Room for Rivers: an Integrative Search Strategy for Floodplain Restoration

Landscape and Urban Planning 78 (2006) 50–70

Room for rivers: An integrative search strategy for ﬂoodplain restoration

S. Rohde a,∗, M. Hostmann b, A. Peter c, K.C. Ewald d

a Swiss Federal Institute for Forest, Snow and Landscape Research WSL/ETH, 8903 Birmensdorf, Switzerland b Swiss Federal Institute for Environmental Science and Technology EAWAG/ETH, 8600 D¨ubendorf, Switzerland c Swiss Federal Institute for Environmental Science and Technology EAWAG/ETH, 6047 Kastanienbaum, Switzerland d Nature and Landscape Protection, Swiss Federal Institute of Technology (ETH), 8092 Zurich, Switzerland

Received 25 March 2004; received in revised form 30 May 2005; accepted 30 May 2005 Available online 21 November 2005

Abstract

River restoration aims to re-establish the ecological integrity of a river ecosystem. However, restoration measures are nowadays mainly a reactive, site-by-site activity, driven by a single driver (e.g. fisheries, flood protection) rather than based on strategic planning. This study presents an integrated search strategy to identify stream systems where present environmental (e.g. natural flow, sufficient bed load material) and socio-economic (e.g. public attitude) template conditions favour the eco-morphological restoration of floodplains and their biocoenosis. This ‘pre-screening’ process reveals where the greatest benefits (judged according to ecological and socio-economic criteria) are to be expected and thus justify further specific and detailed investigations. It helps to set priorities and thus avoid inefficiency. The search strategy presented in this study is designed to perform a pre-screening process at national level. It is based particularly on spatially explicit information and is balanced between accuracy and costs. A hierarchical filter process combines the facilities of GIS with multiple criteria decision analysis (MCDA) to generate restoration suitability maps. The filter process is based on a list of criteria and indicators that capture the ecological key factors that drive floodplain restoration (hydrology, bed load, connectivity, biodiversity, water quality), as well as crucial socio-economic aspects (e.g. flood protection, public attitude) that need to be taken into account when planning for floodplain restoration. Inevitable limitations, arising from the transfer from theory into practice, are accepted, as the search strategy is dedicated to practical application. A modified Delphi process survey of nine river ecology experts was used to assess the appropriateness of each indicator and to estimate the single indicator suitability function. We used ModelBuilder 1.0a (an ArcView extension) to integrate different data layers into a single Ecological Restoration Suitability Index (ERSI) layer. The practical application of the integrative search strategy for floodplain restoration is illustrated through a case study from the Rhone-Thurˆ Project in Switzerland. © 2005 Elsevier B.V. All rights reserved.

Keywords: River restoration; Priority setting; Restoration suitability; Indicators; Multiple criteria decision analysis; GIS

∗ Corresponding author. Tel.: +41 1 739 23 69; fax: +41 1 739 22 15. E-mail address: [email protected] (S. Rohde).

1. Introduction Answering these questions is not easy. They are key questions that arise also in related planning processes, River floodplains are widely acknowledged as e.g. the location of landfills (Kontos et al., 2003), the biodiversity hotspots (Malanson, 1995; Naiman et al., evaluation of alignments of motorways (Sadek et al., 1993; Ward et al., 2002). However, river canalisations 1999) or the design of reserve networks (Villa et al., have led to major ecological degradation (Erskine, 2002). 1992; Nilsson and Svedmark, 2002; Pedroli et al., 2002; Petts and Calow, 1996). Since the negative impacts of river canalisation have become more and more 2. Aims and scope apparent, several river restoration projects have been realized, for example, in The Netherlands (Neilsen, The integrative search strategy presented in this 2002; Nienhuis et al., 2002) and Switzerland (Rohde et paper is a framework for pro-active planning that moves al., 2004), the UK and Denmark (Holmes and Nielsen, away from the traditional view of river restoration as 1998). a reactive, site-by-site activity towards a framework Ecological restoration is the process of assisting the where restoration occurs at a landscape and catch- recovery of an ecosystem that has been degraded, dam- ment scale and becomes an important, strategic com- aged or destroyed (SER and Policy Working Group, ponent of landscape and regional planning as required, 2002). At present, restoration sites are often selected e.g. by the Water Framework Directive of the Euro- opportunistically and on an ad hoc basis rather than pean Union (Naveh, 1994; Webb, 1997). It focuses according to a strategic planning process (Clarke et on the restoration of riparian floodplains by widening al., 2003; Hobbs and Norton, 1996; Lamy et al., rivers or re-allocating flood levees to allow river braid- 2002). In many cases, restoration projects are not ing or meandering, and thus the re-establishment of a based on higher-level planning but react on local deci- wide array of in-stream and riparian habitats (riffles, sions, e.g. flood defence work or road development pools, gravel bars, willow woodlands, etc.). There are (Holmes, 1998; VAW, 1993). Thus, due attention is other components of the river system which may need not always given to the underlying ecological pro- restoration (e.g. reduction of hydropeaking, increase of cesses that form rivers and their floodplains. Conse- minimal flow). However, due to socio-economic con- quently, many projects have not been self-sustaining straints (e.g. long-term licenses) we regard them as and have required continued management input, for unchangeable framework, in which eco-morphological example, mimicking geomorphic processes with exca- floodplain restoration will take place. vating works. Clarke et al. (2003) argue that river The GIS-based, integrative search strategy pre- restoration will only be sustainable if it is undertaken sented here is: (1) designed as pragmatic decision within a process-driven and strategic framework with support tool, to assist government agencies and man- inputs from a wide range of specialists. agement authorities in identifying those stream systems In present day catchments including multiple forms (we follow the definition proposed by Frissell et al. of land use, it should be noted that restoration possibil- (1986)) on national and catchment level where flood- ities are restricted and that all sectors of society need to plain restoration is less likely to be undermined by be included in planning and decision-making. Limited poor environmental conditions and where the greatest financial and spatial resources launch a debate about benefits (judged according to ecological and socio- the efficiency of restoration measures. Two key ques- economic criteria) are to be expected. The search strat- tions arise: egy is balanced between accuracy and costs to account for practical application. Using objective ecological • Where are the more promising river stretches which and socio-economic criteria enables stream systems are less likely to be undermined by poor environ- to be selected for floodplain restoration in a transpar- mental conditions? ent and reproducible way. The search strategy is also • Where shall we spend our money and space to fulfill thought to (2) provide a checklist of ecological and the various social demands and ecological require- socio-economic criteria and (3) indicators that need ments concerning rivers and their floodplains? to be considered in the planning process of flood- 52 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 plain restoration. The starting point of the proposed will be discussed in more detail in the following sec- search strategy is the ecological suitability of a river for tions. restoration. However, we are aware that, in many cases, ecological restoration is not necessarily the key driver 3.2. Filter 1: pre-selection based on limiting for floodplain restoration. Other drivers in day-to- constraints day restoration include ‘flood protection’ and ‘human recreation’. In the proposed search strategy, they are The first filter defines the minimum pre-requisites to included as socio-economic indicators. be met for eco-morphological floodplain restoration. It The search strategy is not designed to compare determines stream systems to be excluded from fur- different restoration sites within a single stream sys- ther consideration based on the attributes of selected tem. Once a promising stream system is identified, constraints. We considered the following two factors more detailed investigations are necessary to choose as constraints: a suitable location for restoration (site selection). Fur- thermore, different restoration alternatives should be (i) Slope >6%. A spatial analysis of the distribution of compared for the chosen restoration site (alternative floodplains in Switzerland showed that extended selection). It is beyond the scope of this study to address floodplains can only be found in areas with a the ‘site selection’ and ‘alternative selection’ project slope <6%, because steeper slopes naturally result phases. For a discussion of these phases and stake- in straight river courses, which are confined and holder involvement in the decision process, refer to entrenched (Rosgen, 1994). Hence, we regarded Hostmann et al. (2005, in press). The presented search a slope of 6% as a reasonable threshold for eco- strategy focuses on catchment-wide issues and pro- morphological floodplain restoration. vides information on a broad scale (pre-screening). It (ii) Location within built-up areas. As opportunities is based on spatially explicit information for the whole for floodplain restoration within settlements are catchment. Often, the spatial information for ecolog- limited, urban streams are not considered. How- ical and socio-economic indicators is available only ever, the needs of urban inhabitants, e.g. recreation, on a coarse resolution (resolution of 10 km and more). are taken into account in the assessment/selection Therefore, it is important to emphasize that the level of procedure (Filter 3). detail is only sufficient to signal the restoration suitability of different stream systems (with a stream length of 3.3. Filter 2: evaluation of ecological suitability >10 km) within a catchment. and Ecological Restoration Suitability Index (ERSI)

3. The integrative search strategy 3.3.1. Introduction In planning restoration, the processes which form 3.1. A hierarchical filter process the landscape and the wider context in which the project is placed need to be considered (Cals et al., 1998; The search strategy focuses on local eco- Osborne et al., 1993). Filter 2 is based on the idea morphological floodplain restoration by means of river that the environmental template and its modification by widening, man-made secondary channels or flood levee human influence drive the success of floodplain restora- re-allocation (Cals et al., 1998; Florsheim and Mount, tion (Malmquist, 2002; Poff, 1997). Thus, restoration 2002; Rohde et al., 2004; Simons et al., 2001). The suitability is determined by constraints and factors task of assessing restoration suitability is completed in which might restrict or favour restoration efforts. The a hierarchical filter process (Filters 1–3) where the cor- second filter evaluates ecological restoration suitability responding filters consist of several criteria. Its general on the basis of abiotic and biotic driving factors (eco- outline is shown in Fig. 1. The result of this search logical suitability factors) (Innis et al., 2000), as efforts strategy is the identification of stream systems suit- undertaken to restore floodplains (eco-morphological able for local eco-morphological restoration according restoration) should not be hampered by, for exam- to both ecological and socio-economic criteria, which ple, hydropeaking or poor connectivity. Thus, Filter 2 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 53

Fig. 1. Filter-based search strategy to identify river reaches highly suitable for floodplain restoration according to ecological and socio-economic indicators. considers ecological suitability for eco-morphological al., 2002; Poff et al., 1997). River discharge controls, restoration to increase with decreasing human modifi- for example, the formation of point bars, plant growth cation of all other factors. The relevant driving factors and species dispersal (Decamps,´ 1996; Nilsson and and corresponding indicators will be described in the Svedmark, 2002; Stanford et al., 1996). Thus, flow following section and are summarized in Table 1. characteristics are important parameters for the assessment of floodplain restoration suitability. However, direct measurements of the hydrological condition of 3.3.2. Hydrology each stream system typically require the analysis of Near-natural river flows are the key to restor- extended data sets and are thus not appropriate for pre- ing floodplains as the establishment and persistence selecting stream systems for restoration management of riparian habitats and species rely on a complex, on a broad scale. The following three indicators are dynamic hydrological regime with intra- and inter- used as surrogates to evaluate flow characteristics and annual flood variations in timing, duration, magnitude their human modification for restoration purposes: and shape of the hydrograph (Brookes and Shields, 1996; Calow and Petts, 1994; Hughes and Rood, 2003; (i) Water abstraction. Water abstraction for Naiman and Bilby, 1998; Newson, 1994; Pedroli et hydropower production has altered the hydro- 54 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70

Table 1 Ecological suitability factors (criteria) and corresponding indicators (incl. range) (Filter 2) Criteria Indicator Indicator range Hydrology Water abstraction (%) <20 <20 + increased winter flow 20–40 40–60 60–80 >80 Hydropeaking Peak flow: base flow <3(4):1 Peak flow: base flow >3(4):1 Dam No Yes Bed load River-bed erosion Transport capacity:bed load discharge < 4:3 Transport capacity:bed load discharge > 4:3 Water quality Chemistry Very good Good Moderate Bad Very bad Arable land (%) 0–2.33a 2.33–6.69 6.69–12.3 12.3–21.59 21.59–35.88 Connectivity Distance from present floodplains (km) 0–10 10–25 25–50 50–100 >100 Distance from gravel pits (km) <10 >10 Presence of artificial migration barriers (per km)b 0 1–3 >3 Biodiversity Percentage (%) of regional riparian species pool (flora) 0–10a 10–34 34–50 50–70 70–100 Percentage (%) of regional riparian species pool (fauna) 0–7a 7–19 19–32 33–49 49–74

a Classes according to present situation in Switzerland (relative, not absolute assessment). b Vertical height of the barriers: trout zones = 70 cm, all other ﬁsh zones = 25 cm. S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 55

regime of many rivers by changing flow volume, and Calow, 1996). Transient islands and sand/gravel cutting peak flows and changing seasonalities bars are characteristic features of floodplains. These (Stanford et al., 1996). The influence of a changed typical elements are formed by erosion, transport and flow regime on the state of a river is manifold deposition processes due to water and sediment fluxes, and includes reduced survival of aquatic species which are the dominant channel-forming mechanisms in shallow water, life cycle disruption, colmation (Clarke et al., 2003). Thus, eco-morphological restora- and disruption of the dynamic equilibrium tion suitability depends heavily on sufficient sediment between movement of water, sediments and supply. To assess restoration suitability from a geo- succession (Bowen et al., 2003; Bunn and morphologic point of view, the following indicator is Arthington, 2002; Decamps,´ 1996; Lagarrigue proposed: et al., 2002; Poff et al., 1997; Stanford et al., 1996). Thus, restoration suitability decreases (i) River-bed erosion. In many catchments, artifi- with increased water abstraction. The chosen cial bank stabilization, gravel extraction, bed load indicator range (rate of water abstraction) was traps and sediment retention basins have led to a adapted from Spreafico and Weingartern (2001). major lack of bed load material which hampers (ii) Hydropeaking. Hydropeaking limits restoration eco-morphological floodplain restoration and thus suitability because flow and temperature are mod- restoration suitability. In general a lack of sediment ified during power generation (Cereghino et al., is assumed if the ratio between the transport capac- 2002; Frutiger, 2004). This affects the hatch- ity of a river and the bed load discharge exceeds ing periods and growth rates of benthic species, 4:3 for a period longer than 10 years (Bezzola, seedling establishment along the shoreline and 2003; personal communication). If data on trans- puts aquatic species at risk due to wash-out and port capacity and bed load discharge is not avail- stranding (Cereghino et al., 1997, 2002; Decamps,´ able, the extent of river-bed erosion can be used as 1996). an indicator for the status of the sediment regime, as An extensive literature review by Limnex river-bed incision is strongly correlated with defi- (2003) on hydropeaking showed that a ratio of cient bed load transport. River-bed erosion can be about 3(4):1 between the peak flow and base flow assessed according to the written or oral descrip- phases was a critcal value. With smaller ratios no tions of local authorities, photogrammetric chan- major impacts on the river biocoenosis are to be nel data or comparisons of photographs taken of expected. However, Limnex (2003) emphasizes constructions within the river-bed where changes that this value should only be taken as a rough in river-bed level can be roughly estimated from guide. We propose the ratio of 3(4):1 as a first (e.g. bridge piers). The presence of river-bottom approximation and ask for further research on pos- sills also indicates a lack of sediment as they are sible thresholds concerning hydropeaking and its commonly used by river engineers to prevent/stop ecological side effects. river-bed erosion. Having said that, lack of bed load (iii) Dams. Dams prevent free water flow, change the can also be related to natural factors and one has seasonal flow regime, prevent sediment move- also to bear in mind that it is possible that river- ment and hinder species migration, thus limit- bed may be paved (natural bed rock, colmation) so ing the establishment of a natural biocoenosis that there is no river-bed erosion but still a lack of (Cluett and Radford, 2003; Nilsson and Berggren, sediment. 2000; Phillips, 2003). Thus, the presence of dams in a river is considered to decrease its eco- 3.3.4. Water quality morphological restoration suitability. Investigations of benthic macro-invertebrates (Nedeau et al., 2003) and fish communities (Pretty 3.3.3. Bed load et al., 2003) have shown that poor water quality The sediment regime plays a major role in deter- (described by both chemical and physical parameters) mining the biotic composition, structure and function can reduce the positive effect of physical habitat of floodplains (Marriott and Alexander, 1999; Petts restoration. 56 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70

Therefore, the following three indicators are pro- ian woodland. In cases where temperature data is posed to integrate water quality in the evaluation of not available, the presence of hydropeaking, water restoration suitability: abstraction and riparian woodland are proposed as surrogates. (i) Chemical water quality. Chemical water quality affects reproduction, health, competitivness and 3.3.5. Connectivity survial of aquatic species and thus the composi- Rivers are longitudinally, laterally, vertically and tion and structure of benthic species assemblages temporally connected with their environment (Amoros as well as seedling establishment and plant growth and Bornette, 2002; Ward, 1998). Connectivity is a pre- (Camargo et al., 2004; Sweeting, 1996). Bet- requisite for the flux of energy, water, sediments and ter chemical water quality facilitates restoration nutrients, as well as of species dispersal and migra- efforts and thus increases restoration suitability. tion. Thus, the suitability for the restoration of natural The proposed indicator range and characteris- processes and riparian biocoenosis increases with con- tics of the chemical water quality of a river reach nectivity. To assess the degree of spatial connectivity were selected according to the Swiss Program of a certain river reach, the following indicators are for investigating and assessing flowing waters proposed: (BUWAL, 2003) and include: ortho-phosphates, nitrates, nitrites, ammonium, DOC and pH. The (i) Artificial migration barriers. Dams, weirs, etc. are scheme contains temperature-dependent critical artificial barriers which have considerable influ- values to account for the natural differences ence on aquatic life as they decrease ecological between headwaters and lowland rivers. permeability of the system and hence hamper or (ii) Percentage of arable land in the watershed. This interrupt species movement along the river chan- indicator was included because research shows nel. Thus, such barriers impair restoration suit- that arable land use is a major source of pol- ability. Research has shown that trout and other lution with fine sediments of which high loads salmonid species are able to pass barriers up to hamper high benthic diversity and abundance due 70 cm, for all other fish species the maximum to the absence of local flow refugia and spawning height is less than 40 cm (Peter, 1998). Small- grounds. (Allan et al., 1997; Basnyat et al., 1999; sized fish species (Cottus gobio, etc.) are not able Walser and Bart, 1999). to pass barriers >25 cm. As there is no data avail- The indicator range presented in Table 1 is able on the correlation between number of barriers based on percentage classes which represent the and fish migration, the indicator range in Table 1 situation in Switzerland. Classes were derived is proposed as reasonable approximation which using the “natural breaks classification” (Jenk’s needs further investigation. optimization) in ArcView. This procedure identi- (ii) Distance from current floodplains. Distance from fies the most suitable areas according to present species pools is a major factor driving species col- day environmental conditions. Application of this onization at a new established site. Rohde et al. indicator in other countries should be based on (2005) showed that the vegetation composition of own calculations to reflect the status of the sys- river widenings within a distance of 10 km down- tem under consideration. stream of near-natural floodplains was similar to (iii) Presence of riparian woodland. Water quality is that found at the near-natural sites, while the veg- not only described chemically but also physi- etation composition of isolated river widenings, cally, for example, by temperature. Temperature which had no near-natural floodplain upstream, in rivers is of major importance as it drives many was mainly influenced by the immediate sur- chemical processes and the metabolism of liv- roundings. There have been many studies inves- ing organisms (Stanford et al., 1996). The natural tigating species dispersal with stream flow, but temperature regime can be heavily disturbed by there is no general information on dispersal dis- anthropogenic effluents (e.g. power stations or tances as these vary from species to species and sewage treatment plants) and the logging of ripar- depend on flow volume (Bonn and Poschlod, S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 57

1998; Ellenberg, 1996; Pedroli et al., 2002). How- how suitable a stream system is to enhance those ever, the number of dispersed species generally species the following indicator is suggested: decreases with distance from the species pool, as, (i) The presence of riparian species (flora and fauna). for example, shown by Walas (1938) in Ellenberg The selection of taxa to be included should reflect (1996). Thus, the greater the distance from a flora and fauna as well as different functional species pool, the lower the probability of species groups, dispersal strategies and trophic levels. For arrival and therefore the less suitable for restora- Switzerland, for example, Schneider et al. (2003), tion. The proposed indicator range (Table 1)is Schager and Peter (2004) and Rohde et al. (2005) a first approximation based on best professional provide lists of riparian species whose survival judgment obtained from river ecologists, which mainly depends on fluvial habitats. These lists participated in the Rhone-Thurˆ project. However, include fish, birds, mammals, mussels, insects we ask for further research on dispersal thresh- (Carabidae, Saltatoria, Apidae, Heteroptera) and olds. (semi-) terrestrial flora. However, in practice (iii) Distance from gravel pits. Gravel pits have taxa selection will also be determined by data been identified as providing secondary habitats availability. for some riparian species which may function as species pools (Catling and Brownell, 2001; The presence of riparian species is measured as a Pinder, 1997; Santoul, 2002; Sidle and Kirsch, percentage of the local species pool derived from dis- 1993). Additionally, the presence of gravel pits tribution maps. This procedure reflects the current col- is generally well documented. Thus, the distance onization potential and also takes into account biogeo- from gravel pits was also included as an indi- graphical differences. The indicator range presented in cator for connectivity. Research on amphibians, Table 1 is based on percentage classes which repre- for example, has shown that individuals are capa- sent the situation in Switzerland. Classes were derived ble of covering distances up to 3–4 km (Miaud using the “natural breaks classification” (Jenk’s opti- et al., 2000; Ray et al., 2002) and many ripar- mization) in ArcView. Application in other countries ian plant species are not only hydrochor (disper- should be based on own calculations to reflect the sta- sal by water), but also anemochor (dispersal by tus of the system under consideration. wind) and are able to cover long dispersal dis- Species colonization clearly depends not only on tances between sites which are not connected by the species pool, but also on the species abundance, water (Bonn and Poschlod, 1998). Therefore, we species mobility and ecological permeability of the consider a distance of 1 km from gravel pits to region. The extent of species movement within the be reasonable to have a positive impact on the landscape is difficult to assess. Nevertheless, over the restoration suitability of a river stretch. Having longer term we might expect that restoration sites said that, other smaller water bodies may also placed in species-rich regions are more likely to be col- serve as refugia and inoculation sites (Petersen onized by riparian species than sites with a low species et al., 2004; Williams et al., 2004). However, at pool. national scale, data about the distribution of these sites is hardly available and was therefore not 3.3.7. Ecological Restoration Suitability Index included in the search strategy. The suitability factors which affect the restoration potential of a river (hydrology, bed load, water quality, 3.3.6. Biodiversity connectivity and biodiversity) are incorporated in the The number of riparian species present in a region Ecological Restoration Suitability Index, which was boosts the potential for colonization by riparian species developed as part of this study. The ERSI is calculated and thus the probability of re-establishing near-natural by a numerical overlay of the selected indicators and biocoenosis. The more riparian species present in a assess the overall ecological restoration suitability of a river region, the more species could potentially ben- stream system (Fig. 2). efit from restoration efforts (Austrheim and Eriksson, The combination of these indicators in a single 2001; Stanford et al., 1996). For roughly estimating restoration suitability index is a multiple criteria deci- 58 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70

Fig. 2. Spatial multi criteria decision analysis. S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 59 sion analysis (MCDA) problem. This study adapts the 3.4. Filter 3: integration of socio-economic factors multi-attribute value theory (MAVT) approach based on the weighted additive model (Belton and Stewart, 3.4.1. Introduction 2002; von Winterfeldt and Edwards, 1986). To calcu- Floodplain restoration projects affect not only the late the Ecological Restoration Suitability Index, three ecological state of a river, but also economic and social elements are needed: (1) a single value (suitability) aspects (Decamps,´ 2001; Ehrenfeld, 2000). Hence, function for each indicator, which is used to trans- socio-economic factors should be considered in iden- form the indicator levels into an interval-value scale, tifying suitable stream systems for floodplain restora- (2) the weightings to determine the relative importance tion. This is done in Filter 3. We identified the following of each indicator and (3) the prediction of outcomes four factors to be of major importance: (i) flood pro- for the indicators. The overall value for the suitability tection, (ii) existing infrastructure, (iii) recreational status of a cell A is the weighted average of the single opportunities and (iv) public attitudes (Table 3). In indicator values: contrast to the ecological criteria, the socio-economic factors should not be aggregated into a suitability V (A) = wi × vi(ai), (1) index, because the specific conditions of each case study determine the appropriate socio-economic fac- where V(A) is the overall value of the cell A, ai repre- tors which need to be considered. Each socio-economic sents the outcome for indicator i resulting from cell A, factor is represented as an individual GIS map layer. vi(ai) the single indicator suitability function and wi is Depending on the specific decision context, one or a normalized weight for indicator i. The overall value more socio-economic layers can be combined with of a cell V(A) represents the Ecological Restoration the ecological suitability layer. For example, if a deci- Suitability Index of this cell. sion maker is interested in both ecological restoration For the assessment of the single indicator suitabil- and improving flood protection, these two GIS lay- ity functions, the attribute levels of the indicators were ers can be combined. The resulting layer indicates standardized to a continuous scale of suitability from the stream systems with a high ecological suitabil- 0 (the least suitable) to 100 (the most suitable) (indi- ity and a great demand for improving flood protec- cator suitability function, Table 2). Each standardized tion. factor is then multiplied by its corresponding weight Beside the proposed factors, other socio-economic (Table 2). The weights express the relative importance factors may also influence the feasibility of restora- of each indicator (Belton and Stewart, 2002). Weights tion projects. Issues such as ‘costs of the project’ or are usually considered as the most direct expression ‘ownership of the land’ (public or private land) are of the decision-maker’s system of values (Belton and important topics. However, these factors depend very Pictet, 1997). In this study, indicator suitability func- much on the local conditions and are not easily aggre- tions were obtained in a modified Delphi process gated in a national search strategy. However, it is survey on the basis of the best professional judge- important to emphasize that these factors have to be ments of nine river ecology experts working on ben- evaluated in the later decision-making process, when thos, fish, vegetation, riparian habitats, temperature and different locations for restoration or different restora- chemistry. tion alternatives are considered (Hostmann et al., The outcomes resulting from each cell are based on 2005). quantitative, spatially explicit data about the selected indicators, which will be implemented in a geograph- 3.4.2. Flood protection ical information system (grid layers). This data may Flood retention is one of the most important socio- be readily available from inventories or can be gener- economic aspects in floodplain restoration. Providing ated from existing information by using, for example, more room for rivers increases the retention volume and buffer, merge or cost-distance functions provided by thus reduces the risk of damaging the surrounding area. the GIS software. Data scarcity does not limit the appli- Hence, combining ecological restoration and improved cation, as we allowed some redundancy in the indicator flood protection can increase the public acceptance of selection. a project. 60 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70

Table 2 Indicator-suitability functions to calculate the Ecological Restoration Suitability Index (ERSI) and weighting schemes used for sensitivity analysis Indicator Indicator range Suitability Weighting scheme used functiona for sensitivity analysis Expert Abiotic Biotic Equal Water abstraction (%) <20 100 0.22 0.24 0.08 0.1 <20 + increased winter flow 88 20–40 63 40–60 13 60–80 13 >80 13 Hydropeaking Peak flow: base flow <3(4):1 100 0.2 0.18 0.08 0.1 Peak flow: base flow >3(4):1 0 Dam No 100 0.2 0.18 0.08 0.1 Yes 0 Chemistry Very good 100 0.08 0.1 0.03 0.1 Good 100 Moderate 60 Bad 20 Very bad 0 Percentage arable land (%) 0–2.33b 100 0.08 0.1 0.03 0.1 2.33–6.69 75 6.69–12.3 50 12.3–21.59 25 21.59–35.88 0 Downstream distance from present 0–10 100 0.1 0.05 0.2 0.1 floodplains (km) 10–25 83 25–50 60 50–100 40 >100 0 Distance from gravel pits (km) <10 100 0.02 0.05 0.1 0.1 >10 0 Percentage (%) of regional riparian 0–10b 13 0.05 0.05 0.2 0.1 species pool (flora) 10–34 33 34–50 75 50–70 100 70–100 100 Percentage (%) of regional riparian 0–7b 13 0.05 0.05 0.2 0.1 species pool (fauna) 7–19 33 19–32 75 32–49 100 49–74 100

a Derived from a modiﬁed Delphi-process with nine river ecologists. b Classes according to present situation in Switzerland (relative, not absolute assessment). S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 61

Table 3 Socio-economic criteria and corresponding indicators including indicator range (Filter 3) Criteria Indicator Indicator range Flood protection Protection deﬁcits >0 <0 Existing infrastructure Distance away of the infrastructure three times the width of the river Recreational opportunities Distance to populated areas (km) >10 ≤10 Public attitude Public attitude towards env. policies Technocratic Ecological

The following indicator provides information on the 3.4.4. Recreation opportunities flood protection level within the river basin: Natural or near-natural rivers make attractive recreation areas, providing opportunities for activities (i) Protection deficits. The protection deficit is the dif- such as eco-tourism, sport fishing and other out- ference between the protection objective defined by door activities (Costanza et al., 1997; Newsome and the public authority and the existing protection level Stephen, 1999). Hence, improving recreational oppor- for a specific river reach. The need for restoration tunities can be an important objective in restoration measures increases the larger the protection deficit. projects and can increase the public acceptance of the We propose varying protection objectives, which project. depend on the purpose of the area under consider- The potential for recreational activities depends ation. Settlements and infrastructure, for example, on the distance between the river and the next clos- need a greater protection than farming areas. est densely populated area (village, town). Thus, the restored sites should be close to populated areas to 3.4.3. Existing infrastructure allow for local recreation. To assess the suitability of Existing infrastructure may complicate or con- restoration projects for recreation, the following indi- strain restoration projects. There are different types of cator is proposed: infrastructure, such as highways, railways, houses and groundwater recharge stations, which are strong con- (i) Distance between the river and the populated areas. straints on restoration projects since they are not likely We suggest 10 km as an adequate threshold, as a to be removed. In contrast, other types of infrastruc- distance up to 10 km between the recreational site ture such as power supply lines and gas pipes are more and the populated area seems to be a reasonable likely to be relocated, but may still complicate restora- distance to travel for recreation purposes (ARE and tion projects. BFS, 2001). To assess the suitability of a restoration project based on existing infrastructure, the following indica- 3.4.5. Public attitudes tor is proposed: Public attitudes towards river ecosystems are a (i) Distance between the infrastructure and the river. key element for successful river restoration. Decamps´ In general, the necessary space for a river widen- (2001) argues that the survival of riparian landscapes ing depends on the type of the river, the restoration requires that people enjoy and take care of them. The measures and the topography (see Filter 1). As a public attitude might influence the implementation of rough estimation, based on restoration experience restoration projects in different ways. First of all, most in Switzerland, it can be assumed that if the infras- restoration projects are financed by the government tructure is located closer than three times the width (local, regional or federal government), and hence of the existing river-bed, the restoration of the flood- mainly paid for with public money. Furthermore, in plain will be constrained. Switzerland, for example, the public even has in some 62 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 cases to vote in a referendum on a proposed restoration • Class 1: highly suitable. project. Therefore, we assume that if a community has • Class 2: fairly suitable. an ecological attitude this can increase the feasibility of • Class 3: moderate suitable. restoration projects. Therefore, the following indicator is proposed: However, sub-indices values for each indicator are reported with the overall score and all values are used (i) Public attitude towards environmental projects to describe the restoration suitability of an individual (ecological or technocratic). There is a great stream system. This allows users to make their own increase in literature about public participation in assessment about the relative importance of each indi- River Basin Planning (Environment Agency, 2004; cator. Furthermore, ecological deficiencies in the river Walker et al., 2002) and valuation of river ecosys- system whose removal will have a great positive effect tem (Everard, 2004). However, there is hardly any on the overall restoration suitability can be identified. data on public attitude towards river restoration Filter 3 is a visual overlay of the ecological suitabil- projects available on a national scale. In the absence ity map with the single maps of the socio-economic of such data, surrogate data featuring general pub- factors. The overlay is not done numerically as suit- lic attitudes towards environmental policies could ability values and weights depend more on local man- be used instead. This can be obtained from public agement and planning goals and restrictions than on polls (Herrmann and Leuthold, 2001, 2003). general scientific knowledge.

4. Spatial multiple criteria decision analysis 5. Case study

For the hierarchical decision process (Filters 1–3), The integrative search strategy presented here was a geographic information system is used to manage applied as part of the Rhone-Thurˆ Project in Switzer- and analyse the spatial data. The combination of GIS land. The Swiss network of watercourses covers about and MCDA is a powerful approach to land suitability 61,000 km of streams and rivers. Preliminary studies assessment (Joerin et al., 2001) and different appli- suggest that 43% of the stream and river network is in cations have been described in the literature (e.g. need of restoration (Peter et al., 2005). As a result, the Bojorquez-Tapia et al., 2001; Jankowski et al., 1997; Swiss Federal Ministries for environment and water Joerin et al., 2001; Pereira and Duckstein, 1993; Store formulated “sufficient room for water courses” as a and Kangas, 2001). major development objective (BUWAL/BWG, 2003). Within a geographical information system (GIS), The ministries ask to achieve these objectives by con- each indicator is represented in a thematic grid layer, sidering ecological as well as socio-economic criteria. while each cell in the database is taken as an alternative The search strategy was developed as a planning to be evaluated in terms of its quality or appropriate- tool and a preliminary case study was conducted using ness for a given end, e.g. floodplain restoration (Pereira spatial data from various sources (BFS-GEOSTAT, and Duckstein, 1993). In Filter 1, all those areas (cells) 1992/97; BFS-GEOSTAT/BUWAL, 2001; BFS- that are not considered suitable for floodplain restora- GEOSTAT/BUWAL/BUWAL/ARE/BAKOM, 2002; tion are excluded by a Boolean-type selection. In Filter BWG/BUWAL, 2003; CSCF, 2003; Herrmann and 2, the map layer of each indicator was integrated in a Leuthold, 2003; Wohlgemuth et al., 1999). Data was suitability model to calculate the Ecological Restora- available to cover most of the ecological indicators tion Suitability Index (Fig. 2). We used ModelBuilder (Filter 2). Only the indicators ‘bed load’ and ‘pres- 1.0a to create the suitability model, which produces ence of artificial migration barriers’ could not be a suitability map showing the overall ERSI with cell implemented due to incomplete data bases. values ranging from 0 to 100. To make the result- ArcView GIS 3.3. and ModelBuilder 1.0a were used ing map more user-friendly, the Ecological Restora- to perform the spatial multiple criteria decision analy- tion Suitability Index is reclassified into three equal sis. Each suitability indicator represented its own map classes: layer and the data was grided into 100 m × 100 m grid S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 63 cells. Fig. 2 shows the principle of the weighted over- are highly suitable for restoration (Class 1). In total, lay of the input maps for the ecological suitability 80% of all stream systems in the study area are classi- assessment (MCDM-GIS-analysis, see above) and the fied as highly suitable and 20% of the stream systems resulting ecological restoration suitability map on the are fairly suitable (Class 2) for restoration (Fig. 3). catchment scale. None of the rivers are classified as moderately suitable For some of the data GIS layers were readily avail- (Class 3). The majority of stream systems, which are able. Others had to be produced from existing infor- highly suitable or fairly suitable for restoration, can be mation by using spatial function and analysis tools found in the lowland region of Switzerland, in contrast provided by the GIS software. For example, the dis- to the alpine region where restoration suitability was tance to the nearest floodplain reserve (Filter 2) was identified to be rather low. This geographical differen- calculated with the CostDistance function within the tiation is due to the fact, that alpine rivers are espe- SpatialAnalyst extension of ArcView 3.3. We decided cially affected by water abstraction and hydropeaking not to use the buffer function, as this would not take (hydropower production). These factors, which limit into account bends and meanders. restoration suitability, are weighted relatively high by For some criteria (e.g. proportion of arable land the experts (Table 2). (Filter 2)), the suitability of a stream system was not For a more detailed analysis of the results, it is assessed on the basis of thresholds that have an ecolog- important to analyse whether the results are robust ically based rationale. Instead, we ranked the existing towards uncertainty in the input information. For the data. The ranking (classification) of the data was done Ecological Restoration Suitability Index, the following using the ‘natural breaks’ function in ArcView, which information is used (Eq. (1)): the outcomes for indica- finds groupings and patterns inherent in the data and tor i, the single indicator suitability functions and the minimizes the sum of the variance within each of the weights for the indicators. While the outcomes for each classes (Jenk’s optimization). This procedure identifies indicator are based on scientific data, the weights for the the most suitable areas according to present day envi- indicators are based on expert judgement. Hence, the ronmental conditions. weights of indicators are assertive and indicative rather Fig. 2 shows the percentage of the stream systems than sound and precise. Due to the inherent uncertainty highly suitable for ecological restoration within the of professional judgement, we conducted a sensitiv- catchment areas. This result is based on the expert ity analysis to investigate the relative influence of the weighting scheme (Table 2). It is striking that, for the weightings on the ERSI. Three additional weighting majority of the catchment areas, the stream systems schemes were applied for the sensitivity analysis: (i)

Fig. 3. Sensitivity analysis for the Ecological Restoration Suitability Index (ERSI). 64 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 an abiotic scheme, which emphasizes the abiotic crite- analysis show that the data is rather robust in distin- ria, (ii) a biotic scheme, which emphasizes the biotic guishing between the classes ‘moderately suitable’ and indicators and (iii) a third scheme where all indicators ‘fairly/highly suitable’. On the other hand, the weights received equal weightings (Table 2). The results show, of the indicators have a significant influence whether a that for the Ecological Restoration Suitability Index stream system is classified to be ‘highly suitable’ (Class major differences occur between the expert weighting 1) or ‘fairly suitable’ (Class 2). Therefore, for further and the biotic weighting scheme (Fig. 3). Based on the application of the search strategy, it is important that expert weighting scheme, the majority of the stream the weighting of indicators has to be examined very systems are ‘highly suitable’ (Class 1) for restoration, carefully. whilst the biotic weighting classifies the majority as The assessment of the ecological restoration suit- ‘fairly suitable’ (Class 2). This difference is caused by ability (Filter 2) is followed by the assessment of socio- the fact that the biotic model emphasizes the biotic indi- economic factors (Filter 3). We use the factor ‘public cators, whilst most river reaches in Switzerland have a attitudes’ to illustrate how socio-economic factors can poor local species pool (flora and fauna) and are not be included in a spatial search strategy for restoration very close to current near-natural floodplains. How- measures. Fig. 4 shows the ecological suitability map ever, only a small percentage of river reaches (4%) and public attitudes towards environmental projects. is classified in the lowest Class 3 (moderately suit- In general, the majority of the Swiss public supports able) (Fig. 3). In general, the results of the sensitivity restoration projects. A national survey showed that

Fig. 4. Ecological restoration suitability and public attitude (Filter 3). S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 65

78% of the Swiss people want to provide rivers with The results of this study are in line with previous more space (Pro Natura, 2000). However, some regions studies (Joerin et al., 2001; Pereira and Duckstein, are more progressive ecologically than others. Based 1993; Store and Kangas, 2001) who emphasized the on the analysis of 158 federal referenda held between potential usefulness of GIS-based MCDA for land 1981 and 1999, Herrmann and Leuthold (2001) clas- suitability assessment. Whereas the mentioned studies sified each community in Switzerland as taking either concentrate on land suitability assessment, this study an ecological or technocratic stance towards environ- focuses on floodplain restoration suitability includ- mental topics. Fig. 4 shows those areas where pub- ing a wide range of ecological and socio-economic lic attitudes are ecological and where is very high indicators. The relevance of such a strategic, spatial restoration potential. These are areas where the restora- wide planning instrument for floodplain restoration tion process is likely to be successful, in terms of was stressed by Clarke et al. (2003). the planning processes as well as ecological gain. There are many studies which focus on the iden- Our results show that only about half of the stream tification of natural rivers for conservation purposes systems highly suitable for ecological restoration are (e.g. Dunn, 2004; Stein et al., 2002). The presented located in areas where public attitudes are ecologi- search strategy can support this approaches as the pre- cal. However, experience shows that public attitudes sented strategy helps to identify river stretches where it can change with information and stakeholder involve- is most likely to achieve successful floodplain restora- ment. Thus, our results do not imply that the areas tion and thus to strengthen the net of (near-)natural with technocratic attitudes should be excluded from floodplains. There are other approaches which allow consideration, but that there might be more resources the comparison of different restoration options for a needed there to achieve public support. The map in given location, e.g. watershed (Lamy et al.), whereas Fig. 4 is a preliminary result, as the data of Herrmann the presented search strategy helps to identify the most and Leuthold (2003) represents general public atti- promising locations. Additionally, the results of Filter tudes towards environmental projects. There will be 2 show where it is most likely to achieve “a good eco- a nationwide survey within the Rhone-Thurˆ project logical status” as required by the EU Water Framework focusing on public attitudes towards river restoration Directive. which will provide more detailed information. Pub- The case study illustrates the practical application of lic attitude is just one aspect of socio-economic fac- the search strategy. Although the selected criteria and tors which might be important to consider in Filter parameter values represent mainly Swiss conditions, 3 (beside flood protection, existing infrastructure and the principle underpinning the proposed approach can recreation opportunities). The relevant socio-economic easily be adapted to other study areas, e.g. by integrat- factors depend on the specific aims and conditions of ing ‘navigation’ as a socio-economic criterion within each restoration project (e.g. major deficits or important Filter 3. economic aspects). Hence, the selection of the rele- The strategy concentrates on assessing suitability vant socio-economic factors for a specific case study and priority for eco-morphological restoration of flood- has to be made by the responsible restoration author- plains. Other restoration measures, like removing dams ity. and reducing water abstraction, are not specifically addressed, because short to middle term there are no or only little chances for those measures to be conducted 6. Discussion due to economic constraints. Thus, they are seen as unchangeable framework. However, we stress that in The main purposes of this study were: (1) to describe the long term such measures are important if we want to important ecological and socio-economic criteria for regain a healthy river system. However, the model pre- assessing eco-morphological restoration suitability; (2) sented here implies a deficiency analysis which gives to propose feasible indicators for restoration suitability information on where improvements of abiotic con- and (3) to develop a search strategy to identify stream ditions are needed and which measures would have systems where the greatest benefits from restoration the most far-ranging effects favouring the restoration can be expected. efforts. 66 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70

Restoration suitability is driven by numerous fac- level), but cannot provide information on a detailed tors. However, practical applications require a man- level to compare different restoration sites within the ageable set of indicators and data. In this regard, the same stream system. The model presented here pro- search strategy is a compromise between accuracy and duces a suitability map with crisp boundaries between costs, which can guide and support decisions, but never the individual suitability classes. However, real-world ‘make’ decisions. boundaries are mainly continuous ones. Water quality, In order to estimate the Ecological Restoration Suit- for example, will rarely change abruptly but rather will ability Index based on the weighted additive model, be fuzzy with increasing dilution. The crisp boundaries the decision maker’s preference should satisfy a condi- in the suitability model are an artefact resulting from tion known as mutual preferential independence. This abstraction of real-world data into the GIS-compatible requires that every subset of attributes should be prefer- map layers of the input data. Hence, the level of detail entially independent of its complement (Belton, 1999). is only sufficient to signal stream systems of differ- There are different ways to deal with a lack of mutual ent restoration suitability on the catchment scale. It is preferential independence. It may be possible to rede- important to emphasize that this search strategy does fine or restructure the attributes in a way which achieves not replace more detailed investigations which provide preferential independence (Belton, 1999). Another way the foundation for comparing different restoration sites is to estimate the interactions of the attributes and use within one stream system and different alternatives for the multiplicative model (Keeney and Raiffa, 1976; the chosen restoration site. Thereby, important aspects von Winterfeldt and Edwards, 1986). In this study, we of operational practice are issues such as ‘ownership selected the ecological indicators so as to be as indepen- of the land’ and ‘potential funding’ which depend very dent from each other as possible. However, some redun- much on the local conditions. The strength of this dancy between the indicators was allowed to enable the search strategy lies in the pre-screening of spatial data application of the search strategy in situations where on a national scale and its ability to focus restoration data is scarce. It is important to emphasize that the indi- activity on the most promising areas. cator weights as well as the single indicator suitability Finally, when setting priorities one should aim for functions of the case study represent mainly Swiss con- the connectivity of natural and restored sites to estab- ditions of (sub-)alpine rivers. For applications in other lish a healthy river network and ensure that headwaters, regions, the indicator suitability functions and indica- middle reaches and lower courses from different bio- tor weights can be obtained in a Delphi process survey geographic regions are represented equally so as to with river ecology experts and river managers. sustain the natural array of processes and species which Lack of data limits the completeness of information characterise our floodplains. to be integrated into the suitability model of the search strategy. In cases of data scarcity, one can use surrogate data instead of direct measurements. Data on public 7. Conclusions attitudes, for example, can be estimated from ballot results instead of personal interviews. Having said that, The integrative search-strategy presented and its one has to be careful that the chosen surrogate implies implied GIS-model are valuable tools to assist policy the information needed. The quality of the search strat- makers and planners in making decisions about flood- egy does not solely depend on the implemented factors plain restoration. As is every model there are some con- and data availability. It also depends on accuracy, age straints. For example, the simplification of reality due to and resolution of the input data. When interpreting the limited data input and spatial resolution. Nevertheless, data, one should be aware of the spatial resolution of the we think that the application of the suggested search input data. We worked on a basis of a 100 m × 100 m strategy will enable an efficient planning process, as it: grid for technical reasons. However, spatial resolution (a) eases priority setting and allocation of resources of the input data was much coarser, for example, stream because it helps to identify stream systems where level for hydropeaking or municipal level for the indica- the present conditions favour restoration efforts tor ‘public attitude’. Thus, the proposed search strategy and thus justify further specific and detailed inves- provides information on a broad scale (stream system tigations (pre-screening); S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70 67

(b) merges input from a wide range of specialists and F. Kienast for their valuable comments and suggestions provides a comprehensive set of objective, eco- on the manuscript, as well as to two anonymous review- logical as well as socio-economic indicators or ers who greatly helped to improve the manuscript. This surrogates for assessing restoration suitability. The study was part of the transdisciplinary Rhone-Thurˆ Ecological Restoration Suitability Index signals project (http://www.rhone-thur.eawag.ch/index.html), ecological deficiencies where further action, for financed by EAWAG, WSL, BWG and BUWAL. example, residual flow management, is needed to foster restoration success; (c) can be flexibly adapted to local situations with, for References example, restricted data availability. Its flexibility Allan, J.D., Erickson, D.L., Fay, J., 1997. The influence of catch- also means that different scenarios can be produced ment land use on stream integrity across multiple spatial scales. subject to (future) changes in the environment or Freshwater Biol. 37, 149–161. planning targets; Amoros, C., Bornette, G., 2002. Connectivity and biocomplex- (d) provides a ‘check-list’ of clearly defined criteria ity in waterbodies of riverine floodplains. Freshwater Biol. 47, and indicators, respectively, surrogates for sus- 761–776. ARE, BFS, 2001. Mobilitat¨ in der Schweiz. Ergebnisse des tainable river management. The presented search Mikrozenzus 2000 zum Verkehrsverhalten. Bundesamt fur¨ Rau- strategy supports data-driven decision-making and mentwicklung, Bundesamt fur¨ Statistik, Bern and Neuenburg. ensures as much objectivity and standardization as Austrheim, G., Eriksson, O., 2001. Plant species diversity and graz- possible. Such a replicable and transparent selec- ing in the Scandinavian mountains—patterns and processes at tion procedure could be seen by politicians and different spatial scales. Ecography 24, 683–695. Basnyat, P., Teeter, L.D., Flynn, K.M., Lockaby, B.G., 1999. Rela- stakeholders as being less prescriptive and indi- tionships between landscape characteristics and nonpoint source vidually intrusive than a subjective assessment and pollution inputs to coastal estuaries. Environ. Manage. 23, thus help to ensure public accountability. 539–549. Belton, V., 1999. Multi-criteria problem structuring and analysis in In a nutshell, the search strategy presented here a value theory framework. In: Gal, T., et al. (Eds.), Multicriteria enables a strategic, proactive and efficient planning Decision Making. Kluwer Academic Press, Dordrecht, Nether- lands, pp. 12-1–12-32. process, which is based on both ecological and socio- Belton, V., Pictet, J., 1997. A framework for group decision using economic criteria. Such a systematic planning proce- a MCDA model: sharing, aggregating or comparing individual dure provides transparency and thus helps to ensure information? J. Decision Syst. 6, 283–303. public accountability, and it also helps to set priorities Belton, V., Stewart, T.J., 2002. Multiple Criteria Decision and thus avoid inefficiency. It enables projects to be Analysis—An integrated approach. Kluwer Academic Publish- ers, Boston/Dordrecht/London. located where they are less likely to be undermined BFS-GEOSTAT, 1992/97. Arealstatisik der Schweiz. Bundesamt fur¨ by adverse influences, and where the greatest gains Statistik, Servicestelle GEOSTAT, Neuchatel.ˆ (both ecological and socio-economic) are to be made. BFS-GEOSTAT/BUWAL, 2001. Aueninventar. Bundesamt fur¨ We acknowledge, however, that further development Statistik, Servicestelle GEOSTAT, Neuchatel.ˆ of the presented search strategy is desirable, and we BFS-GEOSTAT/BUWAL/ARE/BAKOM, 2002. Siedlungsgebiete der Schweiz. Bundesamt fur¨ Statistik, Servicestelle GEOSTAT, invite others to become involved in the process of fur- Neuchatel.ˆ ther refinement. Bojorquez-Tapia, L.A., Diaz-Mondragon, S., Ezcurra, E., 2001. GIS-based approach for participatory decision making and land suitability assessment. Int. J. Geograph. Inf. Sci. 15, 129– 151. Acknowledgments Bonn, S., Poschlod, P., 1998. Ausbreitungsbiologie der Pflanzen Mit- teleuropas Grundlagen und kulturhistorische Aspekte. Quelle & We would like to thank our collegues of the Rhone-ˆ Meyer, Wiesbaden, 404 pp. Thur project for their participation in the Delphi- Bowen, Z.H., Bovee, K.D., Waddle, T.J., 2003. Effects of flow regu- process and for fruitful discussions about criteria and lation on shallow-water habitat dynamics and floodplain. Trans. Am. Fisheries Soc. 132, 809–923. indicator selection. We especially benefited from stim- Brookes, A., Shields, F.D., 1996. River Channel Restoration: Guid- ulating discussions with G.-R. Bezzola, C. Marti and K. ing Principles for Sustainable Projects. John Wiley & Sons Ltd., Tockner. We are also very grateful to P. Englmaier and Chichester. 68 S. Rohde et al. / Landscape and Urban Planning 78 (2006) 50–70

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At present she is researcher at Stanford, J.A., Ward, J.V., Liss, W.J., Frissell, C.A., Wiliams, R.N., the Swiss Federal Institute for Forest, Snow and Landscape Research Lichtatowich, J.A., Coutant, C.C., 1996. A general protocol for (WSL) where she recently completed a PhD thesis on river restora- restoration of regulated rivers. Regulat. Rivers: Res. Manage. 12, tion. Her fields of research include methods and indicators to assess 391–413. restoration measures and planning strategies to enhance river restora- Stein, J.L., Stein, J.A., Nix, H.A., 2002. Spatial analysis of anthro- tion. Her other areas of professional interests are landscape ecology, pogenic river disturbance at regional and continental scales: iden- decision support systems, GIS-modelling, ecological and socioeco- tifying the wild rivers of Australia. Landscape Urban Plann. 60, nomic aspects in multi-objective spatial planning and management 1–25. of (peri-)urban space. Store, R., Kangas, J., 2001. Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability Markus Hostmann is presently a researcher at the Swiss Federal modelling. Landscape Urban Plann. 55, 79–93. Institute for Environmental Science and Technology (EAWAG) in Sweeting, R.A., 1996. River pollution. In: Petts, G.E., Calow, P. Zurich, Switzerland. He received his MSc degree in environmen- (Eds.), River Restoration. Blackwell Science Ltd., Oxford, pp. tal science in 2000 from the Swiss Federal Institute of Technol- 7–16. ogy Zurich (ETH). His areas of interest include multiple criteria VAW, 1993. Strada. Flussmorphologisches Gutachten zur geplanten decision analysis (MCDA), decision support systems (DSS), stake- Innrevitalisierung im Zusammenhang mit der Umfahrungsstrasse holder involvement and conflict resolution in the field of river ¨ Strada. Versuchsanstaltfur Wasserbau, Hydrologie und Glaziolo- restoration. Hostmann is author of the restoration guide “Free ¨ gie (VAW), Zurich. water—expeditions to river restoration sites in Switzerland” and sev- Villa, F., Tunesi, L., Agardy, T., 2002. Zoning marine protected areas eral scientific publications. through spatial multiple-criteria analysis: the case of the asi- nara island national marine reserve of Italy. Conserv. Biol. 16, Dr. Armin Peter studied biology and obtained a PhD in fish ecology 515–526. at the Swiss Federal Institute of Technology (ETH), Zurich. Post- von Winterfeldt, D., Edwards, W., 1986. Decision Analysis and doctoral stay at the University of British Columbia, Vancouver, BC. Behavioral Research. Cambridge University Press, Cambridge. Senior scientist at EAWAG (Swiss Federal Institute for Environmen- Walas, J., 1938. Wanderungen der Gebirgspflanzen langs¨ der tal Science and Technology). Research focus in fish ecology, habitat, Tatra-Flusse.¨ Bull. Acad. Polon. Cl. Sci. Math. Nat. Ser.´ B fish migration and river restoration. Lecturer for fish ecology at ETH 58–80. Zurich. Head of the Rhone-Thurˆ project. Walker, B., Carpenter, S., Anderies, J., Abel, N., Cumming, G., Janssen, M., Lebel, L., Norberg, J., Peterson, G.D., Pritchard, Prof. Dr. Klaus C. Ewald has been full professor of nature and R., 2002. Resilience management in social-ecological systems: a landscape protection in the Department of Forest and Wood Sciences working hypothesis for a participatory approach. Conserv. Ecol. since 1993 and since 1998 in the Departement of Environmental 6, 14. Sciences of the ETH Zurich. Prof. Ewald studied geography and Walser, C.A., Bart, H.L., 1999. Influence of agriculture on in-stream biology at the University of Basle. From 1977 to 1986 he established habitat and fish community structure in Piedmont watersheds and directed the section of landscape research at the Swiss Federal of the Chattahoochee River System. Ecol. Freshwater Fish 8, Institute for Forest, Snow and Landscape Research (WSL). His main 237–246. research field is the examination of landscape changes in Switzerland.