Physical Geography RIPARIAN VEGETATION ...

This article was downloaded by: [ECU Libraries] On: 14 March 2014, At: 05:49 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Physical Geography Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tphy20

RIPARIAN VEGETATION VARIABILITY ALONG PERENNIAL STREAMS IN CENTRAL ARIZONA Thad A. Wasklewicz

a

a

Department of Geography , University of Memphis , Memphis, Tennessee 38152 Published online: 15 May 2013.

To cite this article: Thad A. Wasklewicz (2001) RIPARIAN VEGETATION VARIABILITY ALONG PERENNIAL STREAMS IN CENTRAL ARIZONA, Physical Geography, 22:5, 361-375 To link to this article: http://dx.doi.org/10.1080/02723646.2001.10642749

PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/termsand-conditions

RIPARIAN VEGETATION VARIABILITY ALONG PERENNIAL STREAMS IN CENTRAL ARIZONA1

Downloaded by [ECU Libraries] at 05:49 14 March 2014

Thad A. Wasklewicz Department of Geography University of Memphis Memphis, Tennessee 38152 Abstract: The spatial distribution of riparian vegetation is closely allied to abiotic pro cesses along streams and rivers. There are dynamic relations between physical process, fluvial forms, and biotic structures. Explanation of these associations is critical to scientific understanding and practical management of riverine environments. Therefore, this study determines what geophysical parameters lead to the spatial patterns found in species of warm interior and cold montane riparian deciduous forests in central Arizona. Five ripar ian vegetation populations were examined along five perennial streams in the transition zone of central Arizona. The populations included Populus angustifolia (narrowleaf Cot tonwood), two commonly associated species of willow Salix lasiandra (western black wil low) and Salix lasiolepis (arroyo willow), Alnus oblongifolia (Arizona alder), and Platanus wrightii (Arizona sycamore). Canonical correspondence analysis (CCA) with a forward selection was used to assess quantitatively the role of stream power in riparian vegetation patterns. Results indicated 40% of the spatial variability in the riparian populations was explained by channel morphology and several other variables related to changing channel geometry. Although floods are linked to the formation of geomorphic surfaces and the regeneration of riparian vegetation, changing fluvial landforms and channel patterns were closely related to the riparian species patterns in central Arizona. [Key words: Mogollon Rim, channel morphology, multivariate statistics.]

INTRODUCTION The "patchy" and often discontinuous nature of riparian plant distributions pro vides an excellent opportunity for the spatial analyses of species-site relationships. Riparian vegetation exists along complex longitudinal and transverse stream gradi ents (Baker, 1989; Bendix, 1994b). The interactions of multiple factors along these gradients lead to the dynamic structures of plant communities and the distributions of plant species (Zimmermann, 1969; Irvine and West, 1979; Kalliola and Puhakka, 1988; Szaro, 1990; Bendix, 1994a; Baker and Walford, 1995). However, even with knowledge that multiple factors influence the spatial distributions of riparian plant species, the underlying causes of the arrangements have not been appreciated fully (Marston et al., 1995). The present study clarifies linkages between fluvial hydrologic processes, fluvial landforms, and patterns of riparian vegetation populations by using a suite of geomorphic and hydrologic variables. The most significant vari ables were selected from geographic and ecologic studies to determine those phys ical processes and landforms that lead to the spatial patterns of tree and shrub populations in warm interior and cold montane riparian deciduous forests found in central Arizona (Brown, 1994). Physical processes, and the landforms they pro361 Physical Geography, 2001, 22, 5, pp. 361-375. Copyright © 2001 by V. H. Winston & Son, Inc. All rights reserved.


362

THAD A. WASKLEWICZ

duce, provide both a foundation for the establishment of vegetation and boundaries to control the spatial configurations of the riparian plants (Swanson et al., 1988). Studies examining process/form-vegetation interactions increase our understanding of the dynamic patterns of riparian vegetation (Hupp and Osterkamp, 1996; Gurnell, 1997). Several studies in fluvial geomorphology have investigated spatial patterns of energy using stream power as a parameter (Graf, 1983; Magilligan, 1992; Lecce, 1997). Stream power measures the amount of energy expenditure along a crosssection or reach. Geomorphic work is accomplished when potential energy, asso ciated with position, changes to kinetic energy. Kinetic energy, when it is in excess, causes stream-bed and bank erosion. When the energy dissipates, the sediments are deposited. This represents an important disturbance mechanism in many riparian environments and generates new surfaces for riparian vegetation to inhabit. Graf (1983), Magilligan (1992), Lecce (1997), and Knighton (1999) have found that changes in some combination of channel morphology, channel width, channel slope, and geology produced variations in stream power. Graf's (1988) findings led him to suggest the continuum of channel patterns and processes can be investigated best through the use of stream power. The ecological literature has long identified the importance of unimodal (nonlin ear) species distributions (Odum, 1971). Nonlinear distributions result from physi ological processes of individual species, which permit the species to inhabit an area within a range of environmental conditions. Biogeographic research has shown riparian vegetation distributions result from and, in turn, modify these environmen tal conditions (Bendix, 1994a, 1994b; Baker and Walford, 1995). Bendix (1994a) found that some warm interior riparian deciduous forest species patterns were linked to elevation, unit-stream power, and fire history. Baker and Walford found that sediment size and soil development were key variables in explaining a portion of the variability in several cold montane riparian deciduous forest species. They found that other geomorphic parameters were not as significant, but concluded that measures capturing the movement of sediment and water (i.e., stream power) may be a better surrogate for flood disturbance mechanisms. Zimmerman (1969), Baker (1989), and Szaro (1990) found that valley width and channel morphology were significant in determining species patterns in both warm interior and cold montane riparian deciduous forests. Previous studies analyzing channel dynamics in relation to riparian patterns have discovered three major points: (1) channel morphology alters along longitudinal stream profiles given changes in slope, channel width, geology, drainage area, and sediment inputs; (2) unit-stream power changes nonlinearly downstream from vari ations in channel morphology, geology, channel width, and slope; and (3) vegeta tion exhibits nonlinear distributions along streams as a result of changes in physical and biological parameters. These findings lead to three hypotheses for explaining a significant portion of the spatial variability of tree and shrub species in warm inte rior and cold montane riparian deciduous forests in central Arizona: (1) a suite of physical variables, including channel morphology and stream power contribute sig nificantly to riparian vegetation patterns; (2) channel morphology and other chan nel-form variables contribute significantly to riparian vegetation patterns; or (3)

RIPARIAN VEGETATION

363

unit-stream power and other process related physical variables contribute signifi cantly to riparian vegetation patterns. METHOD


Study Area The present study sampled cross-sections along five perennial streams in the Tonto National Forest of central Arizona (Fig. 1). The study sites were located between 1200 and 2300 m in elevation. At the lower end of these elevations were the warm interior deciduous forests and, at the higher elevations, the cold montane riparian deciduous forests. The streams were highly fragmented as a result of the diverse topography of the transition zone of Arizona. Streams transition quickly between three channel morphologies: alluvial channels, bedrock-confined chan nels, and alluvial-confined channels (as defined by Minshall et al., 1989). Alluvial channels exhibited both tranquil and turbulent flow conditions. The streams were single thread or, in some cases, had two low-flow channels. Meandering dominated and it was not uncommon to find multiple abandoned channels or multiple lowflow channels. Most of the disturbance occurred from reworking of stream bed and banks. Terraces and floodplains were common. The second type of channel was narrow bedrock channels. These reaches had confined flows and limited lateral migration. Disturbance was limited, but the magnitude of disturbance increased because the flows became restricted at the bed and bank by bedrock. Sediment was highly mobile. What little sediment was found along the bedrock-confined reaches was trapped by vegetation or stored as small pockets in fractures and depressions in the bedrock. The final channel morphology evaluated was alluvial-confined chan nels. They displayed characteristics of both bedrock-confined and alluvial chan nels. Broad alluvial channels were confined at their lateral margins by bedrock outcrops or colluvial boulders. These reaches had high inputs and mobility of sed iment. Stream gauge data were not available for any of the reaches, but Table 1 dis plays average hydraulic parameters and calculated flows for each reach type. Fluvial Geomorphic Sampling Techniques Sampling of environmental (channel geometry, sediment, microtopographic, and hydraulic) variables was based on an organizational hierarchy of segments, reaches, sites, and parameters (Meador et al., 1993). Segments of streams were defined by abrupt changes in slope or constrained by the major tributary streams. In each seg ment, a series of reaches was established and, within each reach, cross-sections were established based on geomorphic channel units. The measurements were gathered at channel cross-sections (sites), which were established at the center of the dominant channel unit (i.e., pool, riffle, glide, or run). Table 2 contains a list of 14 environmental variables collected at each site and citations for collection techniques. Many of the hydrogeomorphic variables were typical measures found in many studies from fluvial geomorphology, but two of the variables need further explana-


364

THAD A. WASKLEWICZ

Fig. 1. Location of the five drainages examined during the study. All of the streams were perennial and major tributaries to the Salt River.

Table 1. Average Channel Geometry Measures for the Three Types of Reaches Identified in the Present Study Gradient

Sinuosity

Width (m)

Depth (m)

Particle size (cm)

Discharge (cm)

Alluvial

0.028

1.06

5.42

2.03

12.31

11.75

Alluvial confined

0.014

1.11

7.98

2.24

11.72

12.15

Bedrock confined

0.019

1.16

5.90

2.14

14.38

8.04

Morphology

tion. Discharge was calculated using the XSPRO channel cross-section analyzer program (Grant et al., 1992). All five streams in the study area were ungauged, cre ating a problem with regard to direct measures of stream flow and stream power. As a result, stream-power calculations were based on a single discharge. The single discharge integrates the range of flows experienced in each of the streams (Lecce,

RIPARIAN VEGETATION

365

Table 2. The Hydrogeomorphic Variables Sampled at the 29 Sitesa


Hydrogeomorphic variable

Abbreviation

Citation of technique

Riparian zone width

ripzwdt

Valley width inhabited by riparian species

Channel morphology

morphlg

Minshall et al. (1989)

Channel gradient

chngrad

Channel width

chnwdth

USGS topographic maps Harrelson et al. (1994)

Channel depth

chndpth

Harrelson et al. (1994)

Channel width depth ratio

chnwddp

Gordon et al. (1992)

Channel sinuosity

chnsinu

Richards (1982)

Left bank angle

Ifbkang

Platts et al. (1983)

Right bank angle

rtbkang

Platts et al. (1983)

Mean channel particle size

Wolman (1954)

Mean substrate particle size

chnpart subsprt

Wolman(1954)

Cross-sectional stream power

xsecstp

Lecce (1997)

Distance to the thalweg

disthal surfelv

Distance from each individual to thalweg

Surface elevation

Bendix (1994b)

a

The methodology for the techniques can be found in the citations. The abbreviations column refers to the variable codes used in the analyses.

1997). A general assumption has been made that bankfull discharge was the most important discharge in eroding sediment and maintaining the channel form and structure (Wolman and Miller, 1960; Whiting et al., 1999). Channel geometry was determined in the field and discharge at each site was estimated using Manning's equation in XSPRO channel cross-section analyzer program: Q=

AR0.667S0.5n-1

(1)

where Q is discharge (m3/s), A is cross-sectional area (m2), R is hydraulic radius (m), 5 is a dimension less energy gradient derived from channel slope measurements from topographic maps, and n is Manning's roughness estimated by field observa tions using procedures outlined by Arcement and Schneider (1989). Bankfull dis charge was established using field observations and elevation measurements of the low bench at each site (Schumm, 1960; Bray, 1972). The stage of the surface was used to extract the bankfull discharge from the discharges determined with the XSPRO channel cross section analyzer program. Bankfull discharges then were used to compute a measure of stream power. Lecce (1997) showed that cross-sectional stream power varied nonlinearly down stream. Cross-sectional stream power provides a way to measure quantitatively the capacity of water to transport sediment (Phillips, 1989). Cross-sectional stream power was calculated using the following equation:

366

THAD A. WASKLEWICZ

Ω =

γQbS

(2)

where Ω is stream power per unit length (W/m), γ is the specific weight of the water (9810 N/m3), and Q b is the bankfull discharge (m3/s).


Vegetation Sampling Techniques Five dominant tree and shrub species were identified in the study area: narrowleaf cottonwood (Populus angustifolia), willows (Salix lasiandra and Salix lasiolepis), Arizona alder (Alnus oblongifolia), and Arizona sycamore (Platanus wrightii). The tree and shrub populations were sampled along belt transects placed at each site. Plot width equaled the belt transect width (10 m), while the plot length varied with the length of the geomorphic surface. For each individual of the population diameter-at-breast-height for trees, or the basal diameter for shrubs was measured using a diameter tape. A clinometer or a measuring tape was used to measure tree/ shrub height. Plots containing a high density of juvenile plants (especially those where height is less than 1 m) were subsampled in a 1 m x 1 m subplot. Distance to the stream edge and distance to the channel thalweg were measured from each individual. All woody vegetation was identified using Kearney and Peebles' (1960) guide to the flora of Arizona. After collecting all of the vegetation data, the trees and shrubs were broken down into four size classes based on diameter-at-breast-height and height as defined by Szaro (1990) and Walford and Baker (1995). Data Analysis Statistical analyses were based on an ordination technique called canonical cor respondence analysis (CCA) (Ter Braak and Prentice, 1988). An ordination tech nique was used because it permitted analysis of nonlinear data and detected unimodal relations between species and environmental variables (Ter Braak, 1988). CCA, a direct gradient analysis, produced ordination axes constrained to be a func tion of the measured and calculated environmental variables (Table 2). This analysis provided a way to identify complex relations between the hydrogeomorphic (envi ronmental) controls and the riparian vegetation. Direct gradient analysis was selected because it has been shown to be more robust than indirect gradient analy ses (Kupfer et al., 1997). The solution from CCA was displayed in a graphical format (a biplot) as well as a quantitative summary. Forward selection with a Monte Carlo permutation test was used to determine which variables from the solution made sig nificant contributions to the findings (Ter Braak, 1995). The defaults in CANOCO 3.10 were used in defining the direct gradient analysis and CANODRAW was used to produce a biplot of the results from species-environment relations. RESULTS The variation inflation factor from the CCA indicated no multi-collinearity in the matrix (Table 3). Each hydrogeomorphic variable was below the critical variation inflation factor value of 20. Therefore, all of the variables warranted further interpre-

RIPARIAN VEGETATION

367

Table 3. The Variance Inflation Factor Measures the Degree of Multiple Correlation between the Hydrogeomorphic Variables a


Variable

(Weighted) M

SD

SPEC AX1

0

1.0415

SPEC AX2

0

1.0567

SPEC AX3

0

1.1005

SPEC AX4

0

1.1397

ENVI AX1

0

1.0000

ENVI AX2

0

1.0000

ENVI AX3

0

1.0000

ENVI AX4

0

1.0000

Inflation factor

ripzwdt

44.9073

20.5643

7.2777

morphlg

2.0032

0.8778

4.7142

chngrad

0.0169

0.0067

6.2034

chnsinu

1.0787

0.0581

2.7759

Ifbkang

41.3508

26.6890

3.1179

rtbkang

52.7316

27.1400

2.6855

chnpart

11.4536

4.3133

6.1793

chnwdth

6.5903

2.0757

15.5783

chndpth

2.1944

0.8253

11.2319

chnwddp

3.3422

1.4343

12.2660

surfelv

1.2103

0.4774

2.1525

disthal

15.1750

14.0351

9.4129

subsprt

0.8169

0.1945

4.8404

xsecstp

2,145.7450

1,994.7763

7.3330

a

A high variance inflation factor (>20) indicates multi-collinearity and the variable does not war rant interpretation. None of the variables exhibited a high variance inflation factor and all were incorporated into the analysis.

tation. The species-environment correlations indicated that the first two axes were significant at the 9 5 % confidence interval (Table 4). Species-environment relations revealed that 4 0 % of the variability in the matrix was explained by these two axes. Channel morphology and cross-sectional stream power were the two variables most correlated with the first axis (Table 5). Riparian zone width and the slope angle of the left bank were the two highest correlated variables with the second axis (Table 5). A biplot was constructed to elucidate relationships between the environmental variables and the riparian vegetation populations (Fig. 2). The distribution of the narrowleaf cottonwood was tied to alluvial stream reaches, which had high stream-

368

THAD A. WASKLEWICZ

Table 4. Summary Statistics from the Canonical Correspondence Analysis (CCA) 1

2

3

4

Total inertia

Eigenvalues

0.828

0.599

0.555

0.472

5.244

Species-environment correlations

0.960

0.946

0.909

0.877

Axes


Cumulative percentage variance of species data

15.8

27.2

37.8

46.8

of species-environment relation

23.1

39.8

55.3

68.5

Sum of all unconstrained eigenvalues

5.244

Sum of all canonical eigenvalues

3.581

Table 5. Species and Environmental Axes Correlations with the Hydrogeomorphic Variables Variable SPEC AX1

SPEC AX1 SPEC AX2 SPEC AX3 SPEC AX4 ENVI AX1 ENVI AX2 ENVI AX3 ENVI AX4 1

SPEC AX2 -0.0449

1

SPEC AX3

0.0122

-0.0571

SPEC AX4

0.0077

0.0009

ENVI AX1

0.9601

0

1 -0.0463 0

1 0

1

ENVI AX2

0

0.9463

0

0

0

1

ENVI AX3

0

0

0.9087

0

0

0

ENVI AX4 ripzwdt

0

0

0

0.8774

-0.1767

-0.6831

-0.2105

-0.0688

0

0

1 0

1

-0.1840

-0.7218

-0.2317

-0.0784

morphlg

0.6861

0.1811

0.1493

-0.3200

0.7145

0.1914

0.1643

-0.3647

chngrad

-0.4611

0.0244

0.5337

0.0078

-0.4802

0.0258

0.5873

0.0088

chnsinu

-0.2405

0.4201

0.0448

-0.3554

-0.2504

0.4439

0.0493

-0.4050

Ifbkang

-0.3524

0.6550

-0.1450

0.1251

-0.3670

0.6921

-0.1596

0.1426

rtbkang

-0.2189

0.0752

-0.2010

-0.5368

-0.2280

0.0795

-0.2212

-0.6118

chnpart

-0.5541

0.1854

0.3581

-0.1093

-0.5771

0.1959

0.3941

-0.1246

chnwdth

0.5364

0.0008

-0.2827

-0.3191

0.5586

0.0008

-0.3111

-0.3637

chndpth

-0.2011

-0.2980

0.2107

-0.2471

-0.2094

-0.3149

0.2318

-0.2817

chnwddp

0.4675

0.2214

-0.3899

-0.1010

0.4869

0.2340

-0.4291

-0.1151

surfelv

0.0151

-0.1429

0.6043

-0.1691

0.0157

-0.1510

0.6650

-0.1927

disthal

-0.4177

-0.3213

0.0005

0.0631

-0.4350

-0.3395

0.0006

0.0719

subsprt

-0.1278

-0.3024

0.3070

0.1230

-0.1331

-0.3196

0.3379

0.1401

xsecstp

-0.6245

-0.3837

0.0154

-0.0152

-0.6504

-0.4054

0.0170

-0.01 74


RIPARIAN VEGETATION

369

Fig. 2. Biplot showing the species-environment relations in graphical form. The arrows represent the hydrogeomorphic variables and point to the direction of maximum change. The points are weighted averages representing the centroid of the species. To increase the legibility of the plot, not all environ mental variables or species were included in the diagram.

power values, wide riparian zone widths, and low angles on the left bank. The wil low species were located in bedrock-confined channels that produced steep left bank angles. The bedrock-confined reaches exhibited much smaller riparian zone widths and lower cross-sectional stream-power measures. Finally, Arizona sycamore and alder were located along alluvial-confined stream valleys where the riparian zone width was intermediate in comparison to the willows and the cottonwoods. These reaches had low stream-power values and low left bank angle mea sures. A Monte Carlo test using 99 permutations showed that environmental variables were significantly related (.01 level) to the distributions of the riparian tree and shrub species identified in this study.

370

THAD A. WASKLEWICZ

Table 6. Forward Selection from the Canonical Correspondence Analysis (CCA)a


Variable

Extra fit

F ratio p value

Cumulative variance explained

% variance explained

morphlg

0.54

3.10

.01

0.54

15.04

Ifbkang

0.42

2.53

.01

0.96

11.70

chngrad

0.41

2.65

.01

1.37

11.42

ripzwdt

0.33

2.20

.03

1.70

9.19

rtbkang

0.29

2.06

.07

1.99

8.08

surfelv

0.29

2.14

.02

2.28

8.08

xsecstp

0.18

1.35

.15

2.46

5.01

chnpart

0.15

1.16

.31

2.61

4.18

chnwdth

0.20

1.55

.18

2.81

5.57

disthal

0.14

1.09

.30

2.95

3.90

chndpth

0.16

1.24

.19

3.11

4.46

chnwddp

0.23

1.89

.15

3.34

6.41

chnsinu

0.13

1.09

.35

3.47

3.62

subsprt

0.12

1.04

.48

3.59

3.34

a

Each variable tested with 99 permutations with a Monte Carlo test to obtain a p value. Percent of the variance explained was obtained by dividing the extra fit by the total variance explained by the hydrogeomorphic variables.

Although the biplot and correlation matrix provided insights into the speciesenvironment relations, further quantification was accomplished using forward selection (Table 6). Forward selection revealed that channel morphology (15%) accounted for the largest portion of the total variance explained by the hydrogeo morphic variables. Two other variables from the original four identified in the CCA, left bank angle (~12%) and riparian zone width (~9%), were important to the ripar ian vegetation distribution. Cross-sectional stream power did not contribute signifi cantly to the species distributions as it had in the initial findings from the CCA. This would further support the importance of channel morphology and its relation to the first axis. Two additional hydrogeomorphic variables were considered important to the arrangement of the riparian tree and shrub populations. Channel gradient accounted for 11 % of the explained variability, while the surface elevation (the ele vation above the stream bed of the geomorphic surface on which the vegetation had established) explained an additional 8%. A Monte Carlo test with 99 permutations was run on each ranked variable. The five previously mentioned hydrogeomorphic variables differed significantly (