RIVER RESEARCH AND APPLICATIONS River. Res. Applic. 24: 519–527 (2008) Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/rra.1131 ENVIRONMENTAL FLOW METHODOLOGIES TO PROTECT FISHERIES RESOURCES IN HUMAN-MODIFIED LARGE LOWLAND RIVERS VOLKER HUCKSTORF,* WOLF-CHRISTIAN LEWIN and CHRISTIAN WOLTER Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany ABSTRACT The flow regimes of temperate large lowland rivers are manipulated to provide various services for society. Most water policy decisions are based on economic considerations, with little or no consideration toward fish conservation and fisheries. The prerequisite for a stronger implementation of these interests in water policy decisions is the development of appropriate tools for assessing the adequate flow needed to protect fish diversity and fisheries resources. From the 1970s onwards, environmental flow methodologies (EFMs) have been developed primarily to protect endangered fish species and to maintain fisheries resources in human-modified rivers. Until now, their application had mainly been restricted to small upland rivers and headwater streams. Here, we investigate the applicability of commonly used EFMs for predicting and quantifying the consequences of flow manipulation on fish and fisheries of regulated large lowland rivers. Among the range of environmental flow methods currently available, habitat simulation methods are promising tools to assess adequate flow and to quantify the consequences of flow manipulation on the temporal and spatial availability of littoral habitats important for fish. However, habitat simulation methods may be effective only with those fish species whose recruitment is influenced by the availability of those habitats. To increase prediction accuracy, habitat simulation methods have to be linked to population dynamic models. More research is needed to improve understanding of the mechanisms controlling the dynamics of populations and assemblages in regulated large lowland rivers. Copyright # 2008 John Wiley & Sons, Ltd. key words: channelization; environmental flow; lowland rivers; river fisheries; instream flow methodologies Received August 2006; Revised August 2007; Accepted February 2008 INTRODUCTION Riverine ecosystems are among the most impacted ecosystems worldwide (Malmquist and Rundle, 2002). Human activities, such as the construction of dikes, dams, groynes and weirs, the straightening and deepening of river channels, the conversion of floodplains to agricultural land, water abstraction, water transfer and pollution have heavily modified most large lowland rivers (Dynesius and Nilsson, 1994; Aarts et al., 2004). As a result, a large number of fish species became threatened or endangered and the fish productivity of most riverine ecosystems has declined (Welcomme, 2001; Welcomme and Halls, 2004). This is all the more troubling since, large lowland rivers support a significant proportion of the world’s fish diversity and their fisheries provide a major source of food, employment and income to society. Until now, the flow regimes of most large lowland rivers have been heavily manipulated to serve the needs of society. To balance the interests of different stakeholder groups, many countries have implemented water resources management plans. Water policy decisions are typically made with little or no consideration of fish conservation and fisheries, despite a high public perception of fish. The reason is not only the relative lower socioeconomic importance of fisheries compared to ecosystem services such as flood protection and navigation (Dugan et al., 2002). Whereas the optimal flow regime for navigation, agriculture and flood protection (in terms of magnitude, timing and duration of flow events) is comparably easy to determine, the consequences for fish diversity and fisheries are much more difficult to quantify (Welcomme and Halls, 2004). The magnitude, timing and duration of *Correspondence to: Volker Huckstorf, Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, POB 850 119, D-12561 Berlin, Germany. E-mail: volker.huckstorf@igb-berlin.de Copyright # 2008 John Wiley & Sons, Ltd. 520 V. HUCKSTORF, W.-C. LEWIN AND C. WOLTER flow events determine inter alia the temporal and spatial availability as well as the connectivity of different physical habitats required by riverine fish during their various life history stages (Welcomme, 1985; Junk et al., 1989). Consequently there is an urgent need for appropriate predictive tools to quantify the consequences of flow manipulation for fish and fisheries, in particular, against the background of climate warming and human population growth, both causing further hydrological degradation of riverine ecosystems worldwide and increasing water scarcity (Gleick, 1993; Postel et al., 1996; Walther et al., 2002; Daufresne et al., 2003; Hari et al., 2006). A wide range of environmental flow methodologies (EFMs) have been developed to determine flow thresholds for various objectives such as the preservation of natural conditions (Brown, 1991), the maintenance or restoration of ecological integrity (Ward et al., 1999; Whiting, 2002; Richter et al., 2003; Rood et al., 2005) and cultural and recreational values (e.g. Brown and Daniel, 1991, Brown et al., 1991; Duffield et al., 1992). Most of these methods were developed primarily to protect endangered fish species and to maintain fisheries resources in human-modified rivers (Arthington et al., 2003a). Until now, these methodologies have been mostly applied to small upland rivers and headwater streams. Although a growing body of literature summarizes the status of available EFMs (e.g. Dunbar et al., 1998; Arthington et al., 2003a; King et al., 2003; Tharme, 2003; Acreman and Dunbar, 2004), the question remains whether or not these EFMs are suitable to protect fish diversity and fisheries resources in regulated large lowland rivers. This paper describes some of the most commonly used EFMs, discusses their suitability for assessing an adequate flow under the specific conditions of regulated large lowland rivers and outlines areas for further research. ENVIRONMENTAL FLOW METHODOLOGIES Most currently available EFMs can be grouped in four main categories: hydrological methods, hydraulic rating, habitat simulation methods and holistic methodologies (e.g. King et al., 2003; Tharme, 2003). In European countries, hydrological and habitat simulation are the prevailing methods, while some developing countries and countries with newer environmental legislation have focussed on holistic methods (Tharme, 2003; Acreman and Dunbar, 2004).Hydrological methods rely primarily on flow measures and indices, which are drawn from historical time series data on annual or daily mean flow (Smakhtin and Toulouse, 1998). Still widely used is the Tennant method (also known as Montana method), which relates the ratio between river discharge and fish habitat availability to certain percentages of annual flows to meet predefined requirements (Tennant, 1976). The Tennant method assumes similarity of aquatic habitats when carrying the same proportion of average flow but rarely considered the effective habitat quality at varying flows. The method lists eight categories of instream flow that range from maximum to severe degradation. Below the threshold of 10% mean flow, the environmental conditions for fish are judged to be degraded, whereas 50% provides for excellent conditions in terms of stream width, water depth and velocity. While the Tennant method does not explicitly consider duration or the timing of flow events, some extensions integrate flow duration and frequencies (Richter et al., 1997; Smakhtin, 2001 for review). Other hydrological methods include duration percentiles or single flow indices that are usually generated from historical stream flow databases. One example is the widely used 7Q10, which is defined as the ‘seven-day, consecutive low flow with a ten-year return frequency; the lowest stream flow for seven consecutive days that would be expected to occur once in ten years’ (United States Environmental Protection Agency) or similar discharge indices (e.g. Lamouroux and Cattanéo, 2006). Hydraulic rating considers the channel morphology of a given river (O’Shea, 1995) and calculates acceptable flows by relating river discharge with a variety of hydraulic characteristics such as water depth, velocity or wetted perimeter. These methods rely on transects measured across a river section comprising habitat factors that are assumed to be limiting factors for target biota (Gippel and Stewardson, 1998). The wetted perimeter method considers the variation in wetted perimeter or river width with water discharge. Plotting the wetted perimeter against discharge shows a breakpoint where a comparable small decrease in discharge results in a comparably larger decrease in wetted perimeter. This breakpoint is used as a minimum instream flow recommendation (see Annear and Conder, 1984). The widely used habitat simulation methods are sophisticated extensions of hydraulic rating methods within a framework addressing many ecological components of riverine ecosystems (IFIM, Instream Flow Incremental Copyright # 2008 John Wiley & Sons, Ltd. River. Res. Applic. 24: 519–527 (2008) DOI: 10.1002/rra ENVIRONMENTAL FLOW METHODOLOGIES 521 Methodology, Bovee, 1982). Within the context of IFIM, a broad range of modelling tools such as PHABSIM aim to predict how physical habitat conditions (i.e. water depth, velocity, cover, substrata) change with discharge (Bovee, 1982). Typically, detailed hydrological and hydraulic data for a grid of cells in a river stretch are compared with the habitat suitability of a target species. The habitat suitability is expressed as a habitat suitability curve (e.g. suitability index curve, probability of use or preference curve), often seasonally defined, which specifies the assumed seasonal requirements of different species, life stages or habitat guilds (e.g. Aadland, 1993; Jowett, 1997; Lamouroux et al., 1999; Welcomme et al., 2006). The curves depict the relationship of target organism’s response to a gradual changing habitat variable scaling from unsuitable to suitable, which are usually obtained from existing data or field measurements. By comparing the curves with the predicted habitat area at various flows, the minimum flow thresholds can be defined in a way so that the discharge provides optimal habitat conditions, retains a percentage of habitats at average flow or provides a minimum amount of habitat area. Most commonly, the flow threshold is set at the breakpoint in the habitat/flow curve where proportionally more habitat is lost with decreasing flow than is gained with increasing flow (Jowett, 1997). The commonly used output of, for example PHABSIM quantifies the suitability of a location for a target species in terms of a weighted usable area (WUA; expressed as, e.g. m2 1000 m stream length
1). More advanced software tools such as 2D and 3D models achieve greater hydraulic representation. Other models allow for inclusion of water quality, temperature and other biological factors such as prey densities, energy allocation and behavioural components (Leclerc et al., 1995; Hardy, 1998; Lamouroux et al., 1998; Nestler and Sutton, 2000; Guensch et al., 2001; Parasiewicz and Dunbar, 2001; Booker, 2003; Booker et al., 2004; Mouton et al., 2007). The complexity of current models is growing (Ghanem et al., 1996; Extence et al., 1999; Crowder and Diplas, 2000; Blackburn and Steffler, 2002) and there are many approaches to establish statistical techniques that improve the predictability of species abundance on the basis of biotic and abiotic variables (see Ahmadi-Nedushan et al., 2006 for details). The growing recognition that rivers are closely connected to their watersheds has led to the realization that protecting and rehabilitating riverine ecosystems requires sensitivity not only to the key hydrological, biological and ecological, but also to the economic and social aspects of a riverine ecosystem (Arthington, 1998; Arthington et al., 1998). Assuming that a natural flow system will maintain the ecological function of a riverine ecosystem (Poff et al., 1997; Arthington et al., 2006), so-called holistic methodologies will define the critical environmental flows of an entire riverine ecosystem (Ward et al., 2001) rather than focussing on the needs of a single species. Holistic methods rely less on modelling and more on multidisciplinary panels covering biophysical disciplines such as hydrology, geomorphology, sedimentology, water chemistry, botany and zoology. Advanced methodologies such as DRIFT (Downstream Response to Intended Flow Transformations Methodology, King et al., 2003) consist of different modules that integrate biophysical, and economic and social factors (Arthington et al., 2003c; King et al., 2003) and aim at participating stakeholder groups (Acreman and Dunbar, 2004). Within the biophysical module, various EFMs such as habitat-modelling tools can also be implemented. CRITICISM OF THE METHODOLOGIES The underlying assumption of all EFMs is that the biomass or abundance of a target species is directly related to the availability of fish habitats, which are directly affected by changes in flow. However, EFMs differ in their aspects of ecosystem considered and the amount of data required for assessing environmental flow. One has to bear in mind that the effect of flow on fish habitats is controlled by channel morphology (e.g. width, depth) and the roughness, respectively, complexity of physical structures (e.g. pool-riffle-structure, macrophytes, woody debris). In regulated large lowland rivers, woody debris and macrophytes, which are substantial for fish recruitment (Crook and Robertson, 1999; Berrebi-dit-Thomas et al., 2001; Jurajda et al., 2001; Schiemer et al., 2002), are usually confined to the narrow edge of a stabilized riverbank. Even a slight decrease in water level might result in a loss of these habitats (Bischoff, 2002; Wolter and Menzel, 2005). In addition, river engineering has to a certain extent decoupled the physical correlation between discharge and discharge-dependent hydrological parameters (e.g. wetted area, water level, velocity, water temperature) of regulated large lowland rivers (Busch, 2006). The collection of biological data from large lowland rivers is time and labour intensive (Persat and Copp, 1990). Therefore, hydrological methods and hydraulic rating were judged as rapid, resource saving and appropriate when Copyright # 2008 John Wiley & Sons, Ltd. River. Res. Applic. 24: 519–527 (2008) DOI: 10.1002/rra 522 V. HUCKSTORF, W.-C. LEWIN AND C. WOLTER data are limited (Tharme, 2003). However, both methods seem questionable at the above-mentioned river conditions. For example, an excellent flow after Tennant (1976) may not be sufficient to provide access to littoral instream habitat structures. Hydraulic rating presents an improvement of hydrological methods that considers the channel morphology of individual rivers. However, these methods can be affected by constraints associated with interpretation of the discharge-wetted perimeter plot because the breakpoint is often defined on a subjective basis which may be additionally complicated if the curve reveals no clearly defined breakpoints (Annear and Conder, 1984). More specifically, because the effects of flow depend on the river’s morphology, the recommended flow may be sufficient to achieve or maintain a large wetted perimeter but the water depth and velocity may be unsuitable for the target species (Jowett, 1997). This may be particularly important in canalized large lowland rivers where refuge habitats against displacement are rare (Wolter, 2001). In regulated large lowland rivers, which are typically characterized by stabilized riverbanks with a uniform slope, a graphical representation of wetted perimeter against water level or discharge will be linear as long as the water level does not exceed the bank full discharge. The plot therefore fails to show the breakpoint when littoral vegetation becomes dewatered. Most important, hydrological methods and hydraulic rating methods do not directly take into account the habitat requirements of a target species (Gippel and Stewardson, 1998). Therefore, none of these methods provides a sufficient basis for prediction and quantification of the consequences of flow manipulation on fish diversity and fisheries resources. By allowing for the direct assessment of habitat availability and taking into account the habitat requirements of target species and their different life history stages in a variety of flow regimes (Cavendish and Duncan, 1986), habitat simulation methods provide a promising tool. However, discharge-dependent habitat modelling is a controversial issue (Castleberry et al., 1996; Railsback, 1999; Hudson et al., 2003) and the methods share some deficiencies irrespective of the types of rivers to which they are applied. In general, the underlying assumption that the suitability of microhabitats is determined by measured variables is not always well evaluated. The spatial precision of the parameter measurement and definition of representative and critical habitats may also be complicated by the longitudinal and temporal variability of channel characters (Williams, 1996). The comparison of use probability curves with the predicted habitat area may be additionally complicated by the fact that habitat choice and optimum values may be influenced by a particular flow regime (Shirvell, 1990, 1994; Holm et al., 2001). Neither the positive relation between fish biomass or abundance and habitat area nor the underlying assumption that fish prefer specific habitats independent of other excluded variables, is always well evaluated (Mathur et al., 1985; Gore and Nestler, 1988). There are also indications that fish may not always be able to discriminate between flow qualities or that habitat choice may be influenced by behavioural characteristics, site fidelities or other physical and biological factors (Halleraker et al., 2003; Kemp et al., 2003). More specifically, because of the uniformity of flow patterns in the main channel of large lowland rivers (Beavan et al., 2001; Wolter, 2001), modelling tools such as PHABSIM are not able to detect differences in physical habitat conditions within a grid of cells for the largest part of a lowland river main channel and can only predict changes in the availability of littoral habitats under various flow regimes. Although large lowland rivers are characterized by a large number of fish species (e.g. Arthington et al., 2003b; Aarts et al., 2004), habitat simulation models usually focus on a certain target species. The selection of target species is often biased by favouring species of greater recreational or commercial importance such as salmonids (e.g. Capra et al., 1995; Spence and Hickley, 2000; Souchon and Capra, 2004). In contrast, cyprinids typically dominating the fish communities of large lowland rivers commonly receive less attention (Booker and Dunbar, 2004), and the importance of rare and endangered species with lesser known habitat requirements are underestimated (Jowett and Richardson, 1995). Furthermore, habitat simulation models widely ignore biological interactions among fish (e.g. inter- and intra-specific predation and competition) which results in a loss of prediction accuracy. Holistic approaches aiming to address ecological as well as socioeconomic components of entire river catchments may be the best way to protect fish diversity and fisheries resources and to minimize stakeholder conflicts. Such an approach can incorporate habitat simulation methods. However, existing approaches are disposed in their place of origin and only local critiques are provided in the literature (Tharme, 2003). At present, the holistic approach can be seen more as a philosophical framework than as a set of well-defined methods. Predetermined targets such as ‘ecosystem health’ on a catchment scale cannot easily be translated into quantitative thresholds for flow management of regulated large lowland rivers. Furthermore, the holistic approach might be biased by differences in precision and accuracy of its modules, physical modules compared to ecological. Copyright # 2008 John Wiley & Sons, Ltd. River. Res. Applic. 24: 519–527 (2008) DOI: 10.1002/rra ENVIRONMENTAL FLOW METHODOLOGIES 523 FUTURE PERSPECTIVES Although protection and restoration of natural river flow regimes is becoming a major focus of river basin management (Poff et al., 1997; Thoms, 2006), several societal needs prevent restoration of riverine ecosystems to pristine conditions (Cowx and Van Zyll de Jong, 2004). Predicting the dynamics of fish populations and assemblages under different flow regimes is a prerequisite for assessing an adequate flow to protect fish diversity and fish resources in regulated large lowland rivers (Winemiller et al., 2004a). However, this is a complex task which requires detailed knowledge of the mechanisms regulating the population dynamics of riverine fish, which is relatively limited. Accordingly, only basic approaches have been used to quantify and predict the consequences of flow manipulation on fish assemblages and fisheries resources in large lowland rivers (Winemiller et al., 2004a,b). As long as adequate predicting tools are not available, the first step in a short-term solution is to replace EFMs which focus solely on hydrological parameters. The discharge-dependent modelling of habitat availability is a promising tool, as long as the recruitment of a target species is directly related to availability of riparian habitats and their connectivity. However, habitat simulation models should be adapted to a large-scale management by inclusion of modern land survey techniques and large-scale hydraulic mapping that has been applied to upland rivers (e.g. Parasiewicz, 2001; Halleraker et al., 2007). Furthermore, they should overcome the single-species approach (see Lamouroux et al., 2006). Future extensions should take a multi-species approach similar to recent development in fisheries management (e.g. Link, 2002). As long as the models are unable to cope with a high number of species, models focussing on ‘umbrella species’ (Simberloff, 1998) or fish habitat guilds (Leonard and Orth, 1988; Lamouroux and Souchon, 2002; Welcomme et al., 2006) represent a preliminary compromise. However, because approaches that are based only on single components of a fish community are often subject to uncertainty (Olver et al., 1995; Roberge and Angelstam, 2004). Monitoring the outcomes of flow management is indispensable. Over the long term, the linkage between habitat simulation models and dynamic population models is essential to improve the prediction of fish population dynamics under various flow regimes. Such an approach should also include the effects of fisheries on the population dynamics of fish (e.g. Halls et al., 2001). Future research should broaden our knowledge of inter- and intra-specific interactions potentially controlling the population dynamics of large lowland rivers. The effects of flow manipulation on a single species or age group may cascade through the food web, which could complicate the assessment of these effects in particular for those occurring at higher trophic levels (e.g. Wolter and Menzel, 2005). Fisheries as well as fish ecological research typically focus on the 0þ fish, the most sensitive life stages, and on the spawning stock, whilst studies of the age groups in between are rare. However, numerous bottlenecks (i.e. competitive, food, predation, shelter) may affect the older juvenile or early mature life stage. Impacts at these life history stages might become increasingly important in human modified rivers (see Wolter and Menzel, 2005 for an example), and especially, if management actions focus on spawning grounds and nurseries. Additional research should also focus on the habitat requirements of old life stages that ensure the survival of a population under variable environmental conditions (Longhurst, 2002; Berkeley et al., 2004a,b; Bobko and Berkeley, 2004). Future research and management actions should concentrate on habitat improvement (e.g. the restoration of spawning, feeding and refuge habitats). In particular, if an adequate flow is not enforceable, habitat improvement can mitigate negative effects on fish diversity and fisheries (Cowx and Welcomme, 1998; Roni et al., 2002, 2005; Pretty et al., 2003). For example, a rehabilitation of 20% of the bank line in an artificial waterway may lead to a substantial improvement of environmental conditions for fish diversity and persistence of a fish community (Wolter, 2001). To sum up, habitat simulation methods are the most promising tool for the quantification and prediction of the consequences of flow manipulation on fish diversity and fisheries resources in regulated large lowland rivers. Holistic approaches build a framework in which habitat-modelling tools can be integrated. However, more research is needed to improve understanding of the mechanisms controlling the fish population dynamics in regulated large lowland rivers as a prerequisite for a further development of the predicting tools. As long as uncertainties about the effects of flow management on river ecology persist, a precautionary approach based on scientific research should explicitly consider the long-term consequences of flow management. An active, adaptive management practice is required, which should be based on a collection of key, river specific data (see Richter et al., 2006 for details), a Copyright # 2008 John Wiley & Sons, Ltd. River. Res. 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