very well suited for observing sea surface geophysical parameters such as ocean swell. But on a very large scale, SAR data are too sparse for deriving some global information. From the original work of [4], and following some generic assumption on the physics of the swell propagation in deep water, it was shown that using a back-propagating scheme, it was possible to retrieve the source of the swell system and then generate a propagating field. In this paper, we are proposing a simpler and original approach, by assimilating the SAR data into a given swell field and then using a Kalman Filter/Smoother technique for updating the main parameters of the swell (wavelength, direction, and significant wave height) within the complete field. This method shows very encouraging results which will be confronted with in situ measurements when available.

I. INTRODUCTION

The observation of ocean swell using Synthetic Aperture Radar (SAR) on-board satellites has been demonstrated since the ERS-1 mission in 1992. In particular, ocean swell spectra can be derived from SAR images using a quasi-linear transformation. Unfortunately, SAR data are very sparse, acquired at different times and with heterogeneous quality. This statement demonstrates the need to assimilate SAR data, for instance using a third generation ocean wave model (cf. [START_REF] Aouf | On the combined assimilation of RA-2 altimeter and ASAR wave data for the improvement of wave forcasting[END_REF] and [START_REF] Bauer | Assimilation of wave data into the wave model WAM using an impulse response function method[END_REF]). An alternative is also possible. Under deep water and no current assumptions, swell can propagate for thousands of kilometers from the storm source. This idea was exploited in [START_REF] Collard | Monitoring and analysis of ocean swell fields from space: New methods for routine observations[END_REF] to retropropagate SAR observations (backward in time) to the most accurate storm identification and then to re-propagate them (forward in time) along the complete storm event within the corresponding basin. This analysis was so-called "fireworks". Then, [START_REF] Husson | Development and validation of a global observation-based swell model using wave mode operating Synthetic Aperture Radar[END_REF] uses these pseudo-observations to generate complete spatial fields of sea swell using a spatio-temporal interpolation.

In this work, we propose an original methodology to assimilate the SAR observations and interpolate swell fields. As in the fireworks analysis, we only use the along track SAR observations. Our idea is to use these SAR observations to update the integral parameters of the swell, considered as unknown statistical variables. The evolution of these variables are computed sequentially on the grid analysis. Each pixel is seen as a potential storm source and the swell is forwardly propagated along a direction and a group velocity. Using a Ensemble Kalman Filter (EnKF), we artificially create pseudo SAR observations using a random generator and we follow the most probable solution. Then, we proceed in the backward direction using a similar random approach involving an Ensemble Kalman Smoother (EnKS). The paper is organized as follows. Section II presents the methodology used in this article. It corresponds to a statistical model based on SAR data and resolved by EnKF/EnKS. In Section III, we apply the methodology and evaluate the results. We further discuss and summarize the key results of our investigations in Section IV.

II. METHOD

A. SAR data

We use ocean swell data provided by the Advanced-SAR instrument on-board ENVISAT via the wave mode (cf. [START_REF] Kerbaol | Quality assessment of ENVISAT ASAR Wave mode products based on regional and seasonal comparisons with WAM model outputs[END_REF] and [START_REF] Johnsen | ENVISAT ASAR Wave Mode Products-quality assessment and algorithm upgrade[END_REF]). The swells are characterized by three integral parameters: the significant height H s , the wavelength λ and the direction θ of the swell. The data used as case-study in this work correspond to a particular storm in July 2004 into the Southern Pacific Ocean (situations studied in [START_REF] Collard | Monitoring and analysis of ocean swell fields from space: New methods for routine observations[END_REF]). During this event, we keep into account the swell partitions with periods close to 17 s. The SAR observations are very sparse in space and time (cf. Fig. 1).

B. State space model

In this work, we estimate the integral parameters of the swell on a regular spatio-temporal grid. Thus, we define a spatial grid of p pixels into the domain covered by the SAR observations (hatched domain in Fig. 1). Then, for each analysis time t k , we define the unknown n-dimensional state vector x(t k ) with n = 4 × p. It corresponds to the fields of significant height H s , wavelength λ and the zonal and meridional components of the direction, respectively noted θ u and θ v . The state evolution in time is given by

x(t k ) = M (x(t k-1 )) + η(t k ), (1)
where M corresponds to (i) the swell propagation in deep water with a group velocity √ λg/(2 √ 2π) and (ii) the swell energy decay proportional to 1/(α sin(α)) with α the angular great-circle distance from the storm source (supposed to be known) as proposed by [START_REF] Collard | Monitoring and analysis of ocean swell fields from space: New methods for routine observations[END_REF]. The state evolution given in Eq. ( 1) is physically realistic but not completely deterministic. For instance, in the current version of the state operator M, we do not take into account either the swell dissipation, the surface current or the island shadow effects. Therefore, at each time t k , we add a random perturbation noted η(t k ). We assume that the perturbations are Gaussianly distributed with zero mean and a constant in time n × n covariance matrix Q. At the initial time of Eq. ( 1), we introduce an a priori knowledge of the integral parameters. We assume that this background information follows a Gaussian distribution given by the mean x b and the covariance matrix B. In this study, the initial condition is given by the fireworks analysis (cf. [START_REF] Husson | Development and validation of a global observation-based swell model using wave mode operating Synthetic Aperture Radar[END_REF]). It corresponds to a consistent and realistic prior information.

At irregular time, as described in Fig. 1, the integral parameters of the swell are partially observed. They are noted y. The state vector at time t k is related to the observation by the observation equation defined by

y(t k ) = H (x(t k )) + ǫ(t k ), (2)
where the observation operator H is the spatial interpolation from the analysis to the observation grid. We know that the SAR observations have a systematic error. Therefore, in Eq.

(2), we suppose that the stochastic random vector ǫ(t k ) is an additive zero mean Gaussian error characterized by the covariance matrix R. In the current version of the algorithm, the covariance matrices B, Q and R are supposed to be diagonal and, as explained in [START_REF] Collard | Monitoring and analysis of ocean swell fields from space: New methods for routine observations[END_REF], correspond to standard deviation of 0.3 m for H s , 36 m for λ and 17 • for θ. Note that for simplicity, Eq. ( 1) is written with a discrete evolution of the state in time. In reality, this equation is continuous and manages the irregular time sampling of the SAR observations. More precisely, we use an exponential decrease factor for Q, proportional to the time lag between two consecutive observations and/or analysis (see [START_REF] Tandeo | Linear Gaussian state-space model with irregular sampling: application to sea surface temperature[END_REF] for more details).

C. Ensemble Kalman filter

We use the sequential EnKF algorithm proposed by [START_REF] Burgers | Analysis scheme in the ensemble Kalman filter[END_REF] to propagate the state in a forward way. As in [START_REF] Pham | Stochastic methods for sequential data assimilation in strongly nonlinear systems[END_REF], we use a version of the EnKF where the state evolution M and the observation H operators do not need to be linearized. In the initial step of the EnKF algorithm, at time t 1 , an ensemble of x's composed by N members is randomly generated. The members of the ensemble follow a Gaussian distribution given by the vector mean x b and the covariance matrix B. The N initial members are stored in the vectors x f i (t 1 ) ∀i ∈ {1, ..., N }. Then, we proceed forward from k = 1 to k = K using the update step and the analysis step as described below. In the update step, at each time t k , we randomly generate N samples of η i and ǫ i ∀i ∈ {1, ..., N } with respective covariances Q and R. Then, following Eq. ( 1), the i-member of the updated state is given by

x f i (t k ) = M (x a i (t k-1 )) + η i (t k ), (3)
and the mapping from the forecast state space to the observational space of the i-member is computed as

y f i (t k ) = H k x f i (t k ) . ( 4
)
The N members of the ensemble are used to estimate the sample means of the propagated state in the state space and in the observational space denoted by x f (t k ) and y f (t k ) respectively. In the analysis step, we follow [START_REF] Pham | Stochastic methods for sequential data assimilation in strongly nonlinear systems[END_REF] methodology which avoids the linearization of the observational operator. The Kalman gain is computed from

K(t k ) = P f xy (t k ) P f yy (t k ) + R -1 , (5)
where P f xy (t k ) is the sample cross-covariance matrix and P f yy (t k ) is the sample covariance matrix, which are determined by

P f xy (t k ) = 1 N -1 × N i=1 x f i (t k ) -x f (t k ) y f i (t k ) -y f (t k ) ⊤ (6)
and

P f yy (t k ) = 1 N -1 × N i=1 y f i (t k ) -y f (t k ) y f i (t k ) -y f (t k ) ⊤ . (7)
Having K(t k ) from Eq. ( 5), the N members of the ensemble are then updated by

x a i (t k ) = x f i (t k ) + K(t k )d i (t k ) (8)
where d i (t k ) ∀i ∈ {1, ..., N } are the N innovation vectors in which we use perturbed observations such as

d i (t k ) = y(t k ) + ǫ i (t k ) -y f i (t k ).
Finally, the updated analyzed state is represented by the sample mean x a (t k ) and the sample covariance P a (t k ).

D. Ensemble Kalman smoother

The backward recursions correspond to the sequential EnKS algorithm proposed by [START_REF] Evensen | An ensemble Kalman smoother for nonlinear dynamics[END_REF]. It uses the results of the EnKF computed above. In the initial step of the EnKS algorithm, at time t K , we use the members of the filtered state, ∀i ∈ {1, ..., N }, such as x s i (t K ) = x a i (t K ) and P s (t K ) = P a (t K ). Then, we proceed backward from k = K -1 to k = 1 using the analysis step and we compute

x s i (t k ) = x a i (t k ) + K s (t k ) x s i (t k+1 ) -x f i (t k+1 ) (9)
where K s (t k ) is the Kalman smoother gain matrix given by

P a xx (t k ) P f (t k+1 ) -1 with P a xx (t k ) = 1 N -1 × N i=1 (x a i (t k ) -x a (t k )) (M (x a i (t k )) -M (x a (t k ))) ⊤ . (10)
The Gaussian distribution of the updated state estimate is given by the sample mean and covariance respectively denoted by x s (t k ) and P s (t k ).

III. RESULTS

Here we apply the state space model given in ( 1)-( 2) to assimilate the SAR observations using the EnKF/EnKS with N = 1000 members. The time-lag between two analysis is 3 h and the analysis grid is 3 • × 3 • . The results of the estimated integral parameters of the swell for the middle time of the assimilation window are given in Fig. 2. It corresponds to the results of the EnKS, i.e. the x s vector and the standard deviation of the diagonal elements of the P s matrix. In the areas with low standard deviation (East part of the analysis), the results are consistent with the outputs of the WaveWatch 3 model and the fireworks analysis (not shown in this paper). In a future work, we plan to compare precisely these different analysis with buoy data from the National Oceanographic Data Center (NODC).

IV. CONCLUSION AND PERSPECTIVES

In this work, we assumed a stochastic swell field process characterized by integral parameters (significant height, wavelength, direction) sparsely observed by SAR measurements. Compared to the fireworks analysis which generates pseudoobservations using backward and then forward propagations, our methodology only assimilate SAR data once without reprocessing them. Then, our sequential model uses the memoryless Markovian property and each pixel of the grid analysis is seen as a potential storm source where we generate random perturbations of the integral parameters. The results show a good consistency with the fireworks analysis and the wave model outputs. Although the physic used in our model is simple, it avoids the use of a complete wave model which can be critical in a data assimilation scheme with a large number of members.

The perspectives for future works will consist of using another interesting property of the state space model proposed here: the ability to assimilate easily other data sources. For instance, we plan to combine SAR measurements, buoy data from NODC, altimeters and seismographs as proposed in [START_REF] Husson | Revealing forerunners on Envisatâs wave mode ASAR using the Global Seismic Network[END_REF]. These data sources can observe totally or partially the integral parameters (for instance, only H s for altimeters) with different error measurements and space-time sampling.

Fig. 1 .

 1 Fig. 1. SAR along track observations from the 13 July (blue) to the 18 July 2004 (red). The swell data are generated by a storm located in 55 • S, 170 • E (gray dot) into the Southern Pacific Ocean. The data are corresponding to swell partitions with periods close to 17 s.

Fig. 2 .

 2 Fig.2. Estimated mean (first column) and standard deviation (second column) of the significant height (first row), wavelength (second row) and direction with the corresponding streamlines (third row) the 15 th of July, 2004 at 1200 UTC.

ACKNOWLEDGMENTS

We would like to thank the GlobWave project for providing SAR data. This study was supported by the Institut Mines-Telecom and the Marine Collaborative Ground Segment (MCGS) project.


Robyn Johnston

Jan Cools Bc

Stefan Liersch

Sylvie Morardet

Clement Murgue Ef

Marie Mahieu Acf

Istvan Zsuffa

G P Uyttendaele

WETwin: a structured approach to evaluating wetland management options in data-poor contexts

Keywords: wetland management, ecosystem services, vulnerability, multi-criteria analysis, stakeholder participation Highlights

This special issue of Environmental Science and Policy presents the outcomes of the WETwin project (Enhancing the role of wetlands in integrated water resources management for twinned river basins in EU, Africa and South-America in support of EU Water Initiatives), an international research project funded by the FP7 programme of the European Commission. The project aimed to improve wetland management by maximizing benefits from wetland use while maintaining ecological health, using case studies from Europe, Africa and South America.

In much of the less developed world, data on wetland functions, processes and values are scarce even while wetlands often provide a critical component of livelihoods. Management decisions on balancing competing demands for wetland use must often be made in the absence of comprehensive information. This paper introduces the approach developed and tested under WETwin to evaluate wetland management structures and solutions in data-poor contexts, summarizing a conceptual framework which has evolved from seven very diverse case studies. A structured, modular approach was devised which combined multi-criteria analysis, trade-off analysis and vulnerability analysis, drawing on best available information, including quantitative modelling, qualitative "expert opinion", and local stakeholders' knowledge and values. The approach used in WETwin has three important strengths: it involves stakeholders at all stages of the decision process, it combines qualitative and quantitative data (and therefore allows inclusion of poorly known and potentially important system components) and finally, it provides a relatively simple and structured approach to evaluate wetland management interventions and integrate impact, feasibility and institutional assessments, vulnerability analysis and trade-off analysis. The overall conceptual framework developed for WETwin was found to be robust and transferable to different contexts.

Introduction

This special issue of the journal Environmental Science and Policy presents the outcomes of the WETwin project (Enhancing the role of wetlands in integrated water resources management for twinned river basins in EU, Africa and South-America in support of EU Water Initiatives), an international research project funded by the FP7 program of the European Commission from 2008 to 2011. The overall objective of WETwin was to enhance the role of wetlands in basin-scale integrated water resources management, with the aim of improving the community service functions while conserving good ecological status. The project consortium consisted of research, educational and governmental institutions from Africa, South-America and Europe, and the project drew on case studies from the three continents, supporting the global exchange of expertise on wetland management.

This paper introduces the overall approach developed under WETwin to evaluate wetland management structures and solutions in data-poor contexts. It is primarily a theoretical discussion, summarizing a conceptual framework which has evolved from seven very diverse case studies. A structured, modular approach was devised which combined multi-criteria analysis (MCA), trade-off analysis (TOA) and vulnerability analysis (VA), drawing on best available information, including quantitative modelling, qualitative "expert opinion", and local stakeholders' knowledge and values.

Details of implementation of the approach in the case studies are presented in other papers in this volume. Depending on the concerns and skills of the stakeholders involved, individual case studies focused on specific components of the framework, and this is reflected in the diversity of the papers in this volume. [START_REF] Arias-Hidalgo | A multi-criteria analysis for wetland management in a river basin context: the "Abras de Mantequilla" case study in the Guayas River Basin, Ecuador[END_REF] describe application of MCA to prioritise management measures for the Abras de Mantequilla wetland in Ecuador. [START_REF] Liersch | Vulnerability of food production in the Inner Niger Delta to water resources management under climate variability and change[END_REF] and [START_REF] Pataki | Vulnerability assessment for supporting the revitalisation of river floodplains[END_REF] focus on vulnerability assessment in the Inner Niger Delta (IND) and Gemenc wetlands respectively, while Cools et al. 2012a extend the concepts of VA to analyse adaptive capacity in the IND, specifically in the context of human health. [START_REF] Namaalwa | A characterization of the drivers, pressures, ecosystem functions and services of Namatala wetland, Uganda[END_REF] illustrate the process of characterizing the ecosystem services provided by the Namatala wetland in Uganda, and the current trends in land use and management that jeopardise those services. Other papers report on technical studies which underpin management approaches -for example, ecological niche models [START_REF] Funk | Ecological niche models for the evaluation of management options in an urban floodplain ─ conservation vs. restoration purposes[END_REF]) and floodplain restoration options [START_REF] Baart | Supporting analysis of floodplain restoration options by historical analysis[END_REF] for the Lobau wetlands in Austria; and a study of the impact of water quality on aquatic biota in Abras de Mantequilla [START_REF] Alvarez-Mieles | Relationship between aquatic biotic communities and water quality conditions in a tropical river wetland system[END_REF]. Two papers contrast experiences from the developed and developing worlds relating to integrating wetlands into broader catchment management [START_REF] Rebelo | Integrating wetlands into IWRM: the case of the Inner Niger Delta (Mali) and the Lobau Floodplain[END_REF], and the impact of institutional capacity on wetland management in different contexts in Africa and Europe [START_REF] Ostrovskaya | Capacity for sustainable management of wetlands: Lessons from the WETwin project[END_REF]. Finally the outcomes and conclusions of the project, drawing from all the case studies, are synthesised in a closing paper [START_REF] Cools | Tools for wetland management: lessons learnt from a comparative assessment[END_REF]).

Project context and objectives

Wetlands are amongst the world's most threatened ecosystems [START_REF] Ma | Ecosystems and Human Well-Being: a Framework for Assessment[END_REF]. The reasons behind this are complex, related not only to land and water use within the wetland, but also to management of upstream catchments, external pressures such as climate change and population growth, and institutional factors affecting management such as unclear or overlapping spheres of authorities and lack of effective power to enforce laws and regulations [START_REF] Finlayson | Ecosystem Services and Human Well-being: Wetlands and Water Synthesis[END_REF]IPCC 2007). The multiple benefits provided by wetlands often mean that there are competing priorities for wetland use [START_REF] Verhoeven | Agricultural use of wetlands: opportunities and limitations[END_REF][START_REF] Mccartney | Wetlands, agriculture and poverty reduction[END_REF]. Management must thus balance the competing needs of different uses and users, as well as the threat of degradation from external pressures.

In much of the developing world, data on functions, processes and values of particular wetlands are scarce and management decisions on balancing competing demands for wetland use must often be made in the absence of comprehensive information. Thus WETwin aimed specifically to establish methods that could be applied in data-poor contexts, by combining best available local information and knowledge with understanding of wetland processes garnered from international experience. The project drew on case studies from wetlands in Africa, South America and Europe. The location of these wetlands is shown in Figure 1, and their characteristics are summarised in Table 1. The focus of the WETwin project is on inland wetlands that are closely linked to the river basin, and where there are potential or actual conflicts and trade-offs between different ecosystem services. Sites were selected to reflect the diversity of inland wetlands and a range of management challenges and issues.

Figure 1: location of WETwin case study wetlands

WETwin Conceptual Framework

WETwin starts from four basic premises of wetland management: wise use; adaptive management; integrated water resource management (IWRM); and participation of local communities and stakeholders. "Wise use" (Ramsar Convention Secretariat, 2007) encapsulates the understanding that wetlands provide a wide range of ecosystem services and are an important component of livelihood systems. As such, the aim is to manage for a range of functions, but to do this in ways that protect and enhance ecological status. Adaptive management recognises management as an ongoing cyclical process, not an end point; the critical components of such an approach for wetlands have been described by [START_REF] Dickens | Guidelines for integrating the protection, conservation and management of wetlands into catchment management planning[END_REF] in the "Critical Path" approach, adopted by Ramsar as a standard for wetland management (Ramsar Convention Secretariat 2007). Integrated water resource management acknowledges that wetlands function within a hydrological context, where the management of the catchment impacts on the health of the wetland; and the wetland contributes to the overall functioning of the catchment (CIS, 2003;UNESCO, 2009). Participatory planning and management recognise that local communities and stakeholders are ultimately both the actors and the beneficiaries of management, and must be involved at all stages (UN, 1994).

The Conceptual Framework for wetland management developed in the WETwin project nests adaptive management of the wetland within the adaptive management cycle of the river basin, with on-going feedback between the two (Figure 2). An actual merge or transfer of responsibilities is not envisaged, since wetlands remain to have their own dynamics, need to be managed at a different scale and have different challenges from river basins.

Figure 2: The conceptual framework developed by the WETwin project for adaptive and integrated wetland and river basin management

The focus of the WETwin project was to contribute to building management plans for each case study wetland, by working with stakeholders to identify and evaluate potential management responses. Implementation and monitoring of plans are the responsibility of local authorities and stakeholders, and were not part of this project. The scope of the project was thus restricted to the preparatory and planning stages of the Critical Path adaptive management cycle, as indicated in Figure 2. This sub-system has been developed into a Decision Support Framework (DSF), drawing on concepts from [START_REF] Gamboa | Social multi-criteria evaluation of different development scenarios of the Aysén region, Chile[END_REF] and Paneque [START_REF] Salgado | Participative multi-criteria analysis for the evaluation of water governance alternatives.A case in the Costa del Sol (Málaga)[END_REF]. Figure 3 gives an overview of the main steps of the DSF, which are further detailed in sections 4 and 5 below.

Evaluation of different potential management paths for the case study wetlands is a complex, inherently multi-dimensional problem, needing to take into account the multiple functions and values of the wetland, multiple stakeholders with varying perspectives, feedback between the wetland and the catchment, and vulnerability to external drivers of change. In assessing management responses in WETwin, five key questions were considered:

1. Does it work? (impact assessment) 2. Is it technically feasible and cost effective? (feasibility assessment) 3. Will it work in the future if external conditions change? (vulnerability) 4. Who wins and who loses? Are there trade-offs or synergies between different sectors or stakeholders? (trade-off analysis) 5. Does it have local support? (stakeholder acceptance).

The DSF is structured around using multi-criteria analysis (MCA) as a primary evaluation tool to support assessment of impact, feasibility, vulnerability and trade-offs. The approach is based on a combination of participatory methods, observations and modelling tools. A requirement of the project was to provide methods to combine data from different sources and of different degrees of accuracy, suitable for use in contexts where hard data are often not available. Methods were developed using comparative scoring, based on both quantitative and qualitative information. Stakeholder acceptance was assessed directly through consultation and participatory approaches to planning.

Definitions of basic terms, as used in the WETwin project and throughout this special issue, are given in Appendix (included as supplementary material).

Constructing the decision space

Characterisation of the wetland system and problem definition

The initial stage of each case study involved a review of current understanding of the wetland and its context, to define the components of the decision space. The initial assessment covered the biophysical, socio-economic, institutional and governance context. Information on the wetland and basin was collated using the structure of the Ramsar Information Sheets (Ramsar, 2010). Information was collected by case study teams based on literature review, reports of previous projects and consultation with stakeholders. The problems and issues to be dealt with in each wetland case study were characterised through analysis of Drivers -State -Impacts -Responses (DSIR), using a simplified version of the DPSIR approach developed by the European Environmental Agency (EEA, 2005). An assessment was also undertaken of the management structures and institutions and the related legal framework for both wetlands and river basins for each case study site. Based on concepts outlined in TEEB (2010), a summary "report card" of wetland status and sensitivity to future changes was produced for each wetland. Rapid assessment methods were used to summarise and structure existing knowledge on wetland health and ecosystem services, and the institutional context for management in each river basin (Figure 4; see Section 4.6).

Figure 4: example results from qualitative assessments of ecosystem services of Ga-Mampa wetland [START_REF] Murgue | Participatory analysis of tradeoffs between wetland ecosystem services in the Ga-Mampa valley, Limpopo Province, South Africa. Lessons for resources management aiming at wetland sustainability[END_REF] and institutional context of Olifants River Basin [START_REF] Pahl-Wostl | From applying panaceas to mastering complexity: toward adaptive governance in river basins[END_REF]

Stakeholder engagement

Stakeholder involvement plays a fundamental role in the WETwin decision process. The WETwin Decision Support Framework explicitly acknowledges that decision processes are subjective, driven by the needs and interests of particular groups. Local knowledge is a valuable resource, particularly in contexts where data is otherwise lacking. Knowledge, opinions and preferences of stakeholders are incorporated into the evaluation at several stages. Management solutions are evaluated in two parallel pathways: expert evaluation carried out by independent scientists which aims to be as objective as possible; and evaluation by interested stakeholders, which is explicitly subjective.

An analysis was carried out to identify relevant stakeholders for each case study, and a strategy for stakeholder engagement was formulated. Stakeholders were involved through consultation in workshops, small groups and individual discussions. Innovative methods for consultation were explored -for example, the use of role-playing games to structure discussions in Ga-Mampa [START_REF] Morardet | Wet-WAG, a role-playing game to support stakeholder dialogue on wetlands management[END_REF] and the Inner Niger Delta. Input from stakeholders was used in five main ways: to reveal stakeholder perceptions of the system; to elucidate the preferences underlying decisions (used to establish criteria categories and weightings in MCA); to assist in the qualitative scoring of indicators; to identify and refine management solutions for further assessment; and to identify preferred management solutions directly, for comparison with results from expert evaluation. The details of the stakeholder engagement process necessarily differed in each case study, in response to different stakeholders and conditions; for example, the process for the Abras de Mantequila wetland is described in [START_REF] Arias-Hidalgo | A multi-criteria analysis for wetland management in a river basin context: the "Abras de Mantequilla" case study in the Guayas River Basin, Ecuador[END_REF]; and the process for Ga-Mampa in [START_REF] Murgue | Participatory analysis of tradeoffs between wetland ecosystem services in the Ga-Mampa valley, Limpopo Province, South Africa. Lessons for resources management aiming at wetland sustainability[END_REF].

Scenarios

Wetland management does not operate in isolation, but must work within the physical and economic realities of the catchment and broader societal context. An important component of the initial analysis was to define the management domain for each case study site: which drivers are within the scope of management and which are external (that is, whose effects must be dealt with but cannot be influenced directly e.g. population growth, climate change). The distinction between external and internal (manageable) drivers is not always clear-cut, but depends on the scale at which management occurs. For example, operation of a dam upstream of a wetland is within the management sphere of a catchment management agency; but is an imposed external condition for a wetland community. In WETwin, impacts of external drivers are explored using scenarios, postulated sets of conditions that describe possible futures.

The aim of scenario analysis in WETwin is twofold: firstly, to illustrate the potential range of future conditions under which wetland management may operate, and the way external factors influence what will or won't work; and secondly to find management responses that are robust under a range of external conditions. Different scenarios define different decision spaces: economic growth may open up new development possibilities; or a shift in climate may change ecological values. Although these forces may be beyond local control, managers must take account of the shifts entailed. Conditions under different scenarios are compared to baseline conditions (formulated to represent current conditions). "Business as usual" (BAU) scenarios (with external changes, but no change in management) are used to distinguish the effects of external (scenario) change from management impacts.

At the global scale, [START_REF] Liersch | Report on Initial Vulnerability Assessment for Each Case Study[END_REF] identified population growth, climate change and different trajectories of economic development as the main drivers of changes affecting wetland management; and delineated three representative global scenarios which define boundary conditions for regional and local change. Within these bounds, local, site-specific scenarios were developed for each case study, to represent a range of different long-term outcomes (to 2050). Scenario simulations explored the impacts on wetland ecosystem functions using models and expertise available within the case studies. For example, potential impacts of climate change and changes in upstream water management on the Inner Niger Delta were assessed using an ecohydrological model (see [START_REF] Liersch | Vulnerability of food production in the Inner Niger Delta to water resources management under climate variability and change[END_REF].

Management options and solutions

The Millennium Ecosystem Assessment [START_REF] Ma | Ecosystems and Human Well-Being: a Framework for Assessment[END_REF] defined management responses as actions, policies, strategies and interventions undertaken by different actors, from governments to communities. Responses can operate from local to international scales, depending on the driver or issue being addressed. As well as technological and infrastructural measures, management responses can range from legal and economic measures (such as land use regulations and payment for environmental services) to social and cognitive responses aiming to change behavior (such as public education and awareness campaigns) [START_REF] Chambers | Typology of responses. Chapter 2 in MA (Millennium Ecosystem Assessment)[END_REF]. A distinction is drawn here between management options (addressing a single issue or component) and management solutions (packages of options ready to be developed into management plans); the term "management responses" encompasses both.

In each case study, potential management options to address specific wetland issues were identified in consultation with stakeholders, drawing on international experience (Table 2 illustrates the variety of management options available). In most cases, a mix of technological and local regulatory responses (mainly land use zoning and restriction of agrochemicals) was proposed. Working at the community level, economic and legal mechanisms were not favoured, or were perceived as beyond the capacity or responsibility of local groups.

Table 2: Possible management responses identified in the case studies, grouped by management domain and type of intervention Because of the multiple values of wetlands, management usually addresses more than one component or ecosystem value. Management solutions designed to provide desired outcomes for the wetland system as a whole were constructed by combining management options addressing specific components. Options can be combined as complementary (addressing different elements of the system); enabling (interventions designed to support or enhance another intervention -for example, land tenure changes to support land use change); or mitigating (designed to offset or compensate for adverse impacts of another intervention). Many of the responses identified are "no regrets" measures, where impacts are positive or neutral across all criteria: for example, improvements in wastewater treatment and agricultural practices.

Formulation of management solutions from a long list of potential options requires a pragmatic approach to selecting feasible combinations and narrowing down to a practical number for evaluation, based on stakeholder preferences and practical considerations for implementation. The diversity of the WETwin case studies required somewhat different approaches in each case study. For example, in Nabajjuzi, a preliminary, qualitative assessment was run for proposed management options addressing specific system components, and the favoured options for each component were combined. In Abras de Mantequilla, a progressively more comprehensive set of land management options was proposed for evaluation (see [START_REF] Arias-Hidalgo | A multi-criteria analysis for wetland management in a river basin context: the "Abras de Mantequilla" case study in the Guayas River Basin, Ecuador[END_REF]. In Ga-Mampa, management solutions were formulated separately by the research team and stakeholders to address different equilibrai between the priorities ofeconomic development, environmental conservation and, social equity, as well as an integrated approach seeking a balance between them. [START_REF] Murgue | Participatory analysis of tradeoffs between wetland ecosystem services in the Ga-Mampa valley, Limpopo Province, South Africa. Lessons for resources management aiming at wetland sustainability[END_REF].

Criteria and indicators

Management solutions were evaluated and compared against criteria chosen to reflect the values and interests of all stakeholders, in three key domains:  Ecosystem services (including livelihood support, agricultural production, water supply, sanitation);

 Ecosystem health and integrity (including hydrology, geomorphology, vegetation, biodiversity);

 Factors influencing feasibility of implementation, including technical difficulty, cost, policy, organizational and institutional factors.

Where possible, quantitative indicators were identified for each criterion, but measurable indicators could not be identified for all important criteria. Setting the criterion aside would skew the analysis by ignoring important values, simply because they could not be quantified. To avoid this, qualitative indicators scored by combining available information and expert judgement were used where other options were not available.

The number and type of indicators used in each case study varied, reflecting the different issues and priorities, and the availability of data. Table 3 lists the groups of criteria with the number of indicators used within each group assessed qualitatively using expert opinion or quantitatively using models or measurement. In the Lobau, where a long-term data collection program exists and a large research project has been executed, all indicators are numerical (see [START_REF] Funk | Ecological niche models for the evaluation of management options in an urban floodplain ─ conservation vs. restoration purposes[END_REF][START_REF] Baart | Supporting analysis of floodplain restoration options by historical analysis[END_REF]. However, in developing countries this is not the case. In Ga-Mampa and the Inner Niger Delta, where previous research programs have run, modeled data were available, but only for about half of the indicators (see for example Morardet et al. 2010;[START_REF] Liersch | Vulnerability of food production in the Inner Niger Delta to water resources management under climate variability and change[END_REF]. For the Abras de Mantequilla, although little research was available before the start of the project, a multidisciplinary team of researchers was able to quantify up to 40% of the indicators, during the run time of the project [START_REF] Arias-Hidalgo | A multi-criteria analysis for wetland management in a river basin context: the "Abras de Mantequilla" case study in the Guayas River Basin, Ecuador[END_REF][START_REF] Alvarez-Mieles | Relationship between aquatic biotic communities and water quality conditions in a tropical river wetland system[END_REF]. In Uganda, focus was on labourintensive field data collection by means of sampling and lab analysis, and only 10-20% of the indicators could be quantified [START_REF] Namaalwa | A characterization of the drivers, pressures, ecosystem functions and services of Namatala wetland, Uganda[END_REF]. In case of the Gemenc, 7 model-based hydroecological indicators for vulnerability analysis [START_REF] Pataki | Vulnerability assessment for supporting the revitalisation of river floodplains[END_REF], and 4 qualitative indicators for institutional analysis [START_REF] Ostrovskaya | Capacity for sustainable management of wetlands: Lessons from the WETwin project[END_REF] were applied.

Scoring and value functions

To construct the evaluation matrices for MCA, each management solution is scored in terms of its impact on each indicator; then, to compare disparate criteria, indicator scores are normalised to a common unit and range. Scoring can be qualitative or quantitative.

Qualitative scoring is used in WETwin in three different contexts. The first is where the indicator / criterion of interest is inherently qualitative -for example, indicators relating to institutional capacity. The second is in cases where insufficient data were available to measure or score an indicator quantitatively. The third case is where the criteria is a complex variable integrating several components, for example the Wet-Health scores [START_REF] Macfarlane | WET-Health: A technique for rapidly assessing wetland health[END_REF]. In general, qualitative assessment and scoring is a subjective process based on expert judgement. For example, in the Abras de Mantequilla case study stakeholders were asked to allocate scores for impact of management changes on qualitative indicators, using the commonly applied Lickert scale with a seven point range from strongly positive (3) to strongly negative (-3), with zero representing no change (see [START_REF] Arias-Hidalgo | A multi-criteria analysis for wetland management in a river basin context: the "Abras de Mantequilla" case study in the Guayas River Basin, Ecuador[END_REF].

It is possible to establish more structured, repeatable and transparent approaches using scoring rubrics which describe in detail the logic behind allocating particular scores. In South Africa, such tools have been developed using semi-quantitative methods for assessing wetland health (WET-Health - [START_REF] Macfarlane | WET-Health: A technique for rapidly assessing wetland health[END_REF] and ecosystem services provision (WET-EcoServices - [START_REF] Kotze | WET-EcoServices: A technique for rapidly assessing ecosystem services supplied by wetlands[END_REF]. These tools allow different levels of assessment, based on the degree of available information, from simple desktop analysis to rigorous field-based assessments. They are structured using checklists with detailed descriptions of the features to be scored and the rationale for assigning scores. Simplified versions of these tools were adopted for use in WETwin case studies to provide a structured approach to assessing ecological status and likely changes under different management regimes. For the assessment of institutional capacity, a similar questionnaire based method has been developed under the European-funded FP7 project Twin2Go [START_REF] Pahl-Wostl | From applying panaceas to mastering complexity: toward adaptive governance in river basins[END_REF] and applied to the WETwin river basins.

A range of quantitative biophysical and socio-economic modelling approaches was used, where sufficient data were available to construct and calibrate them. Hydrological models of different complexity were used to describe flows and in some cases water quality. For example, in Abras de Mantequilla, an embedded modelling framework comprising HEC-HMS rainfall-runoff model (USACE, 2010a), HECRAS hydrodynamic model (USACE, 2010b) and WEAP water allocation model (Stockholm Environment Institute, 2010) were used to simulate changes in delivery of water to the wetland under different conditions. In Ga-Mampa, a dynamic simulation model (WETSYS) combining biophysical and socio-economic components was developed using the STELLA® platform [START_REF] Costanza | Editorial: Introduction to Special Issue Ecological Modelling on modelling ecological and economic systems with STELLA[END_REF] to simulate the impacts of wetland management strategies and external pressures on wetland ecosystem functioning, ecosystem services and ultimately on community well-being in Ga-Mampa area (Morardet et al.,2010). Surface flows were modelled within WETSYS, and groundwater interactions with the river and wetland simulated using a monthly water balance [START_REF] Kogelbauer | Groundwater study of a subtropical small-scale wetland ( Ga-Mampa wetland , Mohlapetsi River catchment , Olifants River basin , South Africa )[END_REF].

For the Inner Niger Delta, the SWIM model [START_REF] Krysanova | Development of the ecohydrological model SWIM for regional impact studies and vulnerability assessment[END_REF] has been applied for hydrological studies, with an additional module developed to simulate reservoir operation [START_REF] Koch | Integrating water resources management in ecohydrological modelling[END_REF]. In case of the Gemenc, a quasi-two-dimensional hydrodynamic model [START_REF] Zsuffa | Multi-criteria decision support for the revitalisation of river floodplains[END_REF] was used for simulating the water regime of the floodplain water bodies.

In order to compare disparate criteria in MCA, indicator scores must be translated to a common unit and range. Normalization enables comparison and combination of raw evaluation results (indicator values), which are otherwise non-commensurable. The role of the value function is to capture the target state, and so to give a normative direction in relation to the planned management solutions [START_REF] Boulanger | Sustainable development indicators: a scientific challenge, a democratic issue[END_REF]. Value functions were used to normalise scores to a range from 0 (representing the worst outcome) to 1 (best outcome). Value functions can be defined for quantitative and qualitative indicators; the shape of the function can be varied to describe different relationships between the indicator and the criteria score, including thresholds. It is important to note that value functions inherently imply subjectivity (since the concept of worst and best varies between stakeholders), and so it is possible for different stakeholders to define different value functions for the same criterion. Depending on the case studies, two approaches to value functions were used: defined by scientists on the basis of scientific knowledge; or defined according to stakeholders' preferences towards the target state.

Evaluation and analysis

The WETwin evaluation process has three linked components: a comparative multi-criteria analysis (MCA) of the outcomes of different management responses in terms of both impacts and feasibility; an analysis of the trade-offs between wetland functions and between stakeholders; and an assessment of the vulnerability of the system to external pressures to determine whether proposed management options are robust in the context of imposed change. In each case, the underlying information for analysis was compiled in the form of evaluation matrices setting out comparative scores for key criteria for the system under different scenarios and management regimes (Figure 5). The evaluation matrices provide a consistent basis for all assessments.

Figure 5: Linked analysis of impacts/ feasibility, trade-offs and vulnerability, based on evaluation matrices

MCA and mDSS

Multi-criteria analysis (MCA) techniques offers a transparent, accountable and auditable procedure for decision makinginvolving multiple objectives [START_REF] Hajkowicz | A Review of Multiple Criteria Analysis for Water Resource Planning and Management[END_REF]. In the WETwin project, the MULINO Decision Support System (mDSS) was used to guide the MCA process. mDSS was developed under the EU Framework, to assist decision makers in managing environmental issues in catchment scale water resource management and is able to integrate hydrological, ecological or socio-economic models with multi-criteria analysis methods [START_REF] Giupponi | Decision Support Systems for implementing the European Water Framework Directive: The MULINO approach[END_REF]. mDSS uses the DPSIR framework as an underlying conceptual model. An analysis matrix is built by scoring options against designated criteria. The software provides a range of techniques for aggregating decision preferences, including Simple Additive Weighting (SAW), Ordered Weighted Averaging (OWA), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and an outranking technique (ELECTRE). Different case studies explored different MCA techniques, depending on data availability, although SAW was most commonly applied.

An important component of MCA as applied in WETwin is comparison of preferences of different stakeholders, expressed as weights for particular values (criteria). Stakeholder preferences were explored in workshops and meetings, both as negotiated group preference and as preferences for individuals. The ranking of management solutions was found to be sensitive to the weights applied and in many cases the total scores did not differ greatly. Rankings should be considered mainly as an input to discussions with stakeholders.

Trade-off analysis

Explicit trade-offs occur when an improvement in one ecosystem value or service is achieved at the expense of a decrease in another: for example, increase in agricultural production at the expense of natural wetland vegetation. Implicit trade-offs may occur between stakeholders where the objectives or values of stakeholders groups differ, where one group benefits at the expense of another or has to forgo benefits to protect the interests of another. Common approaches to addressing trade-offs include economic valuation, multi-criteria analysis (eg [START_REF] Brown | Trade-off analysis for marine protected area management[END_REF], and a range of modelling approaches, linking biophysical and socio-economic systems either heuristically or dynamically (eg Morardet et al., 2010).

In the WETwin analytical framework, trade-offs are explored at two stages: qualitatively, as part of the initial DSIR and stakeholder analysis; and quantitatively at the MCA phase using comparison of criteria scores to identify direct trade-offs, and analysis of preferences (expressed as weightings) to explore implicit trade-offs between stakeholders.

For all case studies, initial DSIR analysis identified high-level trade-offs in terms of land or water use: for example, conversion of wetlands for agriculture or urban use (e.g., Lobau, Ga-Mampa); or diversion of wetland flows for irrigation or hydropower (e.g., Inner Niger Delta, Abras de Mantequilla). Identification of trade-offs at an early stage in the process, and the structured approach to identifying and assessing management solutions collaboratively with stakeholders, resulted in two different responses. First, the stakeholder groups involved in some case studies considered the decisions determining major trade-offs to be outside their management sphere, and treated them as externally imposed scenarios. Efforts were then focused on identifying management options to adapt wetland use and conditions to these externally imposed conditions. Secondly, potential trade-offs were explicitly built into the choice of solutions at the design stage.

For example, in Ga-Mampa, packages of options (solutions) were specifically designed to address potentially competing management objectives for the wetland as "conservation oriented", "economic oriented", "socially oriented" and "integrated". Ranking was dominated by stakeholder preferences for a specific orientation rather than relative scoring, since each solution scored well in its particular domain. In Abras de Mantequilla, a management continuum was designed with progressive addition of options favouring environmental outcomes at the expense of agricultural production; the choice for stakeholders was thus about the degree, not the direction, of change. In working communally to identify acceptable management solutions, a large number of proposed responses were "no regret" options deliberately designed to benefit all stakeholders (such as improvements water quality and land management practices).

Within a MCA framework, concepts of Pareto optimality can be used to identify and quantify tradeoffs using pairwise comparison of criteria to find non-dominated solutions (that is, solutions where the score for one criterion cannot be increased except by decrease in another). [START_REF] Sanon | Trade-Off Analysis for Floodplain Restoration : -A Case Study of the Lobau Floodplain in Vienna , Austria. Evaluation[END_REF] applied this method to explore trade-offs for the Lobau wetland. In other case studies, where assessments were mainly qualitative (with only a few value levels), pairwise comparison of criteria was usually not sufficiently sensitive to determine non-dominance, but the approach was useful for visualising potential trade-offs and as a starting point for explaining MCA. Thus in most case studies, assessment of trade-offs was focused on direct analysis of the way that stakeholder preferences influenced rankings, and negotiation to find mutually acceptable solutions.

Vulnerability, resilience and adaptive capacity

Vulnerability and resilience have become important elements in discussions of global change, but are conceptualised differently in different studies: see, for example, reviews by [START_REF] Gbetibouo | Mapping South African Farming Sector Vulnerability to Climate Change and Variability[END_REF], [START_REF] Füssel | Climate Change Vulnerability Assessments: An Evolution of Conceptual Thinking[END_REF] and [START_REF] Turner | Framework for vulnerability analysis in sustainability science[END_REF]. Within WETwin, we are primarily concerned with the role of management in reducing vulnerability (or increasing resilience) of wetland systems to change; and with the degree to which management solutions remain viable in the face of change. For this reason, a framework for assessment of vulnerability was adopted that focuses on adaptive capacity relative to impacts of external change. In this framework, resilience is considered to be a characteristic of the state of the whole system (including the institutional, biophysical, infrastructural and behavioural aspects); while robustness relates to specific management options or solutions.

Vulnerability is usually described in terms of three components: exposure, sensitivity and adaptive capacity. The impact of external stress (external impact or EI) is a function of exposure to stressors and the sensitivity of the system to that stress. Adaptive capacity (AC) is the extent to which these impacts can be withstood or mitigated. The change in vulnerability (residual vulnerability or ΔV) of the system as it moves from its initial state to a new state can be described by the sum of (usually negative) external impacts and (usually positive) adaptive capacity, that is:

ΔV = EI +AC
Where the adaptive capacity of the system exceeds the external impacts (AC>EI, ΔV>0), the system is resilient; where external impacts exceed adaptive capacity (EI>AC, ΔV<0), the system is vulnerable. If the state of a system can be described using criteria or indicators representing key values (above), and scores can be allocated for these criteria under different conditions, then the vulnerability of the system to change can be described, at least in relative terms. Composite indicators to assess vulnerability are widely used, and have proved valuable for identifying trends and to capture the complexity of vulnerability in reasonably simple terms [START_REF] Gbetibouo | Mapping South African Farming Sector Vulnerability to Climate Change and Variability[END_REF]. Figure 6 depicts the WETwin framework for vulnerability assessment of future states. Application of this framework to the Inner Niger Delta and Gemenc case studies is detailed in [START_REF] Liersch | Vulnerability of food production in the Inner Niger Delta to water resources management under climate variability and change[END_REF] and [START_REF] Pataki | Vulnerability assessment for supporting the revitalisation of river floodplains[END_REF].

Discussion

The WETwin methodology was initially devised to handle a large number of both management solutions and evaluation criteria, to allow consideration of a wide range of management possibilities and to ensure that a wide range of values were taken into consideration in evaluating outcomes. However, experience in all case studies emphasized the need to simplify, and to focus on the most important options and criteria. This is driven partly by the need to present results to stakeholders in reasonably simple terms; and partly by the paucity and quality of available data for evaluation.

Through the process of working with stakeholders the number of management responses to be evaluated was narrowed down to a few (5-10), albeit as packages of multiple options grouped into management solutions. Only in the Lobau case study was a large number (31) of solutions assessed; and this was possible primarily because there was sufficient sensitivity in scoring different options, as a result of strong biophysical models (validated with extensive monitoring and field data), that could simulate changes in conditions under different management regimes. In the other case studies, the lack of sensitivity in scoring meant that distinctions could only be made at relatively high level. The results from case studies emphasized that highly quantitative approaches to scoring and ranking are only justified when supported by quality data.

Similarly, for discussing and presenting the final rankings all case studies condensed indicators into a limited set of criteria classes (between 5 and 8). Although weighting and combining large indicator sets is mathematically straightforward, it can be problematic in terms of presenting and explaining results. Grouping indicators into criteria classes (e.g., ecological health; contribution to livelihoods) reduced the complexity, but may in some cases have obscured contradictory results within classes. However, a large number of criteria may also work to obscure the important issues. In theory, weighting criteria to reflect stakeholder priorities will draw out those that are significant. In practice, it was observed that when asked to weight a long list of criteria (for example, by distributing 100 pebbles amongst 23 criteria in 5 classes) stakeholders do not assign zero weight to any criterion; so that the number of indicators in a criteria class skews the importance of the class.

The evaluation matrix provides an important way to summarise and present information on management outcomes. The use of scoring has a number of advantages. It allows comparison between different types of variables and enables inclusion of a much wider range of criteria. In addition, scores normalised to give a ranking from "bad" (0) to "good" (1) are easily understood, and facilitate reporting of results to non-technical audiences. However, the inherent weaknesses of scoring approaches must be taken into account. There are inconsistencies in comparing well defined modeled parameters (where a shift in value of 0.1 is meaningful) with data scored on a three class scale of "poor -moderate -good" (where a shift in value of 0.1 is not significant). The WETwin methodology does not explicitly track uncertainty associated with different parameters, so that the overall uncertainty associated with rankings cannot be described. This is a shortcoming in the methodology which should be addressed.

The ranking of solutions using MCA was very sensitive to weightings, and ranking became more an exploration of the preferences of different stakeholders than a definitive way to "choose" solutions, concurring with the findings of [START_REF] Hajkowicz | A Review of Multiple Criteria Analysis for Water Resource Planning and Management[END_REF] that the strength of MCA is as tool to support discussion, rather than a primary decision making tool.

The MCA was conceptually structured to allow analysis of trade-offs between different criteria. However, major trade-offs identified in the initial DSIR assessments often either were, or were perceived to be, outside the management domain of the wetland managers. Trade-offs between different stakeholders within the wetlands were explicitly addressed as part of the management solutions. Stakeholders side-stepped conflicts and tradeoffs by seeking compromise within the proposed management solutions: that is, by seeking solutions that packaged measures responding to the concerns of all groups. The strong preference for "no regrets" measures reflects the fact that for all stakeholders, a healthy wetland delivers more benefits.

Vulnerability analysis required ability to score management responses under both current and future conditions. In most of the case studies, the information available to score future management regimes was not sufficiently sensitive to reflect differences between scenarios. Only in the Inner Niger Delta, where there is potentially a very large change in the water regime due to upstream development, and in the Gemenc, where morphological changes are progressively degrading the state of the system, were scenarios considered in any detail. In other case studies, visioning of future scenarios was important in helping stakeholders to identify potential issues and trends, but quantitative analysis of vulnerability was not possible.

Conclusions

The challenge faced in the WETwin project was to find a robust methodology to assist wetland communities in a range of contexts to identify and assess management solutions. The starting point for the project was the understanding that the multiple uses and users of wetland are likely to engender different perspectives about what constitutes "best" management; that competing objectives mean that a wide range of assessment criteria are needed to adequately capture those perspectives; and that trade-offs and compromise are integral to wetland management. Building from current international best practice, a structured approach was devised which combined multi criteria analysis, trade-off analysis and vulnerability analysis and involved stakeholders at all stages.

The methodological framework was applied in case studies in Africa, South America and Europe.

The approach used in WETwin has three important strengths. First, it involves stakeholders at all stages of the decision process, and explicitly acknowledges and incorporates different perspectives so that local concerns are reflected in both the choice of options for evaluation and the final rankings. Secondly, it combines qualitative and quantitative data, so that assessments can be based on all important criteria, whether quantifiable or not. This allows inclusion of information relating to system components that are poorly known (but potentially important), not just components which can be measured with high confidence. Thirdly, it provides a relatively simple, structured approach to the complex problem of evaluating diverse wetland management interventions and a conceptually coherent framework to integrate impact and feasibility assessment, vulnerability analysis and trade-off analysis, based on evaluation matrices.

While the overall conceptual framework developed for WETwin was found to be robust and transferable to different contexts, the realities of implementation varied significantly between case studies. Not all components were applicable in all case studies; and the practical aspects of implementation depended on context, and particularly on the stakeholders involved. Working with stakeholder groups was a challenging and essential component of the project, and their different interests and concerns shaped the way the framework was applied. Ultimately, the strength of the approach was not in the rankings resulting from the analysis, but in the participatory process of exploration, debate and negotiation used to derive them.

Figure 3 :

 3 Figure 3: WETwin decision support framework.

Figure 6 :

 6 Figure 6: WETwin framework for vulnerability assessment of future states.

Table 1 :

 1 description of WETwin case study wetlands and management issues

Table 3 :

 3 Number of indicators used in selected case studies to evaluate management responses, per criteria group and type of indicator (qualitative or quantitative)

Table 1 :

 1 description of WETwin case study wetlands and management issues

	Wetland	Ramsar	River basin/	Major issues
	(size)	site	country
			(climate zone)

Table 3 :

 3 Number of indicators used in selected case studies to evaluate management responses , listed by criteria group and type of indicator (qualitative or quantitative. ) Indicators scored qualitatively using expert judgment, are denoted by E; those scored quantitatively using models or measurements, are denoted by M.Author-produced version of the article published in Environmental Science & Policy, 2013, N°34, p.3-17. The original publication is available at http://www.sciencedirect.com/science/article/pii/S1462901112002341 Doi: 10.1016/j.envsci.2012.12.006

				Criteria group
	Wetland case study	Indicator type	Livelihood/ economic benefits	Ecological health	Feasibility	Total
	Ga-Mampa	E M	4 5	3 3	4 4	23
	Inner Niger Delta	E M	5 10	-6	8 -	29
	Abras de Mantequilla	E M	1 3	2 4	8 -	18
	Nabajjuzi	E M	9 3	3 1	8 -	24
	Namatala	E M	3 -	10 2	8 -	23
	Lobau	E M	-43	-34	--	77
	Gemenc	E M	--	-7	4 -	11

Author-produced version of the article published in Environmental Science & Policy, 2013, N°34, p.3-17. The original publication is available at http://www.sciencedirect.com/science/article/pii/S1462901112002341 Doi: 10.1016/j.envsci.2012.12.006

Acknowledgements

The authors of this special issue wish to acknowledge the European Commission for funding and supporting the implementation of the WETwin project. We also would like to thank Prof. Dr. Uri Shamir (Technion -Israel Institute of Technology) and Prof. Dr. Jos Verhoeven (Utrecht University) for acting as guest editors and for pre-reviewing the articles.

Author-produced version of the article published in Environmental Science & Policy, 2013, N°34, p.3-17. The original publication is available at http://www.sciencedirect.com/science/article/pii/S1462901112002341 Doi: 10.1016/j.envsci.2012.12.006