Geomorphic dynamics of floodplains: ecological implications and a potential modelling strategy

Geomorphic dynamics of floodplains: ecologicalimplications and a potential modelling strategy

KEITH RICHARDS, JAMES BRASINGTON and FRANCINE HUGHES

Department of Geography, University of Cambridge, Cambridge, U.K.

SUMMARY

1. The dynamics of channel migration and floodplain renewal constitute an important

control of the ecological diversity of river corridors. Restoration initiatives should therefore

assess whether these dynamics must be reinstated in order to address the cause rather than

the symptoms of floodplain biodiversity decline.

2. Restoration of reach-scale dynamism in rivers where this is a natural behavioural

process will restore smaller-scale geomorphological and sedimentological processes that

encourage vegetation regeneration, but may require catchment-scale management of

material flows.

3. Channel dynamics depend on the style of river–floodplain interaction, and this may be

summarised in qualitative, classificatory, sedimentological models of floodplain architec-

ture that have been somewhat neglected in the ecological literature.

4. One approach to the assessment of floodplain biodiversity and its restoration would be

through the development of simulation models based on specified channel styles, and

involving simplified hydrodynamics and successional changes. Such models, currently the

subject of research as a spin-off from modelling studies of landscape evolution, would

permit evaluation of the consequences for ecological diversity of implementing various

management options that may affect the dynamics of channel migration.

Keywords: braiding, channel dynamics, meandering, modelling, reach scale, succession

Introduction: ecological concepts

and management

Interest in integrated restoration of rivers and their

floodplains has developed in response to declining

floodplain biodiversity, in spite of the naturally high

level of ecological diversity in riparian corridors

(Naiman, Decamps & Pollock, 1993). This decline

reflects the influences of flood control, flow manage-

ment, channelisation and land use changes in these

environments, all of which have separated the river

from its riparian zone and floodplain. Responses have

included both attempts to restore connectivity across

the river–floodplain, and direct attempts to restore

ecosystem state, for example of floodplain woodland

(Peterken & Hughes, 1995). The practices of such

restoration have often depended less on the applica-

tion of theoretical principles than on empirical

experience, which may risk failure through lack of

understanding of differences between reaches and

sites. This paper outlines an approach that addresses

some of the theoretical underpinnings required by the

restoration objective. It begins with an evaluation of

diversity concepts, which concludes that the channel

dynamics often constitute an essential control of

floodplain ecological diversity. These dynamics are

then shown to reflect the channel–floodplain associ-

ation, as classified in sedimentological models, which

have been neglected in ecology. Finally, an approach

is discussed, based on simulation modelling (cf.

Malanson, 1993; pp. 218–219) of the relationships

between channel dynamics and biodiversity for par-

ticular channel types. The form of modelling envis-

aged, which is the subject of our ongoing research, is a

Correspondence: Keith Richards, Department of Geography,

University of Cambridge, Cambridge CB2 3EN, U.K.

E-mail: [email protected]

Freshwater Biology (2002) 47, 559–579

Ó 2002 Blackwell Science Ltd 559

simplified, coupled hydrodynamic-ecological model

which captures the dynamics of channel pattern

evolution and relevant plant succession trends, and

which could eventually be used to explore the impacts

of river management practices on floodplain biodi-

versity.

An initial conceptual issue to consider is the role of

channel dynamics in relation to biodiversity, which

itself, as Table 1 indicates, depends on several related

factors including species richness (SR) and relative

abundance (the latter also is needed because rare

species may be missed when sampling to estimate an

SR index). Species richness reflects the number of

species per habitat (the a-diversity), and the number

of habitats (N) in a region (Whittaker, 1960). If the

‘region’ is a floodplain reach, the number of habitats

reflects the geomorphological dynamics and the sedi-

mentological diversity. Total SR is, however, not

simply a sum of values of a across the N habitats, as

some species have wide tolerance, and appear in

several habitats; an ‘inverse’ b-diversity is thus also

required. There are then other aspects of within-

species diversity that these measures do not consider.

One is the diversity of age structure. In geomorpho-

logically dynamic environments, erosion and depos-

ition processes will locally destroy older vegetation,

and create new surfaces for colonisation by pioneer

species. Finally, diversity reflects the gene pool in a

particular environment, and the number of distinct

clones of each species. Despite the evident multifactor

definition required for ‘biodiversity’, there is strong

evidence from river environments that physical hab-

itat heterogeneity plays a crucial role (Ward &

Tockner, 2001). This heterogeneity depends on the

channel dynamics; and these dynamics in turn

encourage age structure diversity (Salo et al., 1986;

Nilsson et al., 1991). Thus, in developing restoration

proposals for floodplain environments, a valuable tool

would be one allowing assessment of the consequence

for habitat diversity of rates of river migration and

sedimentary turnover. Such a tool would permit

evaluation of the consequence of restoring channel

dynamics for the diversity of habitats and vegetation

communities, while also indicating the sustainability

of this diversity over time, and revealing the cases

where lateral channel stability inhibits turnover and

suppresses diversity as floodplain vegetation becomes

more uniform over time.

A second issue is that river ecology has spawned

several qualitative concepts to account for aspects of

spatial variation in ecology, but that do not provide a

rigorous framework for the analysis of restoration

options. The longitudinal ‘river continuum concept’

(Vannote et al., 1980) assumes longitudinal resource

gradients, with maximum biodiversity in the middle

reaches of rivers. Headwater streams have low ther-

mal heterogeneity, light levels and nutrient status,

while lowland reaches have high turbidity and low

oxygen levels; optimal conditions for biodiversity

occur in middle reaches. These, however, are also

characterised, at least in medium-sized rivers, by high

stream power (Lawler, 1992), implying greater pro-

pensity for disturbance, and contradicting another

qualitative model, the ‘intermediate disturbance

hypothesis’ (Connell, 1978). The intermediate distur-

bance hypothesis also involves a trade-off, between

competitive dominant species which monopolise sta-

ble habitats, and the few fugitive species that survive

high levels of instability. Maximum diversity is thus

expected in locations with intermediate levels of

disturbance. A third model emphasises lateral

connectivity, particularly through the ‘flood pulse

concept’ (Junk, Bayley & Sparks, 1989; Middleton,

1999), in which seasonal variation in river water level

controls the recruitment of obligate riparian species.

Without this flow variation, there is progressive

change to terrestrial (dry) species and communities.

Less extreme flow variations also influence the lateral

distribution of moisture, nutrients and sediments

(Tockner, Malard & Ward, 2000). The flood pulse is

also linked to the dynamics of lateral channel migra-

tion, which renew habitat for colonisation and regen-

eration, and are themselves flood-related. Channel

Table 1 Various measures of ecological diversity

Measure Definition

a-Diversity Species numbers in each

habitat

b-Diversity Proportion of habitats in

which a given species is

present

c-Diversity Total number of species in a

region

Habitat diversity Number of habitats in an area

Age diversity Frequency distribution of ages

of a species in an area or

habitat

Genetic diversity A measure of clonal variation in

a species

560 K. Richards et al.

Ó 2002 Blackwell Science Ltd, Freshwater Biology, 47, 559–579

dynamics generate diverse habitat patch sizes, max-

imising the niches for colonisation by both edge and

interior species. Laterally, stable rivers tend to have

larger habitat patches, and low diversity because of

the limited extent of edge habitat. Highly disturbed

river environments exclude interior species (Ward,

Tockner & Schiemer, 1999). Thus the intermediate

disturbance hypothesis and the flood pulse concept

are closely interrelated, through their mutual depend-

ence on the channel dynamics.

These qualitative concepts provide useful organis-

ing principles for the diverse data from ecological case

studies. However, they lack the quantitative reliability

needed to provide a theoretical framework for prac-

tical management. Empirical data from field sites are

influenced by numerous causal factors, the controls of

observed longitudinal and lateral spatial patterns are

often unclear, and it is therefore risky drawing

management conclusions. However, the channel

dynamics are identified in the foregoing discussion

as a key control both of biodiversity and of spatial

pattern. This is because (i) biodiversity may be taken

at the river reach scale to be strongly related to habitat

diversity; (ii) habitat diversity reflects channel migra-

tion processes and (iii) the channel dynamics integrate

flood pulse and disturbance influences on the renewal

of succession and the regeneration of species. Thus,

one strategy to improve the capacity for successful

restoration initiatives is to develop simulation models

of the interdependent dynamics of channels and

floodplain vegetation that permit scenario evaluation.

This paper provides a review of the background to

recently initiated research by the authors to develop

such models, and to examine the practical potential

for such a modelling approach. In discussing this

background, the paper also seeks to identify know-

ledge gaps, and to encourage the closer integration of

the geomorphological and vegetation sciences in the

development of integrative modelling approaches to

riverine landscapes and river management.

Scales, processes and ecological management

As noted above, there are different approaches to

restoration, a particular issue being whether to focus

on restoring ‘products’ (species or ecosystems)

directly, or on ‘processes’, which then generate the

desired products in a quasi-natural manner. The latter

may represent a more sustainable approach requiring

less cumulative intervention. However, processes

vary in their significance with time and space scales,

and this places a premium on identification of the

significant processes. In Fig. 1, a range of linked,

scale-dependent fluvial and ecological processes is

suggested across a hierarchy of fluvial landscape units

(cf. Brierley & Fryirs, 2000). The ecological processes

identified are those relevant to the riparian ecology,

although variants may be equally applicable to the

aquatic ecology. The diagram implies feedback

amongst scales, with the larger spatial scales both

determining and being determined by processes at

smaller scales. A critical scale in this figure, however,

is the ‘reach’ scale, where the channel pattern

dynamics take place. When these dynamics operate

naturally, they are associated with sediment transport

processes that at smaller scales create bar-forms,

bedforms and particle motions that sustain ecological

dynamics at equivalent scales. At the reach scale, the

dominant fluvial and ecological processes seem to be

fundamentally congruent – involving both the

dynamic changes of meandering or braiding channel

patterns, and the patch dynamics of ecosystem turn-

over and maintenance (Pickett & White, 1985; Poole,

2002; Ward et al., 2002). These processes contribute to

biodiversity as measured at various levels – habitat

diversity, species diversity within patches, diverse age

structure between patches. Natural processes of flu-

vial disturbance thus create a mosaic of alluvial

surfaces with vegetation stands in different succes-

sional stages.

The underlying determinant of these processes is

the (intermediate) disturbance created by the flood

pulse. Usually in the ecological literature, the flood

pulse is concerned with water level variation, and

with moisture, nutrient and sediment supply factor,

which together provide regeneration opportunities

influential at a scale similar to that of an individual

plant. However, the flood pulse is also responsible for

erosion and sedimentation process, which provide

such opportunities at the scale of habitat patches.

Erosion and sedimentation may, however, occur at

particular locations in different events (Hughes, 1997);

thus the extension of the ‘flood pulse’ to the ‘flow

pulse’ concept (Tockner et al., 2000) is also a natural

concern for the fluvial geomorphologist. Furthermore,

a flood of a particular magnitude has different effects

on channel dynamics depending on the initial condi-

tion of the channel pattern prior to the event; for

Geomorphic dynamics of floodplains 561


example, such an event may fail to cut off a bend until

bank erosion has created sufficient sinuosity. Critic-

ally, however, the channel dynamics lead to new

surfaces for colonisation and regeneration; and mod-

elling tools are required to enhance understanding of

the ecological consequences of reach-scale channel

dynamics, and of their alteration by river manage-

ment practices.

Attempts have been made to convert the flood pulse

concept into a practical flow management tool, for

example in the ‘recruitment box’ method of Mahoney

& Rood (1998). This method is based on the flood as a

control over species regeneration, rather than as a

control either of ecosystem or of channel dynamics.

The recruitment box defines a seasonal period for

viable seedling establishment, when the timing of

seed release coincides with an appropriate range of

variation in stage and floodplain water table range,

and a rate of decline of the water table that seedlings

are capable of surviving (Fig. 2a). Such a scheme

clearly works best in rivers with a predictable spring

flood related to a measurable winter snow-pack. The

scientific basis for the definition of the ‘recruitment

box’ can, of course, be further improved through

experimental investigations of the tolerance of indi-

vidual species. Understanding is needed of such

phenomena as the optimal timing relationships

between seed production and seasonal flooding, the

critical soil water potentials for seed germination, and

the critical rates for seedling performance of soil water

decline following flooding (Hughes et al., 2000;

Karrenberg, Edwards & Kollmann, 2002). In addition,

there is room for elaborating the concept in relation to

plant communities or habitats rather than to individ-

ual species, as well as for improving the capacity to

simulate channel, habitat and ecosystem dynamics in

response to less predictable flood histories than those

fed by snowmelt.

Nevertheless, the ‘recruitment box’ idea, and its

scientific basis, offer the possibility of a predictive

model comparable with the aquatic habitat model

PHABSIM (Milhous, Updike & Schneider, 1989), but

applicable to the germination and survival of riparian

seedlings. This could be used to underpin flow

Fig. 1 A hierarchical representation of the correlated fluvial (bold text) and ecological (normal text) processes at different scales

in the fluvial environment; the highlighted reach scale processes are hypothesised as those whose manipulation is likely to be most

successful in conservation or restoration projects, because the processes are most strongly linked.



management practices that are ecologically beneficial

for riparian ecosystems, as is increasingly required

where river and flow management acknowledge the

needs of ecosystem maintenance (Petts, 1996). In

South Africa, for example, a recent Water Act makes

provision for defining and reserving the water

requirements for ecosystem conservation (Milton,

Gilvear & Hooper, 1995; Moon et al., 1997). It remains

a challenge to establish practical principles for

multi-objective ecological flow management, and to

implement these. As Fig. 2b illustrates various flow

requirements exist for different elements of a land-

scape consisting of a range of ecosystems (Hill &

Platts, 1991). However, a key point which is recog-

nised in flow allocation methods such as the Building

Block Methodology (King & Louwe, 1998) is that

different ecosystems require managed flows at differ-

ent times, and with different frequencies. Thus, the

flood pulse necessary for successful establishment

of riparian seedlings is only required intermittently,

and flow management in other years can be selected

to optimise other ecological processes. Where

multi-objective management broadens to include res-

toration of channel dynamism, additional assessment

tools will be required. Simulation models capable of

providing insights into the rates and patterns of

renewal of habitat as a result of actively managed

lateral channel migration would therefore add to the

battery of techniques available to those concerned

with riverine habitat conservation or restoration.

Channel dynamics, habitats

and floodplain ecology

The habitat diversity of floodplain environments is

partly dependent on dynamic characteristics of the

river system which express themselves at the reach

scale (Fig. 1). These include the type of channel and

the suite of sedimentary environments created by its

evolution; the processes of erosion and deposition that

drive the channel evolution; the rates of bank erosion,

channel migration and floodplain sediment turnover;

local patterns of erosion and sedimentation and their

effects on plant recruitment; and the effects of flow

control and channel management. There is often a

close interdependence between the channel dynamics

that renew habitat and succession processes, and the

ecological dynamics – as when the succession is partly

dependent on sedimentation accelerated by the pres-

ence of vegetation, or tree-throws cause erosion and

channel avulsion. Hence, in Fig. 1, the suggestion

emerges that the reach scale is that at which the most

intimate mutual association occurs between channel

and vegetation (patch) dynamics, and the greatest

potential for biogeomorphological management

exists; and that although other processes may interact

at both larger and smaller scales, they are favoured by

particular reach-scale circumstances.

Fluvial styles and habitat diversity

The balance of processes of channel pattern change,

and their rates, depend on channel pattern type, and

classification is a precursor to analysis of the relation-

ship between channel and ecological dynamics. A

useful classification in the habitat context is provided

by the facies models of fluvial architectural style

developed by Miall (1985). These models relate closely

to the classification of floodplains generated by

Nanson & Croke (1992) (Table 2), with the advantage

of explicit representation of the sedimentary elements

Fig. 2 (a) The ‘recruitment box’ concept; seedling establishment

occurs when seed release coincides with a favourable stage

range and rate of stage decline (after Mahoney & Rood, 1998).

(b) Minimum monthly flow requirements for fisheries, channel

maintenance, riparian habitat and valley maintenance, in the

Salmon River, Idaho (after Hill & Platts, 1991).



that define the range of habitats found in different

river environments. Each fluvial style has a set of

characteristic elements (Table 3), each of which is

composed of a range of lithofacies at a smaller scale.

This is ecologically significant, as a generally gravel-

based element can contain locally abundant fine

sediment in patches, and these may be important for

moisture retention and seed germination (Petts et al.,

2000). The lithofacies are various forms of deposit of

gravel, sand and fines, with various small-scale

sedimentary structures (bedforms) such as imbrica-

tion, cross-bedding and lamination (Miall, 1996, p. 79).

In common with the Nanson & Croke (1992)

classification, the fluvial styles in Miall’s (1985) clas-

sification vary with stream power and sediment

calibre. Miall (1985) identifies 16 distinctive fluvial

styles, and these range from low-power, mud-sand

dominated anastomosing rivers (class C2b in the

Nanson & Croke classification; Table 2), through

sandy, single-thread, high-sinuosity meandering riv-

ers (class B3b) to high power, multithread, braided

rivers (B1). Fig. 3 illustrates this spectrum of fluvial

styles, extracting from Miall’s continuum a set of

styles representing the range of basic geometries and

sedimentary facies. Fig. 3a shows the general spatial

structure of sedimentary environments characteristic

of an anastomosing river (Miall’s Model 8 in Table 3),

with extensive areas of overbank floodplain fines (FF),

Table 2 A classification of floodplains based on Nanson &

Croke (1992)

Class Fluvial style

A High energy, non-cohesive floodplains

A1 Confined, coarse-textured floodplains

A2 Confined, vertical-accretion floodplains

A3 Unconfined, vertical-accretion floodplains

A4 Cut-and-fill floodplains

B Medium-energy, non-cohesive floodplains

B1 Braided river floodplains

B2 Wandering gravel-bed river floodplains

B3 Meandering river, lateral-migration floodplains

B3a Lateral-migration, non-scrolled floodplains

B3b Lateral-migration, scrolled floodplains

B3c Lateral-migration/backswamp floodplains

B3d Lateral-migration, counterpoint floodplains

C Low-energy, cohesive floodplains

C1 Laterally stable, single-channel floodplains

C2 Anastomosing river floodplains

C2a Anastomosing river, organic-rich floodplains

C2b Anastomosing river, inorganic floodplains

Table 3 Common fluvial styles and their main architectural elements (after Miall, 1985, 1996)

Classification Architectural

no. Fluvial style Sedimentary facies element*

Gravel-dominated rivers

1 Gravel braided with sediment Gravel, minor sand SG (GB, SB)

gravity flows

2 Shallow gravel braided Gravel, minor sand GB (SB)

3 Deep gravel braided Gravel, minor sand, fines GB, SB, DA (FF)

Gravel wandering Gravel, minor sand, fines GB, DA, LA (FF)

4 Gravel meandering Gravel, minor sand, fines GB, DA, LA (FF)

Sand-dominated, high sinuosity rivers

5 Gravel-sand meandering Sand, pebbly SB, LA, FF (GB)

6 Sandy meandering Sand, minor fines LA, SB, FF, LV, CR, CS, FF (CH)

Ephemeral sandy meandering Sand, minor fines LA, SB (FF)

7 Fine-grained meandering Fine sand, silt, mud LA, SB, FF, LV, CR, CS, FF (CH)

8 Anastomosing Sand, fines SB, CH (LA), FF, LV, CR, CS

Sand-dominated, low-sinuosity rivers

Low sinuosity braided- Sand DA, LA, SB, FF

meandering with alternate bars

9 Shallow perennial braided rivers Sand SB (FF)

10 Deep perennial braided rivers Sand, minor fines DA, LA, SB (FF)

High energy sand-bed braided Sand, minor fines DA, SB, HO (FF)

11 Sheetflood distal braided Sand, minor fines SB (FF)

12 Flashy ephemeral sheetflood Sand, minor fines LS (FF)

*CH: channels, LS: laminated sand sheet, GB: gravel bars and bedforms, FF: overbank fines, SB: sandy bedforms, LV: levee, DA:

downstream-accretion macroform, CR: crevasse channel, LA: lateral-accretion macrofrom, CS: crevasse splay, HO: scour hollows,

CH(FF): abandoned channel, SG: sediment gravity flows.



coarser-grained areally distributed crevasse splay

deposits (CS), linear channel fill deposits (CS) and

occasional areas of lateral accretion deposit (LA).

Higher-energy meandering rivers with mainly sandy

bed material have the element structure suggested by

Fig. 3b (Miall’s Model 6), with similar sedimentary

elements in different proportions and spatial associ-

ations to those in Model 8, and with more extensive

lateral accretion deposits. Furthermore, they may

have additional features such as levees (LV) and

abandoned channel fills [CH(FF)], depending on the

sediment load character and the rates of bank erosion,

bend migration and bend cut-off. Fig. 3c shows

Miall’s Model 3, the deep, gravel-bed river with

well-defined topographic levels which are flooded

with different frequency. The dominant sedimentary

elements in this case are gravel bars and bedforms

(GB), sandy bedforms (SB), and overbank fines (FF).

Again, some other elements may occur (channel fills,

lateral and downstream accretion macro-form depos-

its) in specific examples.

Channel dynamics and biodiversity

Within each of these channel types, the dominant

processes of sediment transport, erosion and depos-

ition result in a particular spatial organisation of

sedimentary units, and thus create a habitat mosaic. In

anastomosing channels (Fig. 3a), strong interactions

may occur between fluvial and ecological processes,

because when an anastomosing floodplain is forested

(for example, the Gearagh on the River Lee in County

Cork, Ireland; Brown, Stone & Harwood, 1995), tree-

throws may play an important role in creating

crevasse splays, encouraging avulsion, causing the

abandonment of channels which subsequently infill,

and providing patch-regeneration opportunities. In a

single-thread meandering river, the dominant fluvial

processes are those of bend migration (which is

Fig. 3 A spectrum of fluvial styles, based on Miall (1985, 1996).

(a) An anastomosing river. (b) A sand-bed meandering river.

(c) A deep, gravel-bed braided river with well-defined topo-

graphic levels (printed with permission from Springer-Verlag).

Fig. 4 The vegetation mosaic of the lower Ain River, France

(from a map created by Amoros et al., 1986). The figure

illustrates the habitat complexity and diversity created by

the dynamics of river meander migration. The horizontal line at

the bottom is 1 km in length (printed with permission from

the authors).



associated with scroll bar deposition), bend cutoff

(associated with sedimentation in cut-off bends), and

the progressive in-fill of ox-bow lakes. The habitat

mosaic resulting from these processes includes levees,

back-swamps and crevasse splays. This results in high

levels of habitat diversity because of the geomorpho-

logical, topographic, sedimentological and edaphic

diversity, and also because of the diversity of ages of

(particular examples of) a given physical feature

within a reach. The processes of bank erosion, scroll

bar deposition and point bar growth (Nanson &

Beach, 1977; Salo et al., 1986; Shankman, 1993; Ward,

1998) have received most attention as processes of

habitat renewal and diversification. In particular,

scroll bars (see Fig. 3b) result in significant topo-

graphic differentiation between the resulting ridges

and swales on the surface of point bar complexes,

with a strong age structure amongst the trees on

successive ridges (Hickin, 1974). However, channel

avulsion, channel abandonment and abandoned chan-

nel in-fill are also significant factors in the generation

of a habitat mosaic. Fig. 4, an extract from a map

created by Amoros et al. (1986), is an excellent

example of this mosaic from the lower Ain River

close to its confluence with the Rhone in France

(Marston et al., 1995). This map was based on meti-

culous field surveys and remote sensing using aerial

photography. It shows the rich detail of a dynamically

evolving meandering riverine landscape, in which the

vegetation records the geomorphological history, and

that history defines the habitat diversity of the

landscape.

In a braided river, gravel and sand-bar and bedform

migration are the dominant sedimentary processes,

often resulting in channel avulsion because of the

water-level variations associated with bar migration

(Werritty & Ferguson, 1980). If there is a general

tendency for downcutting as channels change position

through avulsion (often into palaeochannels that have

not been infilled because of a lack of fines), then there

will be a pattern of abandoned bar surfaces of

differing age and elevation, on which vegetation

recruitment may be encouraged when thin spreads

of fines have occurred during flood events. The

potential for succession on these surfaces will, how-

ever, reflect the rate of migration and avulsion. In

braided rivers occupying mountain valleys, the loca-

tions of braided reaches may be intermittent, occur-

ring where the valley is wider than average or where

tributary or alluvial fan junctions locally enhance

sediment supply. These ‘sedimentation zones’ are

separated by narrow, single-thread, transport reaches

such as bedrock gorges (Church & Jones, 1982;

Church, 2002). Feedback between fluvial and ecolog-

ical processes in braided rivers manifest in vegetation

patterns on individual gravel-sand bar units and at

the reach scale, when sedimentation and plant suc-

cession processes influence one another. Sedimenta-

tion and bar formation, for example, may be

influenced by large woody debris accumulation

(Gurnell et al., 2000; Gurnell & Petts, 2002). Such

interactions can have an expression at a scale at which

it is difficult to unravel the roles of fluvial and

ecological processes. For example, over a 50-km reach

of the channelised River Isere, the area of vegetated

gravel bars between the dykes has expanded in the

last 50 years, beginning at three or four sites and

spreading upstream and downstream from these

(Fig. 5; Vautier, 2000). This pattern of development

could reflect the existence of gravel sedimentation

zones within the reach, where the bar forms encour-

age vegetation encroachment; or it could be that the

initial sites were locations of seed dispersal. A mixture

of the two processes is likely, reflecting the biophys-

ical nature of the river system.

Floodplain turnover rate and biodiversity

A further way in which the fluvial processes influence

biodiversity is in the general turnover rate of the

Fig. 5 The expansion of the percentage of bar surfaces along a

50 km reach of the Isere which were vegetated at different dates

between 1948 and 1996 (after Vautier, 2000; printed with

permission from the author).



floodplain alluvium, which depends on the rate at

which meanders sweep across the floodplain surface.

If this occurs either very slowly or very rapidly, low

biodiversity is likely, whereas intermediate rates of

turnover would maximise biodiversity (this illustrates

how the intermediate disturbance hypothesis is itself

a reflection of the channel dynamics). The rate of

turnover of the floodplain sediment store affects the

overall structure of the riparian vegetation. Rapid

turnover associated with channel migration causes a

higher proportion of the riparian area to be occupied

by vegetation in the pioneer stages, while a slow

turnover rate results in a higher percentage of mature

vegetation. One measure of turnover is the minimum

age of the oldest parts of the floodplain sediment

store, and Hughes (1997) quotes values of 100–

600 years for this, with the Amazon being an outlier

at 2000 years. In some cases, the floodplain has taken

much of the postglacial time period to evolve and turn

over, whereas the forest turnover time may be only of

the order of 500 years. In such cases, the evolution of

the fluvial landscape exercises little influence on the

ecosystem structure. However, when landscape and

ecosystem turnover rates converge, changes in the

landforms can have large impacts on the ecosystem

characteristics.

Local processes of sedimentation

and vegetation recruitment

Fluvial processes that control sedimentation, bar

growth and dissection, and bedform construction

associated with hydraulic roughness, all occur at

spatial scales below those of the reach-scale channel

dynamics (see Fig. 1). However, their spatial struc-

ture is determined by the larger-scale dynamics, and

within the sedimentary elements defined in Fig. 3,

smaller-scale patterns of sedimentation and sediment

size occur, which reflect the range of grain sizes in

transport, and flow patterns across the topography of

larger-scale forms. For example, Piegay et al. (2000)

demonstrate that sedimentation rates in abandoned

channels (perifluvial aquatic zones) differ systemat-

ically between braided and meandering reaches. Fine

sediment patches on gravel bar surfaces are import-

ant for the recruitment of individuals in the renewal

of plant succession, as seeds germinate and seedlings

survive in the patches of finer sediment that retain

moisture and provide an accessible nutrient store. As

Girel & Pautou (1997) demonstrate, these early

successional species may then trap more sediment,

and generate a microtopography which encourages

further spatial segregation of sediment sizes. In the

middle of a bar, canary grass (Phalaris arundinacea L.)

communities establish, encourage finer sediment

patches around them, and these sustain Calamagrostis

littorea (Schrad.) Beauv. and Festuca arundinacea

Schreb. In between, surface depressions accumulate

fines and attract species such as Ranunculus repens L.

and Deschampsia caespitosa (L.) Beauv. Gradually

these stabilise the surface for the invasion of woody

species (Salix, Populus). In addition, of course, there

are processes that favour vegetative reproduction.

Sedimentation buries woody debris and existing

seedlings, and encourages subsequent sprouting of

adventitious shoots. This suggests that the balance

between seed-based regeneration and vegetative

reproduction, and therefore the genetic diversity of

a riparian plant community, might be dependent on

the balance of erosive and depositional processes.

This hypothesis can be difficult to test, however. In a

comparative study of vegetation on bar surfaces in a

channelised and freely braiding reach of the River

Drome, M. Winfield and N. Barsoum (personal

communication) sampled leaf material from closely

spaced sites along eroding banks and at mid-bar

locations, avoiding sampling shoots which were

clearly from the same clone. The results of cluster

analysis of amplified fragment length polymorphism

(AFLP) bands show that the sampled individuals

were genetically very similar, but not sufficiently to

be regarded as clonal, with no differences between

the two river reaches. This finding suggests that, in

spite of the local and visible evidence of vegetative

regeneration, the bar-surface vegetation may be

dominated by seed-based recruitment.

Channel management and biodiversity

River regulation (by channelisation or flood control)

results in terrestrialisation of the vegetation, associ-

ated with a reduced rate of turnover of the fluvial

landscape, reduced rates of ecosystem change, reduc-

tions of channel and ecosystem dynamics and of

mosaic detail, reduced flood frequency, and loss

of habitat and age diversity. These consequences of

regulation on Alpine rivers such as the Rhone and the

Isere have been recorded by Girel & Pautou (1997).



The Isere has experienced a complex history of river

and flow management (Vautier, 2000), including

recent incision because of gravel extraction, and

reduction of flows because of reservoirs impounded

for hydropower generation. Today, there are stable

islands (both medial and lateral dyke-attached

islands), with a gravel substrate and silty sand at the

surface, anchored by vegetation growth. These veget-

ated islands are developing relatively uniform veget-

ation, whose flow resistance causes an increase of

flood water levels of about 1–1.5 m for a given

discharge. There is accordingly a need to destabilise

these islands to inhibit vegetation growth, reduce flow

resistance and maintain the integrity of the flood

protection afforded by the dykes. One means of

achieving this is to cut the vegetation, but this is an

expensive option because of the necessity for repetit-

ive cutting after rapid re-growth. An alternative

autogenic, self-maintaining approach is to enable the

re-introduction of sediment supply in order to restore

the dynamics of river scour and fill, with its potential

to create dynamic behaviour in the bar-forms (Dykaar

& Wigington, 2000). A similar set of ideas about

restoration of river bed dynamics has been considered

at the catchment scale by Bravard et al. (1999); renewal

of sediment supply restores channel dynamics, and

thus restores the dynamics of riparian vegetation. It

emerges that the biodiversity of islands is actually

enhanced by a management practice which encour-

ages sediment movement (J. Girel & F. Vautier,

personal communication); both at community and

species levels, islands on which vegetation is felled,

and surface sediment and roots are removed, appear

to be more diverse than islands where the vegetation

is simply cut. Although this is an artificial example, it

suggests a clear link to the conservation of ecological

diversity from the interdependence and maintenance

of fluvial and ecosystem dynamics.

Empirical investigation of channel

and vegetation dynamics

One means of assessing the relationship between

channel dynamics and biodiversity is an empirical

approach using remote sensing methods [cf. Vautier’s

(2000) work on the Isere shown in Fig. 5]. Sequential

multi-temporal remotely sensed imagery is a well-

established method for the analysis of channel

dynamics (Mertes, 2002). This may be based on

manual analysis of high-resolution aerial photogra-

phy, providing a synoptic perspective on channel

changes over wide areas (Lewin & Weir, 1977; Dykaar

& Wigington, 2000). However, developments in

spaceborne multi- and hyper-spectral imaging sys-

tems offer the potential to map fluvial environments

semi-automatically from surface reflectances (Muller,

Decamps & Dobson, 1993; Mertes, 2002). At first, this

was hindered by the mismatch between the scale of

fluvial landforms and the resolution of early satellite-

borne sensors (e.g. object space resolution of Landsat

MSS ¼ 80 m; Landsat TM ¼ 30 m). Subsequently, air-

borne imaging systems such as the Daedalus ATM

and the CASI, with high spatial and spectral resolu-

tions, have been used for geomorphological and

ecological studies on smaller rivers (Winterbottom &

Gilvear, 1997). However, by the late 1990s, spaceborne

sensors with appropriate spectral and spatial resolu-

tions have become available (Gilvear, Bryant & Hardy,

1999). These technical applications are set within a

theoretical debate about the potential of remote

sensing for vegetation mapping. Single classes may

not reflect the floristic composition of a multi-level

plant community, and as a result, mapping the habitat

may not be equivalent to mapping the vegetation.

However, in floodplain environments, the morphody-

namic and hydrological processes play a primary role

in structuring the vegetation, and there is a close

equivalence of habitat and plant community. Muller

(1997), thus, has shown how vegetation classifications

derived from aerial photography can be draped onto a

DTM, and then compared with flood extents mapped

through the use of inundation algorithms.

Additional technical developments, such as the

spatial database tools of Geographical Information

Systems (GIS), have greatly assisted the analysis of

channel dynamics using remotely sensed data. The

GIS facilitates the combination of information on

channel form from a variety of sources and scales,

with convenient intercomparison using simple over-

lay functions to analyse channel changes (Gurnell,

1997; Johnson, 2000). Moreover, GIS software allows

direct quantification of errors, and thus the means of

assessing the accuracy of detection of change. The

capacity to employ different sources of imagery

allows re-examination of archived aerial photographs

to gain insight into channel changes over time scales

relevant to plant and other ecological processes and

succession. For example, Rumsby, Brasington &



McVey (2001) have studied the plan-form dynamics of

the gravel-bedded River Feshie, U.K. [a wandering

gravel-bed river according to Miall’s (1985) classifica-

tion], analysing a multiscale (1 : 10 000–1 : 27 000)

combination of cartographic and aerial photographic

data, covering similar summer low flow periods of a

small 900–400 m reach between 1899 and 1997. Each

data source was rasterised and rectified to the

ordnance survey (OS) National Grid, and then resam-

pled to image files with a common object space pixel

resolution. After registration, geomorphological fea-

tures on the images were interpreted and a classifi-

cation scheme separating vegetated and unvegetated

zones of the currently active and the palaeochannel

network was manually digitised ‘on-screen’ with the

GIS software ArcView. Fig. 6 shows the geomorpho-

logical maps derived from the 1989 and 1997 sources.

These digital spatial databases can be analysed to

calculate changes in the areal proportion of channel

environments and habitats over time, using overlay

functions to determine the directions and types of

change between images. Validation tests on the

registration and digitising errors suggested that dif-

ferences greater than 4.5 m may be treated as signi-

ficant at the 95% confidence interval. A useful method

of representing the pattern and rate of typical channel

and floodplain changes is through the production of

tables which compare the surface cover properties of

areas digitised from one epoch to those at another;

Table 4 shows percentage changes between 1989 and

1997. Care is needed in interpreting these data, which

are sensitive to errors and uncertainty in the classifi-

cation. However, some changes are clearly evident.

For example, 36.4% of the active exposed gravel was

re-incorporated into the active wetted channel

between 1989 and 1997, while 2.4% of this same

surface type had been colonised and vegetated by

1997, and 19.3% of the active wetted channel in 1989

had become disconnected from the active channel and

converted to vegetated palaeochannel gravel.

While such analysis of changing morphology can

provide insights into the interplay between fluvial

and ecological dynamics, it is based on static views of

the channel at more or less arbitrary intervals. Any

direct link to particular floods is complicated by the

uneven distribution of such events over time, and the

non-linear relationship between flood magnitude and

channel change. Uncertainty about these relationships

can be reduced by reference to accurate river

discharge data and historical evidence, but such

Fig. 6 Maps of the geomorphology and vegetation of the River Feshie study reach based on 1989 and 1997 aerial photography

(after Rumsby et al., 2001).



empirical investigation of the direction and mechanism

of channel dynamics will always remain susceptible to

sampling errors. Thus, simulation modelling offers an

additional tool to interrogate the processes of channel

and vegetation dynamics in floodplain environments.

Modelling channel dynamics and biodiversity

Empirical approaches to the assessment of time

variation in the spatial structure of habitats and

communities in floodplain environments provide

valuable data on the interaction between channel

dynamics and biodiversity, but it is difficult to

extrapolate their results to other sites, and to use

them for management guidance in different locations.

An alternative whose potential has yet to be fully

explored, but which has been emphasised throughout

this paper, is the use of coupled models of channel

dynamics and plant community succession. The

output of a channel dynamics model is the spatial

mosaic of physical units (or habitats), and the ages

since the last destruction and renewal of the surface at

particular sites. A successional model could be linked

to this channel dynamics model, and would show

how the plant succession interacts with the channel

dynamics in generating different levels of species or

community diversity. In an uncoupled form, the

succession would simply follow the variation in

surface stability, but a coupled form could involve a

feedback in which the erodibility or rate of sedimen-

tation is a function of the vegetation properties at

different stages in the succession. Whichever mode is

employed, this simulation approach will permit

exploration of the ways in which key parameters of

both component sub-models affect the biodiversity of

the simulated reach; and will also assist in providing

quantitative tests of some qualitative hypotheses, such

as the intermediate disturbance hypothesis. It should

also allow simulations of the consequences of changes

arising through flow and river control, and therefore

provide a useful management tool.

Such a modelling approach requires a combination

of sub-models of (i) the channel dynamics and (ii) the

succession process. The nature of the first of these sub-

models will depend on the channel type (fluvial style),

and the two classes of channel dynamics model

discussed here are for single-thread meandering

rivers (Fig. 3b) and braided rivers (Fig. 3c). The

succession process is represented by an empirical

relationship based on observed successional path-

ways on floodplains in particular climatic regions.

These components are discussed in the sections

below.

The dynamics of single-thread meandering rivers

A simulation model of meandering river dynamics,

including a representation of the evolution of the

floodplain topography, is that developed by Howard

(1992). It has three main components. The first is a

model of flow, bed topography and sediment trans-

port in a meandering river. This model is based on the

Table 4 Percentage changes in the areas of various surface types in the reach of the River Feshie shown in Fig. 6, between 1989 and

1997. For example, 45.7% of the area occupied by the active wetted channel in 1989 was also active wetted channel in 1997, while

30.1% had changed to active exposed gravel

Surface type in 1989

Active zone Inactive zone

Active Active Palaeo- Palaeo-

Surface type wetted exposed Vegetated Palaeo- vegetated unvegetated

in 1997 channel gravel gravel channel Gravel Gravel Unclassified

Active wetted channel 45.7 36.4 7.6 0.7 1.0 0.1 3.0

Active exposed gravel 30.1 34.6 10.3 0.6 0.4 1.5 5.9

Vegetated gravel 0.3 2.4 0.0 0.0 0.0 0.0 0.0

Palaeo-channel 0.2 0.8 0.0 59.9 5.2 17.7 0.7

Palaeo-channel, 19.3 13.3 69.2 27.8 73.9 38.1 1.3

vegetated gravel

Palaeo-channel, 1.9 3.0 12.9 10.4 6.1 42.6 11.7

unvegetated gravel

Unclassified 2.6 9.5 0.0 0.6 13.4 0.0 77.4



work by Johannesson & Parker (1989), which although

one-dimensional, implicitly (if approximately) deals

with the effects of channel curvature on bed topog-

raphy (such as the point bar lateral slope), and on flow

and sediment transport. The second component is a

relationship of near-bank depth and velocity to the

rates of bank erosion and lateral migration. This

defines the bank erosion rate as a relationship

between the increasing local deviations of the near-

bed velocity, depth and shear stress from the average,

and the changing curvature around a bend. As the

river migrates and bends evolve as a result of spatially

differentiated bank erosion rates, circumstances arise

in which acute bends approach a neck cut-off position.

The model thus has a threshold distance at which

approaching channel segments are forced to cut off

the bend between them, and the bend is abandoned

and separated from the channel. The third component

is a model of floodplain sedimentation. This involves

two processes, those of point bar deposition and

overbank sediment diffusion. The deposition rate is

modelled as a function of relative floodplain height,

and distance from the channel, providing a crude

approximation of deposition close to the bank (form-

ing levees) and more distant overbank sedimentation.

When the channel sweeps through a model cell, the

elevation is set equal to the mean bed elevation, but as

the channel moves away, the elevation is adjusted to

represent the lateral depth perturbation on the point

bar side of a channel bend.

This model produces realistic simulations of sinu-

ous meander trains from initially straight channels

with random perturbations. After a few thousand

iterations, the simulated channel has developed

enough cut-off bends to create a path that wanders

laterally as well as displaying bends of different

amplitude, shape and ‘age’. Fig. 7 illustrates a short

section from a longer reach simulated by this model,

showing the properties the model generates that are

critical for the question of vegetation succession and

the age and elevation of the floodplain surface. With

relatively low deposition rates, the abandoned

channels do not fill-in with sediment, and remain

low-lying habitats conducive to the maintenance of

wetlands (these are marked in Fig. 7b as ‘sloughs’).

Point bars have an internal age variation consistent

with point bar growth, but after bend cut-off, adjacent

‘fossil’ point bars have different ages. The top left-

hand corner of Fig. 7a illustrates this clearly, because

a series of adjacent abandoned point bars have

maximum ages (in numbers of iterations) of 500,

600, 800, 1300 and 1500. The physical meaning of an

iteration has to be determined through comparison of

the simulation with a suitable real-world (prototype)

case of a dynamically evolving meandering river. The

elevation diagram (Fig. 7b) shows no levee develop-

ment, but Howard (1992) reviews the need to refine

the deposition model to allow the changing rates of

deposition with distance from the channel also to

reflect variation in grain size, and for an improved

Fig. 7 An illustration of the Howard (1992) simulation model

for a freely meandering river, showing (a) contours of floodplain

age in hundreds of iterations (areas older than 2100 iterations are

bordered by dashed lines and are uncontoured), and (b)

contours of floodplain elevation for a relatively low deposition

rate (low elevation sloughs shown by ‘S’) (from Howard, 1992;

printed with permission from John Wiley & Sons Ltd, New

York).



representation of discharge variation. However, the

model clearly has considerable potential for evaluating

the relationship between meandering channel dynam-

ics, habitat diversity and diversity of plant communi-

ties (as illustrated in Fig. 4), as it captures the main

features of the elevation and age structure of the

floodplain. Coupling its predictions of floodplain

properties with simple succession models such as

that shown in Fig. 9 (see below) would provide an

excellent basis for testing in a more quantitative

manner such concepts as the intermediate disturbance

hypothesis, simply by sensitivity analyses of the

ecological consequences of simulations with different

parameter values controlling the rates of bank erosion

and floodplain deposition.

The dynamics of braided rivers

A model which may be used to simulate the dynamics

of braided river systems for the purpose of investi-

gating the habitat diversity of their floodplains is that

of Murray & Paola (1997). This is a cellular automata,

or coupled map lattice model, based on the routing of

water and sediment across a regular grid topography.

It proceeds by routing an input of water at the top

edge of a reach consisting of nx by ny cells, with initial

topography such as a random elevation field added to

a linear plane whose slope represents the valley

gradient. A predefined discharge, Q, is routed from

each input cell (denoted by subscript i) to those cells

in the next row downstream that are lower in

elevation (denoted by the subscript j), in proportion

to the gradients to these cells (slope, S), and according

to the rule

Qi ¼ ½Sni =ð1=RSn

j Þ�Qn

where the normalisation by the sum of slopes ensures

that all water entering a cell leaves it within an

iteration of the model, and the exponent n is normally

0.5. The water transports sediment from cell to cell

according to a transport relationship in which the

transport rate is a function of discharge and gradient

(i.e. stream power). A variety of forms of transport

law may be employed, with or without a threshold of

erosion. A simple form is

Qsi ¼ K½QiSi þ eRQujSuj�m

where the second term adjusts the sediment flux into

each cell by the sum of the stream powers from the

three adjacent upstream cells (here identified by the

subscript uj), to represent the effect of flow momen-

tum from the upstream cells driving sediment against

adverse gradients. The parameter e is a fraction set by

Murray & Paola (1997) at 0.35. The exponent m is

normally taken to be about 2.5, in common with many

published sediment transport relationships for fluvial

environments (see, for example, Kirkby, 1971; Rich-

ards, 1982, p. 113).

During each iteration of the model, the cell eleva-

tions are adjusted according to a simple sediment

continuity relationship. This lowers the elevation by

an amount equivalent to net volumetric export of

sediment from the cell (that is, output less input)

divided by the cell area, or is aggraded by an

elevation change in which net import of sediment is

divided by the cell area and is also adjusted to reflect

the higher porosity of the deposited sediment. The

topography is rapidly self-organised by the transport

law until, depending on the initial topography and

the various parameter values selected, a braided

pattern is created (Fig. 8). As continuing erosion and

deposition takes place, and occasional avulsions

occur, the details of the geometry change, for given

sets of parameter values, an ‘average’ and reasonably

stable morphological structure may be maintained

over a relatively large number of model iterations. In

the example in Fig. 8, the model included addition of

a sediment flux into the upper end of the simulated

reach, and this was varied sinusoidally with a period

of 10 000 iterations. During the high sediment feed

stages of the cycle, aggradation occurred at the upper

end of the simulated reach. The evolution of the

channel is illustrated by the map of discharge. It is

clear that an increased area of bar surface which is

inundated by shallow flow develops in the upper part

of the reach as the accumulating sediment progrades

downstream. In addition, although the periods of low

sediment feed result in incision of the channel, the

channel does not become locked into a stable position,

and even in the downstream reaches there are major

shifts of the channel. With this model, it is a relatively

straightforward procedure to count the number of

iterations for which each cell has been stable, and to

generate a map at selected time steps of the ‘ages’ (in

numbers of iterations) of every cell. This means that it

is possible to generate a history of the intermittent

renewal of vegetation succession within the simulated

reach.



To use this model in ecological simulation, further

developments are required. For example, proper

scaling of the model to real time (rather than iteration

counts) is necessary so that succession processes

lasting several decades can be represented. Murray

& Paola (1997) provide some insights into the scaling,

which requires selection of a prototype real stream,

the assumption that the model scales like the proto-

type in some respects (for example, that length scales

are similar), and then a calculation of other scale ratios

(such as the time–scale ratio of model to protoype)

using the routing equations built into the model,

which involve some non-linearities. One simple first

approximation is, however provided by considering

the iteration period. In a single model iteration, the

discharge that enters at the top of the reach is routed

to the bottom. If a length scale is assumed that

matches the model to a real prototype, then an

approximate estimate can be made of the velocity,

and hence of the time period implied by an iteration.

In Fig. 8, a cell size of 10 m implies an iteration

equivalent to about 12 h, and the evolution from the

pattern in the left-hand diagram to that in the right

represents about 500 years. During this period, signi-

ficant channel shifts and bar developments has

occurred in the model, with obvious implications for

the distribution of habitats, the progress of succession

and the biodiversity.

A successional sub-model to coupleto the fluvial dynamics sub-model

Whether the simulated channel is meandering or

braided, the objectives of the simulation will only be

satisfied if a succession sub-model can be linked to

the sub-model of channel dynamics. There are no

deductive or theoretical grounds on which a general,

quantitative succession model can be based, so it will

inevitably rely on empirical data. Furthermore, the

particular sequence of species and communities in a

riparian plant succession will be specific to the

regional climatic and biophysical conditions for the

simulated case, and the model of plant succession

will therefore be case-dependent. An empirically

generated set of rules defining the successional

process will, of course, run the risk of being affected

by factors other than those related to channel

dynamics (which include surface age, elevation,

sediment type and moisture availability). For exam-

Fig. 8 A run of the Murray & Paola (1997) braided river model

in a reach of 22 · 400 cells with a sinusoidally varying sediment

feed having a period of 10 000 iterations. Darker shades in the

topography map are lower elevations, light shades are higher

elevations. Darker shades in the discharge map are higher cell

discharges. The flow (and channel) pattern has changed mark-

edly between 135 000 and 475 000 iterations (from Murray &

Paola, 1997; printed with permission from John Wiley & Sons

Ltd, New York).



ple, if the set of field sites investigated in the

construction of the succession model straddles cli-

matic zones, the empirical evidence of transitions

from one community to another may be distorted by

this effect, as will be the simulated diversity arising

from linking this model to that of the channel

dynamics. Even more insidiously, if the floodplains

sampled in developing an empirical succession

model are associated with a river whose dynamics

are non-equilibrium in their style and rate – for

example, because of historic flow and channel man-

agement practices – this too will distort the succes-

sion simulated in response to the channel dynamics

defined by one the models discussed above. Thus, a

premium is placed on the manner in which fieldwork

is conducted to define a succession model.

Cordes, Hughes & Getty (1997) provide an example

of the kind of field investigation required to construct

a successional model. This involved mapping at

representative sites, using field survey and aerial

photography to identify in an iterative manner the

range of riparian plant communities. Communities

were identified in relation to both their topographic

position, in terms of landform unit and elevation

above low flow level, and their age as measured using

dendrochronology. The communities were then

organised into a successional model using space-time

substitution based on examining transects from the

active channel margins to the distal parts of the

floodplain. Two models were constructed. The first

was for the upper Red Deer River in Alberta, Canada,

a gravel-bed river with narrow, locally incised chan-

nels with limited floodplain development. Early

successional stages here involve sparsely vegetated

gravel bars, which are then colonised by willows

which trap sediment and are followed by poplars or

larger, more mature willows, and eventually spruce.

Later succession depends on the density of poplar

establishment in the earlier stages, and this is partly

dependent on the elevation, landform and substratum

type. The model for the lower Red Deer River reflects

the different biophysical and climatic zone of its

lower reaches, and the sandier bed material and

distinctive channel morphology in this meandering

channel, with many alluvial islands and extensive

point bar areas with large stands of riparian wood-

land. The lower Red Deer River has many of the

characteristics of Miall’s (1985) Model 6 channel style

(see Fig. 3b).

Fig. 9 illustrates, in two different but simplified

forms, a succession model for this reach. The succes-

sion here is towards a cottonwood-dominated com-

munity similar to that described by Dykaar &

Wigington (2000) for the Willamette River in Oregon,

U.S.A. One successional path follows a relatively

direct route from seedlings on sandy, gravelly bars

through various forms of cottonwood or cottonwood-

poplar mixtures, to a shrub-grass community. Some

locations, however, experience various deviations

from this path, reflecting the topography and soils of

particular sites. For example, the ‘young cottonwood’

community (CY) is confined to narrow linear bands on

sandy levees, while the CO community (see Fig. 9) is

mainly found on scroll-bar ridges. There is also a

‘herbaceous wetland’ community (H) which is initi-

ated at low elevations, and essentially occupies the

habitat of abandoned channels after bend cutoffs, and

is a distinctive community reflecting another kind of

topographic element created by the channel dynamics.

The implications of this complexity of successional

trajectories are, of course, that a more sophisticated set

of simulation rules is required than simply a model in

which the correlated variables of age and height

determine the vegetation community. There is an

interaction between age, height, and the habitat

‘patch’ characteristics, partly defined by patch shape

and spatial arrangement, and partly by the patch

sedimentology, soil type and moisture status. There is

also likely to be a stochastic element, in which there

are differential probabilities of taking one or the other

route at a particular junction (as in Fig. 9), depending

on the type of habitat patch. None of these would

constitute insurmountably difficult additional ele-

ments of a successional sub-model. Indeed, the rich-

ness of behaviour that they would represent would

give interesting possibilities for an exploration of the

sensitivity of habitat, community and age diversity to

different values of the critical age, height and patch

properties at which vegetation communities change,

and the different probabilities that control the timing

of these changes. A further area for added sophisti-

cation lies in the addition of routines to allow full

coupling of the successional sub-model to the channel

dynamic sub-model. These would be required to

effect a feedback between the evolving vegetation

community and the parameters in the meandering or

braiding models that control rates of bank erosion and

overbank sedimentation. Rules that define different



rate constants for bank erosion for different riparian

vegetation communities could be based on their levels

of root reinforcement; and rules for varying rates of

sedimentation would reflect the flow resistance typ-

ical of different communities. Although these rela-

tionships cannot be defined reliably at present, the

potential offered by the simulation modelling strategy

outlined here suggests the value of a research

programme to improve their representation, and to

enhance the capability of developing this approach in

order to take full advantage of the understanding it

will enhance.

Discussion and conclusion

This paper has emphasised that the existence, main-

tenance and restoration of total floodplain ecosystem

diversity (that is, the combination of habitat, species

and age diversities) reflects the continued functioning

of the channel dynamics at the reach scale. Smaller

scale processes (Fig. 1) are also likely to be restored as

the freedom of the channel to migrate and adjust its

pattern is reinstated. Diversity of habitats in freely

migrating dynamic rivers also extends to the range of

types of waterbodies, and channel dynamism there-

fore also encourages diversity of aquatic environ-

ments. However, quantification of the level of this

impact may be difficult to achieve. This is because

techniques for simulation of ecological conditions in

streams such as PHABSIM, which rely on the main-

tenance of a stable channel as a model boundary

condition, will then be open to question. The channel

dynamics which influence riparian biota act at a scale

beyond the short stretches of river in which changing

discharges occur within an essentially fixed container;

the common scale for PHABSIM applications. Thus, a

conflict may initially arise between the restoration of

riparian and aquatic ecosystems because if channel

dynamics are emphasised in the maintenance and

restoration of the former, it will be more difficult to

determine the appropriate conditions for the latter.

These observations suggest a need for a closer

collaboration between aquatic and terrestrial biolo-

gists and fluvial geomorphologists, to inform the

Fig. 9 The succession of plant communities observed in riparian and floodplain areas of the upper Red Deer River, as a function

of elevation above low flow level (height, in metres) and age (in years) of surface (based on Cordes et al., 1997).



choice of restoration aims, policy and practice, and to

ensure that the research and data needs are met for

restoration of the appropriate dynamics at the appro-

priate scale, in cases where this becomes economically

and politically viable (Dykaar & Wigington, 2000).

These research needs focus on dynamic channels and

ecosystems at a coarser spatial scale than the present

emphasis at the grain, bedform and microhabitat

scale, and this presents a challenge for fluvial geo-

morphologists, ecologists and river managers, who

will face new questions and a lack of reliable answers

until the gaps in current knowledge have been filled.

Nevertheless, a particular advantage of a modelling

strategy is that it draws attention to such existing

deficiencies, and the focus of this paper on simulation

modelling of the interaction between channel and

ecosystem dynamics has encouraged identification of

some key research needs. These require interdisci-

plinary research at the interface between hydrology,

geomorphology and ecology. For example, successful

manipulation of the flood pulse for ecological restor-

ation requires more information on the optimal timing

of relationships between seed production and flood-

ing; critical soil water potentials for the germination of

seeds; critical rates of soil water decline to optimise

seedling performance and more information on the

response of community dynamics to hydrological

processes to supplement that on the behaviour of

individual species. Restoration of geomorphological

dynamics will require more reliable data on, descrip-

tions of, and parameters to represent: the relationship

between rates of channel change, floodplain turnover

and habitat diversity for different channel patterns;

the balance of seed-based regeneration and vegetative

reproduction in relation to erosion and sedimentation

and their effects on genetic diversity; the effects of

different riparian vegetation on bank erosion rates;

and the rates and patterns of sedimentation within

riparian vegetation during overbank flow. Investiga-

tions into these questions will inform the develop-

ment and calibration of simulation models of the kind

discussed in this paper, so that these models may be

used to address a variety of practical questions.

Topics of practical relevance are likely to include

establishing the magnitude and frequency of the

controlled flood pulse required to maintain an appro-

priate floodplain turnover rate and pattern-related

habitat diversity in order to sustain ecosystem

dynamics. As most restoration initiatives will be

relatively local in scale, eco-geomorphological mod-

elling will help to determine which rivers, and which

reaches within them, are most suited to conservation

or restoration of natural channel dynamics. It will also

help to answer questions about the desirability of

permitting channel dynamics in a succession of

reaches in order to encourage larger-scale river

corridor ecological processes, for example at meta-

population levels. Of course, there will also be many

issues to address which are more dependent on policy

and politics. Restoring channel dynamics may require

that flood embankments are retired further from the

river or abandoned, but this could jeopardise the

integrity of adjacent land uses, and create conflict

between the restoration objective and economic activ-

ities, requiring cost-benefit analyses to resolve the

conflict. The feasibility of restoration of the dynamic

behaviour of river channels in their floodplains may

also depend on legal challenges to land ownership, as

bank erosion, channel migration and avulsion occur.

However, the practice of river and ecosystem man-

agement can only be assisted by the development of

simulation models that provide the capacity to exam-

ine a range of scenarios, to establish the available

choices, and to underpin review of the costs and

benefits of conservation and restoration of the eco-

system diversity of dynamic floodplain environments.

Acknowledgments

This paper is based on research conducted for two

EC-funded research projects: Floodplain Biodiversity

and Restoration (FLOBAR): Hydrological and geo-

morphological mechanisms influencing floodplain

diversity and their application to the restoration of

European floodplains (1996–99; EC Contract No.

ENV4-CT96-0317); and ‘Floodplain Biodiversity and

Restoration (FLOBAR 2): Integrated natural science

and socio-economic approaches to catchment flow

management’ (2000–2003; EC Contract No. ENK1-CT-

1999-00031 FLOBAR2). We are endebted to colleagues

and partners in these projects, in Cambridge, Gre-

noble, Clermont-Ferrand, Toulouse, and Umea; Bill

Adams, Adrian Hayes, Nadia Barsoum, Mark Win-

field, Jean-Luc Peiry, Guy Pautou, Jacky Girel, Phil-

lippe Belleudy, Remi Foussadier, Franck Vautier,

Gerard Marigo, Etienne Muller, Henri Decamps, Luc

Lambs, Helene Guilloy, Christer Nilsson and Mats

Johansson.



References

Amoros C., Bravard J.P., Castella C. et al. (1986)

Recherches Interdisciplinaires sur les ecosystemes de la

Basse-Plaine de l’Ain (France): potentialites evolutives et

gestion. Documents de Cartographie Ecologique 29.

Universite Scientifique, Technologique et Medicale de

Grenoble, CNRS, Grenoble, 166 pp.

Bravard J.P., Landon N., Peiry J.-L. & Piegay H. (1999)

Principles of engineering geomorphology for man-

aging channel erosion and bedload transport, exam-

ples from French rivers. Geomorphology, 31, 291–311.

Brierley G.J. & Fryirs K. (2000) River styles, a geomorphic

approach to catchment characterization: implications

for river rehabilitation in Bega Catchment, New South

Wales, Australia. Environmental Management, 25, 661–

679.

Brown A.G., Stone P. & Harwood K. (1995) The Biogeo-

morphology of a Wooded Anastomosing River: The Gearagh

on the River Lee in County Cork, Ireland. Occasional Paper

32. Department of Geography, University of Leicester,

Leicester. 76.

Church M.A. (2002) Geomorphic thresholds in riverine

landscapes. Freshwater Biology, 47, 541–557.

Church M.A. & Jones D. (1982) Channel bars in gravel-

bed rivers. In: Gravel-Bed Rivers (Eds R.D. Hey, J.C.

Bathurst & C.R. Thorne), pp. 291–338. John Wiley &

Sons, Chichester.

Connell J.H. (1978) Diversity in tropical rain forests and

coral reefs. Science, 199, 1302–1310.

Cordes L.D., Hughes F.M.R. & Getty M. (1997) Factors

affecting the regeneration and distribution of riparian

woodlands along a northern prairie river: the Red Deer

River, Alberta, Canada. Journal of Biogeography, 24, 675–

695.

Dykaar B.B. & Wigington P.J. Jr (2000) Floodplain

formation and cottonwood colonization patterns on

the Willamette River, Oregon, USA. Environmental

Management, 25, 87–104.

Gilvear D.J., Bryant R. & Hardy T. (1999) Remote

sensing of channel morphology and in-stream fluvial

processes. Progress in Environmental Science, 1, 257–

284.

Girel J. & Pautou G. (1997) The influence of sediment on

vegetation structure. In: Buffer Zones: Their Processes and

Potential in Water Protection (Eds N.E. Haycock, T.P.

Burt, K.H.T. Goulding & G. Pinay), pp. 93–112. Quest

Environmental, Harpenden.

Gurnell A.M. (1997) Channel change on the River

Dee meanders, 1946–1992 from the analysis of air

photographs. Regulated Rivers: Research and Manage-

ment, 12, 13–26.

Gurnell A.M. & Petts G.E. (2002) Island-dominated

landscapes of large floodplain rivers, a European

perspective. Freshwater Biology, 47, 581–600.

Gurnell A.M., Petts G.E., Harris N.M., Ward J.V., Tockner

K., Edwards P.J. & Kollman J. (2000) Large wood

retention in river channels: the case of the Fiume

Tagliamento, Italy. Earth Surface Processes and Land-

forms, 25, 255–275.

Hickin E.J. (1974) The development of meanders in

natural river channels. American Journal of Science, 274,

414–442.

Hill M. & Platts W.S. (1991) Ecological and geomorpho-

logical concepts for instream and out-of-channel flow

requirements. Rivers, 2, 319–343.

Howard A.D. (1992) Modelling channel migration and

floodplain sedimentation in meandering streams. In:

Lowland Rivers: Geomorphological Perspectives (Eds P.A.

Carling & G.E. Petts), pp. 1–41. John Wiley & Sons Ltd,

Chichester.

Hughes F.M.R. (1997) Floodplain biogeomorphology.

Progress in Physical Geography, 21, 501–529.

Hughes F.M.R., Barsoum N., Richards K.S., Winfield M.

& Hayes A. (2000) The response of male and female

black poplar (Populus nigra L. subsp. betulifolia (Pursh)

W. Wettst.) cuttings to different water table depths and

sediment types: implications for flow management and

river corridor biodiversity. Hydrological Processes, 14,

3075–3098.

Johannesson J. & Parker G. (1989) Linear theory of river

meanders. In: River Meandering (Eds S. Ikeda &

G. Parker), pp. 181–204. Water Resources Monograph

12, American Geophysical Union, Washington, DC

Johnson W.C. (2000) Tree recruitment and survival in

rivers: influence of hydrological processes. Hydrological

Processes, 14, 3051–3074.

Junk W.J., Bayley P.B. & Sparks R.E. (1989) The flood

pulse concept in river-floodplain systems. Canadian

Special Publication of Fisheries and Aquatic Sciences, 106,

110–127.

Karrenberg S., Edwards P.J. & Kollmann J. (2002) The life

history of Salicacaeae living in the active zone of flood-

plains. Freshwater Biology, 47, 733–748.

King J. & Louwe D. (1998) Instream flow requirements

for regulated rivers in South Africa using the building

block methodology. Aquatic Ecosystem Health and Man-

agement, 1, 109–124.

Kirkby M.J. (1971) Hillslope process-response models

based on the continuity equation. In: Slopes: Form and

Process (Ed. D. Brunsden), pp. 15–30. Institute of British

Geographers, London.

Lawler D.M. (1992) Process dominance in bank erosion

systems. In: Lowland Rivers: Geomorphological Perspec-



tives (Eds P.A. Carling & G.E. Petts), pp. 117–143. John

Wiley & Sons Ltd, Chichester.

Lewin J. & Weir M.J.C. (1977) Morphology and recent

history on the lower Spey. Scottish Geographical Maga-

zine, 93, 45–51.

Mahoney J.M. & Rood S.B. (1998) Streamflow require-

ments for cottonwood seedling recruitment – an

integrative model. Wetlands, 18, 634–645.

Malanson C.P. (1993) Riparian Landscapes. Cambridge

University Press, Cambridge.

Marston R.A., Girel J., Pautou G., Piegay H., Bravard J.P.

& Arneson C. (1995) Channel metamorphosis, flood-

plain disturbance, and vegetation development – Ain

River. Geomorphology, 13, 121–131.

Mertes L.A.K. (2002) Remote sensing of riverine land-

scapes. Freshwater Biology, 47, 799–816.

Miall A.D. (1985) Architectural element analysis: a new

method of facies analysis applied to fluvial deposits.

Earth Science Reviews, 22, 261–308.

Miall A.D. (1996) The Geology of Fluvial Deposits: Sedimen-

tary Facies, Basin Analysis, and Petroleum Geology.

Springer, Berlin.

Middleton B. (1999) Flood Pulsing and Disturbance

Dynamics. John Wiley & Sons Ltd, New York.

Milhous R.T., Updike M.A. & Schneider D.M. (1989)

Physical Habitat Simulation system reference manual –

Version II, Instream Flow Information Paper No. 26,

Vol. 89, U.S. Fish and Wildlife Service, Biological

Report, Washington, DC.

Milton E.J., Gilvear D.J. & Hooper I.D. (1995) Investi-

gating river channel changes using remotely sensed

data. In: Changing River Channels (Eds A.M. Gurnell &

G.E. Petts), pp. 277–301. John Wiley & Sons, Chiches-

ter.

Moon B.P., van Niekerk A.W., Heritage G.L., Roger K.H.

& James C.S. (1997) A geomorphological approach to

the ecological management of rivers in the Kruger

National Park: the case of the Sabie River. Transactions,

Institute of British Geographers, New Series, 22, 31–48.

Muller E. (1997) Mapping riparian vegetation along

rivers: old concepts and new methods. Aquatic Botany,

58, 411–437.

Muller E., Decamps H. & Dobson M.K. (1993) Contribu-

tion of space remote sensing to river studies. Freshwater

Biology, 29, 301–312.

Murray A.B. & Paola C. (1997) Properties of a cellular

braided-stream model. Earth Surface Processes and

Landforms, 22, 1001–1025.

Naiman R.T., Decamps H. & Pollock M. (1993) The role of

riparian corridors in maintaining regional biodiversity.

Ecological Applications, 3, 209–212.

Nanson G.C. & Beach H.F. (1977) Forest succession and

sedimentation on a meandering river floodplain,

Northeast British Columbia, Canada. Journal of Bio-

geography, 4, 229–251.

Nanson G.C. & Croke J.C. (1992) A genetic classification

of floodplains. Geomorphology, 4, 459–486.

Nilsson C., Grelsson G., Johansson M. & Sperens U.

(1991) Small rivers behave like large rivers: effects of

postglacial history on plant species richness along river

banks. Journal of Biogeography, 18, 533–541.

Peterken G.F. & Hughes F.M.R. (1995) Restoration of

floodplain forests in Britain. Forestry, 68, 187–202.

Petts G.E. (1996) Water allocation to protect river

ecosystems. Regulated Rivers: Research and Management,

12, 353–365.

Petts G.E., Gurnell A.M., Gerrard A.J. et al. (2000)

Longitudinal variations in exposed riverine sediments;

a context for the ecology of the Fiume Tagliamento,

Italy. Aquatic Conservation: Marine and Freshwater Eco-

systems, 10, 249–266.

Pickett S.T.A. & White P.S. (Eds) (1985) The Ecology of

Natural Disturbance and Patch Dynamics. Academic

Press, San Diego.

Piegay H., Bornette G., Citterio A., Herouin E., Moilin B.

& Statiotis C. (2000) Channel instability as a control on

silting dynamics and vegetation patterns within peri-

fluvial zones. Hydrological Processes, 14, 3011–3029.

Poole G.C. (2002) Fluvial landscape ecology: addressing

uniqueness within the river discontinuum. Freshwtaer

Biology, 47, 641–660.

Richards K.S. (1982) Rivers: Form and Process in Alluvial

Channels. Methuen, London. 361 pp.

Rumsby B.T., Brasington J. & McVey R. (2001) The

potential for high resolution fluvial archives in braided

rivers: quantifying historic reach-scale channel and

floodplain development in the River Feshie, Scotland.

In: River Basin Sediment Systems: Archives of Environ-

mental Change (Eds D. Maddy, M.G. Macklin &

J. Woodward). Balkema, Rotterdam.

Salo J., Kalliola R., Hakkinen I., Makinen Y., Niemala P.,

Puhakka M. & Coley P.D. (1986) River dynamics and

the diversity of Amazon lowland forests. Nature, 322,

254–258.

Shankman D. (1993) Channel migration and vegetation

patterns in the southeastern coastal plain. Conservation

Biology, 7, 176–183.

Tockner K., Malard F. & Ward J.V. (2000) An extension of

the Flood Pulse Concept. Hydrological Processes, 14,

2861–2883.

Vannote R.L., Minshall G.W., Cummins K.W., Sedell J.R.

& Cushing C.E. (1980) The river continuum concept.

Canadian Journal of Fisheries and Aquatic Sciences, 37,

130–137.

Vautier F. (2000) Dynamique geomorphologique et vegetali-

sation des cours d’eau endigues: l’exemple de l’Isere dans le



Gresivaudan. PhD Thesis, l’Universite Joseph Fourier,

Grenoble, France.

Ward J.V. (1998) Riverine landscapes: biodiversity pat-

terns, diversity regimes and aquatic conservation.

Biological Conservation, 83, 269–278.

Ward J.V. & Tockner K. (2001) Biodiversity: towards a

unifying theme for river ecology. Freshwater Biology, 46,

807–819.

Ward J.V., Tockner K., Arscott B.D. & Claret C. (2002)

Riverine landscape diversity. Freshwater Biology, 47,

517–539.

Ward J.V., Tockner K. & Schiemer F. (1999) Biodiversity

of floodplain ecosystems: ecotones and connectivity.

Regulated Rivers: Research and Management, 15, 125–139.

Werritty A. & Ferguson R.I. (1980) Pattern changes in a

Scottish braided river over 1, 30 and 200 years. In:

Timescales in Geomorphology (Eds R.A. Cullingford,

D.A. Davidson & J. Lewin), pp. 53–68. John Wiley &

Sons, Chichester.

Whittaker R.H. (1960) Vegetation of the Siskyou Moun-

tains, Oregon and California. Ecological Monographs, 30,

279–338.

Winterbottom S. & Gilvear D.J. (1997) Quantification of

channel bed morphology in gravel-bed rivers using

airborne multispectral imagery and aerial photography.

Regulated Rivers: Research and Management, 13, 489–499.

(Manuscript accepted 11 November 2001)



Geomorphic dynamics of floodplains: ecological implications and a potential modelling strategy

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