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Quantification and Ecological Role of Snag Habitat in the Apalachicola River, Florida

Permanent Link: http://ufdc.ufl.edu/UFE0022366/00001

Material Information

Title: Quantification and Ecological Role of Snag Habitat in the Apalachicola River, Florida
Physical Description: 1 online resource (98 p.)
Language: english
Creator: Burgess, Matthew
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: apalachicola, bay, chattahoochee, discharge, ecology, estuary, fauna, flint, florida, flow, geomorphology, habitat, level, minimum, quantification, regulated, river, snag, stage, wood
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The Apalachicola River has the greatest discharge of any river in the State of Florida, and has one of the largest forested floodplains of any river in the southeastern US. Rapid urbanization of the upper ACF basin, as well as several extensive droughts in the region have resulted in increased demands for water withdrawals and flow regulation for municipal, commercial, and agricultural uses throughout the basin. This has positioned the states of Florida, Georgia, and Alabama, along with several federal agencies, in a surface water allocation and management conflict. Of particular concern are minimum flows and levels required to maintain healthy biotic communities during periods of regional drought, when water demands are at their highest, and the resource is most limited. Very low flows confine the primarily sandy-bottomed Apalachicola River to its main channel, where snags serve as the only stable structural habitat for the riverine fauna. This study aimed to assess the ecological importance, and quantify the amount of snags submerged in the Apalachicola River as a result of variations in flow regime. Additionally, the distributions of snags based on river-bank habitat and geomorphological characteristics were also examined to assess their role in snag habitat availability. Traditional aquatic snag quantification methods were not feasible in the exceedingly turbid, high-order Coastal Plain river; therefore, a novel method using digital imaging analysis techniques was developed for analysis. Area and percentage of available snag habitat submerged were analyzed at 0.5-m elevations above water level for 60 sampling stations along the Apalachicola River at a relatively-low river discharge. Snag area values generated using the novel methods presented in this study were credible for steep sloping bank, gentle sloping bank and dike field habitat types, but were erroneously-elevated for sandbar stations. Snag quantities of non-sandbar stations were found to be greatest within the first 1.0 m of exposed bank for nearly all sites surveyed, while steep sloping banks typically exhibited the most uniform vertical snag distribution. In most cases, geomorphic classifications demonstrated no considerable effect on non-sandbar habitat snag distribution; however, the outer banks of river bends exhibited a more balanced vertical distribution of snags than inner banks of river bends or along the banks of river straightaways. Limitations and proposed modifications to the digital imaging methods are discussed, and recommendations are provided in support of increased water flows for ecological sustainability in the Apalachicola River.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Matthew Burgess.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Wise, William R.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022366:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022366/00001

Material Information

Title: Quantification and Ecological Role of Snag Habitat in the Apalachicola River, Florida
Physical Description: 1 online resource (98 p.)
Language: english
Creator: Burgess, Matthew
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: apalachicola, bay, chattahoochee, discharge, ecology, estuary, fauna, flint, florida, flow, geomorphology, habitat, level, minimum, quantification, regulated, river, snag, stage, wood
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The Apalachicola River has the greatest discharge of any river in the State of Florida, and has one of the largest forested floodplains of any river in the southeastern US. Rapid urbanization of the upper ACF basin, as well as several extensive droughts in the region have resulted in increased demands for water withdrawals and flow regulation for municipal, commercial, and agricultural uses throughout the basin. This has positioned the states of Florida, Georgia, and Alabama, along with several federal agencies, in a surface water allocation and management conflict. Of particular concern are minimum flows and levels required to maintain healthy biotic communities during periods of regional drought, when water demands are at their highest, and the resource is most limited. Very low flows confine the primarily sandy-bottomed Apalachicola River to its main channel, where snags serve as the only stable structural habitat for the riverine fauna. This study aimed to assess the ecological importance, and quantify the amount of snags submerged in the Apalachicola River as a result of variations in flow regime. Additionally, the distributions of snags based on river-bank habitat and geomorphological characteristics were also examined to assess their role in snag habitat availability. Traditional aquatic snag quantification methods were not feasible in the exceedingly turbid, high-order Coastal Plain river; therefore, a novel method using digital imaging analysis techniques was developed for analysis. Area and percentage of available snag habitat submerged were analyzed at 0.5-m elevations above water level for 60 sampling stations along the Apalachicola River at a relatively-low river discharge. Snag area values generated using the novel methods presented in this study were credible for steep sloping bank, gentle sloping bank and dike field habitat types, but were erroneously-elevated for sandbar stations. Snag quantities of non-sandbar stations were found to be greatest within the first 1.0 m of exposed bank for nearly all sites surveyed, while steep sloping banks typically exhibited the most uniform vertical snag distribution. In most cases, geomorphic classifications demonstrated no considerable effect on non-sandbar habitat snag distribution; however, the outer banks of river bends exhibited a more balanced vertical distribution of snags than inner banks of river bends or along the banks of river straightaways. Limitations and proposed modifications to the digital imaging methods are discussed, and recommendations are provided in support of increased water flows for ecological sustainability in the Apalachicola River.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Matthew Burgess.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Wise, William R.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022366:00001


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QUANTIFICATION AND ECOLOGICAL ROLE OF SNAG HABITAT
IN THE APALACHICOLA RIVER, FLORIDA




















By

MATTHEW ALEXANDER BURGESS


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2008

































2008 Matthew Alexander Burgess

































To my parents, George and Linda Burgess









ACKNOWLEDGMENTS

I thank the members of my graduate committee: Dr. William R. Wise, Dr. Stephen J.

Walsh, and Dr. Joann Mossa for their insightful questions and advice, valuable expertise, and

patience throughout my prolonged research and writing process. Each of them was very

accommodating during my efforts towards this degree.

I also extend appreciation to my field crew; boat operator Robert J. Lewis and technician

Denise R. Gregoire, for their willingness to assist with the data collection involved in this study.

This research would not have been possible without their help.

I am indebted to Drs. Colin A. and Lauren J. Chapman, formerly of the University of

Florida, for their mentorship, and providing the opportunity for invaluable laboratory and

international field experience that prepared me for graduate studies.

Funding for this research was supported by a grant from the USGS Eastern Region State

Partnership Program. Additionally, the USGS Center for Aquatic Resource Studies, Gainesville,

Florida, supplied logistical resources as well as supplementary funding to facilitate the

completion of this research.

Finally, I express sincere thanks to my family, especially to my parents George and Linda,

to my brother Nathan, and to Brandy for their encouragement and support during this journey.









TABLE OF CONTENTS



A C K N O W L E D G M E N T S ..............................................................................................................4

L IST O F T A B L E S ......................................................................................................... ........ .. 7

LIST OF FIGURES ......................................................... ...........................8

L IST O F A B B R E V IA TIO N S .............................................. ...............................................9.......

A B S T R A C T .......................................................................................................... ..................... 1 1

CHAPTER

1 IN TR OD U CTION AN D OBJECTIVE S ................................................................................13

2 APALACHICOLA RIVER, ACF BASIN, AND THE TRI-STATE WATER
C O N F L IC T ........................................................................................................... ........ .. 16

A palachicola R iver and A CF B asin........................................ ........................ ................ 16
W ater U se W within the A CF B asin ................. .............................................................. 18
M modifications W within the A CF B asin ....................................... ...................... ................ 19
Tri-State 'W ater W ars' C conflict ..................................................................... ................ 21

3 CHARACTERIZATION, FLUVIAL EFFECTS, AND SIGNIFICANCE OF SNAGS .......28

D efin itio n o f S n ag s ...................... .... .......... .... ...................................... ..................... 2 8
Effects of Snags on Energy Flow and Nutrient Cycling....................................................29
G eom orphic and H ydraulic Effects of Snags .................................................... ................ 31
Snag D ecom position and D eadhead Logging.................................................... ............... 34
Influence of Snags on A quatic Fauna................................................................ ................ 36

4 NOVEL METHOD FOR QUANTIFICATION OF EXPOSED SNAG MATERIAL IN
FLUVIAL SYSTEMS USING DIGITAL IMAGING ANALYSIS .................................40

History of Aquatic Snag Quantification ........................................................ 40
Study D esign and M ethods .................................................. .... ................ 42
D igital Photograph Processing and A nalysis..................................................... ................ 44

5 HYDROLOGIC ANALYSES, RESULTS, AND DISCUSSION ....................................57

Hydrologic Analyses ............................... ............ ............................. 57
R esu lts ........................................................................................................... 58
D iscu ssio n .............................................................................................................. ........ .. 6 0
Recommendations ............. .................... .. ........... .....................................66









APPENDIX

A SAM PLING STATION FIELD DATASHEET ...................... .................... .....................83

B GUIDELINES FOR IMAGE OPTIMIZATION, PROCESSING, AND ANALYSIS OF
D IGITAL PH OTOGRAPH S .................................................. .............. ................ 84

REFERENCE LIST ....................................................... ........................... 86

B IO G R A PH IC A L SK E T C H .............. ...................................................................... 98









LIST OF TABLES


Table page

4-1 Location of field sites on the Apalachicola River......................................... ............... 48

4-2 Geomorphic and bank habitat classifications of sampling stations on the
A p alachicola R iv er.................................................... ................................................ 4 9

5-1 Equivalent stage, discharge, and elevation readings at baseline conditions for the
B lountstow n gage, A palachicola River......................................................... ................ 68

5-2 Bank habitat classification summary for sampling stations on the Apalachicola River....68

5-3 Geomorphic classification summary for sampling stations on the Apalachicola River ....68

5-4 Bank habitat classification effects on mean area and relative percentage of total
sn ag s su b m erg ed ................................................................................................................ 6 9

5-5 Geomorphic classification effects on mean area and relative percentage of total snags
su b m erg ed ........................................................................................................ ........ .. 6 9

5-6 Effects of bank location within a river bend on mean area and relative percentage of
total snags subm erged ................................................. .............................................. 70









LIST OF FIGURES


Figure page

2-1 Map of the ACF drainage basin in Florida, Georgia, and Alabama ................................27

4-1 The four m ajor reaches of the Apalachicola River....................................... ................ 51

4-2 Map of the Apalachicola River basin and surrounding region .....................................52

4-3 Representative photographs of the four bank habitat types encountered during this
stu dy .......................................................................................................... 53

4-4 Map of the 55.3-km intensive study reach of the Apalachicola River...............................54

4-5 Example of a digital image captured using the methods detailed in this study ..............55

4-6 Filtering and processing steps used to prepare photographs for digital image analysis .....56

5-1 Linear mean daily discharge duration curve for the Apalachicola River at the
C hattahoochee gage (1929-2006) ....................................... ....................... ................ 71

5-2 Logarithmic mean daily discharge duration curve for the Apalachicola River at the
C hattahoochee gage (1929-2006) ....................................... ....................... ................ 72

5-3 Chattahoochee gage Blountstown gage equivalency curve.......................................73

5-4 Stage-discharge rating curve for the Apalachicola River at the Blountstown gage
(M arch 2004-M arch 2006).. ....................................................................... ................ 74

5-5 Stage-discharge hydrograph for the Apalachicola River at the Blountstown gage
(M arch 2004-M arch 2006).. ....................................................................... ................ 75

5-6 Bank habitat classification effects on mean area of snags submerged for all sampling
station n s ........................................................................................................... . ....... .. 7 6

5-7 Non-sandbar bank habitat classifciation effects on mean area of snags submerged .........77

5-8 Geomorphic classification effects on mean area of snags submerged ................................78

5-9 Effects of bank location within a river bend on mean area of snags submerged ............79

5-10 Bank habitat classification effects on percentage of total available snags submerged...... 80

5-11 Geomorphic classification effects on percentage of total available snags submerged ......81

5-12 Effects of bank location within a river bend on percentage of total available snags
su b m erg ed ........................................................................................................ ........ .. 82












ACF

ACFRBC

ACT

cfs

cms

DEP

FFWCC

ft

GPS

IFIM

km

LWD

m

MB

MOA

NGVD 29

NOAA

NWFWMD

PHABSIM

PVC

RM

TNC

UNESCO

US


LIST OF ABBREVIATIONS

Apalachicola-Chattahoochee-Flint

Apalachicola-Chattahoochee-Flint River Basin Compact

Alabama-Coosa-Tallapoosa

Cubic feet per second

Cubic meters per second

Department of Environmental Protection

Florida Fish and Wildlife Conservation Commission

Feet

Global positioning system

Instream Flow Incremental Methodology

Kilometer

Large woody debris

Meter

Megabyte

Memorandum of Agreement

National Geodetic Vertical Datum of 1929

National Oceanic and Atmospheric Administration

Northwest Florida Water Management District

Physical Habitat Simulation

Polyvinyl chloride

River mile

The Nature Conservancy

United Nations Educational, Scientific, and Cultural Organization

United States









USACE United States Army Corps of Engineers

USCB United States Census Bureau

USFWS United States Fish and Wildlife Service

USGS United States Geological Survey

WGS 84 World Geodetic System of 1984









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

QUANTIFICATION AND ECOLOGICAL ROLE OF SNAG HABITAT
IN THE APALACHICOLA RIVER, FLORIDA

By

Matthew Alexander Burgess

August 2008

Chair: William R. Wise
Major: Interdisciplinary Ecology

The Apalachicola River has the greatest discharge of any river in the State of Florida, and

has one of the largest forested floodplains of any river in the southeastern US. Rapid

urbanization of the upper ACF basin, as well as several extensive droughts in the region have

resulted in increased demands for water withdrawals and flow regulation for municipal,

commercial, and agricultural uses throughout the basin. This has positioned the states of Florida,

Georgia, and Alabama, along with several federal agencies, in a surface water allocation and

management conflict. Of particular concern are minimum flows and levels required to maintain

healthy biotic communities during periods of regional drought, when water demands are at their

highest, and the resource is most limited.

Very low flows confine the primarily sandy-bottomed Apalachicola River to its main

channel, where snags serve as the only stable structural habitat for the riverine fauna. This study

aimed to assess the ecological importance, and quantify the amount of snags submerged in the

Apalachicola River as a result of variations in flow regime. Additionally, the distributions of

snags based on river-bank habitat and geomorphological characteristics were also examined to

assess their role in snag habitat availability. Traditional aquatic snag quantification methods









were not feasible in the exceedingly turbid, high-order Coastal Plain river; therefore, a novel

method using digital imaging analysis techniques was developed for analysis.

Area and percentage of available snag habitat submerged were analyzed at 0.5-m

elevations above water level for 60 sampling stations along the Apalachicola River at a

relatively-low river discharge. Snag area values generated using the novel methods presented in

this study were credible for steep sloping bank, gentle sloping bank and dike field habitat types,

but were erroneously-elevated for sandbar stations. Snag quantities of non-sandbar stations were

found to be greatest within the first 1.0 m of exposed bank for nearly all sites surveyed, while

steep sloping banks typically exhibited the most uniform vertical snag distribution. In most

cases, geomorphic classifications demonstrated no considerable effect on non-sandbar habitat

snag distribution; however, the outer banks of river bends exhibited a more balanced vertical

distribution of snags than inner banks of river bends or along the banks of river straightaways.

Limitations and proposed modifications to the digital imaging methods are discussed, and

recommendations are provided in support of increased water flows for ecological sustainability

in the Apalachicola River.









CHAPTER 1
INTRODUCTION AND OBJECTIVES

The Apalachicola River is the State of Florida's largest river by discharge, and has one of

the most extensively forested floodplains of any river in the southeastern Coastal Plain. Home to

a diverse fauna, including many threatened and endangered species, the basin is a significant

natural resource worthy of conservation efforts. The Apalachicola River and Bay system is

remarkable in that it has remained relatively intact as urbanization has transformed comparable

riverine systems within North America. Therefore, conservation and rehabilitation efforts that

are enacted in the Apalachicola River are currently proactive, rather than reactive; consequently,

such efforts tend to be less expensive and have an increased likelihood of success over time. In

light of several major droughts, concerns have arisen over declining water availability in the

river, as well as decreasing freshwater inputs into the Apalachicola Bay estuary, due to rapid

population growth and accelerated water consumption throughout the greater ACF basin.

Regulated flows and competing water withdrawals have generated disputes over states' water

rights, as well as management of federal reservoirs within the region. This has positioned the

states of Florida, Georgia, and Alabama in a water allocation conflict, the eventual consequences

of which may jeopardize biological communities that are dependent on the annual flow cycles of

the rivers. Of particular concern are low-flow conditions and habitat availability during critical

phases in the ecology of river-dependent biota.

Numerous local, state, and federal agencies are responsible for management and

optimization of water resources within the 50,764-km2 ACF basin; consequently, water-

allocation disputes within the region have been contentious. As the metropolitan Atlanta area

continues to grow and water demands multiply, Georgia-based interest groups have endeavored

to store as much surface water as possible in upstream Chattahoochee River reservoirs.









Maintaining equity of water use among consumers in the upper reaches of the ACF basin with

the ecological needs and consumptive use requirements of downstream users has been

challenging. Determining the quantities of reasonable and beneficial river water use varies

greatly among stakeholders depending upon their location within the ACF basin. In watersheds

throughout the world, water managers are beginning to implement adaptive management

techniques to resolve conflicts similar to those exhibited in the ACF basin. Successful adaptive

management is achieved by collecting baseline data of critical components, monitoring

deviations over time, and making sensible modifications to management plans as environmental

conditions change (Richter et al. 2003). The monitoring and documentation of rehabilitation

efforts in fluvial systems is critical to the success of adaptive management strategies (Bash and

Ryan 2002).

With habitat loss considered a primary threat to imperiled species, critical habitats within

fluvial ecosystems have been targeted as goals for conservation. In the context of rivers, snags

are defined as any woody structures, regardless of size, located within the banks of a

watercourse. During low water flows, the primarily sandy-bottomed Apalachicola River

becomes almost completely confined to its main channel, and as a result, snags provide the only

stable structural habitat and cover available for its river-based fauna. For years, aquatic

ecologists have recognized the importance of snag habitat in maintaining productive ecosystems.

However, it was not until fairly recently that focused efforts were made to quantify riverine snag

habitat. Due to the dynamic nature of a river system, it is difficult to predict rates of wood input

and depletion as they vary over space and time. Wallace and Benke (1984) stated that the

quantification of riverine wood habitat is essential in assessing past or potential impacts of snag

removal on ecosystem processes. Furthermore, determining the amount of available snag









material and its ecological role is vital in understanding how anthropogenic alterations to fluvial

systems influence ecosystem success and dynamics. In Florida, very little research has been

performed that quantifies the loss of habitat for aquatic fauna when snag material is removed

from the system, or when woody material is exposed during decreasing river discharges. As

minimum flows and levels are discussed within the management of the ACF basin, it is

imperative to know how changes in flow affect snag habitat availability. Scientists in various

disciplines have been requested to collect data and provide input to assist officials in making

informed decisions concerning the regulation and management of water resources within the

ACF basin. This study endeavored to provide insight into the quantity of aquatic snags

submerged in the Apalachicola River at various flow regimes using a novel digital imaging

analysis technique. In addition, the distribution of snags based on river bank habitat and

geomorphological characteristics was also examined to indicate their prospective influence on

snag habitat availability within the Apalachicola River.









CHAPTER 2
APALACHICOLA RIVER, ACF BASIN, AND THE TRI-STATE WATER CONFLICT

Apalachicola River and ACF Basin

Two large rivers in the southeastern US, the Chattahoochee and the Flint, converge to form

Lake Seminole, a shallow 152-km2 man-made reservoir in southeastern Georgia (Figure 2-1).

The Apalachicola River headwaters are created by the tailwater discharge of Lake Seminole at

the Jim Woodruff Lock and Dam; a USACE operated navigation and hydroelectric generation

facility that was completed in 1954. The 805-km long ACF river system drains 50,764 km2 in

the states of Florida, Georgia and Alabama, with approximately 13% of the total ACF basin

contained within the State of Florida (Light et al. 2006).

The Apalachicola River is the largest river in terms of mean annual discharge in Florida,

and has the fourth largest discharge of rivers in the southeastern US (Leitman et al. 1991).

Located in the Florida panhandle, the Apalachicola River basin drains 6,216 km2 of land within

the state, of which about half is drained by the spring-fed Chipola River, its largest tributary

(Leitman et al. 1983). The Apalachicola River is a moderately sinuous, highly turbid, alluvial

bed Coastal Plain river that flows 171 km from the Florida-Georgia state line to Apalachicola

Bay (Light et al. 1998). The river has a relief of 12.5 m from its headwaters at the Jim Woodruff

Lock and Dam to its convergence with the Gulf of Mexico; relatively low for a river of its length

(Meeter et al. 1979). Light et al. (2006) reported that the average Apalachicola River discharge

from 1929-2004 at the USGS gage near Chattahoochee, Florida was 21,900 cfs; however, flows

were greatly influenced by upstream water management practices in the states of Alabama and

Georgia, as well as seasonal variations in precipitation. The lowest daily discharge at the

Apalachicola River, Chattahoochee gage was 3,900 cfs during a severe drought in November

1987; the highest recorded flow was 291,000 cfs, which occurred during a historic flood in









March 1929 (Light et al. 2006). Average annual precipitation in the Apalachicola River basin is

1.42 m, with the driest period typically occurring in the months from September through

November (Leitman et al. 1991).

Unlike most large-river basins of the southeastern US, the floodplain of the Apalachicola

River lacks a major urban center, and is consequently sparsely populated. Land uses along the

river are primarily forestry or conservation lands, which contributes to the scarcity of

development in the region (Leitman et al. 1991). Additional factors contributing to the rural

nature of the Apalachicola River basin include the relatively depressed economic status of the

area, and limited ability for cross-river transportation and exchange of goods, as only four

highway bridges traverse the river along its 171-km length.

The extensive 454-km2 Apalachicola River floodplain is the largest of all rivers in Florida,

and is abundantly forested by many species of cypress, tupelo, and other mixed-bottomland

hardwood tree species, of which most have been logged several times since the year 1870

(Leitman et al. 1983; Elder et al. 1988). The ample forests of the Apalachicola River floodplain

deposit approximately 3.6 x 105 metric tons of organic material onto the floodplain annually

(Elder and Cairns 1982). With one of the highest computed litter fall rates of any temperate

forest, the Apalachicola River ecosystem is reliant on seasonal floods to mobilize, distribute, and

recycle the large quantities of organic material and nutrients that accumulate on its floodplain.

The habitats in and along the Apalachicola River basin contain one of the most species-rich

assemblages of flora and fauna in the southeastern US (Livingston 1984; Leitman et al. 1991;

Mitsch and Gosselink 2000). An estimated 1,500 plant species, 450 vertebrate species, and a

myriad of invertebrate taxa, including the largest number of freshwater mollusk species in the

US, inhabit the Apalachicola River watershed (Heard 1977; Means 1977; Leitman 1984).









Additionally, many endemic and federally listed endangered or threatened species are found in

the basin, making it one of the most significant ecosystems remaining in the US (Myers and

Ewel 1990).

Water Use Within the ACF Basin

Both surface and groundwater resources are used by consumers within the ACF basin.

Surface water is used for domestic and commercial supply, cooling of power plants, hydropower

generation, transportation, irrigation, and recreation. The largest urban center in the basin, the

greater Atlanta metropolitan area, draws nearly all of its water supply from the upper reaches of

the Chattahoochee River at Lake Lanier, with a portion of the water returning to the basin as

treated wastewater. As the city of Atlanta continues to grow, most models indicate that another

source of water will need to be tapped in the near future, or extreme conservation efforts will

need to be enacted in order to maintain the existing growth rate of the urban area. The Georgia

DEP asserts that its projections for future water supply, relying on the Chattahoochee River as a

primary water source, are still sound, while the USACE indicates that the city has already

exploited surface water quantities that equal, or at times have exceeded projections established

for the year 2030 (Seabrook 2002). Discussions of alternative water sources for the Atlanta

metropolitan area have included the proposed construction of several water retention reservoirs

on the upper Flint River, as well as the possibility of interbasin water transfers from the ACT, or

Tennessee River watersheds (Hoehn 2001). These alternatives have failed to materialize due to

intense objections from a variety of political, environmental, and economic interests.

Groundwater resources in the ACF basin are primarily used for self-supply domestic

drinking wells, industrial and commercial applications, and for center-pivot irrigation of

agriculture. Large quantities of land in rural southwest Georgia are cultivated for ornamental,

vegetable, fruit and nut, forage, and row-crop agriculture. These large farms are dependent on









groundwater from the Chattahoochee and Flint river watersheds for irrigation, and ultimately for

economic subsistence. In addition, portions of the extensive Floridan Aquifer are recharged

within the ACF basin, therefore intimately linking surface and groundwater systems (Elder et al.

1988).

Modifications Within the ACF Basin

Over the past 200 years, various navigational enhancements have been made in the ACF

basin to facilitate the movement of commodities on the river. In the 1820's, the first steamboats

began to transport row crops such as corn, cotton, peanuts, and soybeans from cities in Alabama

and Georgia to the seaport of Apalachicola, Florida (Kirkland 2001). Mueller (1990) indicates

that these early steamers would often encounter sections of the rivers where trees and snags

traversed the entire waterway and would have to be displaced to allow boat passage. From 1875

to 1998, selective de-snagging operations in the Apalachicola and lower Chattahoochee rivers

had removed approximately 334,000 woody obstructions including snags, stumps, bushes,

overhanging trees, and drift logs (T. Hoehn, FFWCC, and S. Leitman, NWFWMD, unpublished

data). Ager et al. (1985) indicated that snag removal associated with navigational improvements

has left much of the main channel Apalachicola River with a rather unproductive sandy bottom

devoid of critical habitat. Since 1956, when selective desnagging was most prevalent, the main

channel of the Apalachicola River has actually become shallower and wider, due in part to

removal of riparian snags (H. Light, USGS Tallahassee, personal communication). A total of 16

dams and associated reservoirs (13 on the Chattahoochee River; 3 on the Flint River) have been

constructed and maintained upstream of the Apalachicola River for water storage, recreation,

flood mitigation, navigation, and hydroelectricity generation (Ager et al. 1985). In 1946, as part

of the River and Harbors Act of the previous year, the US Congress authorized the USACE

Mobile District to dredge and de-snag a 2.75-m x 30.5-m navigation channel through a large









portion of the ACF basin to encourage economic development and promote interstate commerce

(Leitman 2005). The constructed navigation channel traversed the entire length of the

Apalachicola River, and extended up to Columbus, Georgia and Phoenix City, Alabama on the

Chattahoochee River, and Bainbridge, Georgia on the Flint River. A plethora of problems

emerged following the completion of the watercourse, but the disposal of large quantities of

dredge spoil at unprotected floodplain easement sites within the banks of the rivers, and the

inability to maintain a mandated 2.75-m depth for barge traffic 95% of the year were critical

shortfalls revealed over time (Leitman et al. 1991). During the years of operation and

maintenance of navigational conditions within the ACF basin, the quantity of barge traffic failed

to meet the utility in which it had been designed and constructed, due primarily to

inconsistencies in channel reliability. Consequently, the majority of freight (sand, gravel,

petroleum, and fertilizer) that was routinely transported by barges in other areas of the US

ultimately was transported by truck or rail within the ACF basin. Leitman et al. (1991) indicated

that in the late 1980's, the unit cost of maintaining the ACF waterway per ton-mile of freight

shipped was the highest of any waterway in the US, and more than 40 times the national average.

In 2003, nine barges used the ACF waterway to transport freight, while it was estimated that

US$6.5 million dollars in tax revenue was spent to maintain the channel (Leitman 2005).

Navigational channel maintenance in the Apalachicola River was carried out by the USACE

until 2005, when the Florida DEP utilized its authority under the Clean Water Act to rescind the

annual river dredging permit.

In addition to the extensive dredging and de-snagging operations implemented to facilitate

river transportation, another modification called 'navigation windows' were used on the

Apalachicola River beginning in the year 1990. During a navigation window, the USACE would









intermittently discharge large quantities of water from upstream reservoirs for a temporary ten-

day, to two-week period to allow scheduled barge traffic movement during low-water conditions

(Leitman et al. 1991). Navigation windows unfortunately altered the natural chemical, physical,

and biological components of the floodplain habitat and its ecology during what were normally

low-flow river conditions. Another issue with navigation windows was the dramatic vertical

drop in river stage over a short period of time, or 'fall rate', which would occur at the end of a

scheduled navigation window. This was particularly evident in April 2000, when a navigation

window decimated fish populations in the Apalachicola River by stranding millions of

reproducing fish and invertebrates in desiccating pools on the floodplain (Hoehn 2001). In

addition, residents with property on upstream reservoirs, especially those on Lake Lanier,

objected to navigation windows that visibly lowered water levels, consequently leaving their

recreational docks high and dry. The practice of navigation windows was effectively

discontinued with the revocation of the Florida DEP dredging permit in 2005, and the cessation

of commercial navigation.

Other Apalachicola River modifications implemented for enhanced water conveyance and

improved river transportation included: 1) the creation of several bend easings and meander

cutoffs to straighten navigationally difficult natural bends in the river; 2) the relocation and

removal of rocky shoals in portions of the upper river; 3) the periodic release of water stores for

flood control and reservoir management; and 4) the installation of river-training dikes to

augment channel bed scour and increase downstream sediment transport (Leitman et al. 1991;

Light et al. 1998).

Tri-State 'Water Wars' Conflict

As the human population continues to grow, there are increased demands for natural

resources with limited availability. One of the greatest public concerns is the accessibility to









freshwater resources, particularly in areas that have already exceeded their capacity to support

growth. Officials at multiple levels of government have been assigned the task of maintaining

adequate water stores for natural and consumptive uses, as well as planning for future water

demands. Due to precipitation generated by the warm moist air from the Gulf of Mexico and

Atlantic Ocean, southeastern US states have historically had sufficient water resources to meet

the requirements of their growing populations (Leitman et al. 1991). However, concerns have

arisen recently in regards to adequate freshwater availability during seasonal droughts, and as

rates of urbanization continue to increase throughout the region. Two substantial droughts

occurred in the southeastern US during the 1980's that generated significant consideration to the

limits of water availability in the ACF basin, and triggered the states to become increasingly

acrimonious in regards to their water resources. This has placed the states of Alabama, Georgia,

and Florida in a surface water allocation conflict, the eventual consequences of which may

jeopardize the ecology of the biota in the ACF basin, as well as in the extensive Apalachicola

Bay estuary.

In the US, the states have the authority to regulate the use of freshwater within their

borders, with the exception of waterways used for navigation, and federally constructed

reservoirs. Each state has established its own water laws and mechanisms for modification of

water regulations; however, congressional approval is required for any change in interstate water

resource allocation. When the US Congress authorized the development of the ACF waterway

for navigation, hydropower, and flood control in 1946, they fundamentally removed state control

of surface water in the basin in favor of federal management. As with any water allocation and

management decision in the US, an array of federal laws and regulations must be adhered to by

the states. While not entirely comprehensive, some of the principal legislative acts pertinent to









water management in the ACF basin include: the Rivers and Harbors Acts of 1945 and 1946, the

Rivers and Harbors Flood Control Act of 1944, 1958, and 1962, the Water Resources Act, the

Federal Power Act, the Clean Water Act, the Water Quality Control Act, the National

Environmental Policy Act, the Endangered Species Act, the Migratory Bird Treaty Act, the

Marine Mammal Protection Act, the Fish and Wildlife Coordination Act, and the Coastal Zone

Management Act (Sherk 2005).

The ACF basin is one of the largest freshwater contributors into the Gulf of Mexico

(Livingston 1984). The inputs from the Apalachicola River into Apalachicola Bay deliver

significant quantities of valuable detritus and nutrients, as well as beneficially reduce the salinity

of the estuary, therefore furnishing an ideal environment for shellfish, shrimp, and crabs. Inputs

from the river also control the distribution of essential estuarine habitats including seagrass beds,

mangrove stands, tidal marshes, and mud flats necessary for productive estuaries (Myers and

Ewel 1990). Coastal cities in Franklin and Gulf counties near the mouth of the Apalachicola

River rely heavily on the commercial fisheries of Apalachicola Bay for their existence and

livelihood. Apalachicola Bay, a 549-km2 lagoon-and-barrier island complex, is regarded as one

of the most productive and least polluted estuaries in the US, and generates approximately 90%

of Florida's oysters, making up about 10% of the United States' annual harvest (Livingston

1984; Ruhl 2005; Wang et al. 2008). The salinity pulse generated by the seasonal variation in

river flows is critical to the health of oyster populations in the bay (Livingston et al. 2000). In

addition, Apalachicola Bay serves as an important nursery area for many marine species, and

produces Florida's third largest shrimp fishery, as well as a robust blue crab fishery (Oesterling

and Evink 1977). The Apalachicola Bay estuary has been recognized as a water body worthy of

special protection, and is therefore designated as a UNESCO 'International Biosphere Reserve',









a NOAA 'National Estuarine Research Reserve', a Florida DEP 'Aquatic Preserve' and

'Outstanding Florida Water'.

Analysis of time spent participating in outdoor activities within the US revealed that

Florida trailed only Texas in time devoted to wildlife-related recreation (Struhs and Mainella,

2000). A report by Southwick and Allen (2003) indicated that in 2001, over 40% of Floridians

participated in wildlife-related activities, and in addition, over 800,000 visitors came to the state

specifically to partake in wildlife related recreation. The Apalachicola River basin is of

tremendous economic importance to Florida, and its floodplain and environs provide abundant

opportunity for outdoor recreational activities such as fishing, hunting, camping, and hiking.

The FFWCC (2008) boasts the state as being the 'Fishing Capital of the World', emphasizing the

values of both recreational and commercial fishing to the state economy. A combined report by

the USFWS and USCB (2002) estimated that in 2001, freshwater fishing in Florida generated

US$1.057 billion in retail sales alone. Decreased water flow in the Apalachicola River severely

affects fisheries in the river, as well as in Apalachicola Bay, two highly significant economic

contributions to the State of Florida.

With multiple authorities having control of water resources in the ACF basin, the states of

Alabama and Florida along with the USACE quarreled with the State of Georgia in the 1960's

and 1970's regarding the opinion that water consumption for urban and agriculture uses within

Georgia had superseded the needs of other water-users and ecosystems to the south and the west.

In January 1982, in lieu of imminent litigation, a 'Memorandum of Agreement' (MOA) was

signed by the governors of the three states, and the USACE, in which all four parties agreed to

develop a comprehensive basin-wide water assessment, a navigation maintenance plan, a drought

management plan, and a water management strategy for the ACF watershed (Leitman et al.









1991). The ACF basin MOA attempted to develop a rational and scientific water management

policy based on a 'live and let-live' principle. However, after several extensions, the MOA had

failed to result in a compromise due to insufficient funding, incomplete habitat assessments,

withholding of information, threats of new litigation, changes in elected officials, and overall

differences in opinion regarding definitions of reasonable water use (Dellapenna 2004). In early

1996, the states of Florida, Georgia, and Alabama revisited the water allocation problems, and

began drafting an outline to develop an interstate water compact (Carriker 2000). During their

1997 legislative sessions, the three states passed the framework program, the governors signed

the measure, and sent the proposal to Washington D.C. for congressional approval. The US

Congress ratified the Apalachicola-Chattahoochee-Flint River Basin Compact (ACFRBC) on

November 20, 1997, that established an agenda, timeline, and an interstate basin commission, for

developing an agreement to allocate water from the shared river system (Carriker 2000; Sherk

2005). There were many points of contention during the years of negotiations under the

ACFRBC, but the fundamental disagreement among the parties concerned whether the State of

Georgia would be responsible for delivering only the minimum flow of water, regardless of

hydrologic conditions, to the Florida border (Snowden 2005). It seemed as if a stalemate was

inevitable; however, on July 22, 2003, after numerous deadline extensions, the states of Florida,

Georgia, and Alabama signed a 'Memorandum of Understanding' that indicated that they had

reached an 'agreement in principle' regarding various terms of a water allocation formula, and

committed the states to additional negotiations (Sherk 2005). Unfortunately, little progress was

made during talks in the months that followed as the states became increasingly unwilling to

make concessions; therefore, on August 31, 2003, without another extension, the ACFRBC

terminated (Dellapenna 2004). The expiration of the ACFRBC officially ended objective









dialogue between the states of Florida, Georgia, and Alabama regarding water allocation in the

ACF basin, and has forced all subsequent decisions to be made within the federal court system.












N
t
0 20 10 60 80
0 20 10 60 80
miles


GEORGIA


Cha ttrahoochee


A LABA N


Flint River


FLORIDA


Figure 2-1. Map of the ACF drainage basin in Florida, Georgia, and Alabama.









CHAPTER 3
CHARACTERIZATION, FLUVIAL EFFECTS, AND SIGNIFICANCE OF SNAGS

Definition of Snags

The term 'snag' is used in lotic systems to refer to any woody structure, regardless of size,

that lies within the banks of a watercourse. Snags are ubiquitous and integral components of

rivers and streams flowing through forested floodplains. The importance of snags as a habitat

component in the ecology of aquatic systems has become increasingly recognized during the last

30 years (e.g., Bilby and Likens 1980; Wallace and Benke 1984; Bilby and Ward 1991; Beechie

and Sibley 1997). Tree trunks, limbs, branches, leaves, seeds, bark, and root wads make up the

majority of allochthonous input deposited in and along rivers and streams (Hynes 1975; Dolloff

and Webster 2000). However, during high water inundation, roots, trunks, and low-hanging

limbs of living trees can also serve as snag habitat for aquatic dwellers. In the southeastern US,

downed woody material can be a result of bank undercutting and erosion, natural tree fall,

forestry operations, fire, flood, lightning, windthrow, disease, insect infestation, or episodic

weather events such as tornadoes and hurricanes.

The majority of existing research concerning the ecology and fluvial effects of aquatic

woody material has been carried out in the high-gradient rivers and streams flowing through

timber forests of Australia, as well as those in the US Pacific Northwest (e.g., Anderson and

Sedell 1979; Naiman and Sedell 1979; Triska and Cromack 1980; Webb and Erskine 2003;

Woldendorp et al. 2004). Some of the earliest studies of the subject compared natural

abundances of wood in undisturbed watersheds with those where wood was deposited as a result

of timber harvesting (Warren and Olsen 1964; Bilby 1981). Other studies focused primarily on

woody material of at least 0.1-m in diameter, known as 'large woody debris' (e.g., Keller and

Swanson 1979; Bisson et al. 1987; Lienkaemper and Swanson 1987; MacDonald and Keller









1987). The term 'large woody debris' (LWD) originated in the logging industry, and referred to

waste products, specifically the larger branches, limbs, and unusable trash logs left at a logging

site after the profitable stems were removed (Murphy and Koski 1989). With increased

recognition of the significance of woody material in fluvial systems, aquatic ecologists have

recently suggested that the term LWD be abandoned in favor of the term 'large wood,' thereby

eliminating any possible negative connotation associated with the word 'debris' (Gregory et al.

2003).

Effects of Snags on Energy Flow and Nutrient Cycling

Ecotones are defined as regions of transition associated with sharp gradients in

environmental factors or in community composition (Stiling 1999). Riparian zones such as

floodplain forests are vital ecotones characterized by high species diversity, and high

productivity, between terrestrial upland and lowland aquatic ecosystems. Often depicted in two

dimensions, it is imperative to consider that riparian zones are three-dimensional,

biogeochemically open systems in nature; they are laterally connected to upslope terrestrial

localities, as well as functionally connected longitudinally to upstream aquatic locations (Mitsch

and Gosselink 2000). By serving as superior filters, floodplains are functional and valuable

ecotones within fluvial systems.

Aquatic snags have a prominent influence on numerous ecosystem processes, including

energy budgeting, primary and secondary production, as well as nutrient resource cycling and

exchange. The pattern of nutrient loading, transport, utilization, and storage on the floodplain is

critical to the survival of healthy riparian communities (Vannote et al. 1980; Baldwin and

Mitchell 2000). This pattern is regulated by the 'flood pulse' concept; a periodic flooding of

fluvial systems that provides a vital ecological interaction between the river channel and its

floodplain (Junk et al. 1989; Benke 2001). Organic input is an essential component of the energy









budget of aquatic habitats (Benke and Wallace 1990). The bulk of riverine animal biomass is

derived from production of organic matter that occurs on the floodplain (Junk et al. 1989).

During floods, a substantial flux of organic matter and nutrients are flushed off the floodplain

where they either accumulate behind snags, or are deposited into the main river channel (Elder et

al. 1988; Benke and Wallace 1990). Snags further influence the routing of sediments, particulate

organic matter, and nutrients by creating areas of low shear stress and low water velocity,

facilitating deposition of suspended materials from the water (Wallerstein 2003). Seasonal

flooding also influences soil oxygen levels on the floodplain, whereby transitions from aerobic to

anaerobic conditions affect rates of organic matter decomposition and nutrient mineralization.

Floodplains act as nutrient sinks for lateral runoff from uplands, but also serve as nutrient

transformers for downstream water flows (Mitsch and Gosselink 2000). By trapping particulate

organic matter, snags help to retain potential nutrient and energy resources from washing rapidly

downriver, as well as serve as a long-term source of nutrient loading for the floodplain (Wallace

and Benke 1984).

Critical linkages exist between natural flow variations and ecological fitness of fluvial

systems. Alterations of the timing, magnitude, and duration of extreme flows in rivers are

significant, particularly in anthropogenically controlled watersheds (Gibson et al. 2005).

Artificial adjustments of flow regime have cascading effects on the chemical, physical, and

biological components of a river. Lower than normal riverine flows: 1) reduce the wetted

perimeter of a waterway that decreases riparian habitat availability; 2) alter water-quality

parameters by reducing dilution effects; and 3) limit connectivity between the river and its

floodplain (Light et al. 1998). Increasing flows and rising water levels can be critical biological

cues for riverine organisms to migrate up- or downstream, or for others to move from habitats in









the main river channel to those on the floodplain where food resources and structure are readily

abundant for reproduction (Ross and Baker 1983; Light et al. 1998; Postel and Richter 2003).

Variations in peak flow timing and magnitude can disrupt the mobilization of organic matter and

nutrients from the floodplain, alter the rates of sediment erosion and deposition, and significantly

influence the migratory and recruitment success of aquatic species (Knighton 1998).

Geomorphic and Hydraulic Effects of Snags

Two major factors that govern channel morphology are sediment supply and temporal flow

variability, both of which can be influenced by the presence or absence of snags. Due to their

irregular shapes and sizes, snags can accumulate upon each other and develop into hazards for

river transportation, as well as accumulate floating litter. Therefore, snags have been removed

from rivers for many years in an attempt to create waterways suitable for navigation, as well as

for aesthetic purposes. Other justifications employed for the removal of snags from rivers

include: 1) to eliminate barriers to fish migration; 2) to reduce the risk of downstream bridge

piling and navigational marker damage; 3) to reduce rates of river bank erosion; and 4) to

improve flood mitigation efforts (Harmon et al. 1986; Bisson et al. 1987; Gippel et al. 1992,

Diehl and Bryan 1993). It was often believed that removal of snags from rivers was a good

course of action in flood prevention; however, snag removal tends to increases stream velocity,

decreases riparian vegetation quantity, and increases channel bed scouring and incision that

promotes bank failure as sediment is carried downstream (Zimmerman et al. 1967; Wilson 1973;

MacDonald and Keller 1987; Erskine 1994). Increased bank stability generated by snag material

is especially important along the outside bank of meander bends where the channel tends to

migrate laterally (Bisson et al. 1987; Diehl and Bryan 1993). Conserving the snag material that

naturally accumulates in the riparian areas of fluvial systems helps to fortify the channel banks,

trap sediment in natural levees, increase structural complexity and habitat, as well as reduce the









mean velocity of water in the channel and on the floodplain during high-water events (Diez et al.

2001).

The most conspicuous effects of snags in rivers and streams are physical: wood can

influence channel shape, sediment storage and erosion rates, and the path of water flow.

Downed wood on the floodplain that is large enough to be immobile during floods can have a

significant influence on morphology, geometry, and profile of the floodplain (Braudrick et al.

1997). When a log lies parallel to the flow of a floodplain slough, the streambed may be eroded

in front of the log forming a lateral scour pool. Snags can divert the mainstream flow of a slough

from one side of the channel to the other, forming a backwater pool. Beechie and Sibley (1997)

found that pool area and pool spacing varied greatly with channel width and slope in streams

containing snags. Pools formed by wood on the floodplain provide essential habitat and

complexity to the entire bionetwork (Bilby 1981; Dolloff 1994; Baillie and Davies 2002). Pool

formation is just one of the physical effects that snags can have on fluvial systems.

Another physical effect of snags in fluvial systems is bank armoring, or flow divergence.

Snag material can divert stream flow away from a bank, therefore limiting downstream shoreline

erosion (Gippel 1995; Berg et al. 1998). Snags can also divert water into a bank, causing bank

undercutting and stream widening. Conversely, wood lying alongside and parallel to the bank

can prevent bank erosion (Cherry and Beschta 1989). Snags can also shift water flow from one

side of a channel to the other, divert flow from the main channel to a side channel, or even force

the creation of alternate channels. Channel migration can also create point bars of alluvial

sediments, oxbow lakes, and backwater swamps. The influence of snags on formation of these

local hydrologic features is extensive; however, the impact of humans on fluvial systems tends to









constrain channel processes and linearizes corridors, while natural hydrology and

geomorphology tends to create heterogeneity of these habitats.

Zones of erosion, storage and transport, and deposition are defined along the course of a

river system based on its geomorphology, hydrology, and physical processes. Snags can

influence the deposition patterns of sediments in rivers and on their floodplains. Water may be

forced to go around, over, under, or along a snag, resulting in a range of water velocities. Fine

sediments such as silts and clays will accumulate where the water velocity is lowest, such as in

backwater pools, whereas only coarse sediments remain stationary in faster flows. The presence

of snags in rivers can reduce the scouring effect of high water flow, and aid in sediment

deposition (Baillie and Davies 2002). Rootwads may act as streambank anchors against high

flows during floods, reducing soil loss to erosion and downstream sedimentation. In relatively

low-gradient floodplains, snags can form logjams which can increase the immediate water level

and inundate large areas that do not normally experience regular flooding. Often these

temporary floods deposit considerable amounts of suspended materials (Ward and Aumen 1986).

Snags are therefore considered an important factor in fluvial sediment deposition.

Ironically, in many locations around the world substantial amounts of time and money are

invested in redepositing snags into rivers and streams that were previously cleared (Gore 1985;

Andrus et al. 1988; Osborne and Koviac 1993). Determining where snags should be

reintroduced, how they should be oriented, and the quantities of woody material that should be

returned vary by watershed (Hrodey and Sutton 2008). Piegay (2003), Swanson (2003), and

Reich et al. (2003) propose various frameworks for wood input and redistribution based on

specific parameters of individual fluvial systems. The challenge for river managers is to find and









establish a reasonable balance between the effects of bank erosion and navigational concerns

with the ecological benefits of leaving snags in rivers (Hilderbrand et al. 1998).

Snag Decomposition and Deadhead Logging

Most stream inhabiting organisms do not feed directly on snags, but the presence or

absence of these resources can have a significant influence on food availability and the diversity

of fauna in the ecosystem. Helfman (2007) indicated that in low-gradient coastal rivers, snags

are the most biologically rich habitat available, and can produce four times as much prey than

mud or sand habitats alone. The ecological link between energy availability and production of

higher trophic levels has been well documented (e.g., Myers 1977; Benke et al. 1984; Mattraw

and Elder 1984; Kemp and Boynton 2004; Kiffney and Roni 2007). Leaves and small twigs that

fall into the stream are an important food source for microbes, bacteria, and many species of

aquatic invertebrates (Bilby and Likens 1980). Large, stable snags trap smaller pieces of wood,

that in turn, capture leaves and other organic detritus creating nutrient reservoirs on which

organisms feed (Bilby 1981). A 1984 study by Wallace and Benke determined that 75% of the

organic matter stored in a South Carolina stream and floodplain system was directly associated

with snag material. Wood on the floodplain located above existing water levels contributes to

available refugia at higher water levels (Benke et al. 1985). Logs suspended above the channel

can be colonized by a variety of plants and animals, creating a lush microcosm above the water

(Brown 2002). Eventually, the suspended log will enter the waterway and add to its wood

supply.

The methods and rates of dead wood decomposition in terrestrial and aquatic habitats are

remarkably different. Decay of dead woody material in terrestrial systems is primarily driven by

fungi, and rate of decomposition is rapid due to an abundance of available atmospheric oxygen

(Rayner and Todd 1979; Elder and Cairns 1982; Baker et al. 1983). In aquatic systems however,









decomposition of snags is achieved primarily by single-celled bacteria, namely actinomycetes

(Aumen et al. 1983), and rate of decomposition is determined by microbial quantity and

detritivore palatability (Boling et al. 1975; Bilby 2003). Bacteria and algae living on the surfaces

of submerged snags form a slimy coating called biofilm, which becomes food for other

microscopic biota (Robertson et al. 2001). Biofilms on snags can also beneficially withdraw

nutrients from water flowing by, helping to regulate potentially harmful algal blooms and

downstream macrophyte growth, as well as conserve potential energy resources (Tank and

Webster 1998). With the exception of the outermost layers of submerged dead wood, the

dissolved oxygen concentrations throughout the core of a snag are very low; therefore,

breakdown of its structural components is much slower than in a terrestrial system (e.g.,

Anderson et al. 1978; Whiles and Wallace 1997; Bilby et al. 1999; Spanhoff and Meyer 2004).

Old-growth longleaf pine and cypress forests were extensively logged throughout the

southeastern US in the 19th and early 20th centuries to support worldwide demands for lumber.

Typically, felled timbers would be floated down rivers to coastal sawmills for conversion into

useable boards. It is estimated that five to ten percent of the dense heartwood timbers became

waterlogged and sank on their attempted journey to the mill sites (Dye and Frydenborg 1999). In

coastal rivers and streams of the southeastern US where clays, mud, and sand constitute the

primary bottom sediments, large wood can become partially or entirely buried in anoxic

conditions, and is therefore increasingly resistant to decay (Mitsch and Gosselink 2000). These

submerged 'deadhead logs' can remain on the river bottom for hundreds of years, and are

extremely valuable in the commercial wood-products industry due to their tight grain pattern and

unique wood colors. Individual high-grade deadhead logs can fetch three to five thousand US

dollars apiece, and generate lumber that is upwards of ten times more valuable than conventional









wood (Dye and Frydenborg 1999). The high-end wood produced from old-growth deadhead

logs are utilized primarily in the furniture, paneling, and flooring industries.

Removing deadhead logs from rivers has created legal disputes between log salvaging

operations and environmental groups. Log salvaging representatives argue that the logged-

timbers were not present in rivers in the first place, and should therefore be removed.

Environmental and cultural interests assert that deadhead logs have become integral parts of

rivers over time, and should consequently remain undisturbed. Management of these non-

renewable submerged resources became increasingly necessary, so several US states prohibited

underwater deadhead logging operations while environmental studies were conducted to evaluate

potential physical, chemical, and biological impacts of deadhead log removal. These studies

generated contradicting results, and consequently many states have developed an annual fee-

based permitting process to manage log removal quantities, and to monitor impacts of deadhead

removal while additional research is conducted.

Influence of Snags on Aquatic Fauna

The presence of snags increases the quantity and diversity of available habitats for aquatic-

dwelling organisms. Snags generate effective habitat heterogeneity due to their complex

structure that in turn provides a variety of nooks and crannies suitable for refuge. Snags are

especially important in altered or degraded rivers, as well as in rivers where other more stable

bottom substrates, such as rock or gravel, are absent.

Macroinvertebrates such as insects, mollusks, crustaceans, and worms are highly sensitive

to changes in their environs; therefore, their population levels are often investigated and

monitored to assess the overall health and biodiversity of aquatic ecosystems. Due to this, many

scientific studies have been conducted through the years to examine invertebrate use of snag

habitat (e.g., Nilsen and Larimore 1973; Anderson et al. 1978; Molles 1982; Benke et al. 1984;









Smock et al. 1985; Benke et al. 1985; Thorp et al. 1985; Lemly and Hilderbrand 2000; Braccia

and Batzer 2001). Most of these studies have shown that a greater number of individuals and a

greater diversity of invertebrate species are found in fluvial reaches containing snags in

comparison to similar reaches without snags. Aquatic insects utilize snag habitats for feeding

(whether scraping, grazing, or filtering), resting, predator avoidance, egg deposition, and for

pupation and emergence (Anderson et al. 1978, Benke et al. 1984; Drury and Kelso 2000). In a

lower Coastal Plain river in the southeastern US, Benke et al. (1984) found that the diversity of

invertebrate taxa on snags was much greater than that of sand or mud; however, snag habitat

made up only 6% of the available substrate. Ager et al. (1985) determined that in a southeastern

US fluvial system, snag habitat had the highest density of macroinvertebrates when compared to

all other potentially available benthic substrates. In large sandy bottom rivers, like those found

in the Coastal Plain of the southeastern US, snags are extremely vital as they provided the only

stable periphyton habitat for many invertebrates.

The unionid mussel fauna of the southeastern US was at one time the most species-rich in

the world, and the ACF basin is considered to be the center of unionid mussel speciation (Brim

Box and Williams 2000). However, modem ACF mussel assemblages have experienced an

abrupt decline, perhaps by as much as 50%, as a result of habitat degradation, pollution,

impoundment, and introduction of exotic species (Williams et al. 1993; Golladay et al. 2004).

Chastain et al. (2006) indicated that the Flint River had 76% of its historical mussel species

remaining, while Brim Box and Williams (2000) reported that only remnant and isolated unionid

populations remain in the Chattahoochee River. Of the remaining ACF mussel assemblages,

64% of the species are categorized as either endangered, threatened, or of special concern (Brim

Box and Williams 2000). Unionid reproduction is unique in that it is reliant on specific fish









species to serve as hosts for their specialized larvae; successful mussel reproduction is therefore

dependent on the spawning and rearing success of these critical fish species. Freshwater mussels

are an important component of Coastal Plain fluvial ecosystems as they filter nutrients from the

water and accumulate potentially harmful chemicals and metals into their bodies and shells (Hart

and Fuller 1974). Decreased water flows in the ACF basin leaves unionid mussel populations

vulnerable to extirpation which could ultimately have impacts on water-quality within the

watershed.

An increasing number of studies have been published recently regarding snags as essential

fish habitat. Analogous to the structural cover provided by coral reefs in marine ecosystems,

snags serve as a feeding, spawning, and nursery site for fish in fluvial systems. Submerged

snags are especially significant in shifting sandy-bottomed lotic systems, where they provide

niche variation, velocity refuge, and often the only available stable substrate and cover (Wallace

and Benke 1984; Braccia and Batzer 2001). Benke et al. (1984) found that several species of

game fish foraged exclusively on invertebrates associated with snag material, and Benke et al.

(1985) reported that major warm-water fishes in a southeastern US Coastal Plain stream obtained

at least 60% of their prey biomass entirely from snag habitat. Anglers have historically been the

greatest advocates for snags in fluvial systems, as they have long recognized that snags serve as

effective fish aggregation structures (Lobb and Orth 1991). Ager et al. (1985) indicated that

river habitat containing snags was found to have twice as many game fish species as similar

habitats without snags. Alteration of snag abundance can also influence the distribution of apex

predators and prey. Studies by Angermeier and Karr (1984) and Peterson and Bayley (1993)

determined that the removal of snags from streams altered the predator-prey balance by

effectively reducing the number of apex predators, and increasing the number of smaller fish









species. In high gradient streams, fish often congregate in dammed plunge pools created by

snags and large wood as an escape from high water velocities, and as refuge from predators

(Angermier and Karr 1984). Reduction in riverine snag quantity and distribution can severely

limit the quantity of food resources and protective cover available to fish, two essential

components of healthy fish populations.

Invertebrates and fish are not the only fauna that use snags as habitat in fluvial systems.

Snags emerging from a river provide a preferred site for resting, foraging, and roosting for many

aquatic turtle, snake, and bird species. Snags on the floodplain can be valuable habitat for

herpetofauna such as salamanders, skinks, lizards, frogs and toads, as well as for mammalian

predators such as rat, raccoon, opossum, and armadillo that often forage at floodplain snags sites

(Means 1977). Next to humans, the most influential contributor to snag habitat abundance is the

beaver, whose impoundments and lodges constructed from wood obtained on floodplains can

significantly alter stream hydrology, and introduce large quantities of snag material into fluvial

systems (McTaggart and Nelson 2003; Pollock et al. 2003).









CHAPTER 4
NOVEL METHOD FOR QUANTIFICATION OF EXPOSED SNAG MATERIAL IN
FLUVIAL SYSTEMS USING DIGITAL IMAGING ANALYSIS

History of Aquatic Snag Quantification

To assess the potential importance of snags as habitat for aquatic fauna, it is necessary to

quantify the woody material in lotic systems. Historically, estimates of snag abundance and

density in freshwater aquatic systems were generated as a byproduct of other biological or

hydrologic investigations, and it was not until the late-1970's that studies began to focus

specifically on the quantification of aquatic wood (Gippel et al. 1996). Using methods originated

in the forestry industry for calculation of residual logging waste, ecologists looked to enhance

existing techniques for the quantification of aquatic wood (e.g. Anderson et al. 1978; Triska and

Cromack 1980; Wallace and Benke 1984; Benke and Wallace 1990). The line intersect

technique developed by Warren and Olsen (1964) and further modified by Van Wagner (1968),

Bailey (1970), and de Vries (1974) was a practical method used to estimate the quantity of wood

lying on or near the ground by simply obtaining the diameters of all woody stems that crossed a

hypothetical sample line. Applied to fluvial systems, the line-intersect technique was reasonably

effective for rapid assessment of large diameter wood exposed along the banks, or submerged in

clear water, low-order reaches. In turbid, tannic, or high-order fluvial systems, however, the

line-intersect technique was not a feasible option for quantification of submerged wood. In

addition, the method was found to be significantly inaccurate at estimating quantities of small

diameter woody material, and did not reveal much information about the distribution of wood

along the sample transect (Gippel et al. 1996).

Due to the dynamic nature of fluvial systems, it is difficult to predict rates of wood

recruitment and depletion over space and time. In addition to natural variations in river stage

and downstream snag transport, anthropogenic influences such as forestry operations, and









deadhead logging perturb total wood volumes in fluvial systems. Due to the limitations of the

line-intersect method for wood quantification in turbid or lengthy river reaches, alternative

methods such as low-level aerial surveys and side-scanning sonar have been used (Hamilton and

Bergersen 1984). Unfortunately, these techniques have substantial drawbacks as well. Aerial

surveys of river banks: 1) are generally expensive; 2) tend to be obscured by overhanging

vegetation; and 3) do not provide an accurate vertical scale for the distribution of snags above the

waterline (Fitzgerald et al. 2006). Side-scanning multi-beam sonar can be used to profile

submerged snags even in turbid water. However, the technique: 1) is exclusively limited to the

mapping of underwater material; 2) tends to perform better in deeper water with a uniform

bottom profile; and 3) is susceptible to failure when the boat-towed sonar transducer becomes

ensnared in the woody material that it is mapping (Flug et al. 1998).

In situations where stream flow was a limiting factor in the availability of aquatic habitat

resources, an incremental methodology called IFIM, and a model dubbed PHABSIM were

developed in the 1970's by a collaboration of federal and state agencies to predict changes in

physical microhabitat associated with modifications in hydraulic flow regime (Bovee 1982,

1986). One of the most commonly utilized outputs from the IFIM and the PHABSIM model is

an 'index of weighted usable area' that aids water managers in negotiating low-flow targets and

assessments of critical habitat availability (Milhaus et al. 1989). The IFIM and the PHABSIM

model are challenging to use because they entail multiple pathways and many steps that are

based on user-level understanding of the problem at hand, and they require integrating existing

long-term streamflow datasets of flow regimes, surface elevations, and water velocities, which

are not always available (Milhaus et al. 1984). In addition, the IFIM and the PHABSIM model

are limiting because: 1) their final outputs vary due to disparities in user-defined indices of









channel characteristics; 2) the methodology and model have several significant assumptions that

are difficult to overcome; and 3) the methodology and model do not account for critical water-

quality or energy-input components desired in the interest of aquatic ecology (Milhaus 1999).

Very little research, especially in Florida, has been done to quantify the loss of habitat for

aquatic fauna when snag material is exposed above water level during low-water conditions.

Several studies by Ray (1999a-d) discussed the ecological and morphological significance of old

growth deadhead logs as habitat for macroinvertebrates in several Florida panhandle rivers and

streams, while a report by Estevez and Sprinkel (2000) examined the distribution and abundance

of wood in the Santa Fe and lower Suwannee Rivers based on water level fluctuations. Wood

quantification techniques used in these surveys were not feasible options for the conditions

present in the Apalachicola River. Therefore it became apparent that another method of snag

habitat quantification would need to be developed, perhaps using digital image analysis.

Digital image analysis is a computer-based technique used to generate numerical data by

examining detailed properties of an image. Many scientific disciplines have turned to digital

image analysis due to its widespread applicability, ease of use, and low cost. By utilizing a

variety of methods and procedures, computers are able to accurately, dependably, and repeatedly

identify and measure properties of an image that the human eye is unable to quantify. Historical

limitations of using digital image analysis were primarily rooted in low image resolutions and

slow computer processors; however, these restrictions have been surpassed by increasingly

affordable advances in technology. In many scientific fields, digital image analysis has

developed into an ideal method for rapid and inexpensive data analysis.

Study Design and Methods

Ager et al. (1987) defined six bank habitat types for the Apalachicola River based on

steepness of the riverbank, substrate type, and presence of submerged aquatic vegetation. Steep









sloping banks (bank angle greater than or equal to 450 from horizontal), gentle sloping banks

(bank angle less than 450 from horizontal), and sandbar habitats comprised 92.6% of the

Apalachicola River banks (41.7%, 27.0%, and 23.9% respectively), while the remaining 7.4% of

bank habitats were classified as dike fields (2.3%), rock (2.1%), and submerged aquatic

vegetation (3.0%) (Ager et al. 1987). Rock habitats were found exclusively in the uppermost

portion of the Apalachicola River, while submerged aquatic vegetation was found exclusively in

the tidal reaches of the river.

Four major reaches in the Apalachicola River were defined by Leitman (1984) based on

differences in their geomorphic and physiographic characteristics: A) upper reach, B) middle

reach, C) non-tidal lower reach, and D) tidal lower reach (Figure 4-1). For this study, an

intensive study reach of 55.3 km was selected within the middle and non-tidal lower reach

portions of the Apalachicola River; from just downstream of Estiffanulga Landing (RM 62.4) to

just upstream of the confluence of the Apalachicola River with the Chipola River (RM 28.1)

(Figure 4-2). This particular study reach was chosen based on its incorporation of four (steep

banks, gentle banks, sandbars, and dike fields) of the six bank habitat types delineated by Ager et

al. (1987) (Figure 4-3). Within the study reach, 30 sites were designated equidistantly from each

other (z2.0 km by river) using USGS 7.5-minute topographic quadrangle maps (Figure 4-4).

Specific details regarding the location of the individual study sites are found in Table 4-1. At

each of the 30 sites, both the left- and right-descending banks were evaluated for a total of 60

sampling stations. Geomorphic and bank habitat classifications of the sampling stations are

summarized in Table 4-2.

In the field, a Garmin GPS III PlusTM (ver. 2.06) navigation unit was used to position the

survey crew at each of the 30 pre-selected river study sites. Each sampling station consisted of









four semi-contiguous 10-m long segments of riverbank. Every effort was made to have

concurrent 10-m long segments for photography; however, certain segments were shifted

upstream slightly (typically no more than 5 m) due to site topography. A Bushnell Yardage

Pro laser rangefinder was used by the boat operator to position a boat 35- to 40-m from the

shoreline, bow directed upstream, into the current. From this position on the water, each of the

10-m segments of shoreline was digitally photographed three to five times in repetition by the

photographer on the boat. In each photograph, a vertical reference scale was attained by having

a field technician stand on the riverbank holding a stadia rod perpendicular to the water surface

at the point where the bank and water converge. The stadia rod used for vertical reference was a

3.5-m x 0.05-m PVC pipe having 0.5-m black and white gradations along its length.

Photographs were taken of the river shoreline from the existing water level to at least bankfull

elevation or higher, with the stadia rod held vertically at the downstream end of each 10-m long

segment (Figure 4-5). Field notes in regards to specific parameters for each sampling station

were recorded on custom generated snag abundance datasheets (Appendix A).

Color photographic images were captured using a Nikon Coolpix E5600 (ver. 1.0)

handheld digital camera. The 'normal' imaging mode setting was used, with automatic focus

and white balance, neutral exposure, single image capture, and standard color, which generated

photographs with a pixel resolution of 2592 x 1944. Digital photographs were saved on Secure

Digital (SD) memory cards in .jpg (24 bit) format. The file size for each digital image was

approximately 1.0 MB.

Digital Photograph Processing and Analysis

All digital photographs were uploaded from the SD memory cards onto a Microsoft

Windows-based desktop computer where they were appropriately labeled and catalogued into a

photographic database. For each of the 10-m shoreline segments photographed, a single









representative photograph was selected from the three to five images captured in the field. The

representative photograph was chosen based on its optimization of the following seven criteria:

1) image clarity; 2) focus; 3) resolution; 4) brightness; 5) image-shoreline parallelism; 6)

shoreline-stadia rod perpendicularity; and 7) absence of avian or flying-insect interference.

Segment photographs were optimized for digital image analysis using Adobe Photoshop

7.0 ( 2002 Adobe Systems, Inc.) photo editing software. Original color images (Figure 4-6A),

were 'inverted' to form a photographic negative and then converted to a grayscale format

consisting of 256 shades of gray (Figure 4-6B). Grayscale images were reduced in size, and

saved as uncompressed tagged image files (.tif).

Calculation of snag area was accomplished using Image J (ver. 1.35s) image processing

and analysis software. Image J is a Java-based computer program developed at the US National

Institutes of Health that runs in most major operating systems and is available free of charge as

public domain software (Rasband 2002). By converting individual picture elements (pixels) to a

unit of measurement, Image Jis capable of calculating areas of irregular-shaped objects using

user-defined scales.

Each grayscale .tif image file was opened in Image J for digital image analysis.

Measurement scale was reset for each image by instructing the program to count the number of

pixels necessary to traverse 1.0 m on the stadia rod (n z 110). After the scale for a photograph

was defined, a 10.0-m horizontal line was stretched out digitally along the water surface using

the 'line' and 'measurement' tools, and ultimately sketched on the photograph using the 'draw'

command. Utilizing the 'box' tool, a 0.5-m tall x 10.0-m long rectangle block was expanded

adjacent to the digitally sketched horizontal line, and the vertical stadia rod as a 5.0-m2

measurement boundary for calculation. The entire image was then filtered in Image Jwith a









simple thresholding algorithm at a threshold pixel brightness value of 128 to produce a binary

image suitable for analysis (Ridler and Calvard, 1978) (Figure 4-6C). The thresholding

procedure enhanced the snag material from its surroundings by converting all the grayscale

pixels in the image to either a black or white pixel depending on its grayscale brightness value

(0-128=black pixel; 129-256=white pixel).

Within the 5.0-m2 measurement block, Image J counted all of the black pixels using the

'analyze particles' command, and generated an area (m2) value based on the previously defined

measurement scale. The measurement block was then moved 0.5 m up the stadia rod using the

'hand' tool, and the measurement process was repeated until all seven of the 5.0-m2 blocks had

been measured (Figure 4-6D). Area values generated by Image Jwere recorded into Microsoft

Office Excel (ver. 2003 SP2) spreadsheets for data management and further analyses. Detailed

guidelines for digital photograph optimization, processing, and analysis techniques utilized in

this study are contained in Appendix B.

Prior to actual data collection on the Apalachicola River, two preliminary studies were

conducted to assess the repeatability, sensitivity, and logistics of using the proposed digital

image analysis techniques for snag area quantification. In the first study, a 0.5-m x 0.5-m

Plexiglas square was constructed, painted white, and subsequently framed with a 0.025-m wide

black border as a sample object of known area. The test square was attached 1.75 m above

ground level on a vertical pole, with one edge of the square parallel to the ground surface. A

100.0-m measuring tape was extended outward from the pole, and survey flags were inserted into

the ground at 10.0-m increments. Three un-zoomed photographs of the test square were taken at

each 10.0-m distance away from the pole. The test square was then rotated 450 and the

photographic procedure was repeated. All photographs were then analyzed using the digital









image analysis techniques to determine errors associated with variation in horizontal distance

and target orientation. The results of the first pilot study indicated that horizontal distances

within 80.0-m of the target object produced area values with less than 5.0% error, while

distances within 50.0-m of the target produced less than 2.0% error. Orientation of the target

was found to have no measurable effect on calculated areas using the proposed methods.

A second pilot study was conducted on the Suwannee River to address logistical details of

the field-based methods. During this trial, a field assistant was positioned along the river shore

with the 3.5-m stadia rod, and photographs were taken at various distances (-15.0-60.0 m) from

the bank to assess variations in snag detail. Additionally, 10.0- to 25.0-m lengths of shoreline

were photographed at a distance of 40.0-m from the bank to evaluate the length of shoreline

necessary to generate abundant area data within each of the 0.5-m elevations above water level.

Results of the second study indicated that photography at a distance of 40.0-m from the shore

generated ample resolution of even the smallest snags along the bank, and 10.0-m lengths of

shoreline produced sufficient area data for analyses.










Table 4-1. River mile and geocoordinates of field sites located within the 55.3-km intensive
study reach of the Apalachicola River. River mile is the approximate distance
upstream from the mouth of the river determined by USGS topographic maps. GPS
positions are based on the WGS 84 datum.


Field Site Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30


River Mile
62.4
61.1
59.9
58.8
57.5
56.3
55.2
54.0
52.8
51.7
50.5
49.3
48.1
46.9
45.9
44.6
43.4
42.3
41.4
40.0
38.7
37.7
36.5
35.4
34.3
33.1
31.9
30.7
29.4
28.1


Latitude
300 18' 22.53" N
300 18' 00.90" N
300 17' 08.06" N
300 16' 20.94" N
300 15' 32.89" N
300 14' 54.27" N
300 14' 23.99" N
300 13' 41.19" N
300 13' 14.78" N
300 12' 41.40" N
300 12' 49.13" N
300 12' 28.43" N
300 11' 43.16" N
300 10' 52.64" N
300 10' 07.22" N
300 09' 31.99" N
300 08' 36.99" N
300 08' 08.41" N
300 07' 19.90" N
300 06' 55.95" N
300 06' 32.16" N
300 06' 22.89" N
300 05' 42.88" N
300 05' 16.61" N
300 04' 18.37" N
300 03' 38.04" N
300 02' 36.71" N
300 01' 50.05" N
300 01' 26.11" N
300 00' 56.13" N


Longitude
850 02' 59.08" W
850 03' 25.74" W
850 03' 25.74" W
850 03' 41.66" W
850 03' 42.74" W
850 04' 19.94" W
850 04' 46.05" W
850 04' 57.32" W
850 05' 25.93" W
850 06' 03.12" W
850 06' 40.85" W
850 07' 11.06" W
850 07' 19.82" W
850 07' 57.00" W
850 08' 23.99" W
850 07' 54.86" W
850 08' 14.29" W
850 08' 16.97" W
850 08' 39.48" W
850 07' 51.97" W
850 08' 20.72" W
850 08' 51.80" W
850 09' 08.76" W
850 08' 20.01" W
850 08' 18.76" W
850 08' 11.80" W
850 08' 09.12" W
850 07' 20.40" W
850 06' 26.86" W
850 05' 37.79" W









Table 4-2. Geomorphic and bank habitat classifications of sampling stations within the 55.3-km
intensive study reach of the Apalachicola River. Geomorphic classifications derived
from USGS topographic maps, and bank habitat classifications based on Ager et al.
(1987).


Geomorphic If a Bend, Inner or Bank Habitat
Classification Outer Bank Classification


Station
Number
lA
1B
2A
2B
3A
3B
4A
4B
5A
5B
6A
6B
7A
7B
8A
8B
9A
9B
10A
10B
11A
11B
12A
12B
13A
13B
14A
14B
15A
15B
16A
16B
17A
17B
18A
18B
19A
19B
20A


Left or Right
Descending Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Right Bank
Left Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank
Right Bank
Left Bank


Straightaway
Straightaway
Straightaway
Straightaway
Exiting Bend
Exiting Bend
Straightaway
Straightaway
Exiting Bend
Exiting Bend
Bend Apex
Bend Apex
Exiting Bend
Exiting Bend
Exiting Bend
Exiting Bend
Bend Apex
Bend Apex
Bend Apex
Bend Apex
Straightaway
Straightaway
Exiting Bend
Exiting Bend
Straightaway
Straightaway
Exiting Bend
Exiting Bend
Bend Apex
Bend Apex
Exiting Bend
Exiting Bend
Exiting Bend
Exiting Bend
Exiting Bend
Exiting Bend
Exiting Bend
Exiting Bend
Bend Avex


Gentle Bank
Steep Bank
Gentle Bank
Gentle Bank
Steep Bank
Gentle Bank
Steep Bank
Gentle Bank
Steep Bank
Sandbar
Gentle Bank
Sandbar
Steep Bank
Gentle Bank
Steep Bank
Gentle Bank
Steep Bank
Sandbar
Steep Bank
Sandbar
Gentle Bank
Steep Bank
Sandbar
Steep Bank
Gentle Bank
Steep Bank
Steep Bank
Sandbar
Steep Bank
Sandbar
Steep Bank
Sandbar
Sandbar
Steep Bank
Gentle Bank
Steep Bank
Gentle Bank
Steep Bank
Steep Bank


Outer Bank
Inner Bank


Outer Bank
Inner Bank
Outer Bank
Inner Bank
Outer Bank
Inner Bank
Outer Bank
Inner Bank
Outer Bank
Inner Bank
Outer Bank
Inner Bank


Inner Bank
Outer Bank


Outer Bank
Inner Bank
Outer Bank
Inner Bank
Outer Bank
Inner Bank
Inner Bank
Outer Bank
Inner Bank
Outer Bank
Inner Bank
Outer Bank
Outer Bank









Table 4-2. Continued.
Station Left or Right
Number Descending Bank
20B Right Bank
21A Left Bank
21B Right Bank
22A Left Bank
22B Right Bank
23A Left Bank
23B Right Bank
24A Left Bank
24B Right Bank
25A Left Bank
25B Right Bank
26A Left Bank
26B Right Bank
27A Left Bank
27B Right Bank
28A Left Bank
28B Right Bank
29A Left Bank
29B Right Bank
30A Left Bank
30B Right Bank


Geomorphic
Classification
Bend Apex
Entering Bend
Entering Bend
Straightaway
Straightaway
Bend Apex
Bend Apex
Bend Apex
Bend Apex
Bend Apex
Bend Apex
Exiting Bend
Exiting Bend
Bend Apex
Bend Apex
Straightaway
Straightaway
Exiting Bend
Exiting Bend
Bend Apex
Bend Apex


If a Bend, Inner or
Outer Bank
Inner Bank
Outer Bank
Inner Bank


Inner Bank
Outer Bank
Outer Bank
Inner Bank
Inner Bank
Outer Bank
Inner Bank
Outer Bank
Inner Bank
Outer Bank


Outer Bank
Inner Bank
Outer Bank
Inner Bank


Bank Habitat
Classification
Gentle Bank
Steep Bank
Sandbar
Steep Bank
Gentle Bank
Sandbar
Steep Bank
Steep Bank
Sandbar
Gentle Bank
Steep Bank
Steep Bank
Dike Field
Steep Bank
Gentle Bank
Gentle Bank
Steep Bank
Steep Bank
Gentle Bank
Steep Bank
Gentle Bank













XMap 4.5


Data use subject to license km
02004 DeLorme XMap45 0 4 8 12 16 20 24 28
www.delorme.com MN (3.2 W) Data Zoom 8-0


Figure 4-1. The four major reaches of the Apalachicola River as defined by Leitman (1984).
A) Upper reach (RM 106.3-77.4). B) Middle reach (RM 77.4-42.0). C) Non-tidal
lower reach (RM 42.0-20.6). D) Tidal lower reach (RM 20.6-0.0).


Li.i^M-l.'.IJ














XMap 4.5


mI..^


Data use subject to license.
2004 DeLorme. XMap 4.5.
www.delorme.com


MN (3.2 W)


km
0 4 8 12 16 20 24 28
Data Zoom 8-0


Figure 4-2. Map of the Apalachicola River basin and surrounding region. Large box indicates
the location of the 55.3-km intensive study reach. Selected cities are denoted by
circles, and river gaging stations indicated by squares.
























Al B















C D

Figure 4-3. Representative photographs of the four bank habitat types defined by Ager et al. (1987) encountered during this study.
A) Steep sloping bank. B) Gentle sloping bank. C) Sandbar. D) Dike field. These images not used for analysis purposes.











XMap 4.5


Data use subject to license. km
@ 2004 DeLorme. XMap 4.5. 0 1 2 3 4 5 6 7
www delorme.com MN (3.1 W) Data Zoom 10-0


Figure 4-4. Map of the 55.3-km intensive study reach of the Apalachicola River indicating the
specific locations of the 30 study sites. At each study site, both the left- and right-
descending banks were evaluated for a total of 60 sampling stations.


^J.BM-I.'.IJ





































Figure 4-5. Example of a digital image captured using the methods detailed in this study. Note
the field technician on the riverbank holding the 3.5-m long stadia rod perpendicular
to the water surface at the location where the bank and water converge.



















I

A
A -


A B


















C D

Figure 4-6. Filtering and processing steps used to prepare photographs for digital image analysis. A) Original color image. B)
Grayscale negative of the original color image. C) Thresholded black-and-white image. D) Thresholded image illustrating
the seven, 0.5-m tall x 10.0-m long superimposed measurement blocks used for digital image analysis.









CHAPTER 5
HYDROLOGIC ANALYSES, RESULTS, AND DISCUSSION

Hydrologic Analyses

In order to appraise riverine habitat availability in relation to river stage or discharge, it is

necessary to understand the hydrology of the basin. By examining time series data from gaging

stations, inferences can be made regarding changes in river geomorphology with time, as well as

the likelihood of experiencing similar hydrologic conditions in the future (McCuen 2005). For

this study, real-time hydrologic stage and flow data were available from three USGS surface-

water gaging stations on the Apalachicola River. Gages were located at Chattahoochee (USGS #

02358000) (RM 105.8), Blountstown (USGS # 02359170) (RM 77.6), and near Sumatra (USGS

# 02358700) (RM 20.6) (Figure 4-2). Data from the Chattahoochee gage were used in this study

for all long-term flow analyses based on its extensive period of record (1929-present). All short-

term flow analyses were made from data generated at the Blountstown gage due to its proximity

to the 55.3-km intensive study area, therefore minimizing lag time effects. According to Light et

al. (1998), Apalachicola River flows below 15,000 cfs at the Sumatra gage are generally tidally

influenced, so data from this gaging station were not utilized in this low-flow study.

Based on 1929-2006 daily discharge data obtained from the Chattahoochee gaging station,

a linear mean daily discharge duration curve was constructed to determine the percentage of time

a given discharge was equaled or exceeded (Figure 5-1). In order to interpret the likelihood and

magnitude of extreme flow events, the daily discharge data were transformed to produce a

logarithmic mean daily discharge plot (Figure 5-2). Because the State of Florida and the USACE

use data from the Chattahoochee gage to monitor and regulate water flows in the Apalachicola

River, and because this study utilized stage and discharge data obtained from the Blountstown

gage, an equivalency curve approximating the relation of Chattahoochee gage discharge readings









with Blountstown gage stage readings for the Apalachicola River was generated (Figure 5-3).

Additionally, a stage-discharge rating curve (Figure 5-4) and a stage-discharge hydrograph

(Figure 5-5) were constructed from data obtained at the Blountstown gage spanning the duration

of this study (March 2004-March 2006).

Due to the dynamic nature of fluvial systems, and because parameters and units used to

specify water levels, flows, and elevations can become confounded, a datum designated as

'baseline' was defined in this study to signify the river conditions during data collection.

Baseline readings at the Blountstown gage were a stage of 4.08 ft, and a discharge of 10,100 cfs.

Snag quantification for this study was performed at a total of seven, 0.5-m distances above

baseline. Table 5-1 contains equivalent stage, discharge, and NGVD 29 sea-level elevations at

the Blountstown gage for baseline conditions, as well as at each of the 0.5-m distances above

baseline.

Results

From 10-13 October 2005, a total of 1,060 digital photographs were captured of shoreline

habitat within the 55.3-km intensive study reach of the Apalachicola River. Within this reach,

240 digital images totaling 2.4 km of river shoreline were quantified for snag abundance and

distribution in each of the seven 0.5-m tall x 10.0-m long measurement blocks above baseline,

using the digital imaging analysis techniques detailed in Chapter 4. Based on bank habitat

classifications defined by Ager et al. (1987), nearly all of the 60 sampling stations in this study

were classified as steep sloping banks, gentle sloping banks, or sandbar habitats; only one dike

field station was encountered during the survey (Table 5-2). Most of the sampling stations

(96.6%) were geomorphically classified using USGS topographic maps as being located at the

apex of a bend, exiting a river bend, or along a river straightaway, while only 2 stations were

located at the entrance to a bend in the river (Table 5-3).









Visual inspection of the original color images of river banks captured in the field indicated

that sandbar habitats typically possessed the lowest quantity of available snag material (e.g.,

Figure 4-3C); however, comparison of mean snag area values generated for sandbar habitats

using the novel methods presented in this study, with those of the three other habitats

encountered, revealed that sandbar area values were erroneously elevated (Figure 5-6). Data

from sandbar habitats were consequently omitted from subsequent analyses due to their

inaccuracy. Analysis of mean snag area submerged for non-sandbar habitats indicated that the

greatest quantities would occur within the first meter above baseline; gentle sloping bank habitat

having the highest mean area submerged (3.19 m2), followed by steep sloping banks, and dike

field habitats (2.56 and 1.71 m2, respectively) (Table 5-4; Figure 5-7). Mean snag area

submerged for non-sandbar habitats based on geomorphic classification revealed the greatest

quantities of snags would be submerged at a river stage between 0.5-m to 1.0-m above baseline;

river banks entering a bend having the highest mean snag area submerged (3.97 m2), followed by

straightaway, exiting bend, and bend apex locations (2.97, 2.83, and 2.37 m2, respectively)

(Table 5-5; Figure 5-8). Further geomorphic analyses of non-sandbar habitats showed that

within the first 0.5-m above baseline the inner banks of bends in the river have the most snag

area submerged (3.09 m2), followed the outer banks of river bends that would have a maximum

mean area submerged of 2.50 m2 at a distance between 0.5-m to 1.0-m above baseline (Table 5-

6; Figure 5-9).

Examination of the sampling stations subdivided into Ager et al. (1987) habitat

classifications indicated that 50% of the total available snag material would be submerged at

0.92 m above baseline for gentle sloping banks, 0.97 m above baseline for dike field habitat, and

1.32 m above baseline for steep sloping banks (Figure 5-10). Separating the non-sandbar habitat









sampling stations into geomorphic classifications showed that the distance above baseline at

which 50% of the total available snag material would be submerged at a range from 1.10 m for

river straightaways, to 1.32 m for sampling stations entering a river bend (Figure 5-11).

Additional geomorphic evaluation revealed that the distance above baseline at which 50% of the

available snags would be submerged was 0.94 m for inner banks of river bends, 1.10 m for river

straightaways, and 1.32 m for outer banks of river bends (Figure 5-12).

Discussion

In fluvial systems, hydrologic variability analyses and incremental methodologies are

useful approaches for determining minimum instream flow requirements needed to maintain

optimal ecological function and biotic integrity during low flows (Richter et al. 1997).

Examination of the discharge duration curve (Figure 5-1) indicates that the Apalachicola River

has experienced a remarkable variation of discharge readings during its 77-year period of record,

with extreme high and low-discharges recorded on occasion. Because the curve generated in

Figure 5-1 covers such a large range of values with many occurring infrequently, the data were

transformed to produce a logarithmic flow duration plot to assist with interpretation of low-flow

frequency (Figure 5-2). The relatively linear shape of the curve in Figure 5-2 indicates that the

Apalachicola River has a strong baseflow component that can be attributed to both the immense

size of the upstream Chattahoochee and Flint drainage basins, as well as to the significant

groundwater influence within the basin (Elder et al. 1988). Mean daily discharge for the period

of record at the Chattahoochee gage equaled or exceeded 15,900 cfs 50% of the time, while

discharges of 8,480 cfs and 5,000 cfs were equaled or exceeded 90 and 99% of the time,

respectively (Figure 5-2). Based on these curves, it appears that low-flow conditions in the

Apalachicola River are not a frequent occurrence. However, the long period of record at the

Chattahoochee gage includes 25 years of pre-impoundment, non-regulated discharge data that









tends to amplify daily discharge means (Leitman et al. 1983). Additionally, increased

consumption of water in the ACF basin in response to growing urbanization and agricultural

demands, as well as increased rates of evapotranspiration due to river impoundment have

decreased downstream river flows (Elder et al. 1988). Light et al. (2006) reported that recent

discharge reductions in the Apalachicola River have been exacerbated by anthropogenic

activities along with natural climatic change throughout the ACF basin.

The equivalency curve in Figure 5-3 indicates that a Blountstown gage stage of 4.08 ft

(baseline in this study) is generated by a discharge of 10,200 cfs at the Chattahoochee gage.

Other key Blountstown stage values are 5.72 ft and 7.36 ft (0.5 and 1.0 m above baseline,

respectively), which correspond to a Chattahoochee discharge of 13,100 and 16,400 cfs,

respectively (Figure 5-3). The shape of the stage-discharge rating curve for the Blountstown

gage (Figure 5-4) indicates that at low flows, the river is confined primarily to its main channel;

a small change in discharge results in a fairly substantial change in river stage. The curve also

illustrates the distributional effects of the expansive Apalachicola River floodplain, in that once

the river exceeds flood stage, large increases in discharge must be attained to notice appreciable

changes in river stage (Figure 5-4).

The digital imaging analysis methods for snag quantification that are presented in this

study are best suited for extremely low-flow conditions. Exposed snag material along the banks

of the Apalachicola River was to be photographed at the lowest water levels possible; ideally at

or near the State of Florida mandated minimum flow of 5,000 cfs at the Chattahoochee gage.

Photography was scheduled to take place the first week of September 2004, as the summer had

been reasonably dry, and water levels in the river were steadily declining towards the state

minimum (Figure 5-5). However, the untimely arrival of Hurricane Frances to the Florida









panhandle curtailed these plans. To complicate things further, Hurricanes Ivan and Jeanne

followed several weeks later, which elevated water levels above flood stage, and eliminated low-

flow photographic opportunities until September of the following year. With yearly tropical

cyclone activity highly unpredictable, and having a limited timeframe for data collection,

photography for this study transpired in mid-October 2005 at relatively low flows (Figure 5-5).

In an attempt to reduce the introduction of additional error and complexity to the digital

imaging analysis methods, all photographs were filtered, processed, and analyzed in exactly the

same manner. However, a major limitation of using the analysis techniques as described in

Chapter 4 was revealed for sandbar habitats when comparing the computed mean snag area

values with the original color images captured in the field. Nearly all photographs of sandbar

habitats on the Apalachicola River resembled the image in Figure 4-3C; large aggregations of

river sand with an occasional interspersed woody snag. Mean snag area values generated for

sandbar habitats were erroneously elevated, particularly in the lowest intervals above baseline

(Figure 5-6). Visual examination of the original color photographs revealed that images of

generally shaded habitats types such as steep sloping banks, gentle sloping banks, and dike fields

normally presented lightly-colored snag material against relatively darker backgrounds (e.g.,

Figure 4-5). Conversely, images captured of sandbar habitats typically contained darker-colored

snag material against a nearly white sandy background. It was also determined that wet, and

consequently darker-colored sand in the measurement intervals nearest to the water level for

sandbar habitats were inaccurately interpreted by the analysis methods as snag material. Similar

setbacks were not evident for snag areas computed of steep sloping banks, gentle sloping banks,

or dike field habitats which were usually shaded from direct sunlight. Another drawback that

was encountered exclusively at sandbar habitat stations was a depth-of-field problem created by









the low-gradient bank angle that often produced a considerable distance between the stadia rod

and the river bank in the background of the image. Unfortunately, the limitations of the analysis

methods for sandbar habitats were not discovered during the pilot study on the Suwannee River,

as only steep and gentle sloping banks were photographed in that trial. Potential modifications

of the methods to reduce errors produced for sandbar habitats include: 1) an adjustment of the

white-balance, or exposure settings of the camera when images of sandbar habitat are captured in

the field; 2) use of an alternative threshold value other than 128 in the image processing steps; or

3) the development of an image processing algorithm that further isolates snag material from its

surroundings by incorporation of ambient light levels with image contrast ratios. With visual

inspections of original color photographs indicating nominal snag quantities on sandbar habitats,

and due to the considerable quantification error revealed using the existing imaging analysis

methods, mean snag area data from the 12 sandbar stations examined in this study were omitted

from all subsequent analyses.

Mean area of snags submerged for steep sloping bank habitat appears to diminish fairly

evenly from baseline to the 3.5-m distance above baseline, whereas snag area for gentle sloping

banks was greatest from baseline to 1.0 m above baseline, then quickly tapered off (Figure 5-7).

Diehl and Bryan (1993) indicated that steep sloping banks generally occur along the outside

banks of river bends where erosion rates are fairly high. As the steep river banks are incised and

undercut, snag material from the top of the bank tends to fall towards the river where it will often

hang by its rootwad, or by a network of vines, until it ultimately becomes detached from the

bank and deposited in the river (Golladay and Battle 2006). Gentle sloping banks stations on the

Apalachicola River were for the most part located along the inner banks of a bend in the river, or

along straightaways of the river (Table 4-2). Water velocities tend to be lower at these locations









and consequently snags have a propensity to be deposited during decreased flows conditions.

Additionally, Figure 5-7 indicates that when discharge and river stage increase, snags are picked

up and transported by the increased water velocity, leaving the upper elevations of gentle sloping

bank habitats without appreciable snag quantities. Dike field habitat was only represented in this

study at one sampling station within the 55.3-km intensive study reach (Table 5-2), therefore the

curve generated by these data was plotted for reference only, and further interpretation was

reserved (Figure 5-7).

The entering bend geomorphic classification was also weakly represented in this study

with a total of two sampling stations (Table 5-3). Only one of the two entering bend geomorphic

stations was a non-sandbar habitat type, therefore, these data were plotted as a reference and

interpretations should be made with caution (Figure 5-8). Analyses of the other curves within

Figure 5-8 indicates that geomorphic classification of non-sandbar bank habitat type had

relatively little influence on mean area of snags submerged, as well as vertical distribution within

the 3.5-m distance above baseline. The majority of snags that would be submerged at greater

river flows are found in the elevations just above baseline conditions, and steadily decreases as

river stages approach flood stage levels (Figure 5-8). This trend would be expected as the main

river channel is the usual collection site, and downstream transport vehicle for products washed

off the floodplain (Ward et al. 1999). In addition, river velocities tend to decrease as stage

decreases, so snags that would ordinarily be transported downriver during high-flow conditions

end up being deposited along the river banks at lower river velocities (Gurnell 2003).

Throughout the bends and straightaways of the Apalachicola River, snags quantities appear to be

encountered fairly homogeneously.









Figure 5-9 illustrates that snag distribution along the outer banks of a river bend are

somewhat more evenly distributed throughout the range from baseline to 3.5 m above baseline

than along river straightaways, or along the inner banks of river bends. As the majority of outer

bank river bend sampling stations were also classified as steep sloping habitats (Table 4-2), the

increased rates of erosion and bank failure observed at these locations contributes to the slightly

more even distribution of snag material. At both inner bank and river straightaway stations, the

distribution of snag material is greater in the first 1.5-m elevations above baseline, and then

rapidly diminishes at higher elevations (Figure 5-9).

Interpretation of the curves in Figures 5-6 through 5-9 should not be extrapolated beyond

the axes on which they are plotted. The abundance and distribution of snag material below

baseline conditions remains undetermined, and it should not be assumed that the existing trends

would hold true at distances other than what are presented. Since this was a low-flow study, all

snag material below baseline conditions was presumed to remain submerged at baseline

discharges or greater.

Assuming that all quantified snags would be submerged at the 3.5-m distance above

baseline, a relative percentage of total available snags was computed for each 0.5-m distance

above baseline. In order to compare these curves, the distance above baseline where 50% of the

available snags would be submerged was arbitrarily selected as a point of evaluation, in addition

to the general shape of the curve. Analyses of the plots illustrating the relative percentage of

snags submerged based on bank habitat classifications (Figure 5-10), geomorphic classifications

(Figure 5-11), and by bank location within a river bend (Figure 5-12) exhibited results similar to

those of the area submerged plots: 1) steep sloping banks exhibited the most uniform vertical

snag distribution, while gentle sloping banks tended to have greater snag quantity at lower









distances above baseline; 2) geomorphic classification had no considerable effect on snag

distribution; and 3) outer banks of river bends tended to have a more balanced distribution of

available snags throughout the range of measurement than did inner banks of river bends or

straightaways.

Recommendations

Officials responsible for making water allocation choices should continue to rely on

scientific research to assist with their decisions. Based on the results of this study, and those of

scientists from other agencies, the State of Florida should continue to pursue increased river

discharges from the Jim Woodruff Lock and Dam. As water levels decline in the river, so does

the availability of valuable snag habitat which can have cascading negative effects on vital

physical, chemical, and biological components of the ecology within the Apalachicola River and

Bay ecosystems.

The water allocation issues that have developed within the ACF watershed are truly

complex. Development of a water management plan for the basin which satisfies human

consumptive demands while maintaining optimal ecosystem integrity and functionality is a

difficult task, especially for a basin of its size. Intuitively, humans prefer to fix problems at the

local level so immediate results can be achieved (Sparks 1995). However, in large watersheds

like the ACF, a system-level approach should be encouraged for increased equity of success.

Based on the increasing number of stakeholders with interests for water in the basin, there

appears to be no feasible way to completely satisfy all of its users during unseasonably dry

periods. With urbanization and agricultural growth continuing at a rapid pace, the inability to

meet future water demands will most likely occur with increased frequency. Water conservation

efforts among all users in the basin must continue to be endorsed, and rates of urban growth need

to be checked. The effects of urbanization greatly exceed the delineated boundaries of urban









areas. With this in mind, it is imperative that local, state, and federal officials remain committed

to seeking common sense solutions towards an effective balance between the competing water

demands and conservation needs of river-impacted flora and fauna within the ACF basin.









Table 5-1. Equivalent stage, discharge, and elevation readings at baseline conditions, and at 0.5-
m distances above baseline, for the Blountstown gage, Apalachicola River.


Distance Above
Baseline (m)
3.5
3.0
2.5
2.0
1.5
1.0
0.5
Baseline


Blountstown
Stage (ft)
15.56
13.92
12.28
10.64
9.00
7.36
5.72
4.08


Blountstown
Discharge (cfs)
39,700
33,400
28,300
23,700
19,600
16,000
12,900
10,100


Blountstown
Discharge (cms)
1,124.6
946.2
801.7
671.4
555.2
453.3
365.6
286.0


Distance Above
NGVD29 (m)
12.96
12.46
11.96
11.46
10.96
10.46
9.96
9.46


Table 5-2. Bank habitat classification summary for the 60 sampling stations within the 55.3-km
intensive study reach of the Apalachicola River. Habitat classifications based on
Ager et al. (1987).
Habitat Classification Number of Stations % of Total Study Area
Steep Sloping Bank 29 48.3
Gentle Sloping Bank 18 30.0
Sandbar 12 20.0
Dike Field 1 1.7


Table 5-3. Geomorphic classification summary for the 60 sampling stations within the 55.3-km
intensive study reach of the Apalachicola River. Geomorphic classifications derived
from USGS topographic maps.
Geomorphic Classification Number of Stations % of Total Study Area
Bend Apex 20 33.3
Exiting Bend 24 40.0
Straightaway 14 23.3
Entering Bend 2 3.4









Table 5-4. Bank habitat classification effects on mean area of snags submerged, and relative percentage of total snag area submerged,
for non-sandbar habitat stations on the Apalachicola River. Snag areas submerged at 0.5-m distances above baseline are
per 10.0-m of shoreline, and percentages are relative to all snags being submerged at 3.5-m above baseline. Bank habitat
classifications based on Ager et al. (1987).
Steep Sloping Bank (n=29) Gentle Sloping Bank (n=18) Dike Field (n=1)
Distance Above
Baseline (m) Snag Area Relative % Snag Area Relative % Snag Area Relative %
(m2) (m2) (m2)
3.5 0.99 100.0 0.71 100.0 0.62 100.0
3.0 1.12 90.7 0.67 93.1 0.47 91.6
2.5 1.40 81.3 0.63 86.9 0.47 85.9
2.0 1.78 70.0 1.11 81.3 0.73 79.9
1.5 2.28 56.4 2.36 72.1 1.35 70.0
1.0 2.56 38.5 3.14 53.7 1.61 51.8
0.5 2.29 18.0 3.19 28.1 1.71 28.3


Table 5-5. Geomorphic classification effects on mean area of snags submerged, and relative percentage of total snag area submerged,
for non-sandbar habitat stations on the Apalachicola River. Snag areas submerged at 0.5-m distances above baseline are
per 10.0-m of shoreline, and percentages are relative to all snags being submerged at 3.5-m above baseline. Geomorphic
classifications derived from USGS topographic maps.
Distance Bend Apex (n=14) Exiting Bend (n=19) Straightaway (n= 14) Entering Bend (n=1)
Above Snag Area Snag Area Snag Area Snag Area
Baseline (m) (m2) Relative % (m2) Relative % (m2) Relative % (m2) Relative %
3.5 0.88 100.0 0.76 100.0 0.99 100.0 1.47 100.0
3.0 0.94 91.5 0.86 92.2 1.00 91.0 1.70 92.5
2.5 1.15 83.1 1.00 84.5 1.06 82.5 2.43 83.7
2.0 1.50 72.9 1.56 76.0 1.32 74.0 3.03 71.4
1.5 2.05 60.0 2.39 63.8 2.29 63.8 3.60 56.3
1.0 2.37 41.7 2.83 45.4 2.97 46.4 3.97 38.4
0.5 2.29 20.6 2.61 22.4 2.86 23.1 3.72 18.6









Table 5-6. Effects of bank location within a river bend on mean area of snags submerged, and
relative percentage of total snag area submerged, for non-sandbar habitat stations on
the Apalachicola River. Snag areas submerged at 0.5-m distances above baseline are
per 10.0-m of shoreline, and percentages are relative to all snags being submerged at
3.5-m above baseline. Bank locations derived from USGS topographic maps.
Distance Above Inner Bank (n= 11) Outer Bank (n=23)
Baseline (m) Snag Area (m2) Relative % Snag Area (m2) Relative %
3.5 0.62 100.0 0.94 100.0
3.0 0.60 93.7 1.06 91.1
2.5 0.56 87.8 1.37 82.0
2.0 1.19 82.6 1.77 70.8
1.5 2.44 72.3 2.21 57.1
1.0 3.04 53.1 2.50 39.2
0.5 3.09 28.0 2.23 18.5











300,000


270,000


240,000


210,000


180,000


150,000


120,000


90,000


60,000


30,000


0


0 10 20


30 40 50 60 70
Percent of Time a Given Discharge is Equaled or Exceeded


90 100


Figure 5-1. Linear mean daily discharge duration curve for the Apalachicola River at the Chattahoochee gage (1929-2006).












1000000
800000 -
600000 -
400000 -


200000 -


100000 -
80000 -
4 60000 -
S 40000 -


20000 -


10000 -
8000 -
6000 -
4000 -


2000 -


1000 I i i i i
0.01 0.1 1 10 30 50 70 90 99 99.9 99.99
Percent of Time a Given Discharge is Equaled or Exceeded


Figure 5-2. Logarithmic mean daily discharge duration curve for the Apalachicola River at the Chattahoochee gage (1929-2006).











30.0


25.0



20.0



15.0
15. FLOOD STAGE



10.0



5.0



0.0



-5.0

0 0 0 0 0 0 0 0 0 0

Chattahoochee Discharge (cfs)


Figure 5-3. Equivalency curve approximating the relation of Chattahoochee gage discharge readings with Blountstown gage stage
readings for the Apalachicola River. Curve based on unpublished data supplied by H. Light, USGS Tallahassee, 2002.












30.0


25.0




20.0




15.0
FLOOI



10.0




5.0




0.0




Discharge (cfs)



Figure 5-4. Stage-discharge rating curve for the Apalachicola River at the Blountstown gage (March 2004-March 2006).












25.00


20.00






15.00






10.00


FLOOD STAGE -


iy1,30'






68,000






36,900






22,000






11,700


5.00JIJ


U.UU00


Date


Figure 5-5. Stage-discharge hydrograph for the Apalachicola River at the Blountstown gage (March 2004-March 2006). Shaded box
indicates the period of time when fieldwork was conducted.


i i


0tr^-rr


1


I












3.5 39,700
------ --- --------------------------------------- FLOOD STAGE


3.0 33,400



2.5 28,300



S2.0 23,700 Steep Sloping Bank (n=29)
a Gentle Sloping Bank (n=18)
S'-Dike Field (n=l)
1.5 19,600 Sandbar (n=12)
1.5 19,600-Ogg



1.0 16,000
-NOTE-
Sandbar habitat
data are
0.5 12,900 inaccurate



0.0 --- 10,100
0.0 1.0 2.0 3.0 4.0 5.0

Mean Area of Snags Submerged (m2)


Figure 5-6. Bank habitat classification effects on mean area of snags submerged at 0.5-m distances above baseline. Curves generated
from all data collected within the 55.3-km intensive study reach of the Apalachicola River. Snag areas submerged at 0.5-m
distances above baseline are per 10.0-m of shoreline. Sandbar habitat data are inaccurate, and plotted with a dashed-line as
a reference only. Data from these curves should not be extrapolated.












3.5


3.0



2.5


2.0


1.5


------ --- ---------------------------------------


.

"
















,


Mean Area of Snags Submerged (m2)


Figure 5-7. Non-sandbar bank habitat classification effects on mean area of snags submerged at 0.5-m distances above baseline.
Curves generated from data collected within the 55.3-km intensive study reach of the Apalachicola River. Snag areas
submerged at 0.5-m distances above baseline are per 10.0-m of shoreline. Data from these curves should not be
extrapolated.


39,700
FLOOD STAGE


33,400



28,300



23,700
Steep Sloping Bank (n=29)
Gentle Sloping Bank (n=18)
Dike Field (n=l)
19,600



16,000




12,900



10,100

















3.0


2.5


2.0


-------- --------------------------


39,700
FLOOD STAGE


33,400



28,300



23,700



19,600


16,000



12,900



- 10,100
5.0


Mean Area of Snags Submerged (m2)


Figure 5-8. Geomorphic classification effects on mean area of snags submerged at 0.5-m distances above baseline. Curves generated
from non-sandbar habitat data collected within the 55.3-km intensive study reach of the Apalachicola River. Snag areas
submerged at 0.5-m distances above baseline are per 10.0-m of shoreline. Data from these curves should not be
extrapolated.


- Bend Apex (n=14)
Exiting Bend (n=19)
SStraightaway (n=14)
Entering Bend (n=l)















































1.0 2.0 3.0

Mean Area of Snags Submerged (m2)


39,700
FLOOD STAGE


33,400



28,300




23,700




19,600


-Inner Bank (n=11)
Outer Bank (n=23)
- Straightaway (n=14)


- 16,000




- 12,900



- 10,100
5.0


Figure 5-9. Effects of bank location within a river bend on mean area of snags submerged at 0.5-m distances above baseline. Curves
generated from non-sandbar habitat data collected within the 55.3-km intensive study reach of the Apalachicola River.
Snag areas submerged at 0.5-m distances above baseline are per 10.0-m of shoreline. Data from these curves should not be
extrapolated.
















































25 50 75


39,700

- FLOOD STAGE


33,400




28,300

0

23,700 ______A__
SI Steep Sloping Bank (n=29)
Gentle Sloping Bank (n=18)
zI Dike Field (n=l)
19,600




16,000




12,900



10,100

100


% of Available Snags Submerged



Figure 5-10. Bank habitat classification effects on percentage of total available snags submerged in relation to distance above
baseline. Curves generated from non-sandbar habitat data collected within the 55.3-km intensive study reach of the
Apalachicola River. Dotted lines correspond to the location where 50% of the total available snag material would be
submerged.















































25 50 75
% of Available Snags Submerged


- 39,700

- FLOOD STAGE


33,400



28,300


0

23,700 '




19,600 :




- 16,000




- 12,900



- 10,100
100


Figure 5-11. Geomorphic classification effects on percentage of total available snags submerged in relation to distance above
baseline. Curves generated from non-sandbar habitat data collected within the 55.3-km intensive study reach of the
Apalachicola River. Dotted lines correspond to the location where 50% of the total available snag material would be
submerged.
















































25 50 75


39,700

FLOOD STAGE


33,400




28,300


0

23,700 '




19,600 :




16,000




12,900



10,100

100


-Inner Bank (n=11)
Outer Bank (n=23)
- Straightaway (n=14)


% of Available Snags Submerged



Figure 5-12. Effects of bank location within a river bend on percentage of total available snags submerged in relation to distance
above baseline. Curves generated from non-sandbar habitat data collected within the 55.3-km intensive study reach of the
Apalachicola River. Dotted lines correspond to the location where 50% of the total available snag material would be
submerged.











APPENDIX A
SAMPLING STATION FIELD DATAST{EET


Apsnhisl Rie Snag Survey Faied Datasheet


Date: Meld I
Locality, mUezmo iemda&Aw



Cllcors: l~ear We:
GP aum aKypotCoe Nag- eacang:
..atrtxde *Langiude: uTm:
MOMta Sleep bank C-2 4b) g-enie bAnk Q-4 dike field sandbar
Channel left desceniding bank right descending barnk
Geomnorphology: straightawa entennrg bend bend apex exiting bend
if henot irker bank curter bank
Diagram: awmL ww *www pam, crm~m am ju ar~pu n &u oriaw eqr4



















Photograph Infonmalion: am~i. Now, De n qzrciwu usrEdaw

Tffne, Range
1) 1)

2) 2)_____________________

3) 3)_____________________

4) 4)

Nktes:









APPENDIX B
GUIDELINES FOR IMAGE OPTIMIZATION, PROCESSING, AND ANALYSIS OF
DIGITAL PHOTOGRAPHS

ADOBE PHOTOSHOP:

1. File > Open > (filename.jpg) [CTRL + '0']
-'Discard the embedded profile (don't color manage)'
2. Image > Adjustments > Invert [CTRL + 'I']
3. Image 1 Mode 1 Grayscale
4. Image 1 Image Size 1 Pixel Dimensions
-Width: '55' / 'Percent'
5. File > Save As > (filename.tif) [CTRL + SHIFT + 'S']
-'No image compression'
IMAGE J:

1. File > Open (filename.tif) [CTRL + '0']
2. Adjust window size as needed
3. Select the magnifying glass tool and magnify the stadia rod to the height of the screen
-[mouse click = Zoom In; CTRL+ mouse click = Zoom Out]
4. Select the line tool and stretch a vertical line the length of the stadia rod
5. Analyze Set Scale
-Enter known distance (3.5) and unit of length (meter); check box 'global'
6. Zoom back out to 100% using magnifying glass tool
-[mouse click = Zoom In; CTRL+ mouse click = Zoom Out]
7. Select the line tool and stretch a 10-m horizontal line along the waterline
-[CTRL + 'M'] to measure the line
-Add or subtract length to the stretched out horizontal line using either of the
boxes on the ends of the line
-[CTRL + 'M'] and adjust repeatedly until a 10-m length is achieved
8. On the stretched out horizontal line, grab the center box located at 5 m, and drag the
whole line to the bottom of the stadia rod where the water and shoreline
meet to create a right angle
-[CTRL + 'D'] to draw to line on the image at the waterline
9. Analyze 1 Clear Results
-'Do not save'
10. Select the magnifying glass tool and magnify the non-stadia rod end of the drawn-in line
-[mouse click = Zoom In; CTRL+ mouse click = Zoom Out]
11. Using the line tool, stretch a vertical line upwards of at least 3.5-m length from the end of
the drawn-in line
-[CTRL + 'M'] to measure the line
-If the length is 3.5-m or longer, continue on; if the length is short, use the
uppermost box of the vertical line to add length and measure again; when
at least 3.5-m is achieved, continue on
-[CTRL + 'D'] to draw the vertical line on the image
12. Select the magnifying glass tool and magnify the stadia rod to the height of the screen
-[mouse click = Zoom In; CTRL+ mouse click = Zoom Out]









13. Select the rectangle tool and using the stadia rod as a vertical guide, stretch a 0.5-m tall
rectangle of any length
14. Use the hand tool, select the center box on each of the vertical edges of the rectangle and
extend the rectangle to fit between the stadia rod and the drawn-in vertical
line, which will create a rectangle with dimensions of 10-m x 0.5-m.
15. With the hand tool, use click and drag techniques anywhere within the rectangle to move
it to the lowermost 0.5-m interval above the drawn-in horizontal line
16. Image > Adjust > Threshold [CTRL + SHIFT + 'T']
-'Set' range from '0' to '128'; and 'Black and White'
17. Analyze 1 Analyze Particles
-Use the following settings: '1' / '999999' / '2' / 'Nothing'; and check the following
boxes: 'Display Results' and 'Summarize'
18. In a spreadsheet program, record the total area value from the Summary window
19. Close the Summary window
20. Select 'Reset' on the Threshold window
21. Select the rectangle tool and click in the existing rectangle. Using the drawn in vertical
line and stadia rod as guides, slide the rectangle up 0.5 m
22. Select 'Set' on the Threshold window and set range to '0' to '128'; and 'Black and
White'
23. Analyze 1 Analyze Particles
-Use the following settings: '1' / '999999' / '2' / 'Nothing'; and check the following
boxes: 'Display Results' and 'Summarize'
24. Repeat stepsl8 through 23 until all seven of the 10-m x 0.5-m sections are measured
25. In the Results window, select File 1 Save As 1 (filename.xls)









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BIOGRAPHICAL SKETCH

Destined to be a University of Florida Gator, Matthew Alexander Burgess was born in

1977, in Gainesville, Florida. Growing up, his routine participation in fieldwork with his father,

annual family vacations to Crescent Beach, and summers sailing on the Hudson River and Long

Island Sound helped foster his love of science and the environment. In June 1995, Matthew

graduated near the top of his class from Gainesville High School. After beginning his collegiate

career as a civil engineering major, Matthew soon realized that his desire for working in the

outdoors was stronger than computing integrals, so he changed his major to zoology. In the

summer of 1999, he earned his Bachelor of Science degree from the University of Florida, and

began working full time in the UF Zoology Department where he gained tremendous experience

as a laboratory assistant and international field technician for Drs. Colin and Lauren Chapman.

Matthew then accepted a job in late-2001 as a fisheries biologist for the USGS in Gainesville

where he worked extensively in the panhandle rivers of Florida over the next five years. During

this time, he began his graduate degree in interdisciplinary ecology at UF, and conducted the

planning and field-portions of his thesis research. When his term appointment at USGS ended in

2006, Matthew then worked part-time as an employee of the Florida Program for Shark

Research, at the Florida Museum of Natural History, which kept him in contact with science, and

allowed him time to complete his thesis.





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1 QUANTIFICATION AND ECOLOGIC AL ROLE OF SNAG HABITAT IN THE APALACHICOLA RIVER, FLORIDA By MATTHEW ALEXANDER BURGESS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2008

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2 2008 Matthew Alexander Burgess

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3 To my parents, George and Linda Burgess

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4 ACKNOWLEDGMENTS I thank the members of my graduate comm ittee: Dr. William R. Wise, Dr. Stephen J. Walsh, and Dr. Joann Mossa for their insightful questions and advice, valuable expertise, and patience throughout my prolonged research and wr iting process. Each of them was very accommodating during my efforts towards this degree. I also extend appreciation to my field crew ; boat operator Robert J. Lewis and technician Denise R. Gregoire, for their willingness to assist with the data collectio n involved in this study. This research would not have been possible without their help. I am indebted to Drs. Colin A. and Lauren J. Chapman, formerly of the University of Florida, for their mentorship, and providing the opportunity for inva luable laboratory and international field experience that prepared me for graduate studies. Funding for this research was supported by a grant from the USGS Eastern Region State Partnership Program. Additionall y, the USGS Center for Aquatic Resource Studies, Gainesville, Florida, supplied logistical re sources as well as supplementa ry funding to facilitate the completion of this research. Finally, I express sincere thanks to my family, especially to my parents George and Linda, to my brother Nathan, and to Brandy for thei r encouragement and suppor t during this journey.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........7 LIST OF FIGURES.........................................................................................................................8 LIST OF ABBREVIATIONS.......................................................................................................... 9 ABSTRACT...................................................................................................................................11 CHAPTER 1 INTRODUCTION AND OBJECTIVES................................................................................13 2 APALACHICOLA RIVER, ACF BA SIN, AND THE TRI-STATE WATER CONFLICT.............................................................................................................................16 Apalachicola River and ACF Basin........................................................................................16 Water Use Within the ACF Basin..........................................................................................18 Modifications Within the ACF Basin.....................................................................................19 Tri-State Water Wars Conflict.............................................................................................21 3 CHARACTERIZATION, FLUVIAL EFFE CTS, AND SIGNIFICANCE OF SNAGS.......28 Definition of Snags.................................................................................................................28 Effects of Snags on Energy Flow and Nutrient Cycling.........................................................29 Geomorphic and Hydraulic Effects of Snags.........................................................................31 Snag Decomposition and Deadhead Logging.........................................................................34 Influence of Snags on Aquatic Fauna.....................................................................................36 4 NOVEL METHOD FOR QUANTIFICATI ON OF EXPOSED SNAG MATERIAL IN FLUVIAL SYSTEMS USING DI GITAL IMAGING ANALYSIS......................................40 History of Aquatic Snag Quantification.................................................................................40 Study Design and Methods.....................................................................................................42 Digital Photograph Processing and Analysis..........................................................................44 5 HYDROLOGIC ANALYSES, RESULTS, AND DISCUSSION.........................................57 Hydrologic Analyses............................................................................................................ ..57 Results.....................................................................................................................................58 Discussion...............................................................................................................................60 Recommendations................................................................................................................ ...66

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6 APPENDIX A SAMPLING STATION FIELD DATASHEET.....................................................................83 B GUIDELINES FOR IMAGE OPTIMIZATI ON, PROCESSING, AND ANALYSIS OF DIGITAL PHOTOGRAPHS..................................................................................................84 REFERENCE LIST.......................................................................................................................86 BIOGRAPHICAL SKETCH.........................................................................................................98

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7 LIST OF TABLES Table page 4-1 Location of field sites on the Apalachicola River..............................................................48 4-2 Geomorphic and bank habitat classifi cations of sampling stations on the Apalachicola River.............................................................................................................49 5-1 Equivalent stage, discharge, and eleva tion readings at base line conditions for the Blountstown gage, Apalachicola River..............................................................................68 5-2 Bank habitat classification summary for sa mpling stations on the Apalachicola River....68 5-3 Geomorphic classification summary for sa mpling stations on the Apalachicola River....68 5-4 Bank habitat classification effects on m ean area and relative percentage of total snags submerged................................................................................................................69 5-5 Geomorphic classification effects on mean area and relative percentage of total snags submerged..........................................................................................................................69 5-6 Effects of bank location w ithin a river bend on mean area and relative percentage of total snags submerged........................................................................................................70

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8 LIST OF FIGURES Figure page 2-1 Map of the ACF drainage basin in Florida, Georgia, and Alabama..................................27 4-1 The four major reaches of the Apalachicola River............................................................51 4-2 Map of the Apalachicola River basin and surrounding region..........................................52 4-3 Representative photographs of the four bank habitat types encountered during this study...................................................................................................................................53 4-4 Map of the 55.3-km intensive study reach of the Apalachicola River...............................54 4-5 Example of a digital imag e captured using the methods detailed in this study.................55 4-6 Filtering and processing steps used to pr epare photographs for digital image analysis....56 5-1 Linear mean daily discharge duration curve for the Apalachicola River at the Chattahoochee gage (1929-2006)......................................................................................71 5-2 Logarithmic mean daily discharge durati on curve for the Apalachicola River at the Chattahoochee gage (1929-2006)......................................................................................72 5-3 Chattahoochee gage Blountstown gage equivalency curve............................................73 5-4 Stage-discharge rating curve for the Ap alachicola River at the Blountstown gage (March 2004-March 2006).................................................................................................74 5-5 Stage-discharge hydrograph for the Apal achicola River at the Blountstown gage (March 2004-March 2006).................................................................................................75 5-6 Bank habitat classification effects on mean area of snags submerged for all sampling stations...............................................................................................................................76 5-7 Non-sandbar bank habitat classifciation e ffects on mean area of snags submerged.........77 5-8 Geomorphic classifcation effects on mean area of snags submerged................................78 5-9 Effects of bank location within a river bend on mean area of snags submerged...............79 5-10 Bank habitat classification effects on percen tage of total available snags submerged......80 5-11 Geomorphic classification effects on percen tage of total available snags submerged......81 5-12 Effects of bank location w ithin a river bend on percentage of total available snags submerged..........................................................................................................................82

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9 LIST OF ABBREVIATIONS ACF Apalachicola-Chattahoochee-Flint ACFRBC Apalachicola-Chattahoochee-Flint River Basin Compact ACT Alabama-Coosa-Tallapoosa cfs Cubic feet per second cms Cubic meters per second DEP Department of Environmental Protection FFWCC Florida Fish and Wild life Conservation Commission ft Feet GPS Global positioning system IFIM Instream Flow Incremental Methodology km Kilometer LWD Large woody debris m Meter MB Megabyte MOA Memorandum of Agreement NGVD 29 National Geodetic Vertical Datum of 1929 NOAA National Oceanic and A tmospheric Administration NWFWMD Northwest Florida Water Management District PHABSIM Physical Habitat Simulation PVC Polyvinyl chloride RM River mile TNC The Nature Conservancy UNESCO United Nations Educational, Sc ientific, and Cultural Organization US United States

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10 USACE United States Army Corps of Engineers USCB United States Census Bureau USFWS United States Fish and Wildlife Service USGS United States Geological Survey WGS 84 World Geodetic System of 1984

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11 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science QUANTIFICATION AND ECOLOGIC AL ROLE OF SNAG HABITAT IN THE APALACHICOLA RIVER, FLORIDA By Matthew Alexander Burgess August 2008 Chair: William R. Wise Major: Interdisciplinary Ecology The Apalachicola River has the greatest discharge of any river in the State of Florida, and has one of the largest forested floodplains of any river in the sout heastern US. Rapid urbanization of the upper ACF basin, as well as several extensive droughts in the region have resulted in increased demands for water wit hdrawals and flow regulation for municipal, commercial, and agricultural uses throughout the basin. This has pos itioned the states of Florida, Georgia, and Alabama, along with several fede ral agencies, in a surf ace water allocation and management conflict. Of particular concern are minimum flows and levels required to maintain healthy biotic communities during periods of re gional drought, when water demands are at their highest, and the resource is most limited. Very low flows confine the primarily sandybottomed Apalachicola River to its main channel, where snags serve as the only stable structural habitat fo r the riverine fauna. This study aimed to assess the ecological importance, and quantify the amount of snags submerged in the Apalachicola River as a result of variations in flow regime. Additionally the distributions of snags based on river-bank habitat and geomorphol ogical characteristics were also examined to assess their role in snag habita t availability. Trad itional aquatic snag quantification methods

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12 were not feasible in the exceedingly turbid, high -order Coastal Plain ri ver; therefore, a novel method using digital imaging analysis techniques was developed for analysis. Area and percentage of available snag ha bitat submerged were analyzed at 0.5-m elevations above water level for 60 sampling stations along the Apalachicola River at a relatively-low river discharge. Snag area values gene rated using the novel methods presented in this study were credible for steep sloping bank, gentle sloping bank and dike field habitat types, but were erroneously-elevated for sandbar stations. Snag quantitie s of non-sandbar stations were found to be greatest within the first 1.0 m of ex posed bank for nearly al l sites surveyed, while steep sloping banks typically exhi bited the most uniform vertical snag distribution. In most cases, geomorphic classifications demonstrated no considerable effect on non-sandbar habitat snag distribution; however, the outer banks of ri ver bends exhibited a more balanced vertical distribution of snags than inner ba nks of river bends or along the banks of river straightaways. Limitations and proposed modifications to the digital imaging methods are discussed, and recommendations are provided in support of increased water flows for ecologi cal sustainability in the Apalachicola River.

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13 CHAPTER 1 INTRODUCTION AND OBJECTIVES The Apalachicola River is the State of Florid as largest river by disc harge, and has one of the most extensively forested floodplains of any river in the southeastern Coastal Plain. Home to a diverse fauna, including many th reatened and endangered species the basin is a significant natural resource worthy of conservation efforts. The Apalac hicola River and Bay system is remarkable in that it has remained relatively in tact as urbanization has transformed comparable riverine systems within North America. Theref ore, conservation and rehabilitation efforts that are enacted in the Apalachicola River are currently proactive, rather than reactive; consequently, such efforts tend to be less expensive and have an increased likelihood of success over time. In light of several major droughts, c oncerns have arisen over declining water availability in the river, as well as decreasing fr eshwater inputs into the Apalac hicola Bay estuary, due to rapid population growth and accelerated water cons umption throughout the greater ACF basin. Regulated flows and competing water withdrawal s have generated disputes over states water rights, as well as management of federal reser voirs within the region. This has positioned the states of Florida, Georgia, and Alabama in a wa ter allocation conflict, the eventual consequences of which may jeopardize biological communities that are dependent on the annual flow cycles of the rivers. Of particular concern are low-flow conditions and hab itat availability during critical phases in the ecology of river-dependent biota. Numerous local, state, and federal agenci es are responsible for management and optimization of water resources within the 50,764-km2 ACF basin; consequently, waterallocation disputes within the region have been contentious. As the metropolitan Atlanta area continues to grow and water demands multiply, Georgia-based interest groups have endeavored to store as much surface water as possible in upstream Chattahoochee River reservoirs.

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14 Maintaining equity of water use among consumer s in the upper reaches of the ACF basin with the ecological needs and consumptive use requ irements of downstream users has been challenging. Determining the quantities of reasonable and beneficial river water use varies greatly among stakeholders depe nding upon their location within the ACF basin. In watersheds throughout the world, water managers are begi nning to implement adaptive management techniques to resolve conflicts similar to those exhibited in the ACF basin. Successful adaptive management is achieved by collecting baseline data of critical components, monitoring deviations over time, and making sensible modifications to management plans as environmental conditions change (Richter et al. 2003). Th e monitoring and documentation of rehabilitation efforts in fluvial systems is critical to the su ccess of adaptive manageme nt strategies (Bash and Ryan 2002). With habitat loss considered a primary threat to imperiled species, critical habitats within fluvial ecosystems have been targeted as goals fo r conservation. In the context of rivers, snags are defined as any woody structures, regardless of size, located w ithin the banks of a watercourse. During low water flows, the primarily sandy-bottomed Apalachicola River becomes almost completely confined to its main channel, and as a result snags provide the only stable structural habitat and cover available for its river-based fauna. For years, aquatic ecologists have recognized the importance of snag habitat in maintaining productive ecosystems. However, it was not until fairly recently that focu sed efforts were made to quantify riverine snag habitat. Due to the dynamic natu re of a river system, it is difficu lt to predict rates of wood input and depletion as they vary over space and time. Wallace and Benke (1984) stated that the quantification of riverine wood habitat is essential in assessing past or potential impacts of snag removal on ecosystem processes. Furthermore, determining the amount of available snag

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15 material and its ecological role is vital in unde rstanding how anthropogenic alterations to fluvial systems influence ecosystem success and dynamics. In Florida, very little research has been performed that quantifies the loss of habitat for aquatic fauna wh en snag material is removed from the system, or when woody material is exposed during decreasing ri ver discharges. As minimum flows and levels are discussed with in the management of the ACF basin, it is imperative to know how changes in flow affect snag habitat availability. Scientists in various disciplines have been requested to collect data and provide input to assi st officials in making informed decisions concerning the regulation an d management of water resources within the ACF basin. This study endeavor ed to provide insight into the quantity of aquatic snags submerged in the Apalachicola River at vari ous flow regimes using a novel digital imaging analysis technique. In add ition, the distribution of snags based on river bank habitat and geomorphological characteristics was also examined to indicate their prospective influence on snag habitat availability w ithin the Apalachicola River.

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16 CHAPTER 2 APALACHICOLA RIVER, ACF BASIN, AND THE TRI-STATE WATER CONFLICT Apalachicola River and ACF Basin Two large rivers in the south eastern US, the Chattahoochee and the Flint, converge to form Lake Seminole, a shallow 152-km2 man-made reservoir in south eastern Georgia (Figure 2-1). The Apalachicola River headwaters are created by the tailwater discharge of Lake Seminole at the Jim Woodruff Lock and Dam; a USACE opera ted navigation and hydroelectric generation facility that was completed in 1954. The 805-km long ACF river system drains 50,764 km2 in the states of Florida, Georgia and Alabama, with approximately 13% of the total ACF basin contained within the State of Florida (Light et al. 2006). The Apalachicola River is the largest river in terms of mean annual discharge in Florida, and has the fourth largest discharge of rivers in the southeastern US (Leitman et al. 1991). Located in the Florida panhandle, the Apalachicola River basin drains 6,216 km2 of land within the state, of which about half is drained by th e spring-fed Chipola River, its largest tributary (Leitman et al. 1983). The Apalachicola River is a moderately sinuous, highly turbid, alluvial bed Coastal Plain river that flows 171 km from the Florida-Georgia stat e line to Apalachicola Bay (Light et al. 1998). The ri ver has a relief of 12.5 m from its headwaters at the Jim Woodruff Lock and Dam to its convergence with the Gulf of Mexico; relatively low fo r a river of its length (Meeter et al. 1979). Light et al. (2006) reporte d that the average Apal achicola River discharge from 1929-2004 at the USGS gage near Chattaho ochee, Florida was 21,900 cfs; however, flows were greatly influenced by upstream water management practices in the states of Alabama and Georgia, as well as seasonal vari ations in precipitation. The lowest daily discharge at the Apalachicola River, Chattahoochee gage was 3,900 cfs during a severe drought in November 1987; the highest recorded flow was 291,000 cfs, which occurred during a historic flood in

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17 March 1929 (Light et al. 2006). Av erage annual precipitation in the Apalachicola River basin is 1.42 m, with the driest period typically occurr ing in the months from September through November (Leitman et al. 1991). Unlike most large-river basins of the southeastern US, the floodplain of the Apalachicola River lacks a major urban center, and is consequently sparsely populated. Land uses along the river are primarily forestry or conservation lands, which contributes to the scarcity of development in the region (Leitman et al. 1991). Additional factors c ontributing to the rural nature of the Apalachicola River basin include the relatively depressed economic status of the area, and limited ability for cr oss-river transportation and ex change of goods, as only four highway bridges traverse th e river along its 171-km length. The extensive 454-km2 Apalachicola River floodplain is the largest of all rivers in Florida, and is abundantly forested by many species of cypress, tupelo, and other mixed-bottomland hardwood tree species, of which most have b een logged several times since the year 1870 (Leitman et al. 1983; Elder et al 1988). The ample forests of the Apalachicola River floodplain deposit approximately 3.6 x 105 metric tons of organic mate rial onto the floodplain annually (Elder and Cairns 1982). With one of the highe st computed litter fall rates of any temperate forest, the Apalachicola River ecosystem is reliant on seasonal floods to mobilize, distribute, and recycle the large quantities of organic material and nutrients that a ccumulate on its floodplain. The habitats in and along the Apalachicola Rive r basin contain one of the most species-rich assemblages of flora and fauna in the southeas tern US (Livingston 1984; Leitman et al. 1991; Mitsch and Gosselink 2000). An estimated 1,500 plant species, 450 vertebrate species, and a myriad of invertebrate taxa, in cluding the largest number of freshwater mollusk species in the US, inhabit the Apalachicola River waters hed (Heard 1977; Means 1977; Leitman 1984).

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18 Additionally, many endemic and federally listed endangered or threatened species are found in the basin, making it one of the most significant ecosystems remaining in the US (Myers and Ewel 1990). Water Use Within the ACF Basin Both surface and groundwater resources are used by consumers within the ACF basin. Surface water is used for domestic and commercia l supply, cooling of power plants, hydropower generation, transportation, irrigati on, and recreation. The largest urban center in the basin, the greater Atlanta metropolitan area, draws nearly all of its water supply from the upper reaches of the Chattahoochee River at Lake Lanier, with a portion of the water retu rning to the basin as treated wastewater. As the city of Atlanta continues to grow, most models indicate that another source of water will need to be tapped in the near future, or extreme conservation efforts will need to be enacted in order to maintain the exis ting growth rate of the urban area. The Georgia DEP asserts that its projections for future water supply, relyin g on the Chattahoochee River as a primary water source, are still sound, while th e USACE indicates that the city has already exploited surface water quantities th at equal, or at times have exceeded projections established for the year 2030 (Seabrook 2002). Discussions of alternative water so urces for the Atlanta metropolitan area have included the proposed constr uction of several water retention reservoirs on the upper Flint River, as well as the possibility of inte rbasin water transfers from the ACT, or Tennessee River watersheds (Hoehn 2001). These alte rnatives have failed to materialize due to intense objections from a variety of politic al, environmental, a nd economic interests. Groundwater resources in the ACF basin are primarily used for self-supply domestic drinking wells, industrial and commercial applications, and for cente r-pivot irrigation of agriculture. Large quanti ties of land in rural southwest Geor gia are cultivated for ornamental, vegetable, fruit and nut, forage, and row-crop ag riculture. These large farms are dependent on

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19 groundwater from the Chattahoochee and Flint river watersheds fo r irrigation, and ultimately for economic subsistence. In addition, portions of the extensive Floridan Aquifer are recharged within the ACF basin, therefore intimately linki ng surface and groundwater systems (Elder et al. 1988). Modifications Within the ACF Basin Over the past 200 years, various navigational enhancements have been made in the ACF basin to facilitate the movement of commodities on the river. In the 1820s, the first steamboats began to transport row crops such as corn, cotton, peanuts, and soybeans from cities in Alabama and Georgia to the seaport of Apalachicola, Fl orida (Kirkland 2001). Mu eller (1990) indicates that these early steamers would often encounter sections of the rivers where trees and snags traversed the entire waterway a nd would have to be displaced to allow boat passage. From 1875 to 1998, selective de-snagging operations in the Apalachicola and lower Chattahoochee rivers had removed approximately 334,000 woody obstruc tions including snags, stumps, bushes, overhanging trees, and drift l ogs (T. Hoehn, FFWCC, and S. Leitman, NWFWMD, unpublished data). Ager et al. ( 1985) indicated that snag removal asso ciated with navigational improvements has left much of the main channel Apalachic ola River with a rather unproductive sandy bottom devoid of critical habitat. Since 1956, when selective desnagging was most prevalent, the main channel of the Apalachicola River has actually b ecome shallower and wider, due in part to removal of riparian snags (H. Light, USGS Talla hassee, personal communication). A total of 16 dams and associated reservoirs (13 on the Chat tahoochee River; 3 on the Flint River) have been constructed and maintained upstream of the Ap alachicola River for wate r storage, recreation, flood mitigation, navigation, and hydroelectricity generation (Ager et al. 1985). In 1946, as part of the River and Harbors Act of the previous year, the US Congress authorized the USACE Mobile District to dredge and de-snag a 2.75-m x 30.5-m navigation ch annel through a large

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20 portion of the ACF basin to encourage economic development and promote interstate commerce (Leitman 2005). The constructed navigation channel traversed the entire length of the Apalachicola River, and extended up to Columb us, Georgia and Phoenix City, Alabama on the Chattahoochee River, and Bainbridge, Georgia on the Flint River. A plethora of problems emerged following the completion of the watercour se, but the disposal of large quantities of dredge spoil at unprotected floodplain easement s ites within the banks of the rivers, and the inability to maintain a mandated 2.75-m depth for barge traffic 95% of the year were critical shortfalls revealed over time (Leitman et al. 1991). During the years of operation and maintenance of navigational condi tions within the ACF basin, the quantity of barge traffic failed to meet the utility in which it had been designed and constructed, due primarily to inconsistencies in channel relia bility. Consequently, the majority of freight (sand, gravel, petroleum, and fertilizer) that was routinely tr ansported by barges in other areas of the US ultimately was transported by truck or rail within the ACF basin. Leitman et al. (1991) indicated that in the late 1980s, the unit cost of maintaining the ACF wate rway per ton-mile of freight shipped was the highest of any wa terway in the US, and more than 40 times the national average. In 2003, nine barges used the ACF waterway to transport freight, while it was estimated that US$6.5 million dollars in tax revenue was spent to maintain the channel (Leitman 2005). Navigational channel maintenance in the Apal achicola River was carried out by the USACE until 2005, when the Florida DEP utilized its aut hority under the Clean Wate r Act to rescind the annual river dredging permit. In addition to the extensive dredging and de-s nagging operations implemented to facilitate river transportation, another modification ca lled navigation windows were used on the Apalachicola River beginning in the year 1990. During a navigation window, the USACE would

PAGE 21

21 intermittently discharge large quantities of water from upstream reservoirs for a temporary tenday, to two-week period to allow scheduled ba rge traffic movement during low-water conditions (Leitman et al. 1991). Navigation windows unfort unately altered the natural chemical, physical, and biological components of the floodplain ha bitat and its ecology durin g what were normally low-flow river conditions. Another issue with navigation windows was the dramatic vertical drop in river stage over a short period of time, or fall rate, which would occur at the end of a scheduled navigation window. This was particul arly evident in April 2000, when a navigation window decimated fish populations in the Ap alachicola River by stranding millions of reproducing fish and invertebrates in desi ccating pools on the floodplain (Hoehn 2001). In addition, residents with propert y on upstream reservoirs, especially those on Lake Lanier, objected to navigation windows that visibly lowered water levels consequently leaving their recreational docks high and dry. The pract ice of navigation wi ndows was effectively discontinued with the revocation of the Florid a DEP dredging permit in 2005, and the cessation of commercial navigation. Other Apalachicola River modifications impl emented for enhanced water conveyance and improved river transportation in cluded: 1) the creation of se veral bend easings and meander cutoffs to straighten navigationally difficult natu ral bends in the river; 2) the relocation and removal of rocky shoals in portions of the upper rive r; 3) the periodic rele ase of water stores for flood control and reservoir management; and 4) the installation of river-training dikes to augment channel bed scour and increase downstr eam sediment transport (Leitman et al. 1991; Light et al. 1998). Tri-State Water Wars Conflict As the human population continues to grow, there are increased demands for natural resources with limited availability. One of the greatest public concerns is the accessibility to

PAGE 22

22 freshwater resources, particularly in areas that have already ex ceeded their cap acity to support growth. Officials at multiple levels of government have been assigned the task of maintaining adequate water stores for natural and consumptiv e uses, as well as planning for future water demands. Due to precipitation generated by the warm moist air from the Gulf of Mexico and Atlantic Ocean, southeastern US states have hist orically had sufficient water resources to meet the requirements of their grow ing populations (Leitman et al. 1991). However, concerns have arisen recently in regards to adequate freshwat er availability during seasonal droughts, and as rates of urbanization continue to increase throughout the regi on. Two substantial droughts occurred in the southeastern US during the 1980s that generated significan t consideration to the limits of water availability in the ACF basin, a nd triggered the states to become increasingly acrimonious in regards to their water resources. Th is has placed the states of Alabama, Georgia, and Florida in a surface water a llocation conflict, the eventual consequences of which may jeopardize the ecology of the biota in the ACF basin, as well as in the extensive Apalachicola Bay estuary. In the US, the states have the authority to regulate the use of freshwater within their borders, with the exception of waterways used for navigation, and federally constructed reservoirs. Each state has established its own water laws and mechanisms for modification of water regulations; however, congressional approval is required for any change in interstate water resource allocation. When the US Congress aut horized the development of the ACF waterway for navigation, hydropower, and flood control in 1946, they fundamentally removed state control of surface water in the basin in favor of federa l management. As with any water allocation and management decision in the US, an array of fede ral laws and regulations must be adhered to by the states. While not entirely comprehensive, some of the principal legisl ative acts pertinent to

PAGE 23

23 water management in the ACF basin include: th e Rivers and Harbors Acts of 1945 and 1946, the Rivers and Harbors Flood Control Act of 1944, 1958, and 1962, the Water Resources Act, the Federal Power Act, the Clean Water Act, the Water Quality Control Act, the National Environmental Policy Act, the Endangered Specie s Act, the Migratory Bird Treaty Act, the Marine Mammal Protection Act, th e Fish and Wildlife Coordinati on Act, and the Coastal Zone Management Act (Sherk 2005). The ACF basin is one of the largest freshwat er contributors into the Gulf of Mexico (Livingston 1984). The inputs from the Apalach icola River into Apalachicola Bay deliver significant quantities of valuable detritus and nutrients, as well as beneficially reduce the salinity of the estuary, therefore furnishing an ideal envi ronment for shellfish, shrimp, and crabs. Inputs from the river also control the distribution of e ssential estuarine habitats including seagrass beds, mangrove stands, tidal marshes, and mud flats necessary for productive estuaries (Myers and Ewel 1990). Coastal cities in Franklin and Gulf counties near the mouth of the Apalachicola River rely heavily on the commercial fisherie s of Apalachicola Bay for their existence and livelihood. Apalachicola Bay, a 549-km2 lagoon-and-barrier island comp lex, is regarded as one of the most productive and leas t polluted estuaries in the US, and generates approximately 90% of Floridas oysters, making up about 10% of the United States annual harvest (Livingston 1984; Ruhl 2005; Wang et al. 2008). The salinity pulse generated by the seasonal variation in river flows is critical to the h ealth of oyster populations in the ba y (Livingston et al. 2000). In addition, Apalachicola Bay serves as an importa nt nursery area for many marine species, and produces Floridas third largest shrimp fishery, as well as a robust blue crab fishery (Oesterling and Evink 1977). The Apalachicola Bay estuary has been recognized as a water body worthy of special protection, and is theref ore designated as a UNESCO Int ernational Biosphere Reserve,

PAGE 24

24 a NOAA National Estuarine Research Reserv e, a Florida DEP Aquatic Preserve and Outstanding Florida Water. Analysis of time spent participating in outdoor activities within th e US revealed that Florida trailed only Texas in time devoted to wildlife-related recreation (Struhs and Mainella, 2000). A report by Southwick and Allen (2003) indicated that in 2001, over 40% of Floridians participated in wildlife-related activities, and in addition, over 800,000 visitors came to the state specifically to partake in wildlife related re creation. The Apalachicola River basin is of tremendous economic importance to Florida, an d its floodplain and environs provide abundant opportunity for outdoor recreationa l activities such as fishing, hunting, camping, and hiking. The FFWCC (2008) boasts the state as being the Fishing Capital of the World, emphasizing the values of both recreational and commercial fish ing to the state economy. A combined report by the USFWS and USCB (2002) estimated that in 2001, freshwater fishing in Florida generated US$1.057 billion in retail sales alone. Decreased wa ter flow in the Apalachicola River severely affects fisheries in the river, as well as in Apalachicola Bay, two highly significant economic contributions to the State of Florida. With multiple authorities having control of water resources in the ACF basin, the states of Alabama and Florida along with the USACE quarreled with the State of Georgia in the 1960s and 1970s regarding the opinion that water consumption for urban and agriculture uses within Georgia had superseded the needs of other waterusers and ecosystems to the south and the west. In January 1982, in lieu of imminent litigat ion, a Memorandum of Agreement (MOA) was signed by the governors of the three states, and the USACE, in whic h all four parties agreed to develop a comprehensive basin-wi de water assessment, a naviga tion maintenance plan, a drought management plan, and a water management stra tegy for the ACF watershed (Leitman et al.

PAGE 25

25 1991). The ACF basin MOA attempted to develop a rational and scientific water management policy based on a live and let-live principle. However, after several extensions, the MOA had failed to result in a compromise due to insuffi cient funding, incomplete habitat assessments, withholding of information, threats of new litigation, changes in elected of ficials, and overall differences in opinion regarding definitions of re asonable water use (Della penna 2004). In early 1996, the states of Florida, Georgia, and Alabam a revisited the water a llocation problems, and began drafting an outline to develop an inters tate water compact (Carriker 2000). During their 1997 legislative sessions, the three states pass ed the framework program, the governors signed the measure, and sent the propos al to Washington D.C. for cong ressional approval. The US Congress ratified the Apalachicola-Chattahoo chee-Flint River Basin Compact (ACFRBC) on November 20, 1997, that established an agenda, tim eline, and an interstate basin commission, for developing an agreement to allocate water from the shared river system (Carriker 2000; Sherk 2005). There were many points of contention during the years of negotiations under the ACFRBC, but the fundamental disagreement among the parties concerned whether the State of Georgia would be responsible for delivering onl y the minimum flow of water, regardless of hydrologic conditions, to the Florida border (Snowd en 2005). It seemed as if a stalemate was inevitable; however, on July 22, 2003, after numerous deadline extensions, the states of Florida, Georgia, and Alabama signed a Memorandum of Understanding that indicated that they had reached an agreement in principle regarding va rious terms of a water allocation formula, and committed the states to additional negotiations (Sherk 2005). Unfortunately, little progress was made during talks in the months that followed as the states became increasingly unwilling to make concessions; therefore, on August 31, 2003, without another extension, the ACFRBC terminated (Dellapenna 2004). The expirati on of the ACFRBC officially ended objective

PAGE 26

26 dialogue between the states of Florida, Georgia, and Alabama regarding water allocation in the ACF basin, and has forced all subsequent decisions to be made within the federal court system.

PAGE 27

27 Figure 2-1. Map of the ACF drainage basi n in Florida, Georgia, and Alabama.

PAGE 28

28 CHAPTER 3 CHARACTERIZATION, FLUVIAL EFFE CTS, AND SIGNIFICANCE OF SNAGS Definition of Snags The term snag is used in lotic systems to refer to any woody structure, regardless of size, that lies within the banks of a watercourse. Snags are ubiquitous and integral components of rivers and streams flowing through forested floo dplains. The importance of snags as a habitat component in the ecology of aquatic systems ha s become increasingly recognized during the last 30 years (e.g., Bilby and Likens 1980; Wallace and Benke 1984; Bilby and Ward 1991; Beechie and Sibley 1997). Tree trunks, limbs, branches, l eaves, seeds, bark, and root wads make up the majority of allochthonous input deposited in and along rivers and streams (Hynes 1975; Dolloff and Webster 2000). However, during high wa ter inundation, roots, trunks, and low-hanging limbs of living trees can also serv e as snag habitat for aquatic dwe llers. In the southeastern US, downed woody material can be a result of bank undercutting and erosi on, natural tree fall, forestry operations, fire, flood, lightning, windthrow, disease, in sect infestation, or episodic weather events such as tornadoes and hurricanes. The majority of existing research concerni ng the ecology and fluvial effects of aquatic woody material has been carried out in the hi gh-gradient rivers and streams flowing through timber forests of Australia, as well as thos e in the US Pacific No rthwest (e.g., Anderson and Sedell 1979; Naiman and Sedell 1979; Triska and Cromack 1980; Webb and Erskine 2003; Woldendorp et al. 2004). Some of the earliest studies of the subject compared natural abundances of wood in undisturbe d watersheds with those where wood was deposited as a result of timber harvesting (Warren and Olsen 1964; Bi lby 1981). Other studies focused primarily on woody material of at least 0.1-m in diameter, known as large woody debris (e.g., Keller and Swanson 1979; Bisson et al. 1987; Lienkaempe r and Swanson 1987; MacDonald and Keller

PAGE 29

29 1987). The term large woody debris (LWD) orig inated in the logging i ndustry, and referred to waste products, specifica lly the larger branches, limbs, and unusable trash logs left at a logging site after the profitable st ems were removed (Murphy and Koski 1989). With increased recognition of the significance of woody material in fluvial syst ems, aquatic ecologists have recently suggested that the term LWD be abandoned in favor of the term large wood, thereby eliminating any possible negative connotation associated with the word debris (Gregory et al. 2003). Effects of Snags on Energy Flow and Nutrient Cycling Ecotones are defined as regions of transi tion associated with sharp gradients in environmental factors or in community compos ition (Stiling 1999). Riparian zones such as floodplain forests are vital eco tones characterized by high species diversity, and high productivity, between terrestrial upland and lowland aquatic ecosyst ems. Often depicted in two dimensions, it is imperative to consider th at riparian zones are three-dimensional, biogeochemically open systems in nature; they ar e laterally connected to upslope terrestrial localities, as well as f unctionally connected longitudinally to upstream aquatic locations (Mitsch and Gosselink 2000). By serving as superior f ilters, floodplains are functional and valuable ecotones within fluvial systems. Aquatic snags have a prominent influence on numerous ecosystem processes, including energy budgeting, primary and secondary production, as well as nutrient resource cycling and exchange. The pattern of nutrien t loading, transport, utilizati on, and storage on the floodplain is critical to the survival of healthy riparian communities (Van note et al. 1980; Baldwin and Mitchell 2000). This pattern is regulated by the flood pulse con cept; a periodic flooding of fluvial systems that provides a vital ecological interaction between the river channel and its floodplain (Junk et al. 1989; Benke 2001). Organic input is an e ssential component of the energy

PAGE 30

30 budget of aquatic habitats (Benke and Wallace 1990) The bulk of riverine animal biomass is derived from production of organic matter that occurs on the floodplai n (Junk et al. 1989). During floods, a substantial flux of organic matter and nutrients are flus hed off the floodplain where they either accumulate behind snags, or are deposited into the main river channel (Elder et al. 1988; Benke and Wallace 1990). Snags further in fluence the routing of sediments, particulate organic matter, and nutrients by creating areas of low shear stress and low water velocity, facilitating deposition of suspended materials from the water (Wallerstein 2003). Seasonal flooding also influences soil oxygen levels on the floodplain, whereby transitions from aerobic to anaerobic conditions aff ect rates of organic matter decom position and nutrient mineralization. Floodplains act as nutrient sinks for lateral runoff from uplands but also serve as nutrient transformers for downstream wa ter flows (Mitsch and Gosselink 2000). By trapping particulate organic matter, snags help to retain potential nu trient and energy resource s from washing rapidly downriver, as well as serve as a long-term sour ce of nutrient loading for the floodplain (Wallace and Benke 1984). Critical linkages exist between natural flow va riations and ecologica l fitness of fluvial systems. Alterations of the timing, magnitude, and duration of extreme flows in rivers are significant, particularly in an thropogenically controlled wate rsheds (Gibson et al. 2005). Artificial adjustments of flow regime have cascading effects on the chemical, physical, and biological components of a river. Lower than normal riverine flows: 1) reduce the wetted perimeter of a waterway that decreases ripari an habitat availability; 2) alter water-quality parameters by reducing dilution effects; and 3) limit connectiv ity between the river and its floodplain (Light et al. 1998). In creasing flows and rising water leve ls can be critical biological cues for riverine organisms to migrate upor downs tream, or for others to move from habitats in

PAGE 31

31 the main river channel to those on the floodplain where food resources and structure are readily abundant for reproduction (Ross and Baker 1983; Li ght et al. 1998; Postel and Richter 2003). Variations in peak flow timing and magnitude can disrupt the mobilization of organic matter and nutrients from the floodplain, alter the rates of sediment erosion and deposition, and significantly influence the migratory and recruitment su ccess of aquatic sp ecies (Knighton 1998). Geomorphic and Hydraulic Effects of Snags Two major factors that govern channel mor phology are sediment suppl y and temporal flow variability, both of which can be influenced by th e presence or absence of snags. Due to their irregular shapes and sizes, snags can accumulate upon each other and develop into hazards for river transportation, as well as accumulate floating litter. Therefore, snags have been removed from rivers for many years in an attempt to cr eate waterways suitable fo r navigation, as well as for aesthetic purposes. Other justifications em ployed for the removal of snags from rivers include: 1) to eliminate barriers to fish migratio n; 2) to reduce the risk of downstream bridge piling and navigational marker damage; 3) to re duce rates of river bank erosion; and 4) to improve flood mitigation efforts (Harmon et al. 1986; Bisson et al. 1987; Gippel et al. 1992, Diehl and Bryan 1993). It was often believed that removal of snags from rivers was a good course of action in flood preventi on; however, snag removal tends to increases stream velocity, decreases riparian vegetation quantity, and incr eases channel bed scouring and incision that promotes bank failure as sediment is carried downstream (Zimmerman et al. 1967; Wilson 1973; MacDonald and Keller 1987; Erskine 1994). Increas ed bank stability generated by snag material is especially important along the outside bank of meander bends where the channel tends to migrate laterally (Bisson et al 1987; Diehl and Bryan 1993). Conserving the snag material that naturally accumulates in the ripa rian areas of fluvial systems helps to fortify the channel banks, trap sediment in natural levees, increase structur al complexity and habitat, as well as reduce the

PAGE 32

32 mean velocity of water in the channel and on th e floodplain during high-water events (Dez et al. 2001). The most conspicuous effects of snags in rivers and streams are physical: wood can influence channel shape, sedime nt storage and erosion rates, and the path of water flow. Downed wood on the floodplain that is large enough to be immobile during floods can have a significant influence on morphology, geometry, and profile of the floodplain (Braudrick et al. 1997). When a log lies parallel to the flow of a floodplain sl ough, the streambed may be eroded in front of the log forming a lateral scour pool. Snags can divert the mainstream flow of a slough from one side of the channel to the other, fo rming a backwater pool. Beechie and Sibley (1997) found that pool area and pool spacing varied gr eatly with channel widt h and slope in streams containing snags. Pools formed by wood on the floodplain provide essential habitat and complexity to the entire bionetwork (Bilby 1981; Dolloff 1994; Baillie and Davies 2002). Pool formation is just one of the physical effect s that snags can have on fluvial systems. Another physical effect of snags in fluvial sy stems is bank armoring, or flow divergence. Snag material can divert stream flow away from a bank, therefore lim iting downstream shoreline erosion (Gippel 1995; Berg et al 1998). Snags can also divert water into a bank, causing bank undercutting and stream widening. Conversely, wood lying alongside and parallel to the bank can prevent bank erosion (Cherry and Beschta 1989). Snags can al so shift water flow from one side of a channel to the other, divert flow from the main channel to a side channel, or even force the creation of alternate channels. Channel migr ation can also create point bars of alluvial sediments, oxbow lakes, and backwater swamps. The influence of snags on formation of these local hydrologic features is extens ive; however, the impact of huma ns on fluvial systems tends to

PAGE 33

33 constrain channel processes and linearizes corridors, while natural hydrology and geomorphology tends to create heterogeneity of these habitats. Zones of erosion, storage and transport, and deposition are defined along the course of a river system based on its geomorphology, hydrol ogy, and physical processes. Snags can influence the deposition patterns of sediments in rivers and on their floodplains. Water may be forced to go around, over, under, or along a snag, resu lting in a range of water velocities. Fine sediments such as silts and clays will accumulate where the water ve locity is lowest, such as in backwater pools, whereas only coarse sediments remain stationary in faster flows. The presence of snags in rivers can reduce the scouring eff ect of high water flow, and aid in sediment deposition (Baillie and Davies 2002). Rootwa ds may act as streambank anchors against high flows during floods, reducing soil loss to erosi on and downstream sedimentation. In relatively low-gradient floodplains, snags can form logjam s which can increase the immediate water level and inundate large areas that do not normally experience regular flooding. Often these temporary floods deposit considerable amounts of suspended materials (Ward and Aumen 1986). Snags are therefore consider ed an important factor in fluvial sediment deposition. Ironically, in many locations around the worl d substantial amounts of time and money are invested in redepositing snags into rivers and streams that were previ ously cleared (Gore 1985; Andrus et al. 1988; Osborne and Koviac 1993). Determining where snags should be reintroduced, how they should be oriented, and th e quantities of woody mate rial that should be returned vary by watershed (Hrodey and Sutt on 2008). Pigay (2003), Swanson (2003), and Reich et al. (2003) propose various frameworks for wood input and redistribution based on specific parameters of individual fluvial systems. The challenge for river managers is to find and

PAGE 34

34 establish a reasonable balance between the effe cts of bank erosion and navigational concerns with the ecological benefits of leaving snags in rive rs (Hilderbrand et al. 1998). Snag Decomposition and Deadhead Logging Most stream inhabiting organisms do not feed directly on snags, but the presence or absence of these resources can have a significant influence on food availability and the diversity of fauna in the ecosystem. Helfman (2007) indicat ed that in low-gradient coastal rivers, snags are the most biologically rich habitat available, and can produce four times as much prey than mud or sand habitats alone. The ecological li nk between energy availability and production of higher trophic levels has been well documented (e.g., Myers 1977; Benke et al. 1984; Mattraw and Elder 1984; Kemp and Boynton 2004; Kiffney a nd Roni 2007). Leaves and small twigs that fall into the stream are an important food sour ce for microbes, bacteria, and many species of aquatic invertebrates (Bilby and Likens 1980). La rge, stable snags trap smaller pieces of wood, that in turn, capture leaves and other organic detritus creating nutrient reservoirs on which organisms feed (Bilby 1981). A 1984 study by Wall ace and Benke determined that 75% of the organic matter stored in a South Carolina stream and floodplain system was directly associated with snag material. Wood on the floodplain loca ted above existing water levels contributes to available refugia at higher wate r levels (Benke et al. 1985). Logs suspended above the channel can be colonized by a variety of plants and anim als, creating a lush microcosm above the water (Brown 2002). Eventually, the suspended log will enter the waterway and add to its wood supply. The methods and rates of dead wood decompos ition in terrestrial and aquatic habitats are remarkably different. Decay of dead woody material in terrestrial systems is primarily driven by fungi, and rate of decomposition is rapid due to an abundance of available atmospheric oxygen (Rayner and Todd 1979; Elder and Cairns 1982; Baker et al. 1983). In aquatic systems however,

PAGE 35

35 decomposition of snags is achieved primarily by single-celled bacteria, namely actinomycetes (Aumen et al. 1983), and rate of decompositi on is determined by microbial quantity and detritivore palatability (Boling et al. 1975; Bilby 2003). Bacteria and algae living on the surfaces of submerged snags form a slimy coating ca lled biofilm, which becomes food for other microscopic biota (Robertson et al. 2001). Biofilms on snags can also beneficially withdraw nutrients from water flowing by, helping to regulate potentially harmful algal blooms and downstream macrophyte growth, as well as conserve potential energy resources (Tank and Webster 1998). With the exception of the out ermost layers of submerged dead wood, the dissolved oxygen concentrations throughout the core of a snag are very low; therefore, breakdown of its structural components is much slower than in a te rrestrial system (e.g., Anderson et al. 1978; Whiles and Wallace 1997; Bilby et al. 1999; Spnhoff and Meyer 2004). Old-growth longleaf pine a nd cypress forests were exte nsively logged throughout the southeastern US in the 19th and early 20th centuries to support worldwide demands for lumber. Typically, felled timbers would be floated down ri vers to coastal sawmills for conversion into useable boards. It is estimated that five to ten percent of the dense heartwood timbers became waterlogged and sank on their attempted journey to the mill sites (Dye and Frydenborg 1999). In coastal rivers and streams of the southeastern US where clay s, mud, and sand constitute the primary bottom sediments, large wood can become partially or entirely buried in anoxic conditions, and is therefore increasingly resistan t to decay (Mitsch and Gosselink 2000). These submerged deadhead logs can remain on the river bottom for hundreds of years, and are extremely valuable in the commercial wood-produc ts industry due to their tight grain pattern and unique wood colors. Individual high-grade deadh ead logs can fetch three to five thousand US dollars apiece, and generate lumber that is upwar ds of ten times more va luable than conventional

PAGE 36

36 wood (Dye and Frydenborg 1999). The high-end wood produced from old-growth deadhead logs are utilized primarily in the fu rniture, paneling, and flooring industries. Removing deadhead logs from rivers has cr eated legal disputes between log salvaging operations and environmental groups. Log salv aging representatives argue that the loggedtimbers were not present in rivers in the fi rst place, and should therefore be removed. Environmental and cultural interests assert that deadhead logs have become integral parts of rivers over time, and should consequently remain undisturbed. Management of these nonrenewable submerged resources became increasingl y necessary, so several US states prohibited underwater deadhead logging operati ons while environmental studies were conducted to evaluate potential physical, chemical, a nd biological impacts of deadhead log removal. These studies generated contradicting results, and consequently many states ha ve developed an annual feebased permitting process to manage log removal quantities, and to monitor impacts of deadhead removal while additional research is conducted. Influence of Snags on Aquatic Fauna The presence of snags increases the quantity a nd diversity of availabl e habitats for aquaticdwelling organisms. Snags generate effectiv e habitat heterogeneity due to their complex structure that in turn provides a variety of nooks and crannies suitable for refuge. Snags are especially important in altered or degraded rivers, as well as in rivers where other more stable bottom substrates, such as rock or gravel, are absent. Macroinvertebrates such as insects, mollusks, crustaceans, and worms are highly sensitive to changes in their environs; therefore, their population levels are often investigated and monitored to assess the overall he alth and biodiversity of aquatic ecosystems. Due to this, many scientific studies have been conducted through th e years to examine invertebrate use of snag habitat (e.g., Nilsen and Larimore 1973; Anderson et al. 1978; Molles 1982; Benke et al. 1984;

PAGE 37

37 Smock et al. 1985; Benke et al. 1985; Thorp et al. 1985; Lemly and Hilderbrand 2000; Braccia and Batzer 2001). Most of these studies have shown that a greater number of individuals and a greater diversity of invertebrate species are found in fluvial reaches containing snags in comparison to similar reaches without snags. A quatic insects utilize snag habitats for feeding (whether scraping, grazing, or filtering), resting, predator avoidance, egg deposition, and for pupation and emergence (Anderson et al. 1978, Benke et al. 1984; Drury and Kelso 2000). In a lower Coastal Plain river in the southeastern US Benke et al. (1984) found that the diversity of invertebrate taxa on snags was much greater than that of sand or mud; however, snag habitat made up only 6% of the available substrate. Ager et al. (1985) determined that in a southeastern US fluvial system, snag habitat had the highest density of macroinvertebrates when compared to all other potentially available be nthic substrates. In large sa ndy bottom rivers, like those found in the Coastal Plain of the southeastern US, snag s are extremely vital as they provided the only stable periphyton habitat for many invertebrates. The unionid mussel fauna of the southeastern US was at one time the most species-rich in the world, and the ACF basin is considered to be the center of unionid mussel speciation (Brim Box and Williams 2000). However, modern AC F mussel assemblages have experienced an abrupt decline, perhaps by as much as 50%, as a result of habitat degradation, pollution, impoundment, and introduction of exotic species (Williams et al. 1993; Golladay et al. 2004). Chastain et al. (2006) indicated that the Flint River had 76% of its historical mussel species remaining, while Brim Box and Williams (2000) re ported that only remnant and isolated unionid populations remain in the Chattahoochee River. Of the remaining ACF mussel assemblages, 64% of the species are categorized as either endangered, threaten ed, or of special concern (Brim Box and Williams 2000). Unionid reproduction is unique in that it is reliant on specific fish

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38 species to serve as hosts for their specialized larvae; successful mussel reproduction is therefore dependent on the spawning and rearing success of th ese critical fish species. Freshwater mussels are an important component of Coastal Plain fluvial ecosystems as they filter nutrients from the water and accumulate potentially harmful chemicals and metals into their bodies and shells (Hart and Fuller 1974). Decreased water flows in the ACF basin leaves unionid mussel populations vulnerable to extirpation which could ultimatel y have impacts on water-quality within the watershed. An increasing number of studies have been pub lished recently regarding snags as essential fish habitat. Analogous to the structural cove r provided by coral reefs in marine ecosystems, snags serve as a feeding, spawning, and nursery site for fish in fluvial systems. Submerged snags are especially si gnificant in shifting sa ndy-bottomed lotic systems, where they provide niche variation, velocity refuge, and often the only available stab le substrate and cover (Wallace and Benke 1984; Braccia and Batzer 2001). Benke et al. (1984) found that severa l species of game fish foraged exclusively on invertebrates associated with snag material, and Benke et al. (1985) reported that major warm-water fishes in a southeastern US Coastal Plain stream obtained at least 60% of their prey bioma ss entirely from snag habitat. A nglers have historically been the greatest advocates for snags in fluvial systems, as they have long recognized that snags serve as effective fish aggregation structures (Lobb and Orth 1991). Ager et al (1985) indicated that river habitat containing snags was found to have twice as many game fish species as similar habitats without snags. Altera tion of snag abundance can also influence the distribution of apex predators and prey. Studies by Angermeier and Karr (1984) and Peterson and Bayley (1993) determined that the removal of snags from streams altered the predator-prey balance by effectively reducing the number of apex predators, and increasing the number of smaller fish

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39 species. In high gradient st reams, fish often congregate in dammed plunge pools created by snags and large wood as an escape from high wate r velocities, and as refuge from predators (Angermier and Karr 1984). Reduction in riverine snag quantity and distribution can severely limit the quantity of food resources and protec tive cover available to fish, two essential components of healthy fish populations. Invertebrates and fish are not the only fauna th at use snags as habitat in fluvial systems. Snags emerging from a river provide a preferred site for resting, foraging, and roosting for many aquatic turtle, snake, and bird species. Sn ags on the floodplain can be valuable habitat for herpetofauna such as salamanders, skinks, lizards, frogs and toads, as well as for mammalian predators such as rat, raccoon, opossum, and armadi llo that often forage at floodplain snags sites (Means 1977). Next to humans, th e most influential c ontributor to snag ha bitat abundance is the beaver, whose impoundments and lodges constructed from wood obtained on floodplains can significantly alter stream hydrology, and introduce large quan tities of snag mate rial into fluvial systems (McTaggart and Nelson 2003; Pollock et al. 2003).

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40 CHAPTER 4 NOVEL METHOD FOR QUANTIFICATION OF EXPOSED SNAG MATERIAL IN FLUVIAL SYSTEMS USING DI GITAL IMAGING ANALYSIS History of Aquatic Snag Quantification To assess the potential importance of snags as habitat for aquatic fauna, it is necessary to quantify the woody material in lo tic systems. Historically, es timates of snag abundance and density in freshwater aquatic systems were ge nerated as a byproduct of other biological or hydrologic investigations, and it was not until the late-1970s that st udies began to focus specifically on the quantification of aquatic wood (Gippel et al. 1996). Using methods originated in the forestry industry for calculation of resi dual logging waste, ecologists looked to enhance existing techniques for the quantif ication of aquatic wood (e.g. A nderson et al. 1978; Triska and Cromack 1980; Wallace and Benke 1984; Benke and Wallace 1990). The line intersect technique developed by Warren and Olsen (1964) and further modified by Van Wagner (1968), Bailey (1970), and de Vries (1974) was a practical method used to estimate the quantity of wood lying on or near the ground by si mply obtaining the diameters of all woody stems that crossed a hypothetical sample line. Applied to fluvial syst ems, the line-intersect technique was reasonably effective for rapid assessment of large diamet er wood exposed along the banks, or submerged in clear water, low-order reaches. In turbid, tannic, or high-order fluvial systems, however, the line-intersect technique was not a feasible option for quantifi cation of submerged wood. In addition, the method was found to be significantly inaccurate at estimating quantities of small diameter woody material, and did not reveal mu ch information about the distribution of wood along the sample transect (Gippel et al. 1996). Due to the dynamic nature of fluvial system s, it is difficult to predict rates of wood recruitment and depletion over space and time. In addition to natural vari ations in river stage and downstream snag transport, anthropogenic in fluences such as forestry operations, and

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41 deadhead logging perturb total wood volumes in fluvi al systems. Due to the limitations of the line-intersect method for wood quantification in turbid or lengthy rive r reaches, alternative methods such as low-level aerial surveys and side-scanning sonar have been used (Hamilton and Bergersen 1984). Unfortunately, these techniques have substantial drawbacks as well. Aerial surveys of river banks: 1) are generally expe nsive; 2) tend to be obscured by overhanging vegetation; and 3) do not provide an accurate vertical scale for th e distribution of snags above the waterline (Fitzgerald et al. 2006). Side-scanning multi-beam sonar can be used to profile submerged snags even in turbid water. However, the technique: 1) is exclusively limited to the mapping of underwater material; 2) tends to perform better in deeper water with a uniform bottom profile; and 3) is susceptible to failure when the boat-towed sonar transducer becomes ensnared in the woody material that it is mapping (Flug et al. 1998). In situations where stream flow was a limiting factor in the availability of aquatic habitat resources, an incremental methodology calle d IFIM, and a model dubbed PHABSIM were developed in the 1970s by a collaboration of fede ral and state agencies to predict changes in physical microhabitat associated with modifi cations in hydraulic flow regime (Bovee 1982, 1986). One of the most commonly utilized outputs from the IFIM and the PHABSIM model is an index of weighted usable ar ea that aids water managers in negotiating low-flow targets and assessments of critical habitat availability (M ilhaus et al. 1989). The IFIM and the PHABSIM model are challenging to use because they entail multiple pathways and many steps that are based on user-level understanding of the problem at hand, and they require integrating existing long-term streamflow datasets of flow regimes, surface elevations, and water velocities, which are not always available (Milhau s et al. 1984). In addition, the IFIM and the PHABSIM model are limiting because: 1) their final outputs vary due to disparities in user-defined indices of

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42 channel characteristics; 2) the methodology and m odel have several significant assumptions that are difficult to overcome; a nd 3) the methodology and model do not account for critical waterquality or energy-input compone nts desired in the interest of aquatic ecology (Milhaus 1999). Very little research, espe cially in Florida, has been done to quantify the lo ss of habitat for aquatic fauna when snag material is exposed above water level during low-water conditions. Several studies by Ray (1999a-d) discussed the ec ological and morphological significance of old growth deadhead logs as habita t for macroinvertebrates in seve ral Florida panhandle rivers and streams, while a report by Estevez and Sprinke l (2000) examined the distribution and abundance of wood in the Santa Fe and lower Suwannee Rive rs based on water level fluctuations. Wood quantification techni ques used in these surveys were not feasible options for the conditions present in the Apalachicola River. Therefore it became apparent that another method of snag habitat quantification wo uld need to be developed, perhaps using digital image analysis. Digital image analysis is a computer-based te chnique used to genera te numerical data by examining detailed properties of an image. Many scientific disciplines have turned to digital image analysis due to its widesp read applicability, ease of use, and low cost. By utilizing a variety of methods and procedur es, computers are able to accur ately, dependably, and repeatedly identify and measure properties of an image that the human eye is unable to quantify. Historical limitations of using digital image analysis were primarily rooted in low image resolutions and slow computer processors; however, these rest rictions have been surpassed by increasingly affordable advances in technology. In many sc ientific fields, digital image analysis has developed into an ideal method for ra pid and inexpensive data analysis. Study Design and Methods Ager et al. (1987) defined six bank habita t types for the Apalachicola River based on steepness of the riverbank, substrate type, and presence of submerged aquatic vegetation. Steep

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43 sloping banks (bank angle greater than or equal to 45 from horizontal), gentle sloping banks (bank angle less than 45 from horizontal), and sandbar habitats comprised 92.6% of the Apalachicola River banks (41.7%, 27.0%, and 23.9% respectively), while the remaining 7.4% of bank habitats were classified as dike fields (2.3%), rock (2.1%), and submerged aquatic vegetation (3.0%) (Ager et al. 1987). Rock habi tats were found exclusively in the uppermost portion of the Apalachicola River, while submer ged aquatic vegetation wa s found exclusively in the tidal reaches of the river. Four major reaches in the Apalachicola Rive r were defined by Leitman (1984) based on differences in their geomorphic and physiographi c characteristics: A) upper reach, B) middle reach, C) non-tidal lower reach, and D) tidal lower reach (Figure 4-1) For this study, an intensive study reach of 55.3 km was selected within the middle and non-tidal lower reach portions of the Apalachicola River; from just downstream of Estiffanulga Landing (RM 62.4) to just upstream of the confluence of the Apalach icola River with the Chipola River (RM 28.1) (Figure 4-2). This particular study reach was chos en based on its incorporation of four (steep banks, gentle banks, sandbars, and dike fields) of the six bank habitat type s delineated by Ager et al. (1987) (Figure 4-3). Within the study reach, 30 sites were designated equidistantly from each other ( 2.0 km by river) using USGS 7.5-minute topogr aphic quadrangle maps (Figure 4-4). Specific details regarding the location of the indi vidual study sites are found in Table 4-1. At each of the 30 sites, both the leftand right-d escending banks were evaluated for a total of 60 sampling stations. Geomorphic and bank habitat classifications of the sampling stations are summarized in Table 4-2. In the field, a Garmin GPS III Plus (ver. 2.06 ) navigation unit was used to position the survey crew at each of the 30 pre-selected river study sites. Each sampling station consisted of

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44 four semi-contiguous 10-m long segments of ri verbank. Every effort was made to have concurrent 10-m long segments for photography ; however, certain segments were shifted upstream slightly (typically no more than 5 m) due to site topography. A Bushnell Yardage Pro laser rangefinder was used by the boat oper ator to position a boat 35to 40-m from the shoreline, bow directed upstream, into the current. From this position on the water, each of the 10-m segments of shoreline was digitally photogr aphed three to five times in repetition by the photographer on the boat. In each photograph, a ve rtical reference scale was attained by having a field technician stand on the riverbank holding a stadia rod perpendicular to the water surface at the point where the bank and wa ter converge. The stadia rod used for vertical reference was a 3.5-m x 0.05-m PVC pipe having 0.5-m black and white gradations along its length. Photographs were taken of the ri ver shoreline from the existing water level to at least bankfull elevation or higher, with the st adia rod held vertically at the downstream end of each 10-m long segment (Figure 4-5). Field notes in regards to specific parameters for each sampling station were recorded on custom generated sn ag abundance datasheets (Appendix A). Color photographic images were captured using a Nikon Coolpix E5600 (ver. 1.0) handheld digital camera. The normal imagi ng mode setting was used, with automatic focus and white balance, neutral exposure, single imag e capture, and standard color, which generated photographs with a pixel resolution of 2592 x 1944. Digital photographs were saved on Secure Digital (SD) memory cards in .jpg (24 bit) fo rmat. The file size for each digital image was approximately 1.0 MB. Digital Photograph Processing and Analysis All digital photographs were uploade d from the SD memory cards onto a Microsoft Windows-based desktop computer where they were appropriately labeled a nd catalogued into a photographic database. For each of the 10-m shoreline segments photographed, a single

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45 representative photograph was selected from the th ree to five images captured in the field. The representative photograph was chosen based on its optimization of the following seven criteria: 1) image clarity; 2) focus; 3) resolution; 4) brightness; 5) image-shor eline parallelism; 6) shoreline-stadia rod perpendicularity; and 7) ab sence of avian or flyi ng-insect interference. Segment photographs were optimized for digital image analysis using Adobe Photoshop 7.0 ( 2002 Adobe Systems, Inc.) photo editing software. Original color images (Figure 4-6A), were inverted to form a phot ographic negative and then converted to a grayscale format consisting of 256 shades of gray (Figure 4-6B). Grayscale images were reduced in size, and saved as uncompressed tagged image files (.tif). Calculation of snag area was accomplished using Image J (ver. 1.35s) image processing and analysis software. Image J is a Java-based computer prog ram developed at the US National Institutes of Health that runs in most major operating systems and is available free of charge as public domain software (Rasband 2002). By converting individual picture elements (pixels) to a unit of measurement, Image J is capable of calculating areas of irregular-shaped objects using user-defined scales. Each grayscale .tif image file was opened in Image J for digital image analysis. Measurement scale was reset for each image by inst ructing the program to count the number of pixels necessary to traverse 1.0 m on the stadia rod ( n 110). After the scale for a photograph was defined, a 10.0-m horizontal line was stretched out digitally along the water surface using the line and measurement tools, and ultima tely sketched on the photograph using the draw command. Utilizing the box tool, a 0.5-m tall x 10.0-m long rectangle block was expanded adjacent to the digitally sketched horizontal line, and the vertical stadia rod as a 5.0-m2 measurement boundary for calculation. The entire image was then filtered in Image J with a

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46 simple thresholding algorithm at a threshold pi xel brightness value of 128 to produce a binary image suitable for analysis (Ridler and Calvar d, 1978) (Figure 4-6C). The thresholding procedure enhanced the snag material from its surroundings by converting all the grayscale pixels in the image to either a black or white pixel depending on its gr ayscale brightness value (0-128=black pixel; 129-256=white pixel). Within the 5.0-m2 measurement block, Image J counted all of the bl ack pixels using the analyze particles comma nd, and generated an area (m2) value based on the previously defined measurement scale. The measurement block wa s then moved 0.5 m up the stadia rod using the hand tool, and the measurement process was repeated until all seven of the 5.0-m2 blocks had been measured (Figure 4-6D). Area values generated by Image J were recorded into Microsoft Office Excel (ver. 2003 SP2) spreadsheets for data manage ment and further analyses. Detailed guidelines for digital photograph optimization, processing, and analysis te chniques utilized in this study are contained in Appendix B. Prior to actual data collection on the Apalach icola River, two preliminary studies were conducted to assess the repeatabil ity, sensitivity, and logistics of using the proposed digital image analysis techniques for snag area quan tification. In the fi rst study, a 0.5-m x 0.5-m Plexiglas square was constructed, painted white, and subsequently framed with a 0.025-m wide black border as a sample object of known area. The test square was attached 1.75 m above ground level on a vertical pole, with one edge of the square parallel to the ground surface. A 100.0-m measuring tape was extended outward from the pole, and surv ey flags were inserted into the ground at 10.0-m increments. Three un-zoomed phot ographs of the test square were taken at each 10.0-m distance away from the pole. The test square was then rotated 45 and the photographic procedure was repeated. All photogra phs were then analyzed using the digital

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47 image analysis techniques to de termine errors associated with variation in horizontal distance and target orientation. The results of the firs t pilot study indicated that horizontal distances within 80.0-m of the target object produced area values with less than 5.0% error, while distances within 50.0-m of the target produced less than 2.0% error. Orientation of the target was found to have no measurable effect on cal culated areas using the proposed methods. A second pilot study was conducted on the Suwann ee River to address l ogistical details of the field-based methods. During this trial, a fi eld assistant was positi oned along the river shore with the 3.5-m stadia rod, and photographs were taken at various dist ances (~15.0-60.0 m) from the bank to assess variations in snag detail. Additionally, 10.0to 25.0-m lengths of shoreline were photographed at a distance of 40.0-m from th e bank to evaluate the length of shoreline necessary to generate abundant ar ea data within each of the 0.5-m el evations above water level. Results of the second study indicated that photography at a dist ance of 40.0-m from the shore generated ample resolution of even the sma llest snags along the bank, and 10.0-m lengths of shoreline produced sufficient area data for analyses.

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48 Table 4-1. River mile and geoc oordinates of field sites locate d within the 55.3-km intensive study reach of the Apalachicola River. River mile is the approximate distance upstream from the mouth of the river determined by USGS topographic maps. GPS positions are based on the WGS 84 datum. Field Site Number River Mile Latitude Longitude 1 62.4 30 18 22.53 N 85 02 59.08 W 2 61.1 30 18 00.90 N 85 03 25.74 W 3 59.9 30 17 08.06 N 85 03 25.74 W 4 58.8 30 16 20.94 N 85 03 41.66 W 5 57.5 30 15 32.89 N 85 03 42.74 W 6 56.3 30 14 54.27 N 85 04 19.94 W 7 55.2 30 14 23.99 N 85 04 46.05 W 8 54.0 30 13 41.19 N 85 04 57.32 W 9 52.8 30 13 14.78 N 85 05 25.93 W 10 51.7 30 12 41.40 N 85 06 03.12 W 11 50.5 30 12 49.13 N 85 06 40.85 W 12 49.3 30 12 28.43 N 85 07 11.06 W 13 48.1 30 11 43.16 N 85 07 19.82 W 14 46.9 30 10 52.64 N 85 07 57.00 W 15 45.9 30 10 07.22 N 85 08 23.99 W 16 44.6 30 09 31.99 N 85 07 54.86 W 17 43.4 30 08 36.99 N 85 08 14.29 W 18 42.3 30 08 08.41 N 85 08 16.97 W 19 41.4 30 07 19.90 N 85 08 39.48 W 20 40.0 30 06 55.95 N 85 07 51.97 W 21 38.7 30 06 32.16 N 85 08 20.72 W 22 37.7 30 06 22.89 N 85 08 51.80 W 23 36.5 30 05 42.88 N 85 09 08.76 W 24 35.4 30 05 16.61 N 85 08 20.01 W 25 34.3 30 04 18.37 N 85 08 18.76 W 26 33.1 30 03 38.04 N 85 08 11.80 W 27 31.9 30 02 36.71 N 85 08 09.12 W 28 30.7 30 01 50.05 N 85 07 20.40 W 29 29.4 30 01 26.11 N 85 06 26.86 W 30 28.1 30 00 56.13 N 85 05 37.79 W

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49 Table 4-2. Geomorphic and bank ha bitat classifications of sampli ng stations within the 55.3-km intensive study reach of the Apalachicola Ri ver. Geomorphic classifications derived from USGS topographic maps, and bank habita t classifications based on Ager et al. (1987). Station Number Left or Right Descending Bank Geomorphic Classification If a Bend, Inner or Outer Bank Bank Habitat Classification 1A Left Bank Straightaway Gentle Bank 1B Right Bank Straightaway Steep Bank 2A Left Bank Straightaway Gentle Bank 2B Right Bank Straightaway Gentle Bank 3A Left Bank Exiting Bend Outer Bank Steep Bank 3B Right Bank Exiting Bend Inner Bank Gentle Bank 4A Left Bank Straightaway Steep Bank 4B Right Bank Straightaway Gentle Bank 5A Left Bank Exiting Bend Outer Bank Steep Bank 5B Right Bank Exiting Bend Inner Bank Sandbar 6A Left Bank Bend Apex Outer Bank Gentle Bank 6B Right Bank Bend Apex Inner Bank Sandbar 7A Left Bank Exiting Bend Outer Bank Steep Bank 7B Right Bank Exiting Bend Inner Bank Gentle Bank 8A Left Bank Exiting Bend Outer Bank Steep Bank 8B Right Bank Exiting Bend Inner Bank Gentle Bank 9A Left Bank Bend Apex Outer Bank Steep Bank 9B Right Bank Bend Apex Inner Bank Sandbar 10A Left Bank Bend Apex Outer Bank Steep Bank 10B Right Bank Bend Apex Inner Bank Sandbar 11A Left Bank Straightaway Gentle Bank 11B Right Bank Straightaway Steep Bank 12A Left Bank Exiting Bend Inner Bank Sandbar 12B Right Bank Exiting Bend Outer Bank Steep Bank 13A Left Bank Straightaway Gentle Bank 13B Right Bank Straightaway Steep Bank 14A Left Bank Exiting Bend Outer Bank Steep Bank 14B Right Bank Exiting Bend Inner Bank Sandbar 15A Right Bank Bend Apex Outer Bank Steep Bank 15B Left Bank Bend Apex Inner Bank Sandbar 16A Left Bank Exiting Bend Outer Bank Steep Bank 16B Right Bank Exiting Bend Inner Bank Sandbar 17A Left Bank Exiting Bend Inner Bank Sandbar 17B Right Bank Exiting Bend Outer Bank Steep Bank 18A Left Bank Exiting Bend Inner Bank Gentle Bank 18B Right Bank Exiting Bend Outer Bank Steep Bank 19A Left Bank Exiting Bend Inner Bank Gentle Bank 19B Right Bank Exiting Bend Outer Bank Steep Bank 20A Left Bank Bend Apex Outer Bank Steep Bank

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50 Table 4-2. Continued. Station Number Left or Right Descending Bank Geomorphic Classification If a Bend, Inner or Outer Bank Bank Habitat Classification 20B Right Bank Bend Apex Inner Bank Gentle Bank 21A Left Bank Entering Bend Outer Bank Steep Bank 21B Right Bank Entering Bend Inner Bank Sandbar 22A Left Bank Straightaway Steep Bank 22B Right Bank Straightaway Gentle Bank 23A Left Bank Bend Apex Inner Bank Sandbar 23B Right Bank Bend Apex Outer Bank Steep Bank 24A Left Bank Bend Apex Outer Bank Steep Bank 24B Right Bank Bend Apex Inner Bank Sandbar 25A Left Bank Bend Apex Inner Bank Gentle Bank 25B Right Bank Bend Apex Outer Bank Steep Bank 26A Left Bank Exiting Bend Inner Bank Steep Bank 26B Right Bank Exiting Bend Outer Bank Dike Field 27A Left Bank Bend Apex Inner Bank Steep Bank 27B Right Bank Bend Apex Outer Bank Gentle Bank 28A Left Bank Straightaway Gentle Bank 28B Right Bank Straightaway Steep Bank 29A Left Bank Exiting Bend Outer Bank Steep Bank 29B Right Bank Exiting Bend Inner Bank Gentle Bank 30A Left Bank Bend Apex Outer Bank Steep Bank 30B Right Bank Bend Apex Inner Bank Gentle Bank

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51 Figure 4-1. The four major reaches of the Apalac hicola River as defined by Leitman (1984). A) Upper reach (RM 106.3-77.4). B) Mi ddle reach (RM 77.4-42.0). C) Non-tidal lower reach (RM 42.0-20.6). D) Tidal lower reach (RM 20.6-0.0).

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52 Figure 4-2. Map of the Apalachicola River basin and surrounding region. Large box indicates the location of the 55.3-km intensive study reach. Selected cities are denoted by circles, and river gaging stat ions indicated by squares.

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53 A B C D Figure 4-3. Representative photogr aphs of the four bank habitat types defined by Ager et al. (1987) encountered during this st udy. A) Steep sloping bank. B) Gen tle sloping bank. C) Sandbar. D) Dike field. These images not used for analysis purposes.

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54 Figure 4-4. Map of the 55.3-km intensive study r each of the Apalachicola River indicating the specific locations of the 30 st udy sites. At each study site, both the leftand rightdescending banks were evaluated for a total of 60 sampling stations.

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55 Figure 4-5. Example of a digital image captured using the methods detailed in this study. Note the field technician on the riverbank holdi ng the 3.5-m long stadia rod perpendicular to the water surface at the location where the bank and water converge.

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56 A B C D Figure 4-6. Filtering and processing steps used to prepare photogr aphs for digital image analysis. A) Original color image. B) Grayscale negative of the original color image. C) Threshol ded black-and-white image. D) Thresholded image illustrating the seven, 0.5-m tall x 10.0-m long superimposed measur ement blocks used for digital image analysis.

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57 CHAPTER 5 HYDROLOGIC ANALYSES, RESULTS, AND DISCUSSION Hydrologic Analyses In order to appraise riverine ha bitat availability in relation to river stage or discharge, it is necessary to understand the hydrolog y of the basin. By examining time series data from gaging stations, inferences can be made regarding chan ges in river geomorphology with time, as well as the likelihood of experiencing si milar hydrologic conditions in th e future (McCuen 2005). For this study, real-time hydrologic stage and flow da ta were available from three USGS surfacewater gaging stations on the Apalachicola River. Gages were located at Chattahoochee (USGS # 02358000) (RM 105.8), Blountstown (USGS # 02359170) (RM 77.6), and near Sumatra (USGS # 02358700) (RM 20.6) (Figure 4-2). Data from the Chattahoochee gage were used in this study for all long-term flow analyses based on its extensive period of record (1929-present). All shortterm flow analyses were made from data genera ted at the Blountstown ga ge due to its proximity to the 55.3-km intensive study area, therefore minimi zing lag time effects. According to Light et al. (1998), Apalachicola River flows below 15,000 cfs at the Sumatra gage are generally tidally influenced, so data from this gaging stati on were not utilized in this low-flow study. Based on 1929-2006 daily discharge data obtaine d from the Chattahoochee gaging station, a linear mean daily discharge duration curve was c onstructed to determine the percentage of time a given discharge was equaled or exceeded (Figure 5-1). In order to in terpret the likelihood and magnitude of extreme flow events, the daily discharge data were transformed to produce a logarithmic mean daily discharge plot (Figure 52). Because the State of Florida and the USACE use data from the Chattahoochee gage to monitor and regulate water flows in the Apalachicola River, and because this study utilized stage and discharge data obtained from the Blountstown gage, an equivalency curve approximating the rela tion of Chattahoochee gage discharge readings

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58 with Blountstown gage stage readings for the Apalachicola River was generated (Figure 5-3). Additionally, a stage-discharge rating curve (Figure 5-4) and a st age-discharge hydrograph (Figure 5-5) were constructed fr om data obtained at the Blounts town gage spanning the duration of this study (March 2004-March 2006). Due to the dynamic nature of fluvial systems, and because parameters and units used to specify water levels, flows, and elevations can become confounded, a datum designated as baseline was defined in this study to signify the river conditions dur ing data collection. Baseline readings at the Blountstow n gage were a stage of 4.08 ft, and a discharge of 10,100 cfs. Snag quantification for this study was performe d at a total of seve n, 0.5-m distances above baseline. Table 5-1 contains equivalent stage, discharge, and NGVD 29 s ea-level elevations at the Blountstown gage for baseline conditions, as well as at each of the 0.5-m distances above baseline. Results From 10-13 October 2005, a total of 1,060 digita l photographs were captured of shoreline habitat within the 55.3-km intensiv e study reach of the Apalachicola River. Within this reach, 240 digital images totaling 2.4 km of river shor eline were quantified for snag abundance and distribution in each of the seven 0.5-m tall x 10.0 -m long measurement blocks above baseline, using the digital imaging analysis techniques detailed in Chapter 4. Based on bank habitat classifications defined by Ager et al. (1987), nearly all of the 60 sampling stations in this study were classified as steep sloping banks, gentle sloping banks, or sandbar habitats; only one dike field station was encountered during the survey (Table 5-2). Most of the sampling stations (96.6%) were geomorphically classi fied using USGS topographic maps as being located at the apex of a bend, exiting a river bend, or along a ri ver straightaway, while only 2 stations were located at the entrance to a be nd in the river (Table 5-3).

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59 Visual inspection of the original color images of river banks captured in the field indicated that sandbar habitats typically possessed the lowest quantity of available snag material (e.g., Figure 4-3C); however, comparison of mean snag area values generated for sandbar habitats using the novel methods presented in this st udy, with those of the three other habitats encountered, revealed that sandbar area values we re erroneously elevated (Figure 5-6). Data from sandbar habitats were consequently omitted from subsequent analyses due to their inaccuracy. Analysis of mean snag area submer ged for non-sandbar habitats indicated that the greatest quantities would occur w ithin the first meter above base line; gentle sloping bank habitat having the highest mean area submerged (3.19 m2), followed by steep sloping banks, and dike field habitats (2.56 and 1.71 m2, respectively) (Table 5-4; Fi gure 5-7). Mean snag area submerged for non-sandbar habitats based on geom orphic classification revealed the greatest quantities of snags would be submerged at a ri ver stage between 0.5-m to 1.0-m above baseline; river banks entering a bend having the highe st mean snag area submerged (3.97 m2), followed by straightaway, exiting bend, and bend apex locations (2.97, 2.83, and 2.37 m2, respectively) (Table 5-5; Figure 5-8). Furt her geomorphic analyses of non-sandbar habitats showed that within the first 0.5-m above baseline the inner ba nks of bends in the river have the most snag area submerged (3.09 m2), followed the outer banks of rive r bends that would have a maximum mean area submerged of 2.50 m2 at a distance between 0.5-m to 1.0-m above baseline (Table 56; Figure 5-9). Examination of the sampling stations subdi vided into Ager et al. (1987) habitat classifications indicated that 50% of the total available snag material would be submerged at 0.92 m above baseline for gentle sl oping banks, 0.97 m above baseline for dike field habitat, and 1.32 m above baseline for steep sloping banks (F igure 5-10). Separating the non-sandbar habitat

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60 sampling stations into geomorphic classifications showed that the distance above baseline at which 50% of the total available snag material would be submerged at a range from 1.10 m for river straightaways, to 1.32 m for sampling stations entering a river bend (Figure 5-11). Additional geomorphic evaluation re vealed that the distance above baseline at which 50% of the available snags would be submerged was 0.94 m fo r inner banks of river bends, 1.10 m for river straightaways, and 1.32 m for outer ba nks of river bends (Figure 5-12). Discussion In fluvial systems, hydrologic variability analyses and incremental methodologies are useful approaches for determining minimum inst ream flow requirements needed to maintain optimal ecological function and biotic integrity during low flows (Richter et al. 1997). Examination of the discharge duration curve (Figure 5-1) indicates that the Apalachicola River has experienced a remarkable variation of discharg e readings during its 77-year period of record, with extreme high and low-discharges recorded on occasion. Because the curve generated in Figure 5-1 covers such a large range of values with many occurring infrequently, the data were transformed to produce a logarithmic flow duration pl ot to assist with interpretation of low-flow frequency (Figure 5-2). The rela tively linear shape of the curve in Figure 5-2 indicates that the Apalachicola River has a strong ba seflow component that can be attributed to both the immense size of the upstream Chattahoochee and Flint drai nage basins, as well as to the significant groundwater influence within the basin (Elder et al. 1988). Mean daily discharge for the period of record at the Chattahoochee gage equale d or exceeded 15,900 cfs 50% of the time, while discharges of 8,480 cfs and 5,000 cfs were equaled or exceeded 90 and 99% of the time, respectively (Figure 5-2). Based on these curves, it appears that low-flow conditions in the Apalachicola River are not a fre quent occurrence. However, the long period of record at the Chattahoochee gage includes 25 y ears of pre-impoundment, non-regul ated discharge data that

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61 tends to amplify daily discharge means (Lei tman et al. 1983). Additionally, increased consumption of water in the ACF basin in response to growing urbanization and agricultural demands, as well as increased rates of eva potranspiration due to river impoundment have decreased downstream river flows (Elder et al. 1988). Light et al. ( 2006) reported that recent discharge reductions in the Apalachicola Ri ver have been exacerbated by anthropogenic activities along with na tural climatic change throughout the ACF basin. The equivalency curve in Figure 5-3 indicate s that a Blountstown ga ge stage of 4.08 ft (baseline in this study) is ge nerated by a discharge of 10,200 cf s at the Chattahoochee gage. Other key Blountstown stage values are 5.72 ft and 7.36 ft (0.5 and 1.0 m above baseline, respectively), which correspond to a Chattahoochee discharge of 13,100 and 16,400 cfs, respectively (Figure 5-3). The shape of the stage-discharge rating curve for the Blountstown gage (Figure 5-4) indicates that at low flows, the river is confined primarily to its main channel; a small change in discharge results in a fairly s ubstantial change in river stage. The curve also illustrates the distributional effects of the expa nsive Apalachicola River floodplain, in that once the river exceeds flood stage, larg e increases in discharge must be attained to not ice appreciable changes in river stage (Figure 5-4). The digital imaging analysis methods for snag quantification that are presented in this study are best suited for extremely low-flow c onditions. Exposed snag material along the banks of the Apalachicola River was to be photographed at the lowest water levels possible; ideally at or near the State of Florida mandated minimu m flow of 5,000 cfs at the Chattahoochee gage. Photography was scheduled to take place the fi rst week of September 2004, as the summer had been reasonably dry, and water levels in the river were steadily decl ining towards the state minimum (Figure 5-5). However, the untimely arrival of Hurricane Frances to the Florida

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62 panhandle curtailed these plans. To complicate things further, Hurricanes Ivan and Jeanne followed several weeks later, which elevated wate r levels above flood stage, and eliminated lowflow photographic opportunities until September of the following year. With yearly tropical cyclone activity highly unpredictable, and having a limited timeframe for data collection, photography for this study transpired in mid-Oc tober 2005 at relatively low flows (Figure 5-5). In an attempt to reduce the introduction of a dditional error and complexity to the digital imaging analysis methods, all photographs were f iltered, processed, and analyzed in exactly the same manner. However, a major limitation of us ing the analysis techniques as described in Chapter 4 was revealed for sandbar habitats wh en comparing the computed mean snag area values with the original color images captured in the field. Nearly all photographs of sandbar habitats on the Apalachicola River resembled the image in Figure 4-3C; large aggregations of river sand with an occasi onal interspersed woody snag. Mean snag area values generated for sandbar habitats were erroneously elevated, partic ularly in the lowest intervals above baseline (Figure 5-6). Visual examination of the origin al color photographs revealed that images of generally shaded habitats types su ch as steep sloping banks, gentle sloping banks, an d dike fields normally presented lightly-colored snag materi al against relatively darker backgrounds (e.g., Figure 4-5). Conversely, images captured of sandba r habitats typically co ntained darker-colored snag material against a nearly white sandy bac kground. It was also determined that wet, and consequently darker-colored sand in the measur ement intervals nearest to the water level for sandbar habitats were inaccurately interpreted by th e analysis methods as snag material. Similar setbacks were not evident for snag areas computed of steep sloping banks, gentle sloping banks, or dike field habitats which were usually shaded from direct sunlight. Another drawback that was encountered exclusively at sa ndbar habitat stations was a de pth-of-field problem created by

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63 the low-gradient bank angle that often produced a considerable distance between the stadia rod and the river bank in the background of the image. Unfortunately, the limitations of the analysis methods for sandbar habitats were not discovere d during the pilot study on the Suwannee River, as only steep and gentle sloping banks were photogra phed in that trial. Potential modifications of the methods to reduce errors produced for sandbar habitats incl ude: 1) an adjustment of the white-balance, or exposure settings of the camera when images of sandbar habitat are captured in the field; 2) use of an alternat ive threshold value othe r than 128 in the imag e processing steps; or 3) the development of an image processing algorith m that further isolates snag material from its surroundings by incorporation of ambi ent light levels with image c ontrast ratios. With visual inspections of original color photographs indicating nominal snag quantities on sandbar habitats, and due to the considerable quantification erro r revealed using the existing imaging analysis methods, mean snag area data from the 12 sandbar stations examined in this study were omitted from all subsequent analyses. Mean area of snags submerged for steep slopi ng bank habitat appears to diminish fairly evenly from baseline to the 3.5-m distance abov e baseline, whereas snag area for gentle sloping banks was greatest from baseline to 1.0 m above ba seline, then quickly tape red off (Figure 5-7). Diehl and Bryan (1993) indicated that steep sl oping banks generally occur along the outside banks of river bends where erosi on rates are fairly high. As the steep river banks are incised and undercut, snag material from the top of the bank te nds to fall towards the river where it will often hang by its rootwad, or by a network of vines, until it ultimately becomes detached from the bank and deposited in the river (Golladay and Battle 2006). Gentle sloping banks stations on the Apalachicola River were for the mo st part located along th e inner banks of a be nd in the river, or along straightaways of the river (Table 4-2). Water velocities tend to be lower at these locations

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64 and consequently snags have a propensity to be deposited during decreased flows conditions. Additionally, Figure 5-7 indi cates that when discharge and river stage increase, snags are picked up and transported by the increased water velocity, leaving the upper elevations of gentle sloping bank habitats without appreciable sn ag quantities. Dike field hab itat was only represented in this study at one sampling station within the 55.3-km in tensive study reach (Table 5-2), therefore the curve generated by these data was plotted for re ference only, and further interpretation was reserved (Figure 5-7). The entering bend geomorphic classification wa s also weakly represented in this study with a total of two sampling stat ions (Table 5-3). Only one of the two entering bend geomorphic stations was a non-sandbar habitat type, therefore, these data we re plotted as a reference and interpretations should be made w ith caution (Figure 5-8). Analyses of the other curves within Figure 5-8 indicates that geomorphic classi fication of non-sandbar bank habitat type had relatively little influence on mean area of snags su bmerged, as well as vertic al distribution within the 3.5-m distance above baseline. The majority of snags that would be submerged at greater river flows are found in the elevations just abov e baseline conditions, and steadily decreases as river stages approach flood stage levels (Figure 5-8). This trend would be expected as the main river channel is the usual colle ction site, and downstream trans port vehicle for products washed off the floodplain (Ward et al. 1999 ). In addition, river velociti es tend to decrease as stage decreases, so snags that would ordinarily be transported downriver during high-flow conditions end up being deposited along the river banks at lower river velocities (Gurnell 2003). Throughout the bends and straightaways of the Apalachicola River, snags qua ntities appear to be encountered fairly homogeneously.

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65 Figure 5-9 illustrates that snag distributi on along the outer banks of a river bend are somewhat more evenly distributed throughout the range from baseline to 3.5 m above baseline than along river straightaways, or along the inner banks of river be nds. As the majority of outer bank river bend sampling stations were also classified as steep sloping hab itats (Table 4-2), the increased rates of erosion and bank failure observed at these locations contributes to the slightly more even distribution of snag ma terial. At both inner bank and river straightaway stations, the distribution of snag material is greater in the first 1.5-m eleva tions above baseline, and then rapidly diminishes at higher elevations (Figure 5-9). Interpretation of the curves in Figures 5-6 through 5-9 shoul d not be extrapolated beyond the axes on which they are plotted. The abunda nce and distribution of snag material below baseline conditions remains undetermined, and it s hould not be assumed that the existing trends would hold true at distances other than what ar e presented. Since this was a low-flow study, all snag material below baseline conditions was presumed to remain submerged at baseline discharges or greater. Assuming that all quantified snags would be submerged at the 3.5-m distance above baseline, a relative percentage of total avai lable snags was computed for each 0.5-m distance above baseline. In order to compare these curv es, the distance above baseline where 50% of the available snags would be submerged was arbitrarily selected as a point of evaluation, in addition to the general shape of the curve. Analyses of the plots illustrating th e relative percentage of snags submerged based on bank habitat classifica tions (Figure 5-10), geom orphic classifications (Figure 5-11), and by bank location within a river bend (Figure 5-12) exhibited results similar to those of the area submerged plots: 1) steep slopi ng banks exhibited the most uniform vertical snag distribution, while gentle sloping banks tend ed to have greater sn ag quantity at lower

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66 distances above baseline; 2) geomorphic classi fication had no considerable effect on snag distribution; and 3) outer banks of river bends tended to have a more balanced distribution of available snags throughout the ra nge of measurement than did i nner banks of river bends or straightaways. Recommendations Officials responsible for making water alloca tion choices should continue to rely on scientific research to assist w ith their decisions. Ba sed on the results of this study, and those of scientists from other agencies, the State of Florida should con tinue to pursue increased river discharges from the Jim Woodruff Lock and Dam. As water levels decline in the river, so does the availability of valuable snag habitat wh ich can have cascading negative effects on vital physical, chemical, and biological components of the ecology within the Apalachicola River and Bay ecosystems. The water allocation issues that have developed within the ACF watershed are truly complex. Development of a water management plan for the basin which satisfies human consumptive demands while maintaining optimal ecosystem integrity a nd functionality is a difficult task, especially for a basin of its size. Intuitively, humans prefer to fix problems at the local level so immediate results can be achieved (Sparks 1995). However, in large watersheds like the ACF, a system-level appr oach should be encouraged for increased equity of success. Based on the increasing number of stakeholders with interests for water in the basin, there appears to be no feasible way to completely satisfy all of its user s during unseasonably dry periods. With urbanization and agricultural growth continuing at a rapid pace, the inability to meet future water demands will most likely occur with increased frequency. Water conservation efforts among all users in the basi n must continue to be endorsed, and rates of urban growth need to be checked. The effects of urbanization gr eatly exceed the delineated boundaries of urban

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67 areas. With this in mind, it is imperative that local, state, and federal officials remain committed to seeking common sense solutions towards an effective balance between the competing water demands and conservation needs of river-imp acted flora and fauna within the ACF basin.

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68 Table 5-1. Equivalent stage, discharge, and el evation readings at base line conditions, and at 0.5m distances above baseline, for the Bl ountstown gage, Apalachicola River. Distance Above Baseline (m) Blountstown Stage (ft) Blountstown Discharge (cfs) Blountstown Discharge (cms) Distance Above NGVD29 (m) 3.5 15.56 39,700 1,124.6 12.96 3.0 13.92 33,400 946.2 12.46 2.5 12.28 28,300 801.7 11.96 2.0 10.64 23,700 671.4 11.46 1.5 9.00 19,600 555.2 10.96 1.0 7.36 16,000 453.3 10.46 0.5 5.72 12,900 365.6 9.96 Baseline 4.08 10,100 286.0 9.46 Table 5-2. Bank habitat classifi cation summary for the 60 sampli ng stations within the 55.3-km intensive study reach of the Apalachicola River. Habitat classifications based on Ager et al. (1987). Habitat Classification Number of Stations % of Total Study Area Steep Sloping Bank 29 48.3 Gentle Sloping Bank 18 30.0 Sandbar 12 20.0 Dike Field 1 1.7 Table 5-3. Geomorphic classification summary fo r the 60 sampling stations within the 55.3-km intensive study reach of the Apalachicola Ri ver. Geomorphic classifications derived from USGS topographic maps. Geomorphic Classification Number of Stations % of Total Study Area Bend Apex 20 33.3 Exiting Bend 24 40.0 Straightaway 14 23.3 Entering Bend 2 3.4

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69 Table 5-4. Bank habitat classifi cation effects on mean area of snags submerged, a nd relative percentage of total snag area sub merged, for non-sandbar habitat stations on the Apalachicola River. Snag areas su bmerged at 0.5-m distances above baseline are per 10.0-m of shoreline, and percentages are relative to all snags being submerged at 3.5-m above baseline. Bank habitat classifications based on Ager et al. (1987). Steep Sloping Bank ( n=29) Gentle Sloping Bank ( n=18) Dike Field ( n=1) Distance Above Baseline (m) Snag Area (m2) Relative % Snag Area (m2) Relative % Snag Area (m2) Relative % 3.5 0.99 100.0 0.71 100.0 0.62 100.0 3.0 1.12 90.7 0.67 93.1 0.47 91.6 2.5 1.40 81.3 0.63 86.9 0.47 85.9 2.0 1.78 70.0 1.11 81.3 0.73 79.9 1.5 2.28 56.4 2.36 72.1 1.35 70.0 1.0 2.56 38.5 3.14 53.7 1.61 51.8 0.5 2.29 18.0 3.19 28.1 1.71 28.3 Table 5-5. Geomorphic classification effects on mean area of snag s submerged, and relative percentage of total snag area subme rged, for non-sandbar habitat stations on the Apalachicola River. Snag areas su bmerged at 0.5-m distances above baseline are per 10.0-m of shoreline, and percentages are relative to all snags being submerged at 3.5-m above baseline. Geomorphic classifications derived fro m USGS topographic maps. Bend Apex ( n=14) Exiting Bend ( n=19) Straightaway ( n=14) Entering Bend ( n=1) Distance Above Baseline (m) Snag Area (m2) Relative % Snag Area (m2) Relative % Snag Area (m2) Relative % Snag Area (m2) Relative % 3.5 0.88 100.0 0.76 100.0 0.99 100.0 1.47 100.0 3.0 0.94 91.5 0.86 92.2 1.00 91.0 1.70 92.5 2.5 1.15 83.1 1.00 84.5 1.06 82.5 2.43 83.7 2.0 1.50 72.9 1.56 76.0 1.32 74.0 3.03 71.4 1.5 2.05 60.0 2.39 63.8 2.29 63.8 3.60 56.3 1.0 2.37 41.7 2.83 45.4 2.97 46.4 3.97 38.4 0.5 2.29 20.6 2.61 22.4 2.86 23.1 3.72 18.6

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70 Table 5-6. Effects of bank locat ion within a river bend on mean area of snags submerged, and relative percentage of total snag area s ubmerged, for non-sandbar habitat stations on the Apalachicola River. Snag areas submerged at 0.5-m distances above baseline are per 10.0-m of shoreline, and pe rcentages are relativ e to all snags be ing submerged at 3.5-m above baseline. Bank locations derived from USGS topographic maps. Inner Bank ( n=11) Outer Bank ( n=23) Distance Above Baseline (m) Snag Area (m2) Relative % Snag Area (m2) Relative % 3.5 0.62 100.0 0.94 100.0 3.0 0.60 93.7 1.06 91.1 2.5 0.56 87.8 1.37 82.0 2.0 1.19 82.6 1.77 70.8 1.5 2.44 72.3 2.21 57.1 1.0 3.04 53.1 2.50 39.2 0.5 3.09 28.0 2.23 18.5

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71 0 30,000 60,000 90,000 120,000 150,000 180,000 210,000 240,000 270,000 300,000 0102030405060708090100 Percent of Time a Given Discharge is Equaled or ExceededDischarge (cfs) Figure 5-1. Linear mean daily discharg e duration curve for the Apalachicola Rive r at the Chattahoochee gage (1929-2006).

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72 Figure 5-2. Logarithmic mean daily discha rge duration curve for the Apalachicola Ri ver at the Chattahoochee gage (1929-2006).

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73 -5.0 0.0 5.0 10.0 15.0 20.0 25.0 30.00 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000Chattahoochee Discharge (cfs)Blountstown Stage (ft) FLOOD STAGE Figure 5-3. Equivalency curve approximating the relation of Chattahoochee gage discharge readings w ith Blountstown gage stage readings for the Apalachicola River. Curve based on unpublished data supp lied by H. Light, USGS Tallahassee, 2002.

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74 0.0 5.0 10.0 15.0 20.0 25.0 30.00 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000Discharge (cfs)Stage (ft) FLOOD STAGE Figure 5-4. Stage-discharge rating curve for the Apalachicola River at the Blountstown gage (March 2004-March 2006).

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75 0.00 5.00 10.00 15.00 20.00 25.00Mar. 04 Jun. 04 Sep. 04 Dec. 04 Mar. 05 Jun. 05 Sep. 05 Dec. 05 Mar. 06DateStage (ft) FLOOD STAGE0 11,700 22,000 36,900 68,000 192,300Discharge (cfs) Figure 5-5. Stage-discharge hydrograph for th e Apalachicola River at the Blountstown ga ge (March 2004-March 2006). Shaded box indicates the period of time when fieldwork was conducted.

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76 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.0 1.0 2.0 3.0 4.0 5.0 Mean Area of Snags Submerged (m2)Distance Above Baseline (m) Steep Sloping Bank (n=29) Gentle Sloping Bank (n=18) Dike Field (n=1) Sandbar (n=12) 10,100 12,900 16,000 19,600 23,700 28,300 33,400 39,700Blountstown Discharge (cfs)FLOOD STAGE -NOTESandbar habitat data are inaccurate Figure 5-6. Bank habitat classifi cation effects on mean area of snags submerged at 0.5-m distances above baseline. Curves gen erated from all data collected within the 55.3-km intensive study reach of the Apalachicola River. Snag areas submerged at 0.5-m distances above baseline are per 10.0-m of shoreline. Sandbar ha bitat data are inaccurate, and plotted with a dashed-line as a reference only. Data from these curves should not be extrapolated.

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77 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.01.02.03.04.05.0 Mean Area of Snags Submerged (m2)Distance Above Baseline (m) Steep Sloping Bank (n=29) Gentle Sloping Bank (n=18) Dike Field (n=1) 10,100 12,900 16,000 19,600 23,700 28,300 33,400 39,700Blountstown Discharge (cfs)FLOOD STAGE Figure 5-7. Non-sandbar bank habitat classifi cation effects on mean area of snags s ubmerged at 0.5-m distances above baseline. Curves generated from data collected w ithin the 55.3-km intensive study reach of the Apalachicola River. Snag areas submerged at 0.5-m distances above base line are per 10.0-m of shoreline. Da ta from these curves should not be extrapolated.

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78 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.01.02.03.04.05.0 Mean Area of Snags Submerged (m2)Distance Above Baseline (m) Bend Apex (n=14) Exiting Bend (n=19) Straightaway (n=14) Entering Bend (n=1) 10,100 12,900 16,000 19,600 23,700 28,300 33,400 39,700Blountstown Discharge (cfs)FLOOD STAGE Figure 5-8. Geomorphic classification effect s on mean area of snags submerged at 0.5-m distances above baseline. Curves gener ated from non-sandbar habitat data coll ected within the 55.3-km intensive study reach of the Apalachicola River. Snag areas submerged at 0.5-m distances above base line are per 10.0-m of shoreline. Da ta from these curves should not be extrapolated.

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79 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.0 1.0 2.0 3.0 4.0 5.0 Mean Area of Snags Submerged (m2)Distance Above Baseline (m) Inner Bank (n=11) Outer Bank (n=23) Straightaway (n=14) 10,100 12,900 16,000 19,600 23,700 28,300 33,400 39,700Blountstown Discharge (cfs)FLOOD STAGE Figure 5-9. Effects of bank locat ion within a river bend on mean area of snags submerged at 0.5-m distances above baseline. C urves generated from non-sandbar habitat data co llected within the 55.3-km intensive st udy reach of the Apalachicola River. Snag areas submerged at 0.5-m distances a bove baseline are per 10.0-m of shoreline. Data from these curves should not be extrapolated.

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80 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0 25 50 75 100 % of Available Snags SubmergedDistance Above Baseline (m) Steep Sloping Bank (n=29) Gentle Sloping Bank (n=18) Dike Field (n=1)10,100 12,900 16,000 19,600 23,700 28,300 33,400 39,700Blountstown Discharge (cfs) FLOOD STAGE Figure 5-10. Bank habitat classi fication effects on percentage of total availa ble snags submerged in relation to distance abov e baseline. Curves generated from non-sandbar habitat data collected within the 55.3-km intensive study reach of the Apalachicola River. Dotted lines corres pond to the location where 50% of the tota l available snag material would be submerged.

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81 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0 25 50 75 100 % of Available Snags SubmergedDistance Above Baseline (m) Bend Apex (n=14) Exiting Bend (n=19) Straightaway (n=14) Entering Bend (n=1)10,100 12,900 16,000 19,600 23,700 28,300 33,400 39,700Blountstown Discharge (cfs) FLOOD STAGE Figure 5-11. Geomorphic classification eff ects on percentage of total available snags submerged in relation to distance above baseline. Curves generated from non-sandbar habitat data collected within the 55.3-km intensive study reach of the Apalachicola River. Dotted lines corres pond to the location where 50% of the tota l available snag material would be submerged.

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82 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0 25 50 75 100 % of Available Snags SubmergedDistance Above Baseline (m) Inner Bank (n=11) Outer Bank (n=23) Straightaway (n=14)10,100 12,900 16,000 19,600 23,700 28,300 33,400 39,700Blountstown Discharge (cfs) FLOOD STAGE Figure 5-12. Effects of bank lo cation within a river be nd on percentage of total available snags submerged in relation to dist ance above baseline. Curves generated from non-sandbar habitat data collected within the 55.3-km intensive study reach of the Apalachicola River. Dotted lines corres pond to the location where 50% of the tota l available snag material would be submerged.

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83 APPENDIX A SAMPLING STATION FIELD DATASHEET

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84 APPENDIX B GUIDELINES FOR IMAGE OPTIMIZATION PROCESSING, AND ANALYSIS OF DIGITAL PHOTOGRAPHS ADOBE PHOTOSHOP : 1. File Open (filename.jpg) [CTRL + O] -Discard the embedded prof ile (dont color manage) 2. Image Adjustments Invert [CTRL + I] 3. Image Mode Grayscale 4. Image Image Size Pixel Dimensions -Width: / Percent 5. File Save As (filename.tif) [CTRL + SHIFT + S] -No image compression IMAGE J : 1. File Open (filename.tif) [CTRL + O] 2. Adjust window size as needed 3. Select the magnifying glass tool and magnify the stadia rod to the height of the screen [mouse click = Zoom In ; CTRL+ mouse click = Zoom Out] 4. Select the line tool and stretch a vertical line the length of the stadia rod 5. Analyze Set Scale -Enter known distance (3.5) and unit of length (meter); check box global 6. Zoom back out to 100% using magnifying glass tool [mouse click = Zoom In ; CTRL+ mouse click = Zoom Out] 7. Select the line tool and stretch a 10-m horizontal line along the waterline [CTRL + M] to measure the line -Add or subtract length to the stretched out horizontal line us ing either of the boxes on the ends of the line [CTRL + M] and adjust repeatedly until a 10-m length is achieved 8. On the stretched out horizontal line, grab the center box located at 5 m, and drag the whole line to the bottom of the stadia rod where the water and shoreline meet to create a right angle [CTRL + D] to draw to line on the image at the waterline 9. Analyze Clear Results -Do not save 10. Select the magnifying glass tool and magnify the non-stadia r od end of the drawn-in line [mouse click = Zoom In ; CTRL+ mouse click = Zoom Out] 11. Using the line tool stretch a vertical line upwards of at least 3.5-m length from the end of the drawn-in line [CTRL + M] to measure the line -If the length is 3.5-m or longer, continue on; if the length is short, use the uppermost box of the vertical line to add length and measure again; when at least 3.5-m is achieved, continue on [CTRL + D] to draw the vertical line on the image 12. Select the magnifying glass tool and magnify the stadia rod to the height of the screen [mouse click = Zoom In ; CTRL+ mouse click = Zoom Out]

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85 13. Select the rectangle tool and using the stadia rod as a vertical guide, stretch a 0.5-m tall rectangle of any length 14. Use the hand tool select the center box on each of the vertical edges of the rectangle and extend the rectangle to fit between the stadia rod and the drawn-in vertical line, which will create a rectangle with dimensions of 10-m x 0.5-m. 15. With the hand tool use click and drag techniques anywhe re within the rectangle to move it to the lowermost 0.5-m interval above the drawn-in horizontal line 16. Image Adjust Threshold [CTRL + SHIFT + T] -Set range from to 128; and Black and White 17. Analyze Analyze Particles -Use the following settings : / / / Nothing; and check the following boxes: Display Results and Summarize 18. In a spreadsheet program, record the total area value from the Summary window 19. Close the Summary window 20. Select Reset on the Threshold window 21. Select the rectangle tool and click in the existing rectangl e. Using the drawn in vertical line and stadia rod as guides slide the rectangle up 0.5 m 22. Select Set on the Threshold window and se t range to to 128; and Black and White 23. Analyze Analyze Particles -Use the following settings : / / / Nothing; and check the following boxes: Display Results and Summarize 24. Repeat steps18 through 23 until all seven of the 10-m x 0.5-m sections are measured 25. In the Results window, select File Save As (filename.xls)

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87 Beechie, T. J. and T. H. Sibley. 1997. Rela tionships between channel characteristics, woody debris, and fish habitat in northwestern Wa shington streams. Transactions of the American Fisheries Society 126:217-229. Benke, A. C. 2001. Importance of flood regime to invertebrate habitat in an unregulated river-floodplain ecosystem. Journal of the North American Benthological Society 20:225-240. Benke, A. C., R. L. Henry, D. M. Gillespie, and R. J. Hunter. 1985. Importance of snag habitat for animal production in southeastern streams. Fisheries 10:8-13. Benke, A. C., T. C. Van Arsdall, D. M. Gillespie, and F. K. Parrish. 1984. Invertebrate productivity in a subtropical blackwater river: the importance of habitat and life history. Ecological Monographs 54:25-63. Benke, A. C. and J. B. Wallace. 1990. Wood dynamics in Coastal Plain backwater streams. Canadian Journal of Fisheries and Aquatic Sciences 47:92-99. Berg, N., A. Carlson, and D. Azuma. 1998. Function and dynamics of woody debris in stream reaches in the central Sierra Nevada, California. Canadian Journal of Fisheries and Aquatic Sciences 55:1807-1820. Bilby, R. E. 1981. Role of organic debris da ms in regulating the e xport of dissolved and particulate matter from a forested watershed. Ecology 62:1234-1243. Bilby, R. E. 2003. Decomposition and nutrient dyna mics of wood in streams and rivers. Pages 135-148 in S. V. Gregory, K. L. Boyer, and A. M. Gurnell, editors. The ecology and management of wood in world rivers. Amer ican Fisheries Societ y, Bethesda, Maryland. Bilby, R. E., J. T. Heffner, B. R. Fransen, J. W. Ward, and P. A. Bisson. 1999. Effects of immersion in water on deterioration of wood from five species of trees used for habitat enhancement projects. North American J ournal of Fisheries Ma nagement 19:687-695. Bilby, R. E. and G. E. Likens. 1980. Importance of organic debris dams in the structure and function of stream ecosystems. Ecology 61:1107-1113. Bilby, R. E. and J. W. Ward. 1991. Characteris tics and function of large woody debris in streams draining old-growth, clear-cut, and second-growth forests in southwestern Washington. Canadian Journal of Fish eries and Aquatic Sc iences 48:2499-2508. Bisson, P. A., R. E. Bilby, M. D. Bryant, C. A. Dolloff, G. B. Grette, R. A. House, M. L. Murphy, K. V. Koski, and J. R. Sedell. 1987. Large woody debris in forested streams in the Pacific Northwest: past, present, and future. Pages 143-190 in E. O. Salo and T. W. Cundy, editors. Streamside management: fore stry and fishery interactions. Seattle, Washington. Boling, R. H., E. D. Goodman, J. A. Van Sickle, J. O. Zimmer, K. W. Cummins, R. C. Petersen, and S. R. Reice. 1975. Toward a model of detritus processing in a woodland stream. Ecology 56:141-151.

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89 Dolloff, C. A. 1994. Large woody debris, fish ha bitat, and historical land use. Pages 130-138 in Proceedings of the workshop on coarse woody debris in southern forests: effects on biodiversity. US Department of Agriculture, Forest Servi ce General Technical Report SE94, Washington, D.C. Dolloff, C. A. and J. R. Webster. 2000. Part iculate organic contribu tions from forests to streams: debris isn't so bad. Pages 125-138 in E. S. Verry, J. W. Hornbeck, and C. A. Dolloff, editors. Riparian management in fore sts of the continental eastern United States. CRC Press LLC, Boca Raton, Florida. Drury, D. M. and W. E. Kelso. 2000. Invertebrate colonization of woody de bris in coastal plain streams. Hydrobiologia 434:63-72. Dye, C. W. and R. B. Frydenborg. 1999. Investiga tions of potential habitat effects of deadhead logging in north Florida. Florida Department of Environmental Protection, Miscellaneous Reports and Studies, Tallahassee, Florida. Elder, J. F. and D. J. Cairns. 1982. Production and decomposition of forest litter fall on the Apalachicola River flood plain, Florida. US Geological Survey, Water-Supply Paper 2196-B, Alexandria, Virginia. Elder, J. F., S. D. Flagg, and H. C. Mattraw. 1988. Hydrology and ecology of the Apalachicola River, Florida: a summary of the river qual ity assessment. US Geological Survey, WaterSupply Paper 2196-D, Alexandria, Virginia. Erskine, W. D. 1994. River response to accelerat ed soil erosion in the Glenelg River catchment, Victoria. Australian Journal of Soil and Water Conservation 7:39-47. Estevez, E. D. and J. Sprinkel. 2000. Dispersi on and abundance of wood habitat of the Santa Fe and lower Suwannee River systems in relation to flow and flow-related variables A report of findings. Mote Marine Laboratory, Technical Report Number 646, Sarasota, Florida. FFWCC (Florida Fish and Wild life Conservation Commission). 2008. Welcome to Florida fishing capital of the world. Info rmational Publication. Available: http://floridafisheries.co m/pdf/Fishing%20AD.pdf. (last accessed: March 2008). Fitzgerald, D. G., B. Zhu, S. B. Hoskins, D. E. Haddad, K. N. Green, L. G. Rudstam, and E. L. Mills. 2006. Quantifying submerged aquatic vegetation using aerial photograph interpretation: application in studies assessi ng fish habitat in freshwater ecosystems. Fisheries 31:61-73. Flug, M., H. Seitz, and J. Scott. 1998. Measurem ent of stream channel habitat using sonar. Regulated Rivers: Research & Management 14:511-517. Gibson, C. A., J. L. Meyer, N. L. Poff, L. E. Hay, and A. Georgakakos. 2005. Flow regime alterations under changing climate in two ri ver basins: implications for freshwater ecosystems. River Research and Applications 21:849-864.

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91 Helfman, G. S. 2007. Fish cons ervation: a guide to understanding and restoring global aquatic biodiversity and fishery resources. Island Press, Washington, D.C. Hilderbrand, R. H., A. D. Lemly, C. A. Dolloff, and K. L. Harpster. 1998. Design considerations for large woody debris placemen t in stream enhancement projects. North American Journal of Fish eries Management 18:161-167. Hoehn, T. 2001. The Apalachicola Rive r today. Florida Wildlife 55:12. Hrodey, P. J. and T. M. Sutton. 2008. Fish community responses to half-log additions in warmwater streams. North American Journal of Fisheries Management 28:70-80. Hynes, H. B. N. 1975. The stream and its valley. Verhandlunge n der Internationalen Vereinigung fur Theoretische und Angewandte Limnologie 19:1-15. Junk, W. J., P. B. Bayley, and R. E. Sparks. 1989. The flood pulse concept in river-floodplain systems. Special Publication, Canadian J ournal of Fisheries and Aquatic Sciences 106:110-127. Keller, E. A. and F. J. Swanson. 1979. Effects of large organic material on channel form and fluvial processes. Earth Surface Processes 4:361-380. Kemp, W. M. and W. R. Boynton. 2004. Productivity, trophic structure. and energy flow in the steady-state ecosystems of Silver Springs Florida. Ecologi cal Modeling 178:43-49. Kiffney, P. M. and P. Roni. 2007. Relationshi ps between productivity, physical habitat, and aquatic invertebrate and vertebra te populations of forest str eams: an information-theoretic approach. Transactions of the Amer ican Fisheries Society 136:1088-1103. Kirkland, S. H. 2001. The steamboat era on the Ap alachicola, Chattahoochee, and Flint rivers. Florida Wildlife 55:9-11. Knighton, D. 1998. Fluvial forms & processes: a new perspective. Arnold Publishers, London. Leitman, H. M. 1984. Forest map and hydrol ogic conditions, Apalachic ola River floodplain, Florida. US Geological Survey, Hydrologi c Investigations Atlas HA-672, Alexandria, Virginia. Leitman, H. M., M. R. Darst, and J. J. Nordhaus 1991. Fishes in the forested flood plain of the Ochlockonee River, Florida, during flood and drought conditions. US Geological Survey, Water-Resources Investigations Re port 90-4202, Tallahassee, Florida. Leitman, H. M., J. E. Sohm, and M. A. Frank lin. 1983. Wetland hydrology and tree distribution of the Apalachicola River flood plain, Flor ida. US Geological Survey, Water-Supply Paper 2196-A, Alexandria, Virginia.

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98 BIOGRAPHICAL SKETCH Destined to be a University of Florida Ga tor, Matthew Alexander Burgess was born in 1977, in Gainesville, Florida. Growing up, his rou tine participation in fiel dwork with his father, annual family vacations to Crescent Beach, a nd summers sailing on the Hudson River and Long Island Sound helped foster his love of scien ce and the environment. In June 1995, Matthew graduated near the top of his class from Gaines ville High School. After beginning his collegiate career as a civil engineering majo r, Matthew soon realized that his desire for working in the outdoors was stronger than computing integrals, so he changed his major to zoology. In the summer of 1999, he earned his Bachelor of Science degree from the University of Florida, and began working full time in the UF Zoology Department where he gained tremendous experience as a laboratory assistant and international field technician for Drs. Colin and Lauren Chapman. Matthew then accepted a job in late-2001 as a fisheries biologist for the USGS in Gainesville where he worked extensively in the panhandle rivers of Florida over the next five years. During this time, he began his graduate degree in in terdisciplinary ecology at UF, and conducted the planning and field-portions of his thesis research. When his term appointment at USGS ended in 2006, Matthew then worked part-time as an employee of the Florida Program for Shark Research, at the Florida Museum of Natural Histor y, which kept him in contact with science, and allowed him time to complete his thesis.