Environmental Management (2013) 52:1–18 DOI 10.1007/s00267-013-0070-4

PROFILE

Braided River Flow and Invasive Vegetation Dynamics in the Southern Alps, New Zealand Brian S. Caruso • Laura Edmondson Callum Pithie

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Received: 19 January 2012 / Accepted: 4 May 2013 / Published online: 22 May 2013  Springer Science+Business Media New York 2013

Abstract In mountain braided rivers, extreme flow variability, floods and high flow pulses are fundamental elements of natural flow regimes and drivers of floodplain processes, understanding of which is essential for management and restoration. This study evaluated flow dynamics and invasive vegetation characteristics and changes in the Ahuriri River, a free-flowing braided, gravel-bed river in the Southern Alps of New Zealand’s South Island. Sixty-seven flow metrics based on indicators of hydrologic alteration and environmental flow components (extreme low flows, low flows, high flow pulses, small floods and large floods) were analyzed using a 48-year flow record. Changes in the areal cover of floodplain and invasive vegetation classes and patch characteristics over 20 years (1991–2011) were quantified using five sets of aerial photographs, and the correlation between flow metrics and cover changes were evaluated. The river exhibits considerable hydrologic variability characteristic of mountain braided rivers, with large variation in floods and other flow regime metrics. The flow regime, including flood and high flow pulses, has variable effects on floodplain invasive vegetation, and creates dynamic patch mosaics that demonstrate the concepts of a shifting mosaic steady state and biogeomorphic succession. As much as 25 % of the vegetation cover was removed by the largest flood on record (570 m3/s, *50-year return period), with preferential removal of lupin and less removal of willow. However, most of the vegetation regenerated and spread relatively quickly after floods. Some flow metrics analyzed were highly correlated with vegetation cover, and key

B. S. Caruso (&)
L. Edmondson
C. Pithie Civil and Natural Resources Engineering, University of Canterbury, Private Bag 4800, Christchurch, Canterbury 8140, New Zealand e-mail: [email protected]

metrics included the peak magnitude of the largest flood, flood frequency, and time since the last flood in the interval between photos. These metrics provided a simple multiple regression model of invasive vegetation cover in the aerial photos evaluated. Our analysis of relationships among flow regimes and invasive vegetation cover has implications for braided rivers impacted by hydroelectric power production, where increases in invasive vegetation cover are typically greater than in unimpacted rivers. Keywords Mountains
Braided rivers
Floodplains
Riparian vegetation
Invasive vegetation
New Zealand

Introduction Natural flow regimes are fundamental to the ecological integrity of rivers and streams (Poff and others 1997; Richter and others 1997). The flood and flow pulse concepts also recognize that discharge variability is the primary driver of floodplain ecological processes (Junk and others 1989; Tockner and others 2000; Mathews and Richter 2007). Braided, gravel-bed rivers and associated wetlands in montane basins are dynamic aquatic systems characterized by highly variable flows and alluvial channels in wide floodplains with numerous channels, bars and islands (Mosley 1982, 1983; Bristow and Best 1993). These floodplain ecosystems are complex mosaics with shifting surface water–groundwater interactions in deep gravel hyporheic zones (White and others 2001); interactions between side channels, springs and adjacent wetlands (Gray 2005); plant and animal species highly adapted to extremely variable flows and morphology (Gray and others 2006; Tockner and others 2009); and exotic/invasive plants in newly formed substrates outcompeting some native

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species (Caruso 2006a; Gray and Harding 2007). High and varying discharge drives very high sediment transport rates that change floodplain morphology in complex ways involving variable erosion and deposition in three dimensions and constantly shifting channels, bars and islands (Mosley 1983; Brasington and others 2000; Lane and others 2003). Floods and high flow pulses can also greatly influence and regulate the movement and redistribution of nutrients and other chemicals, organic matter, plants and animals, and can have profound effects on riparian and riverine habitat and aquatic biota such as availability of spawning areas, refugia and removal and redistribution of populations (van der Nat and others 2002, 2003; Malard and others 2006; Tockner and others 2009). Although fluvial geomorphology and sediment movement in braided river floodplains have been well studied, quantification of the full natural flow regime of these systems has received little attention. Alluvial floodplain rivers are recognized to be in a shifting-mosaic steady state with dynamic patch mosaics comprised of natural transient patches (Latterell and others 2006). These patches are produced by the interactions of water and sediment movement and variation and vegetation succession, and are in different developmental states where the proportion of each state remains relatively constant over large scales and long time periods, despite continuing processes of fluvial disturbance and vegetation succession at smaller scales (Latterell and others 2006). The two-way interactions between fluvial landforms and riparian vegetation communities are described by the concept of ‘fluvial biogeomorphic succession’ (Corenblit and others 2007). This concept links fluvial landforms with riparian community evolution within a bi-directional model with succession of fluvial landforms and vegetation comprised of phases representing a shift in the dominance of hydrogeomorphical and ecological processes with positive feedbacks (Corenblit and others 2007). Vegetation has a large effect on roughness, water velocities and shear stress, and affects channel morphology by increasing the resistance of banks to erosion and sediment entrainment. At the same time, rivers affect riparian vegetation through processes such as seed dispersal, scouring and shearing during floods (Murray and Paola 2003; Corenblit and others 2007). In braided rivers, vegetation exerts significant influence on channel geometry, braiding and island dynamics that results in distinct topographical signatures (Gurnell and others 2001; Gran and Paola 2001; Coulthard 2005; Bertoldi and others 2011a). Vegetation patch mosaic dynamics are influenced by geomorphological setting, flow regime, sediment supply and surface–groundwater connectivity, and plants can act as ecological engineers through self organization by trapping and stabilizing sediments, organic matter and propagules, and driving landform and habitat development (Francis and

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others 2009; Gurnell and others 2012). Vegetation changes and dynamics, particularly colonizing trees and shrub pioneer species, can vary considerably over space and time in response to river flows and floods (Bertoldi and others 2011b). Riparian vegetation in many braided river floodplains and catchments disturbed by human activities includes exotic, invasive plant species which may constitute a large proportion of the vegetative cover and threaten the ecological integrity of these ecosystems (Shafroth and others 2002; Caruso 2006a). However, the interactions between flows and invasive vegetation, and effects of floods on invasive vegetation ecology and removal, have not been studied in any detail in these systems. Braided rivers in the Southern Alps of New Zealand are unique, globally important ecosystems that provide critical habitat to numerous native wading and shore bird species, including several threatened or endangered species. Degradation of these floodplains due to invasive vegetation leads to severe adverse impacts on these birds, including increased cover for exotic predators which decimate bird populations, and stabilization of islands and reduction of the bare, shifting gravels these highly-adapted species rely on for habitat (Peat and Patrick 2001; Gray and Harding 2007). Invasive vegetation is a major problem in terrestrial and aquatic environments throughout New Zealand (Owens 1998) which has resulted in a significant decline in native flora and fauna and biodiversity, and extreme limitations on restoration of riverine and other habitats (Williams and Wiser 2004; Norton 2009). The objectives of this study were to (1) quantify flow regimes and some of the important flow and floodplain vegetation dynamics in a montane, braided gravel-bed river using a free-flowing river as a case study, and (2) analyze changes in invasive vegetation characteristics across a reach of this floodplain in response to historical flow regimes and floods using a series of historical aerial photographs over a 20-year period from 1991 to 2011.

Methods Study Area The study area is a reach of the Ahuriri River in the Southern Alps, South Island, New Zealand (Fig. 1). This is one of the last free-flowing rivers in the Upper Waitaki River Basin (UWB), a montane basin in the Canterbury region where braided, gravel-bed rivers predominate, providing 13 % of the total area of braided rivers in New Zealand (Wilson 2001). Water in the UWB is used for hydroelectric power (HEP) generation producing *8000 GWh (20–25 % of New Zealand’s total power) annually from eight power stations (Woolmore and Sanders

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Fig. 1 Location of the lower Ahuriri River in the upper Waitaki Basin, South Island, New Zealand. The figure shows the NIWA flow gauging station (South Diadem gauge) and the 1,100 m study reach

2005). As in fluvial systems throughout the world, however, dams and storage and diversion of water in the UWB have caused segmentation of rivers, severe alteration of flow and sediment regimes, and subsequent degradation of aquatic ecological systems (Williams and Wolman 1984; Petts 1984; Petts and Gurnell 2005; Nilsson and others 2005). The primary invasive vegetation species in floodplains impacted by HEP, as well as free-flowing river floodplains like the Ahuriri, include crack willow (Salix fragilis), Russell lupin (Lupinus polyphyllus), gorse (Ulex europaeus), broom (Cytisus scoparius) and sweet brier (Rosa rubiginosa) (Caruso 2006a). Threatened or endangered species impacted include the black stilt (Himantopus novaezelandiae), wrybill (Anarhynchus frontalis), other fauna such as the native fish upland longjaw galaxias (Galaxias prognathus), and low-lying native plants such as the mat daisy (Raoulia australis) and the moss-like Scleranthus uniflorus, that are specially adapted to the extreme flow variability and floods (Peat and Patrick 2001). Exotic predators that use invasive vegetation as cover to prey on native fauna include stoats (Mustela ermine), ferrets (Mustela furo) and feral cats. Project River Recovery (PRR) is an ecological restoration program initiated by Meridian Energy and the Department of Conservation (DOC) in 1991 to restore wetland and riverine habitats affected by HEP development in the UWB (Peat and Patrick 2001; Caruso 2006a). A significant component of the project involves control of invasive vegetation through mechanical and chemical

means in free-flowing, more pristine river floodplains as a form of compensatory mitigation within the basin. Previous studies have recommended a more holistic, catchmentwide approach to restoration, including more detailed analysis of hydrological and geomorphological processes that may affect floodplain ecology and restoration (Caruso 2006b). Although DOC expends a significant amount of project resources on weed management, large floods have a significant impact on these floodplain ecosystems and may naturally remove a large proportion of invasive vegetation. In some braided rivers impacted by dams, floods are not able to turn over the bed fast enough to contain vegetation encroachment and spraying pest plants for control is required, while in other unimpacted rivers even sub-annual floods turn over large parts of the floodplain (Hicks and others 2007). The Ahuriri River catchment forms the southwestern boundary of the basin. Numerous parts of the floodplain in the lower half of the catchment are impacted by invasive vegetation due to seed and propagule sources in the catchment. The invasive vegetation species that DOC is most interested in managing in the river are crack willow, Russell lupin and sweet briar. The river is therefore a useful case study of the natural flow regime and invasive vegetation dynamics in braided river floodplains. The headwaters are at the Southern Alps main divide and the river is 70 km long, flowing by the township of Omarama near State Highway 8 (Fig. 1). The river discharges to Lake Benmore, a man-made HEP reservoir upstream from the

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Waitaki River at the UWB outlet. The catchment ranges in elevation from 380 to 2,200 m above sea level (asl) and is 1,310 km2 in area. Annual precipitation varies from 500 mm near Omarama to 6,400 mm in the highest headwaters near the Southern Alps main divide, and the catchment is semi-arid. A flow gauging station operated by the National Institute of Water and Atmospheric Research (NIWA; Ahuriri at South Diadem, number 71116) is located in a gorge which separates the upper catchment from the lower catchment (Fig. 1). Flow data are collected at 15-min intervals and used to calculate the minimum, mean and maximum daily flows. The river has some braiding in the upper catchment, but braiding and invasive plant cover becomes much more pronounced in the lower catchment. Land cover in the upper catchment is 46 % tussock grasslands, 31 % low- and high-producing grasslands (with some pastoral sheep grazing) and 17 % alpine gravel and rock (Landcare Research 2010; Caruso and others 2013). Higher elevations are periodically snow covered with a small percentage of permanent snow and ice with several small glaciers (the largest of which is the Thurneysen Glacier). The lower catchment has a mix of low-producing grassland/pasture and high-producing exotic grassland/pasture for sheep and beef cattle grazing, exotic shrubland and some native tussock grassland. Mean annual flow at the gauge is 23.3 m3/s based on a period of record of 48 years (1963–2009). The river exhibits considerable flow seasonality with the greatest flows in spring (Oct–Dec) due to snowmelt, and the flood season generally extends from late spring until mid-summer (Nov–Feb). The study was conducted on a representative reach of the lower Ahuriri River immediately downstream from where the river exits the gorge. The reach is 1,100 m in length with a floodplain width of roughly 500 m, and was selected based on a number of factors, including representative channel sinuosity and braiding, extent of invasive vegetation cover, accessibility of the river and availability of safe crossing points across the primary channels. Results of a 2011 Wolman pebble count (Wolman 1954) for bed surface particle size distribution in the study reach showed that the d50 of the 1500 particles measured was 44 mm. The d90 was 136 mm with the upper 10 % of particles comprised of a combination of cobbles and boulders, while the d10 was 5.1 mm with the lower 10 % comprised of fine gravel, sands or finer materials. The surface substrate is mostly coarse or very coarse gravel, extremely poorly sorted, very coarsely skewed and leptokurtic or very leptokurtic. Gorse and broom do not occur in this reach and are generally only present in lower elevation floodplains. Sweet briar occurs in some much localized places in this reach and comprises a very small proportion of all the vegetation (estimated at \2 %). The exotic grass Agrostis stolonifera (Creeping Bent) is strongly associated with grassland communities,

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which are pasture grasses and all other herbaceous species at ground level, and consistently contributes to total vegetation cover in this reach. These invasive species constitute more than 92 % of the total vegetation in this part of the Ahuriri River floodplain (Woolmore 2011). Flow Regime and Flood Data Analysis We used historical flow data from the gauge to analyze the flow regime and floods from the upper catchment discharging to the lower catchment study reach. Mean, maximum and minimum daily flow data for the Ahuriri at South Diadem gauge were obtained from NIWA for the period of record from 30 September 1963 to 30 September 2011. In the southern hemisphere, the year commencing July 1 and ending June 30 was selected as the hydrological year for analysis. This is the water year used by Environment Canterbury, the Regional Council responsible for river monitoring and management in this region of New Zealand. The characteristics of the Ahuriri River flows and floods were analyzed using the indicators of hydrologic alteration (IHA) software package (Richter and others 1996; The Nature Conservancy 2009). This program calculates 33 ecologically relevant flow statistics derived from daily hydrologic data, such as average monthly flows and the magnitude, frequency, duration and timing of monthly maximum and minimum flows (Table 1). The environmental flow components (EFC) portion of IHA was also used to compute another 34 key flow metrics involving the classification and statistical analysis of the characteristics of monthly low flows and five other flow components: extreme low flows, low flows, high flow pulses, small floods and large floods (Table 2; Mathews and Richter 2007). The IHA and EFC metrics are computed for each year. For the purposes of this study, the average of each metric was computed for the interval between each aerial photo. For the first photo in 1991, the 10-year period from 1981 was used for analysis. A nonparametric statistical analysis was used due to the skewed nature of most hydrological datasets. For the IHA metrics, maximum daily flow values from the gauge were used for evaluation of maximum flow, high flow and flood peaks, and mean daily flow data were used for all other metrics. We used IHA default values for the percentiles or flow thresholds for EFC classification (The Nature Conservancy 2009). To derive these values, flow duration curves (FDC) were first developed to estimate the nonexceedance probabilities for mean and maximum daily flows. The initial classification step for EFC involved distinguishing between high and low flows. The 75th percentile of maximum daily flow values was used as the threshold to classify high flows above this value and low flows below it. The high flows were then categorized into either small or large floods. The 2-year

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Table 1 Indicators of hydrologic alteration (IHA) metrics and rationale for analysis used in this study (modified from The Nature Conservancy 2009) IHA metric

Hydrologic parameters

Rationale for analysis

Magnitude of monthly water conditions

Median value for each month

• Habitat availability and soil moisture availability for floodplain plants • Access by predators to bird nesting sites

Magnitude and duration of annual extreme water conditions

Annual minima, 1-day mean

• Balance of competitive, ruderal and stress-tolerant organisms

Annual minima, 3-day mean

• Creation of sites for plant colonization

Annual minima, 7-day mean

• Structuring of aquatic ecosystems by abiotic versus biotic factors

Annual minima, 30-day mean

• Structuring of river channel morphology and physical habitat conditions

Annual minima, 90-day mean

• Soil moisture stress in plants • Anaerobic stress in plants

Annual maxima, 1-day mean

• Volume of nutrient exchanges between rivers and floodplains

Annual maxima, 3-day mean

• Distribution of plant communities in floodplains

Annual maxima, 7-day mean Annual maxima, 30-day mean Annual maxima, 90-day mean Number of zero-flow days Base flow index: 7-day minimum flow/mean flow for year Timing of annual extreme water conditions

Julian date of each annual 1-day maximum

• Compatibility with life cycles of organisms • Predictability/avoidability of stress for organisms

Julian date of each annual 1-day minimum

• Bird access to special habitats during reproduction or to avoid predation • Evolution of life history strategies

Frequency and duration of high and low pulses

Number of low pulses within each water year

• Frequency and magnitude of soil moisture stress for plants

Median duration of low pulses (days)

• Frequency and duration of anaerobic stress for plants

Number of high pulses within each water year

• Availability of floodplain habitats for floodplain organisms

Median duration of high pulses (days)

• Soil mineral availability

• Nutrient and organic matter exchanges between river and floodplain • Access for waterbirds to feeding, resting and reproduction sites • Influences bedload transport, channel sediment textures, and duration of substrate disturbance (high pulses)

Rate and frequency of water condition changes

Rise rates: median of all positive differences between consecutive daily values Fall rates: median of all negative differences between consecutive daily values

• Drought stress on plants (falling levels) • Entrapment of organisms on islands, floodplains (rising levels)

Number of hydrologic reversals

and 10-year return period flows were estimated, and flood events with peak flows [10-year flow were classified as large floods, and those with values between the 2- and 10-year flows were classified as small floods. The remaining high flows not in those two classes (\2 year flow) were assigned to the high flow pulse class. Lastly, values \10th

percentile of all daily flow values were assigned to the extreme low flow class, and all those between the 10th and 75th percentile flows were classified as low flows. We also computed the average number of floods per year exceeding three times the median flow (FRE3), and its associated flow value, for the Ahuriri River. This is

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Table 2 Environmental flow component (EFC) metrics and rationale for analysis used in this study (modified from The Nature Conservancy 2009) EFC metric

Rationale for analysis

Extreme low flows

During drought periods, the river drops to very low levels that can be stressful for some floodplain plants and may cause some mortality. On the other hand, extreme low flows may provide necessary conditions for other plants, such as pioneer species, to establish, regenerate, or spread in newly exposed drier or transition areas.

Frequency during each water year Median of extreme low flow events: Duration (days) Peak flow (minimum flow during event) Timing (Julian date of peak flow) Monthly low flows Frequency during each water year Median of extreme low flow events: Duration (days) Peak flow (minimum flow during event) Timing (Julian date of peak flow) High-flow pulses Frequency during each water year Median of high flow pulse events: Duration (days) Peak flow (maximum flow during event) Timing (Julian date of peak flow) Rise and fall rates Small floods Frequency during each water year Median of small flood events: Duration (days) Peak flow (maximum flow during event) Timing (Julian date of peak flow) Rise and fall rates Large floods Frequency during each water year Median of large flood events: Duration (days) Peak flow (maximum flow during event) Timing (Julian date of peak flow) Rise and fall rates

The dominant baseflow condition in the river varying over the year. The river returns to this level after a rainfall event or snowmelt period has passed and associated surface runoff from the catchment has subsided. These flows are sustained by groundwater discharge into the river. The seasonally-varying low-flow levels impose a fundamental constraint on the river’s floodplain communities because they determine the amount of terrestrial and riparian habitat available for most of the year. This has a strong influence on substrate and shallow groundwater moisture levels available for floodplain plants. High-flow pulses include any water rises that do not overtop the channel banks. During rainstorms or brief periods of snowmelt, the river will rise above its low-flow level. These pulses provide important and necessary disruptions in low flows. Even a small or brief flush of fresh water can provide much-needed relief from low water levels and deliver a nourishing subsidy of organic material, nutrients and water to support floodplain plants. High-flow pulses can also move some finer sediment that may be deposited in some areas as new substrate for plant establishment and growth, help disperse seeds and propagules, or remove some younger or weaker plants. Small floods include all river rises that overtop the main channel but do not include more extreme and less frequent floods. During small floods, more water can transport greater amounts of organic material and nutrients and disperse seeds and propagules to areas farther downstream. Greater water velocities and shear stresses, along with greater depths and lateral extent of inundation, can cause more bed and bank erosion with potential removal of plants. Uprooting or ‘drowning’ of some plants may also occur. Larger amounts of coarse as well as fine sediment can be transported that may be deposited as new substrate for plant establishment and growth. Shallow flooded areas are typically warmer than the main channel and full of nutrients that can fuel rapid growth in plants. Extreme floods will typically re-arrange both the biological and physical structure of the river and its floodplain. These large floods can flush away many plants and other organisms, thereby depleting some populations but in many cases also creating new competitive advantages for some species, particularly pioneer and/or invasive species. Seed and propagule dispersal from the catchment to new areas far downstream can occur at a large scale. Very high water velocities, shear stresses, and depths, along with potential inundation across the entire floodplain, can cause significant floodplain erosion and removal of plants. Uprooting or ‘drowning’ of plants will likely occur. Larger amounts of coarse sediment, gravels and boulders will be transported that may be deposited as new substrate for plant establishment and growth. Extreme floods may also be important in forming key habitats such as islands and floodplain wetlands.

considered a useful and ecologically significant measure of the frequency of high flows and indicates the tendency for flow fluctuation, consequently preventing the complete development of aquatic plants and animal communities in many New Zealand rivers (Duncan and Woods 2004; Clausen and Biggs 1997, 1998). The FRE3 and its associated flow were compared with the frequencies and thresholds used to define the high flow pulses, small floods and large floods calculated in EFC.

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In addition to the IHA and EFC metrics, several additional metrics not included in IHA were thought to be very important, and perhaps the major drivers, in determining vegetation cover at the time of each aerial photograph. These were referred to as ‘key’ metrics and included the frequency of floods (number of floods per year), largest flood peak (m3/s), average of all flood peaks (m3/s) and the time (days) since the last flood. These metrics were computed for the interval between each photo.

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Aerial Photograph Temporal Analysis

willow, Russell lupin, grassland, bare substrate and water. Grassland was defined as pasture grasses and all other herbaceous species at ground level to fill in gaps and complete mapping of the floodplain. The associated area and proportion of area relative to the total floodplain boundary area for each cover type were calculated. Ground truthing of the vegetation classification was performed during field reconnaissance for the December 2011 aerial survey.

We used a series of historical aerial photographs to analyse the vegetation, bare substrate and water across the floodplain study reach at the time each photo was taken and changes in invasive vegetation over time. Five sets of aerial photos over a 20-year period from 1991 to 2011 (Apr 1991, Feb 1995, Mar 2000, Mar 2001 and Dec 2011) were available for the study reach and were scanned and imported into ArcGIS Version 9.3. The four sets of photos through 2001 were obtained from PRR records, and the 2011 photos were obtained as part of this study. The photos ranged in scale from 1:6,000 to 1:21,000, and the resolution ranged from 0.3 to 1 m2. Each photo was georeferenced to the NZGD 1949 Lindis Peak Circuit coordinate system. For each aerial photo, the study reach and active floodplain boundary within the reach were delineated between two lines extending across the floodplain, perpendicular to the river flow and between two distinct terraces (Fig. 2). However, this boundary area may not be constant over time due to flood effects, scour and channel lateral migration and channel abandonment. Although the elevation difference between floodplain and terraces on the north and south sides of the river ranges from to 1 to [4 m, there are a few locations of noticeable and significant erosion and sloughing along the terraces, especially on the south side. The braiding intensity for the reach was computed using a channel count index (Howard and others 1970; Hong and Davies 1979) as recommended by Egozi and Ashmore (2008) for each aerial photo. The areal cover of the following classes within the reach floodplain boundary was delineated for each aerial photo in ArcGIS based on manual classification: crack

Statistical Analysis We determined the Pearson correlation coefficient for all IHA and EFC metrics with the areal cover for each floodplain class. The correlation coefficient for each key metric with the cover for each vegetation class was also computed. Multiple regression analysis of the key metrics with the cover for each vegetation class was then performed using linear regression to develop a simple predictive model for invasive vegetation cover. Because there were five sets of aerial photos (data points), the multiple regression analysis could have no more than three independent variables, so the average of all flood peaks was excluded and the largest flood peak was used instead, because it was thought that this parameter would have greater impacts on vegetation cover. Therefore, in each model, the key metrics used were flood frequency, largest flood peak and time since last flood. The areal cover of the vegetation classes was the dependent variable and the flow metrics were the independent variables. The coefficient of determination (R2), P values, and F statistics using ANOVA were computed for each model to evaluate goodness of fit.

Fig. 2 1991 aerial photograph of the Ahuriri River floodplain 1,100-m long study reach with upstream and downstream reach lines and boundary delineated

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Table 3 Summary flow statistics for the upper Ahuriri River at South Diadem gauge (period of record 1963–2011) Flow statistic

Flow (m3/s)

Mean annual flow

23.3

Median annual flow

18.1

Mean annual maximum flow (flood)

242

Mean annual minimum flow

8.5

Mean annual 7-day low flow

8.9

Maximum instantaneous flow

570

Minimum instantaneous flow

6.6

Data source: National Institute of Water and Atmospheric Research Ltd

Fig. 4 Ahuriri River flow duration curve for maximum daily and mean daily flows and environmental flow component thresholds. Data source: National Institute of Water and Atmospheric Research Ltd

Fig. 3 Mean monthly flows (m3/s) for the Ahuriri River at the South Diadem gauge (1963–2001). Data source: National Institute of Water and Atmospheric Research Ltd

Results Flow and Flood Data Analysis The Ahuriri River exhibits a substantial range and variability in flow, with a minimum of 6.6 m3/s and maximum (flood peak) of 570 m3/s (January 2004) over the 48-year period of record (Table 3). This flood was estimated to have a return period of almost 50 years (Caruso and others 2013). The river is characterized by some seasonal variation of flows, as shown by a plot of mean monthly flows (Fig. 3). The FDC shows the estimated nonexceedance probabilities for all flows, including the thresholds for the five EFC flow regimes/classifications for extreme low flows, low flows, high flow pulses, small floods and large floods (Fig. 4). Low flows (or base flows) occur most (64.2 %) of the time, and extreme low flows occur only 10 % of the time. High flow pulses occur 21.7 % of the time, and small and large floods are infrequent, with 2.8 % of all recorded flows being classified as small floods and 1.1 % as large floods. For comparison, the ecologically important FRE3 (annual average frequency of high flows greater than three times the median flow) is nine flow

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events per year that are greater than 54.3 m3/s. Over the period of record, there were 186 daily values classified as large floods and 463 values classified as small floods out of the total of 16,808 daily flow values. These values are included as part of four distinct large floods (flood peaks) and 27 individual small floods. The annual flood varies considerably from year to year (82.3–570 m3/s). A plot of all the large and small floods over time in relation to the dates of the aerial photos is shown in Fig. 5. The mean duration of the different flow components also varies considerably. High flow pulses have a very short duration of only 3 days, while large floods have a duration of 47 days, but both have small duration ranges (Fig. 6). Small floods by far have the greatest range of durations. Low flows have a duration of 339 days, and therefore are not included in Fig. 6. Most flow components, such as low flows and high flow pulses, do not exhibit distinct timing patterns and can occur at any time of year. Extreme low flows typically occur during winter (July–August), have also occurred during spring and autumn, but have never occurred during summer. Although small floods can occur any time of year, large floods (only four) have only occurred in late spring and early summer (December and January) over the 48-year period of record (Fig. 7). Aerial Photograph Temporal Analysis The study reach active floodplain boundary area varied somewhat over the 20-year period in response to the flow regime and floods. The boundary area increased by 3 % between the first two sets of aerial photographs between

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Fig. 5 Ahuriri River large (above upper horizontal line) and small (above lower horizontal line) floods (m3/s) showing the dates of the five aerial photographs, frequency of floods and time since the last flood for each photo

Fig. 6 Ahuriri River environmental flow component durations (days). Main bar for each component shows mean and error bars show range (minimum and maximum). Data source: National Institute of Water and Atmospheric Research Ltd

December 4 1991 and February 13 1995, after the largest flood on record (Table 4; Fig. 8a). Most of this increase resulted from a widening of the floodplain to the south at the upstream boundary were the main channel and flow shifted south, eroding the banks towards Highway 8 (Fig. 9). The boundary area remained relatively constant between 1995 and 2001, even though there was another large flood (509 m3/s) in December 1995. During this period, the widening on the southern boundary expanded downstream for 0.5 km, and an area to the north at the downstream boundary became abandoned as most flow occurred in the southern portion. This widening in the southwest was essentially balanced by the narrowing in the northeast, resulting in a constant floodplain area between 1995 and 2001. By 2011, however, the floodplain area increased again, primarily due to re-occupation of the previously abandoned northeastern area. The areal cover of water was similar (13–16 % of the total floodplain area) during all five sets of aerial photographs, with flows at the time of the photos ranging from 15 to 20 m3/s (Table 4; Fig. 8a). In 1991, there was one main channel along the northern floodplain boundary, with

a few smaller channels (Fig. 9). By 1995, after the largest flood on record, the main channel in the upper third of the reach migrated laterally to the extreme southern boundary, crossed through the middle part of the reach towards the north, and then remained positioned farther south than the 1991 channel. By 2000, 4 years after the second large flood, there was much more braiding apparent. In 2001, there was little difference in channel locations compared to 2000, but by 2011, the main channel and most side channels occupied the southern half of the reach. The braiding index showed considerable variability over time and decreased slightly between 1991 and 1995 from 22 to 21 over the reach, and then increased to 38 by 2000. It then decreased to 23 in 2001, and increased again to 28 by 2011. The relative areal cover of total vegetation and bare substrate in the study reach floodplain, varied considerably over the 20-year period. Vegetation cover comprised a third of the total floodplain area on average and bare substrate made up slightly more than half of the area, with water comprising the remainder (Table 4; Fig. 8a). Between 1991 and 1995 after the largest flood recorded, total vegetation decreased by 25 %, and then decreased again by 2000, 4 years after the subsequent 509 m3/s flood. However, a 377 m3/s flood also occurred in November 1999, 3 months before the 2000 photos, which likely contributed to the vegetation decline observed. By 2011, total vegetation increased by 80 %, after more than 15 years without any floods [380 m3/s. The proportion of bare substrate followed an opposite pattern to that of vegetation, with a large increase between 1991 and 2000 after the two large floods, and then a decrease through 2011. The relative areal cover of different invasive vegetation classes in the reach also changed significantly from 1991 to 2011. On average, grassland comprised most of the total vegetation cover in the floodplain, and Russell lupin comprised the least (Table 4; Fig. 8a). Cover for all vegetation classes decreased between 1991 and 1995 after the

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types, there was a notable increase in number of patches between 2001 and 2011 after 15 years with no large floods. Average patch size showed an opposite pattern to the number of patches between years for all vegetation classes. Statistical Analysis

Fig. 7 Day of year and peak flow for all Ahuriri River small and large floods ([220 m3/s). Day 1 is January 1. Data source: National Institute of Water and Atmospheric Research Ltd

largest flood, with lupin decreasing most and willow decreasing least. While willow and grassland continued to decrease between 1995 and 2000 after another large flood, lupin increased considerably. Between 2000 and 2011, when no large floods occurred, all vegetation types increased with willow almost doubling in area and lupin increasing by over 250 %. Grassland increased between 2000 and 2001, and then remained relatively constant from 2001 to 2011. Over the 1991–2011 period, the number of patches and average patch size for the different vegetation classes varied even more than the aerial cover. On average, willow had the greatest number of patches (107 or 51 % of total vegetation patches), while grassland and lupin had 68 and 34 patches, respectively (Fig. 8b). Willow had the smallest average patch size (540 ha), and grassland exhibited the largest size (1,622 ha; Fig. 8c). The number of willow patches tripled from 1991 to 1995 after the largest flood, decreased by 2001, and then increased by[300 % by 2011. Lupin and grassland both exhibited alternating decreases and increases in patch size between intervals. For all plant

Pearson correlation coefficients for flow metrics and vegetation class areal cover showed that large flood metrics (such as rise and fall rates and duration) had relatively large positive correlation with cover for the different vegetation classes (Table 5a). However, there were only three large floods since 1981, so this small sample size may be discounted. There were six flow metrics with a correlation coefficient [0.5 common to willow and lupin, and eight metrics with a correlation coefficient \-0.5 common to these two classes. Grassland had only one flow metric with a correlation coefficient [0.5 in common with both willow and lupin, and one metric with a value \-0.5 in common with these species. Four of the metrics with the highest positive correlation with total vegetation cover were also common to willow and lupin. Likewise, four metrics with the greatest negative correlation with total vegetation cover were also common to these two classes. Other factors also correlated with total vegetation cover, but to a lesser extent. Calculation of Pearson correlation coefficients between the key flow metrics and vegetation class areal cover resulted in values\-0.5 for the largest flood peak with willow and lupin, and values \-0.5 for the average flood peak with lupin (Table 5b). These two flow metrics did not have high negative correlation with grassland. Grassland had greater positive correlation with flood frequency and the time since the last flood. The time since last flood and total vegetation also had a correlation coefficient[0.5, and average flood peak and total vegetation had a correlation coefficient \-0.5. Substrate showed an opposite pattern to total vegetation. Multiple regression analysis using these key flow metrics generally resulted in good fits between predicted and observed areal cover values for all vegetation classes with R2 values ranging

Table 4 Summary of changes between aerial photographs in areal cover (m2) and percent of total area for floodplain class, and averages over 20-year period D1991–1995 m2

D1995–2000 m2

%

D2000–2001 m2

%

D2001–2011 m2

%

Avg 1991–2011 %

m2

%

Boundary

15,195

3.3

1,567

0.3

70

0.0

17,507

3.7

475,032

100.0

Water Willow

-4,226 -1,787

-6.3 -3.8

14,453 -6,602

23.0 -14.4

-11,873 13,090

-15.3 33.4

15,354 21,533

23.4 41.2

70,769 51,752

14.9 10.9

Lupin

-13,130

-69.8

7,263

127.9

14,579

112.6

19,393

70.5

22,374

4.7

Grassland

-28,559

-25.8

-26,653

-32.5

24,585

44.4

-2,898

-3.6

81,030

17.1

Vegetation total

-43,476

-24.6

-25,992

-19.5

52,254

48.6

38,028

23.8

155,156

32.6

62,897

29.4

13,106

4.7

-40,311

-13.9

-35,875

-14.4

249,107

52.5

Substrate

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Environmental Management (2013) 52:1–18

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from 0.79 for total vegetation to 0.99 for lupin, respectively. The P values were all\0.05 and F statistics based on ANOVA were all less than the critical F values, indicating good fits for the models (Table 6).

particular, have been extremely variable with annual flood peaks having an inter-annual variation up to 700 %. Large flood peaks [400 m3/s have only occurred four times in the 48-year record, whereas peaks\125 m3/s have occurred five times. The estimated mean annual flood of 242 m3/s and FRE3 value of nine events per year compare well to previous estimates by NIWA (276 m3/s and 9.4 events per year, respectively; Duncan and Woods 2004). The largest flood on record in 1994 contributed to the main channel migration to the south and other channel changes observed a year later in the 1995 aerial photos. However, our results indicate that even with 25–40 % invasive vegetation cover that helps stabilize islands and channels, a limited number of small floods over a short period, such as 1-year, can still cause considerable channel migration and floodplain changes. Other studies have also shown that high flows and floods in braided rivers can move large quantities of sediment and reshape channels and floodplains (Mosley 1983; Brasington and others 2000), cause significant aquatic habitat change and turnover (Arscott and others 2002; van der Nat and others 2003; Malard and others 2006), and impact riparian and floodplain vegetation (Hering and others 2004; Corenblit and others 2007; Bertoldi and others 2009). Our results demonstrate quantitatively that the flood and high flow pulse concepts of Junk and others (1989) and Tockner and others (2000), respectively, emphasizing the importance of the inter-connection of rivers and their floodplains by hydrological and ecological processes, are clearly important in New Zealand braided river floodplains impacted by invasive vegetation, such as the Ahuriri River. In addition to floods, numerous metrics can be used quantify the natural flow regime, but have not been fully characterized in previous braided river studies. The natural flow regime, especially flood and high flow pulses, is the critical driver of floodplain dynamics in the Ahuriri and other braided rivers, such as the Tagliamento River in northeastern Italy originating in the Alps (Junk and others 1989; Poff and others 1997; Tockner and others 2000). This study adds to this concept by quantifying the full natural flow regime in an important braided river impacted by invasive vegetation, and how specific flow metrics have variable effects on different vegetation classes. Part of the question for this study is how do these concepts apply to a braided river floodplain impacted by a high proportion of invasive vegetation cover, and are the concepts and results different in this type of river system?

Discussion

Changes in Vegetation and Interactions Between Flow and Vegetation

Flow Regime

Vegetation Removal

The Ahuriri River flow regime exhibited significant variability on both an annual and inter-annual basis. Floods, in

Large floods in the Ahuriri River are critical for removing a portion of the invasive vegetation and flushing this braided

Fig. 8 Results of Ahuriri River floodplain changes in a aerial cover (thousands of m2), b number of vegetation patches, and c average vegetation patch size (m2)

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Environmental Management (2013) 52:1–18

Legend

Fig. 9 Delineation of floodplain classes with changes over time based on aerial photograph interpretation. Remaining white areas are bare substrate (Color figure online)

river floodplain ecosystem. The largest flood in January 1994, in combination with the small flood in November 1994, caused considerable habitat turnover and removed at

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least 25 % of the invasive vegetation cover as of early 1995. The number and frequency of floods and high flow pulses both adversely affect willow and lupin cover in the

-0.846

-0.860

-0.939

7-day minimum flow

30-day minimum flow

Large flood duration

-0.886 -0.906

High flow frequency

High pulse no.

-0.762 -0.877 -0.886

No. of reversals Large flood frequency

-0.728

-0.714

-0.653

-0.641

-0.561

-0.546

-0.538

0.516

0.581

0.611

0.616

0.760

0.786

0.877

0.950

0.990

High flow frequency

90-day minimum flow

High pulse no.

Large flood peak

-0.825 -0.884

No. of reversals

Extreme low flow duration

90-day maximum flow

Small flood fall rate

High flow rise rate

Base flow

High flow fall rate

Low pulse no.

Extreme low flow frequency

Small flood peak

High flow duration

High pulse length

Large flood duration

Large flood fall rate

-0.779

-0.732

-0.639

-0.608

0.525

0.579

0.644

0.657

90-day minimum flow

90-day maximum flow

Large flood frequency

Extreme low flow duration

Small flood fall rate

Small flood peak

Large flood peak

0.768

0.809

0.833

0.870

0.930

Lupin

Small flood duration

Low pulse length

Extreme low flow duration

Small flood fall rate

High flow duration

Extreme low flow peak

1-day minimum flow

Low pulse no.

30-day minimum flow

Large flood duration

Large flood rise rate

3-day minimum flow

Small flood rise rate

7-day minimum flow

High flow peak

Grassland

-0.801

-0.743

-0.724

-0.658

0.550

0.644

0.679

0.679

0.688

0.717

0.754

0.782

0.826

0.861

0.918

-0.834 -0.839 -0.925

90-day minimum flow Extreme low flow duration

-0.786

-0.757

-0.730

-0.627

-0.618

-0.605

-0.508

0.564

0.586

0.619

0.662

0.666

0.723

0.748

0.798

0.888

0.957

0.962

Small flood fall rate

Large flood frequency

No. of reversals

Small flood duration

High flow frequency

Low pulse length

High pulse no.

90-day maximum flow

Large flood fall rate

Fall rate

Extreme low flow frequency

Small flood rise rate

Large flow rise rate

Extreme low flow peak

Base flow

Large flood duration

Low pulse no.

High flow duration

High pulse length

Vegetation total

Italized metrics for willow and lupin are common among these types. Italized metrics for grassland and vegetation total are common with either willow or lupin

-0.839

High pulse no.

Fall rate

-0.779

-0.802

Large flood fall rate

-0.762

High flow peak

High flow frequency

Low pulse no.

-0.722

3-day minimum flow

High flow duration

Base flow

-0.650

-0.713

1-day minimum flow

90-day maximum flow

High pulse length

Extreme low flow frequency

-0.520

-0.554

90-day minimum flow

No. of reversals

Large flood rise rate

Extreme low flow frequency

0.671

Willow

Boundary

Table 5 Pearson correlation coefficients [0.5 or \-0.5 for Ahuriri flow metrics and floodplain class areal cover

High flow duration

Large flood duration

High pulse Length

Low pulse no.

Small flood rise rate

Large flood fall rate

Base flow

Extreme low flow peak

High flow peak

1-day minimum flow

3-day minimum flow

Extreme low flow frequency

High flow rise rate

Low pulse length

No. of reversals

Small flood duration

90-day minimum flow

Large flood frequency

Small flood fall rate

Extreme low flow duration

Substrate

-0.969

-0.909

-0.890

-0.832

-0.784

-0.728

-0.671

-0.628

-0.586

-0.549

-0.507

-0.503

0.519

0.569

0.620

0.671

0.673

0.734

0.755

0.908

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Table 6 Multiple regression analysis parameters for key flow metrics (defined in text) and vegetation class areal cover, and goodness of fit statistics Willow

Lupin

Grassland

Vegetation total

Constant

101160

88594

48738

238492

Coefficient Flood frequency

-11928

-12752

11520

-13160

Largest peak

-103

-144

21

-225

Time since last flood

39

48

39

125

R2

0.80

0.99

0.81

0.79

P value

0.041

0.001

0.037

0.044

F statistic

1.25

1.01

1.23

1.27

Critical F value = 6.39 Vegetation class areal cover is the dependent variable and flow metrics are the independent variables

river, supporting the flood and high flow pulse concepts of Junk and others (1989) and Tockner and others (2000), respectively. Flood energy (stream power), timing and return period are primary factors controlling vegetation composition and cover in braided rivers, in addition to substrate texture and mechanical stability, rainfall or water table depth, and vegetation/soils system age (Meurk and Williams 1989). However, our results also show that vegetation removal in the Ahuriri River was preferential, with as much as 70 % of the lupins, and as little as 4 % of the willows being removed. This suggests that a single large flood (*50-year return period) may have little impact on well-established woody tree and shrub invasive species, like willow, typically located on more stable islands, terraces and banks developed though biogeomorphical succession, as recognized in other rivers (Corenblit and others 2007). Hering and others (2004) found similar results in a mountain floodplain in Germany. Willows are well adapted to irregular high and prolonged floods, and these patches are more resistant to erosion and removal by floods (Blom 1999). In the Ahuriri River floodplain, where invasive vegetation dominates and very few native trees and shrubs occur naturally, willows appear to play a key dual role in both mature, successional stages as well as in early, invasive pioneer stages. In pioneer stages, willows act as ‘ecosystem engineers’ through self organization to aid island formation, stability and growth (Moggridge and Gurnell 2009; Francis and others 2009; Gurnell and others 2012). Willows are present on different floodplain development stages with increasing vegetation cover which can be characterized by their vegetation associations, depth of fine sediment and inundation frequency (Reinfelds and Nanson 1993). These

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stages grade from stabilizing bars, incipient floodplains, established floodplains, mature floodplains, to terraces. Our study indicates that a single flood probably only removes these plants in specific locations where the channels may shift and substrate supporting willows along banks is susceptible to lateral erosion. Flood duration can also play an important role in vegetation and habitat dynamics (Bertoldi and others 2009; Gurnell and others 2012). Longer flood durations may cause mortality in floodplain vegetation due to prolonged inundation, submergence and anoxia. However, it appears that few studies have evaluated or quantified the duration of different flow regimes and floods, or the potential effects of duration on vegetation in braided river floodplains. In our study reach some small flood durations can exceed those of large floods: in one instance the duration of a small flood exceeded 50 days, almost as long as the longest large flood. Our results show that high flows with long durations adversely affect willow and lupin cover, but extreme low flows with long durations also negatively affect cover by stressing plants under drought conditions. Fall rates of small floods (the longer the fall rate, the less cover) and the number of flow reversals also have a negative influence on willow and lupin cover, indicating that highly variable changes in flows can reduce cover. The timing of flow regime components (of high flows or floods in particular) is also important to floodplain ecological processes, hydrochory and plant and animal phenology (Tockner and others 2009). High flow timing can influence invasive plant removal or other adverse flow effects (breakage, sediment abrasion, etc.) on plant material (Corenblit and others 2007; Moggridge and Gurnell 2010; Gurnell and others 2012). For example, a mature lupin at maximum height in summer will likely cause more flow resistance and be more susceptible to removal from high velocities and shear stress in the largest floods than smaller, juvenile plants earlier in the spring, even under the same flood conditions. Alternatively, in summer, mature lupins have more established deeper root systems that can help resist or minimize plant and sediment/substrate removal. Grassland cover responds to a different mix of flow metrics than the lupin and willow, which could be due to factors such as soil moisture availability, substrate elevation relative to water levels, and establishment success of, and competition with, lupins and willows. Vegetation Recovery By 2001, total vegetation cover increased considerably, and by 2011, it had recovered to 1991 levels, but with willows and lupins providing more cover than grassland. The invasive vegetation recovers quickly and it appears

Environmental Management (2013) 52:1–18

that the system may never stabilize due to flood disturbances, or has reached a new type of steady-state mosaic dominated by invasive plants. Much of this recovery is due to hydrochory, which plays a major role in dispersing seeds and propagules along river banks. Deposition is governed by seasonal patterns of seed release and the flow regime as well as site elevation, and the greatest deposition occurs in the most frequently inundated parts of the river bank (Gurnell and others 2006; Moggridge and others 2009; Moggridge and Gurnell 2010). Willow regeneration is greatest in protected moist areas (Moggridge and Gurnell 2009). Lupins appear to establish even more quickly and spread on new substrate in lower lying and less stable areas, but are therefore also more susceptible to removal by large floods. With a significant amount of new exposed substrate, such as after the large 1995 flood, and without subsequent large floods, lupins re-established and spread very quickly. Compared to willows, however, much less is known about Russell lupin ecology and relationships with river hydrology, especially in braided rivers. Low-lying grasslands are recognized as having some flood tolerant species (Blom 1999). Although grassland is also comprised of pioneer species that can establish on new substrate and lower lying areas quickly, this community recovers more slowly and eventually is outcompeted by lupins and willows. Both lupins and grassland appear first on active river bed, but sequentially occupy stabilizing bars, incipient floodplains and some established floodplains (Reinfelds and Nanson 1993). Extended periods of high flow pulses and small floods of moderate duration appear to help invasive plant seed and propagule dispersal though hydrochory. They can also provide transitional or periodic moist substrate conditions amenable for plant establishment, growth, and spread without generating high enough flows to remove most vegetation. Baseflow and frequent low flows also appear to allow invasive species to establish and occupy exposed and wetted channel banks. In addition, baseflow can provide continuous shallow subsurface water in alluvial substrate at appropriate depths needed by plants near the channels as well as somewhat farther away. Patch Dynamics The number of patches of willow and other vegetation types increases at some time after a flood due to dispersal and regeneration of new patches, with a corresponding decrease in patch size. However, patch numbers increase even more after a prolonged period without floods, and willow and grassland patch size increases as plants grow and fill in specific areas. Invasive vegetation cover, number of patches and patch size can change dramatically between years or flow events, and patches move towards more

15

mature successional stages with island development and willow growth when floods do not occur. Over a longer time period, however, these variables appear to remain relatively constant. These results are generally similar to those from studies in the Tagliamento River in Italy, showing that relationships between inundation water levels, inundated areas, and shoreline and other habitat dynamics from floods/high flow pulses are very dynamic over an annual cycle (van der Nat and others 2002, 2003; Arscott and others 2002). However, the proportion of island area and active corridor over large areas is relatively constant between years and over longer time periods (Malard and others 2006; Zanoni and others 2008). This reflects dynamic patch mosaics comprised of natural transient patches and a shifting mosaic steady state within the floodplain resulting from complex reciprocal interactions between river flows and fluvial geomorphology with vegetation (Latterell and others 2006; Corenblit and others 2007; Gurnell and others 2012). In some highly impacted rivers, however, such as a braided river in the eastern Italian Alps, considerable long-term changes can occur from flood events with [10–15 year recurrence intervals and resulting alteration in the sediment regime, such as channel narrowing, bed incision and riparian vegetation colonization (Comiti and others 2011).

Implications for HEP-Affected Rivers Our results have some implications for other braided rivers impacted by HEP. Dams and storage and diversion of water have resulted in river segmentation, significant changes in flow and sediment regimes, and degradation of aquatic ecosystems throughout the world (Williams and Wolman 1984; Petts 1984; Petts and Gurnell 2005; Nilsson and others 2005). Studies of dam and diversion impacts on river flows have generally shown decreases in the mean and coefficient of variation of annual peak flows, increases in minimum and low flows, and shifts in seasonal flow variability (Graf 1999; Richter and Thomas 2007; Poff 2009). In New Zealand, reduced flows due to HEP appear to increase invasion vegetation cover in braided river floodplains, which can lead to even more severe negative effects on threatened and endangered native birds (Caruso 2006a). As in free-flowing rivers, these impacts include increased cover for exotic predators causing significant bird population decline, and stabilization of islands and reduction of the bare, shifting gravels these birds need for habitat (Peat and Patrick 2001; Gray and Harding 2007). In the UWB, flows in the Tekapo, Pukaki and Ohau rivers have been severely modified by HEP including dams, diversions and storage, and most of these rivers are highly impacted by invasive vegetation. Observations in these floodplains and

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16

results of this study suggest that although certain flow metrics, such as low flows with long duration and frequent high flows with many reversals can inhibit invasive plants, invasive vegetation cover increases in these rivers largely due to the long-term reduction of flow and floods that would naturally have important flushing effects.

Conclusions The natural flow regime of the braided Ahuriri River in the Southern Alps of New Zealand exhibits considerable variability characteristic of mountain braided rivers, with large variation in floods and other flow regime metrics. The flow regime has variable effects on floodplain invasive vegetation, and creates dynamic patch mosaics that demonstrate the concepts of biogeomorphical succession and a shifting mosaic steady state. As recognized by the flood and high flow pulse concepts, floods and high flows have substantial effects on invasive vegetation in this floodplain ecosystem. An approximately 50-year flood removed up to 25 % of vegetation cover in the study reach, with preferential removal of lupin and less removal of willow, which is present in more mature and stable successional patches. Smaller floods and high flow pulses also have impacts on vegetation in some areas. However, most invasive vegetation is comprised of pioneer species that colonize bare substrate and recover rapidly after floods. The peak magnitude of the largest flood, flood frequency and time since the last flood in the interval between photos are key metrics that explain much of the vegetation cover and provide a simple multiple regression models for cover prediction. Our results indicate that as long as seed and propagule sources exist in upstream catchments and tributaries, the natural flow regime and floods will not remove significant amounts of invasive vegetation over the long term, human control of vegetation will continue to be needed as part of management schemes and restoration of braided rivers will be a great challenge. Other braided rivers impacted by HEP development and operations appear to have some different responses to altered flow and sediment regimes, but increases in invasive vegetation cover greater than in unimpacted rivers is typically observed downstream from HEP due to reductions in flow, floods and high flow pulses. Acknowledgments The authors gratefully thank Chris Woolmore, the Department of Conservation Project Manager for PRR, for provision of most aerial photographs and assistance with the study. The authors also thank Luke Javernick, PhD candidate in the Department of Civil and Natural Resources Engineering at the University of Canterbury, for provision of the 2011 aerial photos and assistance with field work and reconnaissance. Financial and in-kind support for the project was provided by the University of Canterbury and Department of Conservation.

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