Contractor Report 

USGS/BRD/CR--1997-0004 

OCS Study MMS 96-0020 

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AL. i Pensacola 

Mobile ~ 

0, ~ L Tallahassee 

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,Apalachicola ~l 

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STUDY Cedar Key 

AREA 

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Tarpon 

Springs 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

Program : Data Search and Synthesis 

Appendix F, Part 2: County Socioeconomic Summaries 

U .S. Department of the Interior U.S . Department of the Interior 

U .S. Geological Survey AM Minerals Management Service 

Biological Resources Division Gulf of Mexico OCS Region 
Contractor Report 

USGS/BRD/CR--1997-0004 

OCS Study MMS 96-0020 

Northeastern Gulf of Mexico 

Coastal and Marine Ecosystem Program : 

Data Search and Synthesis 

Appendix F, Part 2 : County Socioeconomic Summaries 

August 1997 

Prepared under BRD contract 

1445-CT0009-95-004 

by 

Science Applications International Corporation 

Raleigh, North Carolina 27605 

in cooperation with the 

U.S . Department of the Interior 

Minerals Management Service 

Gulf of Mexico OCS Region 
PROJECT COOPERATION 

This study was procured to meet information needs identified by the Minerals Management Service (MMS) 

in concert with the U .S. Geological Survey, Biological Resources Division (BRD). 

DISCLAIMER 

This report was prepared under contract between the U.S. Geological Survey, Biological Resources Division 

and Science Applications International Corporation . This report has been technically reviewed by the BRD 

and the MMS, and has been approved for publication . Approval does not signify that the contents necessarily 

reflect the views and policies of the BRD or MMS, nor does mention of trade names or commercial products 

constitute endorsement or recommendation for use. 

REPORT AVAILABILITY 

Extra copies of this report may be obtained from 

U.S . Department of the Interior 

US Geological Survey 

Biological Resources Division 

Eastern Regional Office 

1700 Leetown Road 

Kearneysville, WV 25430 

U.S. Department of the Interior 

Minerals Management Service 

Gulf of Mexico OCS Region 

Public Information Office (MS 5034) 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123-2394 

Telephone: (304) 725-8461 (ext. 675) Telephone: (504) 736-2519 or 

1-800-200-GULF 

Copies of this publication are available from the National Technical Information Service, 5285 Port Royal 

Road, Springfield, VA 22161 (1-800-553-6847 or 703-487-4650). Copies also are available to registered 

users from the Defense Technical Information Center, Attn: Help Desk, 8725 Kingman Road, Suite 0944, Fort 

Belvoir, VA 22060-6218 (1-800-225-3842 or 703-767-9050). 

SUGGESTED CITATION 

Science Applications International Corporation . 1997. Northeastern Gulf of Mexico Coastal and Marine 

Ecosystem Program: Data Search and Synthesis ; Appendix F, Part 2 : County Socioeconomic 

Summaries. U .S. Dept. of the Interior, U.S. Geological Survey, Biological Resources Division, 

USGS/BRD/CR--1997-0004 and Minerals Management Service, Gulf of Mexico OCS Region, New 

Orleans, LA, OCS Study MMS 96-0020 . 248 pp. 

ACKNOWLEDGMENT 

These County Summaries were developed and written by Dr. F. Bell of Florida State University. An integrated 

summary written by Dr. Bell for all the counties is located in the Synthesis Report . 
TABLE OF CONTENTS 

Section 

List of Figures . . . . . . . . . . . . . 

List of Tables . . . . . . . . . . . . . 

Introduction . . . . . . . . . . . . . . 

Bay County . . . . . . . . . . . . . . . 

Citrus County . . . . . . . . . . . . . . 

Dixie County . . . . . . . . . . . . . . 

Escambia County . . . . . . . . . . . . . 

Franklin County . . . . . . . . . . . . . 

Gulf County . . . . . . . . . . . . . . . 

Jefferson County . . . . . . . . . . . . 

Levy County . . . . . . . . . . . . . . . 

Okaloosa County . . . . . . . . . . . . . 

Santa Rosa County . . . . . . . . . . . . 

Taylor County . . . . . . . . . . . . . . 

Wakulla County . . . . . . . . . . . . . 

Walton County . . . . . . . . . . . . . . 

References . . . . . . . . . . . . . . . 

Paae 

. . vi 

viii 

1 

3 

. . 23 

. . 41 

. . 57 

. . 79 

. . 99 

117 

133 

151 

171 

191 

209 

227 

247 

v 
LIST OF FIGURES 

Figure Caution Paae 

Figure 1 Map of Bay County, Florida, showing levels of water quality 

and areas of quality testing (St . Andrews Basin) . . . . . 4 

Figure 2 Map of Citrus County, Florida, showing levels of water 

quality and areas of quality testing (Crystal River to 

St . Pete) . . . . . . . . . . . . . . . . . . . . . . . . 24 

Figure 3 Map of Escambia County, Florida, showing levels of water 

quality and areas of quality testing (Perdido Bay Basin) . 58 

Figure 4 Map of Escambia County, Florida, showing levels of water 

quality and areas of quality testing (Pensacola Bay 

Basin) . . . . . . . . . . . . . . . . . . . . . . . . . . 59 

Figure 5 Map of Franklin County, Florida, showing levels of water 

quality and areas of quality testing (Apalachicola 

Bay Basin) . . . . . . . . . . . . . . . . . . . . . . . . 80 

Figure 6 Map of Franklin County, Florida, showing levels of water 

quality and areas of quality testing (New River Basin) . . 81 

Figure 7 Map of Gulf County, Florida, showing levels of water 

quality and areas of quality testing (St . Andrews Bay 

Basin) . . . . . . . . . . . . . . . . . . - - . . - - - 100 

Figure 8 Map of Jefferson County, Florida, showing levels of water 

quality and areas of quality testing (Aucilla 

River Basin) . . . . . . . . . . . . . . . . . . . . . . 118 

Figure 9 Map of Levy County, Florida, showing levels of water 

quality and areas of quality testing (Waccasassa 

River Basin) . . . . . . . . . . . . . . . . . . . . . . 134 

Figure 10 Map of Okaloosa County, Florida, showing levels of water 

quality and areas of quality testing (Pensacola Bay 

Basin) . . . . . . . . . . . . . . . . . . . . . . . . . 152 

Figure 11 Map of Okaloosa County, Florida, showing levels of water 

quality and areas of quality testing (Choctawhatchee Bay 

Basin) - . . . . . . . . . . . . . . . . . . . . . . . . 153 

Figure 12 Map of Santa Rosa County, Florida, showing levels of water 

quality and areas of quality testing (Pensacola Bay 

Basin) . . . . . . . . . . . . . . . . . . . . . . . . . 172 

Figure 13 Map of Taylor County, Florida, showing levels of water 

quality and areas of quality testing (Aucilla River 

Basin) . . . . . . . . . . . . . . . . . . . . . . . . . 192 

vi 
LIST OF FIGURES 

Figure Caption Pace 

Figure 14 Map of Taylor County, Florida, showing levels of water 

quality and areas of quality testing (Econfina 

Creek/Steinhatchee River Basin) . . . . . . . . . . . . 193 

Figure 15 Map of Wakulla County, Florida, showing levels of water 

quality and areas of quality testing (Ochlockonee River 

Basin) . . - - - . . . . . . . . . . . . . . . . . . . 210 

Figure 16 Map of Wakulla County, Florida, showing levels of water 

quality and areas of quality testing (St . Marks River 

Basin) . . . . . . . . . . . . . . . . . . . . . . . . 211 

Figure 17 Map of Walton County, Florida, showing levels of water 

quality and areas of quality testing (Chocttawhatchee 

Bay Basin) . . . . . . . . . . . . . . . . . . . . . . 228 

Figure 18 Map of Walton County, Florida, showing levels of water 

quality and areas of quality testing (St . Andrews 

Bay Basin) . . . . . . . . . . . . . . . . - - . - . . 229 

vii 
LIST OF TABLES 

Table Caption Paae 

Table 1 Trends in Key Economic Aggregate Variables in Bay County, 

Florida, 1980-93 . . . . . . . . . . . . . . . . . . . . . 5 

Table 2 . Trends in Components of Personal Income in Bay County, 

Florida, 1980-93 . . . . . . . . . . . . . . . . . . . . . 6 

Table 3 . Major Export Industries in Bay County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . . . . . 8 

Table 4 . Top Ten Employers in Bay County, Florida and Products 

Produced, 1994 . . . . . . . . . . . . . . . . . - . . - . 8 

Table 5 . Ecosystem-Sensitive Industries in Bay County, Florida. 9 

Table 6 . Ecosystem-Insensiive Industries in Bay County, Florida. . 9 

Table 7 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Bay County, Florida, 1994 . . . . . . . . . . 10 

Table 8 . Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . 12 

Table 9 . Estimated Number of Saltwater Recreational Days 

(Fishing Effort) in the Thirteen County Study Area, 

1993-94 - - - . . . . . . . . . . . . . . . . . . . . . . 12 

Table lo . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . 13 

Table 11 . Economic Value of Wetlands . . . . . . . . . - . . . . . . 14 

Table 12 . Key Saltwater Beaches in Bay County, Florida . . . . . . 16 

Table 13 . Spending, Annual User Value and Asset Value of 

Selected Ecological Resources in Bay County, Florida . . . 17 

Table 14 . An Inventory of Marine-Related Recreational Facilities 

in Bay County, Florida, 1995 (Public and Private) . . . . 18 

Table 15 . Estimation of the Annual User Value for Saltwater Boating 

Off Bay County, Florida, 1993-94 . . . . . . . . . . . . . 18 

Table 16 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Bay County, Florida in 1994 . . . . . . . . . . 20 

Table 17 . Water Quality Indices for Selected Areas of Bay County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . 21 

Table 18 . Trends in Key Economic Aggregate Variables in Citrus 

County, Florida, 1980-93 . . . . . . . - . . 

viii 
LIST OF TABLES 

Table Caption Page 

Table 19 . Trends in Components of Personal Income in Citrus County, 

Florida, 1980-93 . . . . . . . . . . . , . . . , , , . . . 26 

Table 20 . Major Export Industries in Citrus County, Florida and 

Their Contribution to Aggregate Personal Income, 1993 . . . 28 

Table 21 . Top Ten Employers in Citrus County, Florida and Products 

Produced, 1994 . . . . . . . , . . . . . . . . . . . . . . 28 

Table 22 . Ecosystem-Sensitive Industries in Citrus County, Florida . 29 

Table 23 . Ecosystem-Insensitive Industries in Citrus County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . 2 9 

Table 24 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Citrus County, Florida, 1994 . . . . . . . . . 30 

Table 25 . Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . 31 

Table 26 . Estimated Number of Saltwater Recreational Days 

(Fishing Effort) in the Thirteen County Study Area, 

1993-94 . . . . . . . . . . . . . - - - . . . . . . . . . . 32 

Table 27 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . 32 

Table 28 . Economic Value of Wetlands . . . . . . . . . . . . . . . . 34 

Table 29 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Citrus County, Florida . . . . . . 36 

Table 30 . An Inventory of Marine-Related Recreational Facilities 

in Citrus County, Florida, 1995 (Public and Private) . . . 36 

Table 31 . Estimation of the Annual User Value for Saltwater Boating 

Off Citrus County, Florida, 1993-94 . . . . . . . . . . . . 37 

Table 32 . Water Quality Indices for Selected Areas of Citrus County, 

Florida . . . . . . . . . . . . . . . . . . . . , . . . . . 39 

Table 33 . Trends in Key Economic Aggregate Variables in Dixie County, 

Florida, 1980-93 . . . . . . . . . . . . . . . . . . . . . 42 

Table 34 . Trends in Components of Personal Income in Dixie County, 

Florida, 1980-93 . . . . . . . . . . . . . . . . . . . . . 43 

Table 35 . Major Export Industries in Dixie County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . . . . . . 45 

ix 
LIST OF TABLES 

Table Caption pace 

Table 36 . Top Ten Employers in Dixie County, Florida and Products 

Produced, 1994 . . . . . . . . . . . . . . . . . . . . . . 45 

Table 37 . Ecosystem-Sensitive Industries in Dixie County, Florida . 46 

Table 38 . Ecosystem-Insensitive Industries in Dixie County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . 46 

Table 39 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Dixie County, Florida, 1994 . . . . . . . . . 47 

Table 40 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . . . . . . . . . 48 

Table 41 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . 49 

Table 42 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . 49 

Table 43 . Economic Value of Wetlands . . . . . . . . . . . . . . . . 51 

Table 44 . Key Saltwater Beaches in Dixie County, Florida . . . . . 52 

Table 45 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Dixie County, Florida . . . . . . 53 

Table 46 . An Inventory of Marine-Related Recreational Facilities 

in Dixie County, Florida, 1995 (Public and Private) . . . 53 

Table 47 . Estimation of the Annual User Value for Saltwater Boating 

Off Dixie County, Florida, 1993-94 . . . . . . . . . . . . 55 

Table 48 . Water Quality Indices for Selected Areas of Dixie County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . 56 

Table 49 . Trends in Key Economic Aggregate Variables in Escambia 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . 60 

Table 50 . Trends in Components of Personal Income in Escambia 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . 61 

Table 51 . Major Export Industries in Escambia County, Florida 

and Their Contribution to Aggregate Personal Income, 

1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 

Table 52 . Top Ten Employers in Escambia County, Florida and 

Products Produced, 1994 . . . . . . . . . . . . . . . . . 63 

x 
LIST OF TABLES 

Table Caption Paae 

Table 53 . Ecosystem-Sensitive Industries in Escambia County, 

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . 64 

Table 54 . Ecosystem-Insensitive Industries in Escambia County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . 65 

Table 55 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Escambia County, Florida, 1994 . . . . . . . . 66 

Table 56 . Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . 67 

Table 57 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . 67 

Table 58 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . 69 

Table 59 . Economic Value of Wetlands . . . . . . . . . . . . . . . . 69 

Table 60 . Key Saltwater Beaches in Escambia County, Florida . . . . 71 

Table 61 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Escambia County, Florida . . . . . 72 

Table 62 . An Inventory of Marine-Related Recreational Facilities in 

Escambia County, Florida, 1995 (Public and Private) . . . . 73 

Table 63 . Estimation of the Annual User Value for Saltwater 

Boating Off Escambia County, Florida, 1993-94 . . . . . . . 74 

Table 64 . Water Quality Indices for Selected Areas of Escambia 

County, Florida . . . . . . . . . . . . . . . . . . . . . . 76 

Table 65 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Escambia County, Florida in 1994 . . . . . . . 77 

Table 66 . Trends in Key Economic Aggregate Variables in Franklin 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . 82 

Table 67 . Trends in Components of Personal Income in Franklin 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . 83 

Table 68 . Major Export Industries in Franklin County, Florida 

and Their Contribution to Aggregate Personal Income, 

1993 . . . . . . . . . . . . . . . . . - - - - 

. . . . . . 85 

Table 69 . Top Ten Employers in Franklin County, Florida and 

Products Produced, 1994 . . . . . . . . . . . . . . . . . . 85 

xi 
LIST OF TABLES 

Table Caption Pa e 

Table 70 . Ecosystem-Sensitive Industries in Franklin County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . 86 

Table 71 . Ecosystem-Insensitive Industries in Franklin County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . 87 

Table 72 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Franklin County, Florida, 1994 . . . . . . . . 87 

Table 73 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . . . . . . . . . 89 

Table 74 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . 89 

Table 75 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . 91 

Table 76 . Economic Value of Wetlands . . . . . . . . . . . . . . . . 91 

Table 77 . Key Saltwater Beaches in Franklin County, Florida . . . . 93 

Table 78 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Franklin County, Florida . . . . . 94 

Table 79 . An Inventory of Marine-Related Recreational Facilities 

in Franklin County, Florida, 1995 (Public and Private) . . 95 

Table 80 . Estimation of the Annual User Value for Saltwater Boating 

Off Franklin County, Florida, 1993-94 . . . . . . . . . . 95 

Table 81 . Water Quality Indices for Selected Areas of Franklin 

County, Florida . . . . . . . . . . . . . . . . . . . . . 97 

Table 82 . Trends in Key Economic Aggregate Variables in Gulf 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . 101 

Table 83 . Trends in Components of Personal Income in Gulf County, 

Florida, 1980-93 . . . . . . . . . . . . . . . . . . . . 102 

Table 84 . Major Export Industries in Gulf County, Florida and 

Their Contribution to Aggregate Personal Income, 1993 . 104 

Table 85 . Top Employers in Gulf County, Florida and Products 

Produced, 1994 . . . . . . . . . . . . . . . . . . . . . 104 

Table 86 . Ecosystem-Sensitive Industries in Gulf County, Florida . 104 

Table 87 . Ecosystem-Insensitive Industries in Gulf County, Florida . 105 

xii 
LIST OF TABLES 

Table Caption Paae 

Table 88 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Gulf County, Florida, 1994 . . . . . . . . . . .10E 

Table 89 . Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . .107 

Table 90 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . .108 

Table 91 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . .108 

Table 92 . Economic value of Wetlands . . . . . . . . . . . . . . . . .110 

Table 93 . Key Saltwater Beaches in Gulf County, Florida . . . . . . .112 

Table 94 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Gulf County, Florida . . . . . . . .112 

Table 95 . Estimation of the Annual User Value for Saltwater 

Boating Off Gulf County, Florida, 1993-94 . . . . . . . . . .114 

Table 96 . Water Quality Indices for Selected Areas of Gulf County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . .115 

Table 97 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Gulf County, Florida in 1994 . . . . . . . . . . .115 

Table 98 . Trends in Key Economic Aggregate Variables in Jefferson 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . .119 

Table 99 . Trends in Components of Personal Income in Jefferson 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . .120 

Table 100 . Major Export Industries in Jefferson County, Florida 

and Their Contribution to Aggregate Personal Income, 1993 . 121 

Table 101 . Top Ten Employers in Jefferson County, Florida and 

Products Produced, 1994 . . . . . . . . . . . . . . . . . . .122 

Table 102 . Ecosystem-Sensitive Industries in Jefferson County . . . . .122 

Table 103 . Ecosystem-Insensitive Industries in Jefferson County . . . .123 

Table 104 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Jefferson County, Florida, 1994 . . . . . . . . .124 

Table 105 . Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . .125 

xiii 
LIST OF TABLES 

Table Caption Paae 

Table 106 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . . 125 

Table 107 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . . 126 

Table 108 . Economic Value of Wetlands . . . . . . . . . . . . . . . . . 127 

Table 109 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Jefferson County, Florida. . . . . 129 

Table 110 . Estimation of the Annual User Value for Saltwater Boating 

Off Jefferson County, Florida, 1993-94 . . . . . . . . . . . 130 

Table 111 . Water Quality Indices for Selected areas of Jefferson 

County, Florida . . . . . . . . . . . . . . . . . . . . . . 131 

Table 112 . Trends in Key Economic Aggregate Variables in Levy County, 

Florida, 1980-93 . . . . . . . . . . . . . . . . . . . . . . 135 

Table 113 . Trends in Components of Personal Income in Levy County, 

Florida, 1980-93 . . . . . . . . . . . . . . . . . . . . . . 136 

Table 114 . Major Export Industries in Levy County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . . . . . . 138 

Table 115 . Top Ten Employers in Levy County, Florida and Products 

Produced, 1994 . . . . . . . . . . . . . . . . . . . . . . . 138 

Table 116 . Ecosystem-Sensitive Industries in Levy County . . . . . . . 138 

Table 117 . Ecosystem-Insensitive Industries in Levy County . . . . . . 139 

Table 118 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Levy County, Florida, 1994 . . . . . . . . . . . 140 

Table 119. Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . . 141 

Table 120 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . . 142 

Table 121 . Estimated Expenditures by Saltwater Recreational Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . . 142 

Table 122 . Economic Value of Wetlands . . . . . . . . . . . - . . . . . 144 

Table 123 . Key Saltwater Beaches in Levy County, Florida . . . . . . . 145 

xiv 
LIST OF TABLES 

Table Caption pace 

Table 124 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Levy County, Florida . . . . . . . .146 

Table 125 . An Inventory of Marine-Related Recreational Facilities 

in Levy County, Florida, 1995 (Public and Private) . . . . .146 

Table 126 . Estimation of the Annual User Value for Saltwater 

Boating Off Levy County, Florida, 1993-94 . . . . . . . . . .148 

Table 127 . Water Quality Indices for Selected Areas of Levy 

County, Florida . . . . . . . . . . . . . . . . . . . . . . .149 

Table 128 . Trends in Key Economic Aggregate Variables in Okaloosa 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . .154 

Table 129 . Trends in Components of Personal Income in Okaloosa 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . .155 

Table 130 . Major Export Industries in Okaloosa County, Florida 

and Their Contribution to Aggregate Personal Income, 

1993 . . . . . . . . . . . . . . . . - ~ - - - - . . . . . .157 

Table 131 . Ecosystem-Sensitive Industries in Okaloosa County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . .157 

Table 132 . Top Ten Employers in Okaloosa County, Florida and 

Products Produced, 1994 . . . . . . . . . . . . . . . . . . .158 

Table 133 . Ecosystem-Insensitive Industries in Okaloosa County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . .158 

Table 134 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Okaloosa County, Florida, 1994 . . . . . . . . .160 

Table 135 . Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . .161 

Table 136 . Estimated Number of Saltwater Recreational Days 

(Fishing Effort) in the Thirteen County Study 

Area, 1993-94 . . . . . . . . . . . . . . . . . . . . . . . .161 

Table 137 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . .162 

Table 138 . Economic Value of Wetlands . . . . . . . . . . . . . . . . .164 

Table 139 . Key Saltwater Beaches in Okaloosa County, Florida . . . . .165 

Table 140 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Okaloosa County, Florida . . . . . .167 

xv 
LIST OF TABLES 

Table Caution Page 

Table 141 . An Inventory of Marine-Related Recreational Facilities 

in Okaloosa County, Florida, 1995 (Public and Private) . . . 167 

Table 142 . Estimation of the Annual User Value for Saltwater 

Boating Off Okaloosa County, Florida, 1993-94 . . . . . . . 168 

Table 143 . Water Quality Indices for Selected Areas of Okaloosa 

County, Florida . . . . . . . . . . . . . . . . . . . . . . 165 

Table 144 . Trends in Key Economic Aggregate Variables in Santa Rosa 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . . 173 

Table 145 . Trends in Components of Personal Income in Santa Rosa 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . . 174 

Table 146 . Major Export Industries in Santa Rosa County, Florida 

and Their Contribution to Aggregate Personal Income, 

1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 

Table 147 . Top Ten Employers in Santa Rosa County, Florida and 

Products Produced, 1994 . . . . . . . . . . . . . . . . . . 176 

Table 148 . Ecosystem-Sensitive Industries in Santa Rosa County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . - . . 177 

Table 149 . Ecosystem-Insensitive Industries in Santa Rosa County, 

Florida . . . . . . . . . - . . . . . . . . . . . . . - - . 177 

Table 150 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Santa Rosa County, Florida, 1994 . . . . . . . . 178 

Table 151 . Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . . 180 

Table 152 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . . 180 

Table 153 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . . 181 

Table 154 . Economic Value of Wetlands . . . . . . . . . . . . . . . . . 182 

Table 155 . Key Saltwater Beaches in Santa Rosa County, Florida . . . . 184 

Table 156 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Santa Rosa County, Florida . . . . . 185 

Table 157 . An Inventory of Marine-Related Recreational Facilities 

in Santa Rosa County, Florida, 1995 (Public and Private) . . 186 

xvi 
LIST OF TABLES 

Table Caution Page 

Table 158 . Estimation of the Annual User Value for Saltwater Boating 

Off Santa Rosa County, Florida, 1993-94 . . . . . . . . . . .186 

Table 159 . Water Quality Indices for Selected Areas of Santa Rosa 

County, Florida . . . . . . . . . . . . . . . . . . . . . . .188 

Table 160 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Santa Rosa County, Florida in 1994 . . . . . . . .189 

Table 161 . Trends in Key Economic Aggregate Variables in Taylor 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . .194 

Table 162 . Trends in Components of Personal Income in Taylor 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . .195 

Table 163 . Major Export Industries in Taylor County, Florida and 

Their Contribution to Aggregate Personal Income, 1993 . . . .197 

Table 164 . Top Employers in Taylor County, Florida and Products 

Produced, 1994 . . . . . . . . . . . . . . . . . . . . . . .197 

Table 165 . Ecosystem-Sensitive Industries in Taylor County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . .197 

Table 166 . Ecosystem-Insensitive Industries in Taylor County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . .198 

Table 167 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Taylor County, Florida, 1994 . . . . . . . . . .199 

Table 168 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . . . . . . . . . . .201 

Table 169 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . .201 

Table 170 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . .202 

Table 171 . Economic Value of Wetlands . . . . . . . . . . . . . . . . .203 

Table 172 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Taylor County, Florida . . . . . . .205 

Table 173 . An Inventory of Marine-Related Recreational Facilities in 

Taylor County, Florida, 1995 (Public and Private) . . . . . .205 

Table 174 . Estimation of the Annual User Value for Saltwater Boating 

Off Taylor County, Florida, 1993-94 . . . . . . . . . . . . .206 

xvii 
LIST OF TABLES 

Table Caption Page 

Table 175 . Water Quality Indices for Selected Areas of Taylor County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . 208 

Table 176 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Taylor County, Florida in 1994 . . . . . . . . . 208 

Table 177 . Trends in Key Economic Aggregate Variables in Wakulla 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . . 212 

Table 178 . Trends in Components of Personal Income in Wakulla County, 

Florida, 1980-93 . . . . . . . . . . . . . . . . . . . . . . 213 

Table 179. Major Export Industries in Wakulla County, Florida and 

Their Contribution to Aggregate Personal Income, 1993 . . . 215 

Table 180 . Top Employers in Wakulla County, Florida and Products 

Produced, 1994 . . . . . . . . . . . . . . . . . . . . . . . 215 

Table 181 . Ecosystem-Sensitive Industries in Wakulla County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . 215 

Table 182 . Ecosystem-Insensitive Industries in wakulla County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . 216 

Table 183 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Wakulla County, Florida, 1994 . . . . . . . . . 217 

Table 184 . Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . . 218 

Table 185 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . . 219 

Table 186 . Estimated Expenditures by Saltwater Recreational Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . . 219 

Table 187 . Economic Value of Wetlands . . . . . . . . . . . . . . . . . 221 

Table 188 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Wakulla County, Florida. . . . . . 223 

Table 189 . An Inventory of Marine-Related Recreational Facilities 

in Wakulla County, Florida, 1995 (Public and Private) . . . 223 

Table 190 . Estimation of the Annual User Value for Saltwater Boating 

Off Wakulla County, Florida, 1993-94 . . . . . . . . . . . . 224 

Table 191 . Water Quality Indices for Selected Areas of Wakulla 

County, Florida . . . . . . . . . . . . . . . . . . . . . . 226 

xviii 
LIST OF TABLES 

Tab le Caption pace 

Table 192 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Wakulla County, Florida in 1994 . . . . . . . . .226 

Table 193 . Trends in Key Economic Aggregate Variables in Walton 

County, Florida, 1980-93 . . . . . . . . . . . . . . . . . .230 

Table 194 . Trends in Components of Personal Income in Walton County, 

Florida, 1980-93 . . . . . . . . . . . . . . . . . . . . . .231 

Table 195 . Major Export Industries in Walton County, Florida and 

Their Contribution to Aggregate Personal Income, 1993 . . . .233 

Table 196 . Top Ten Employers in Walton County, Florida and Products 

Produced, 1994 . . . . . . . . . . . . . . . . . . , . . . .233 

Table 197 . Ecosystem-Sensitive Industries in Walton County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . .234 

Table 198 . Ecosystem-Insensitive Industries in Walton County, 

Florida . . . . . . . . . . . . . . . . . . . . . . . . . . .234 

Table 199 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Walton County, Florida, 1994 . . . . . . . . . .235 

Table 200 . Estimated Number of Recreational Saltwater Fishermen 

in the Thirteen County Study Area, 1993-94 . . . . . . . . .237 

Table 201 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . . . . .237 

Table 202 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . . . .238 

Table 203 . Economic Value of Wetlands . . . . . . . . . . . . . . . . .240 

Table 204 . Key Saltwater Beaches in walton County, Florida . . . . . .241 

Table 205 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Walton County, Florida . . . . . . .242 

Table 206 . An Inventory of Marine-Related Recreational Facilities 

in Walton County, Florida, 1995 (Public and Private) . . . .242 

Table 207 . Estimation of the Annual User Value for Saltwater Boating 

Off Walton County, Florida, 1993-94 . . . . . . . . . . . . .243 

Table 208 . Water Quality Indices for Selected Areas of Walton County, 

Florida . . . . . . . . . . . . . - . . . - . . . . . - . . .245 

Table 209 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Walton County, Florida in 1994 . . . . . . . . . .245 

xix 
Introduction 

With the possibility of further oil and gas development and production and 

the associated potential for ecological, environmental and socioeconomic 

impacts, the U . S . Geological Survey, Biological Resources Division 

initiated a phased sequence of studies which will produce a comprehensive 

description of the dominant environmental processes, the ecological 

communities, and their potential sensitivities to development in the 

project study area (the Florida Panhandle and the Big Bend region) . As the 

first phase in the process of establishing a rational base for management 

decisions, the present project conducted a comprehensive search and 

integration of existing environmental and socioeconomic information . 

Presentation of project results are in two forms : 

" Comprehensive annotated bibliographies for each of the key topical 

areas of interest, and 

" An descriptive synthesis of information for each of the topical 

areas . 

One of the disciplines examined was socioeconomics, in particular as it 

relates to marine and environmental factors . One chapter in the Synthesis 

Report summarizes the socioeconomic conditions for the various coastal 

counties . That summary chapter was a distillation of separate reports for 

each county . 

To assure broader access to and use of overall project results, BRD decided 

to compile and distribute the individual county reports as a single 

separate project volume . Among the various county reports there may be 

some duplication where state-wide or regional factors were presented. 

However, by incorporating available material for each individual county, 

that report stands as a single source of information . 

In the subsequent material, each report section is a socioeconomic 

description for a separate coastal county in the study area . The Table of 

Contents indicates the order in which the material appears in this report . 

Each of these county socioeconomic summaries was prepared by Dr . Fred Bell 

of Florida State University . 
County Name : Bay, Florida 

Socioeconomic Comvonents and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

BAY .1 Introduction 

Bay County is located in the central section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figure 1) . 

It contains 764 square miles of land, ranking it 29th among the 67 counties 

in Florida . In 1990, Bay County had a population of 126,994, ranking it 

24th among Florida's counties . The population density was 176 people per 

square mile in 1990, ranking it 24th in Florida . Bay County has a 

relatively low median age of 33 .2 years, compared to the Florida-wide 

median of 36 .4 years . 

The population of Bay County had a per capita income of $16,779 in 1992, 

26th of the 67 Florida counties and 18% below the state-wide average of 

$19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income, and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem . For example, a retirement community 

may produce less toxic chemical discharges into waterbodies compared to an 

area where income is earned at a local chemical plant . For Bay County, an 

analysis of the sources of income will be discussed below, along with the 

interaction with the ecosystem . 

Bay County had 11 .20 of the households below the poverty level in 1989, 

which was higher than the State of Florida average of 9 .016 . In 1993, the 

unemployment rate was 9 .1°s (relative to a statewide average of 7 .0%), 

indicating a tight labor market . 

BAY .2 Trends in Population Income and Smployment in Bay County . 1980-93 

Table 1 shows the trend in key economic variables in Bay County from 1980 

through 1993 . Over this interval, resident population increased by 39 .40 

(3 .030 annually), which was the almost the same as the 39 .5% for Florida as 

a whole . Population increases that were induced primarily by industrial 

structure (i .e ., job creation) and natural amenities of the region place 

additional pressure on the carrying capacity of both living (e .g ., coastal 

fishery stocks) and non-living natural resources (e .g ., beaches) . 

Nominal aggregate personal income increased by 1980 from 1980 to 1993 

(Table 1) . Adjusted for inflation, real aggregate personal income 

increased by 66% (5 .1o annually) . Since real income growth outstripped the 

population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

have the financial resources to reduce negative externalities (e .g ., air 

and water pollution) which often accrue from population growth (Hall, 

1994) . 

3 
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ifF 

GE CREEK 

LAKE POWELL 

. . . 

h. . N ^ ;~ . y,; . 

',. 

ST. ANDREWS 

l 

GULF OF MEXICO `ANTHER SWAMP 

Z 

ST. ANDREWS BAY BASIN 

03140101 

WATER QUALITY 

GOOD 

AVERAGE WATER QUALITY ~ THREATENED 

1984-1993 STORET DATA FAIR 

WATERSHED ID NUMBERS LINK MAP TO TABLES POOR 

INDICATES QUALITATIVE ASSESSMENT 0 UNKNOWN 

Figure l . Map of Bay County, Florida, showing levels of water quality and 

areas of quality testing (St . Andrews Bay Basin)[from Bureau of 

Surface Water Management (1994b)] . 
Table 1 . Trends in Key Economic Aggregate Variables in Bay County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

gmployment3 

1980 98,400 $774,650 $940,109 45,984 

1981 100,300 885,723 974,393 47,850 

1982 103,600 972,497 1,007,769 49,429 

1983 105,700 1,069,819 1,074,115 51,259 

1984 108,900 1,202,531 1,157,393 56,002 

1985 112,900 1,324,518 1,230,965 59,970 

1986 117,300 1,438,672 1,312,657 62,101 

1987 120,600 1,517,601 1,335,916 63,614 

1988 122,500 1,616,398 1,366,355 65,358 

1989 124,800 1,741,854 1,404,721 66,668 

1990 127,300 1,908,861 1,460,490 70,129 

1991 130,000 2,054,880 1,508,722 71,111 

1992 133,400 2,191,853 1,562,262 72,234 

1993 137,200 2,311,669 1,559,831 74,228 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100. 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Bay County increased from 45,984 in 1980 to 74,228 

in 1993, a 61 .28 increase . The growth of jobs is stimulated in a region by 

what is known as the export base . Simply put, a region's growth is 

determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region ; income to retirees in Florida and injections 

of-Federal dollars to sustain military bases such as Eglin Air Force Base 

in Okaloosa County . Through a multiplier process, this export income 

sustains both direct export jobs (e .g ., civilians working for the military) 

and indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Bay County grew 

less rapidly than the measure of county output - real aggregate personal 

income - as local entrepreneurs introduced labor-saving technological 

devices to economize on the rising cost of labor. 

BAY .3 Trends in Various Welfare Measures in Bay County , 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing. A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is likely to be more able 

to protect the ecosystem than one which is highly dependent on income 

5 
maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Bay County derived 97 .60 of its personal 

income from earnings, retirement and capital income, compared to 98 .2% for 

the whole of Florida. Thus, the county is less likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem. The trends in the components of personal income per capita are 

shown for Bay County in Table 2 . 

BAY .4 Industrial Base : Bay County 

The "industrial base" for Bay County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy. The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county ; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy . If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

Table 2 . Trends in Components of Personal Income in Bay County, Florida, 

1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $7,875 $5,276 $114 $30 $1,420 $1,036 

1981 8,827 5,824 121 27 1,610 1,244 

1982 9,385 6,034 118 43 1,783 1,408 

1983 10,118 6,547 116 59 1,912 1,484 

1984 11,038 7,327 121 34 1,945 1,610 

1985 11,731 7,770 118 38 2,113 1,692 

1986 12,268 8,064 110 47 2,173 1,874 

1987 12,586 8,284 108 43 2,295 1,855 

1988 13,198 8,690 132 39 2,450 1,887 

1989 13,961 8,892 154 44 2,697 2,174 

1990 14,994 9,547 187 52 2,969 2,239 

1991 15,803 10,085 232 70 3,247 2,230 

1992 16,426 10,395 305 120 3,457 2,150 

1993 16,852 10,628 293 110 3,642 2,180 

Source : BEA (1995) 

6 
of personal income generated by an industry (e .g ., 10%) in an area, 

compared to the same percentage nationally (e .g ., 0 .50), assuming the 

nation consumes all it produces - no imports or exports . This is rather 

simplistic, but it does serve as an indicator of which industries are 

predominately export . This figure, the location quotient (LQ), would be : 

(1) LQ = l0a/ .5o = 20 

Thus, 95% would be in export or 

(2) 1 - LQ-1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 3 shows the main identified export industries and their contribution 

to personal income in Bay County . This county depends primarily on 

tourism, retirement, manufacturing, fishing and the military for its 

economic survival . Some of the largest individual employers in Bay County 

have, from time to time, had negative impacts on the ecosystem . For Bay 

County, Table 4 shows the top ten employers, along with the products they 

produce that may generate conflicts with the environment . Products such as 

oil processing, pulp and paper, and boatmaking must be rigorously 

controlled or they will reduce water and air quality . Historically, Bay 

County has had problems with industries located in this county . Wastewater 

from manufacturing plants and construction runoff have led to some water 

quality problems, however, in 1993, the EPA reported that the companies in 

Bay County did not discharge any toxic chemicals into the surface water . 

BAYS Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Bay County, the industries shown in Table 5 fall into this 

category . 

The Bay County economy is heavily based upon timber which is harvested and 

processed regionally into various paper-based products . This county has a 

deep-water port and serves as a naval and air station for the U.S . military 

and a port for a variety of materials and products . Tourism is also 

important, with Panama City Beach being a major resort area . All of these 

economic activities create various kinds of waste that is a point or 

nonpoint discharge into rivers and coastal waters . These industries are 

primarily involved in the export sector and therefore are critical to this 

coastal county . 

BAY .6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of Citrus County is primarily 

composed of ecosystem-insensitive industries, those which have relatively 

little impact on the environment . These are shown in Table 6 . 

7 
Table 3 . Major Export Industries in Bay County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings % of Personal LQ* 

(000) Income 11 

Tourism 

Hotels and Lodging $42,606 1 .84 2 .7 

Eating and Drinking Places 71,855 3 .1 1 .9 

Other Retail Sales 220,661 9 .44 1 .0 

Retirement 

Real Estate 24,222 .71 1 .5 

Construction 103,232 4 .45 1 .21 

Manufacturing (Assorted) 23,196 1 .0 .2 

Water Transportation 11,720 .5 4 .0 

Fishing (Commercial) 2,082 .1 2 .9 

Federal Employees 137,088 5 .9 2 .5 

Military (Tyndall AFB & US 170,262 7 .4 7 .9 

Naval Reservation) 

*LQ =Location quotient . See Text . 

Source : BEA (1995) 

Table 4 . Top Ten Employers in Bay County, Florida and Products Produced, 

1994 . 

Employer Employees 

1 . Sunshine Food Store, Grocery 725 

2 . HCA Gulf Coast Hospital, Health Care 650 

3 . Hilton, Inc ., Resort 610 

4 . Sallie Mae, Brokers and Loans 605 

5 . Marriott Bay Point, Resort 450 

6 . Stone Container, Linerboard 580 

7 . Arizona Chemical, oil 410 

8 . Edgewater Beach Resort, Resort 284 

9 . Bay Point Resort, Resort 221 

10 . Berg Pipe, Line Pipe 200 

Sub-Total 4,735 

Total 74,228 

Percent of Total 6 .3% 

Source : Florida Department of Commerce (1994) 

8 
Table 5 . Ecosystem-Sensitive Industries in Bay County, Florida . 

Industry Earnings ($000) 

1 . Manufacturing (Assorted) 

Non-Durable $53,596 

Durable 41,383 

2 . Water Transportation 11 .720 

Sub-Total 

Total Earnings (Non-Farm) 

Percent of Total 

$106,699 

$2,311,669 

4 .6 

Source : BEA (1995) 

Table 6 . Ecosystem-Insensitive Industries in Bay County, Florida. 

11 Industry Earnings ($000) 11 

1 . Tourism (Hotels, Retail Stores, etc .) 

2 . Retirement 

3 . Military/Federal Government 

Sub-Total 

Total Earnings 

Percent of Total 

$335,122 

105,564 

307 .350 

$748,036 

$2,311,669 

329. 

Source : Table 3 

In general, industries such as tourism and retirement have a less adverse 

impact on local ecosystem health than other industries in Bay County . Over 

the 1969-93 period, ecosystem-insensitive industries grew faster than the 

ecosystem-sensitive industries, meaning that recent economic growth is less 

of a threat to the marine environment . 

BAY .7 Commercial Fishery Landings in Bay County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Bay County . 

Three categories of fishery products are found : (1) finfish ; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $6 .7 million worth of commercial fishery 

products were landed in Bay County at the ex vessel level (Table 7) . 

Finfish and shrimp account for 89% of this value . Among the finfish, 

9 
Table 7 . Ex Vessel Landings and Value of Commercial Fishery Landings in Bay 

County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Yellowfin Tuna 397,229 $973,211 .60 

Gag Grouper 328,111 731,687 .56 

Ladyfish 1,317,318 526,927 .19 

Red Grouper 191,580 337,180 .81 

King Mackerel 231,791 329,143 .22 

Red Snapper 107,337 259,755 .55 

Bluerunner 649,037 240,143 .69 

Round Scad 739,576 192,289 .75 

Swordfish 49,577 159,142 .17 

All Others 3,391,051 1 .384 .239 .93 

Total $5,291,394 .68 

Invertebrates 

Blue Crabs 527,762 $340,041 .83 

Oysters 314,109 389,495 .16 

Calico Scallops 1,872 1,067 .04 

Squid 2,759 1,020 .83 

Spanish Lobster 494 854 .62 

All others 3 .266 .60 

Total $733,612 .16 

Shrimp (Total) 364,141 645 .191 .78 

Grand Total $6,670,198 .62 

* State average ex vessel price used . 

Source : FDEP (1994) 

yellowfin tuna was the leading species as measured by value . Brown shrimp, 

which depends on wetlands during a phase of its life cycle, was the 

dominant shrimp species . Among the 13 counties in the study area, Bay 

County ranked 2nd in the ex vessel value of all commercial fishery 

landings . 

Even though the ex vessel value does not include value added in processing 

and distribution, commercial fishing is a relatively large component of the 

economic base of Bay County, where aggregate personal income was $2 .3 

billion in 1993 . Over the last fourteen years, commercial fishery landing 

has decreased by 15% while the ex vessel value of the catch has increased 

by 7 .5% . When adjusted for inflation, the value of landings decreased by 

300 (FDNR, 1980) . 

BAY .8 Recreational Fishins 

Recreational fishing data are not collected on a county level . Recently 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively that engage in saltwater 

recreationalfishing in Florida. In Milon and Thunberg (1992), there is 

10 
some regional breakdown embracing the present study area from Hernando 

County north to Escambia County . Such regions include both coastal and 

interior counties . As an approximation, these regional averages can be 

applied to the individual counties . Bell (1993) has only statewide averages 

for tourist saltwater anglers, which are also used as an approximation . In 

an earlier study, Bell, et al . (1982) found that expenditures and days per 

tourist angler for Region I (i .e ., Escambia to Jefferson County) were about 

40-50% higher than the statewide average. Thus, using the latest study of 

Bell (1993), statewide figures may be conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county (Table 8) . Bay County had 13,265 resident anglers purchasing a oneyear fishing license . It should be pointed out that purchase of a license 

in a county does not ensure that one is a resident of that county, but 

informal conversations with Florida Dept . of Environmental Protection 

personnel suggest little bias is associated with that assumption . 

Nonresidents are those that purchased saltwater fishing licenses in noncoastal counties . Such licenses were pro-rated to coastal counties in 

close geographical proximity to each county, using personal judgment, as 

shown in Table 8 . Finally, tourists must purchase a license, and the 

number is shown for the counties in the study area . This may underestimate 

tourist saltwater anglers since tourists may buy a license in an interior 

county and use it in one or more of the coastal counties . 

Table 9 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 8 . The Milon and Thunberg (1992) and Bell (1993) estimates are shown 

as nine and four days (per year) for residents and tourist anglers, 

respectively . Bay County showed a fishing effort of 232,214 days . 

Finally, Table 10 is derived from Table 8 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $18,056,788 in Bay County in 1993-94 . 

Many assumptions were made to arrive at these estimates, however, these 

figures are believed to indicate an order of magnitude and relative 

ranking, and may actually be conservative . That is, it is not surprising 

that Bay (Panama City) and Citrus (Crystal River) counties are the top two 

counties for saltwater recreational fishing expenditures . Multiplier 

effects of nonresidents and tourists were not considered . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing. There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell, et al . (1982) have estimated the per day value 

11 
Table 8 . Estimated Number of Recreational Saltwater Fishermen in the 

Thirteen County Study Area, 1993-94 . 

County Residents Nonresident Z Tourist3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11 .685 6 .926 .5,312 

Total II 

76,383 29,462 94,370 

N, 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

' Non-resident (out of state) saltwater fishing licenses for one year; 

seven days and three days . 

Table 9 . Estimated Number of Saltwater Recreational Days (Fishing Effort) 

in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresidents 

Tourist2 Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167,499 21,248 188,747 

Total 952,605 377,480 1,330,085 

1 9 days per angler year and Table 8 . See Milon and Thttnberg (1992) . 

2 4 days per angler year and Table 8 . See Bell (1993) . 

12 
Table 10 . Estimated Expenditures by Saltwater Recreational Fishermen in the 

Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Touristz Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056 788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8,890 .475 2,337 .280 11,227,755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 8 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table e multiplied by $440 .00 per angler . 

of saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists respectively (in 1994 dollars) . The annual flow 

of value for Bay County can be computed as follows : 

Residents 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 7,011 = $2 .6 million 

Tourists 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 4,121 = $0 .8 million . 

Thus, saltwater recreational fishing generates $10 .4 million per year in 

Bay County with a capitalized value of $346 million using a 3% discount 

rate (i .e ., $10 .4 million = .03) . 

BAY.9 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing . The literature indicates few attempts to 

statistically link marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property, where actual owners cannot capture the implied rental value of 

13 
such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets, such as 

residential development and agricultural use. Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated . This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 11 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida. This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch. 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

Table 11 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 - $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D .C . 

14 
estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Bay County has 8,200 acres of salt marsh 

(NOAA, 1991), which would be worth $43 .6 million ($5,316 x 8,200) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by Bay County wetlands . 

BAY .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier . Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . Table 12 lists the key beaches for Bay 

County . 

In 1984, Bell and Leeworthy (1986) estimated expenditures per day of $12 

(1994 dollars) and $30 (1994 dollars) for residents and tourists, 

respectively, on saltwater beach-related costs such as lodging, food and 

drink, etc . in Pensacola, Florida. These estimates will be used for all 

counties in the study area as an approximation since no recent studies have 

been undertaken . 

15 
Table 12 . Key Saltwater Beaches in Bay County, Florida .* 

Western District 

Environmentally Endangered Lands : 

Panama City Beach and Pier 

Bay County Pier and Park 

Central District 

St . Andrews State Recreational Area 

Eastern District 

Mexico Beach 

*In Bay County alone, the University of West Florida (1985b) 

reported 66 individual saltwater beaches which were 26 .8 miles in 

length and 14 .1 million square feet (public and private) . 

Source : University of West Florida (1985a) 

Using the CV technique, Leeworthy, et al . (1989) found that Escambia, 

Franklin and Bay Counties had an averaged user value of about $3 .0 per day 

(in 1994 dollars) for residents and tourists . In a comprehensive study of 

Florida beaches, the University of West Florida (1985b) projected that Bay 

County would have 2,536,750 saltwater beach days per year in 1990 for the 

beaches listed in Table 12 . By multiplying the user value per day of $3 

times the estimated number of saltwater beach days, the annual flow of 

value is $7 .61 million . These are not actual expenditures, but an estimate 

of annual recreational benefits to beach users . The capitalized value of 

this value flow at a real discount rate of 39. is over $253 million - the 

asset value of the beach . 

Finally, beach-related spending in Bay County in 1990 can be calculated in 

the following manner [with the percentage of residents and tourists taken 

from the University of West Florida (1985b) study] : 

(g Residents) x (Beach Days/Yr .) x (Expenditures/day) 

36 x 2,536,750 x $12 = $10 .9 million 

(o Tourists) x (Beach Days/Yr .) x (Expenditures/day) 

64 x 2,536,750 x $30 = $48 .7 million 

Combined, saltwater beaches in Bay County attracted an estimated $59 .6 

million in beach-related spending in 1990, with tourists accounting for 82% 

of this spending . 

Table 13 identifies three ecological resources that are an asset to Bay 

County and induce a considerable level of economic activity in this 

region . 

16 
Table 13 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Bay County, Florida . 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year' 

Asset Value 

(Millions )2 

Commercial Fishing $6 .73 N/A N/A 

Recreational Fishing $114 $10 .45 $3465 

Saltwater Marsh s N/A .207 6 43 .6 6 

Saltwater Beaches $59 .66 $7 .616 $253 .06' 

Marine Boating' N/A .867' $28 .9' 

Nonmarket value per year 

#1 divided by .03 = Asset Value 

Table 7, ex vessel price 

Table 10, retail price 

To commercial fishery landings only 

See text for discussion 

See Table 15 

BAY .11 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 14 is an 

inventory of these water-dependent facilities in Bay County . Piers, 

boardwalks and jetties facilitate bank recreational fishing, beach use and 

other outdoor recreational activities . 

As an outdoor recreational activity, boating makes use of common property 

water resources . Bell (1995) found that the user value per day, expressed 

in 1994 dollars, is worth $3 .56 more if a marina is used (i .e ., $5 .02 less 

$1 .48) rather than a boat ramp . These are Florida-wide values and may or 

may not be good estimates for Bay County but are used for purposes of 

illustration . 

Bay County has 55 saltwater boat ramp lanes and 2,314 wet slips and dry 

racks, as shown in Table 14 . The number of private docks from which to 

launch pleasure craft is unknown . Combining data from Bell et al . (1982) 

and Bell (1995), the annual user value from boating in the Gulf of Mexico 

off Bay County is estimated and shown in Table 15 . This value is about 

$ .87 million . 

Recreational boating in marine waters is rapidly growing in Bay County . 

Such boating can affect coastal water quality (e .g ., inadequate pumping out 

facilities) as well as adding user value to those using coastal water 

resources . From the FDEP (1983-1992) and Bell (1995) studies, pleasure 

boat registrations in Bay County grew as follows, with projected (P) 

numbers included : 

17 
Table 14 . An Inventory of Marine-Related Recreational Facilities in Bay 

County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number 24 

b . Length (all) (LFT)* 12,236 

2 . Boardwalks/Catwalks 

a . Number 25 

b . Length (all) (LFT)* 7,220 

3 . Jetties 

a . Length (all) (LFT)* 1,300 

Boating 

1 . Boat Ramps 

a . Number 40 

b . Total Lanes 55 

2 . Marinas 

a . Total 28 

b . Slips/Moorings 1,431 

c. Dry Storage 883 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

Table 15 . Estimation of the Annual User Value for Saltwater Boating Off Bay 

County, Florida, 1993-94 . 

Facility 

Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

I1 . Marinas 

$312,274 = $5 .021 x 13,0962 x .193 x 254 

I 2 . Boat Rams 

$324,650 = $1 .481 x 13,096 x .674 x 25 

I3_ Private Docks 

$230,097 = $5 .025 x 13,096 x .14 x 25 

Total Annual User Value = $867,021 

*Asset Value = 867,021 = .03 = $28 .9 million 

Bell (1995), Florida-wide value 

z FDEP (1992), Bay County 

Bell et al . (1982), northwest Florida 

Bell (1995), Bay County 

Assumed $/day same for marinas and private docks 

18 
1983 

1984 

1985 

1986 

1987 

1988 

1989 

1990 

1991 

1992 

2000 

2005 

2010 

10,051 

10,400 

10,966 

11,602 

12,073 

12,525 

12,844 

12,769 

12,997 

13,096 

15,131 (P) 

16,773 (P) 

18,550 (P) 

BAY.12 Water Oualitry the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is 

manifested in the water quality surrounding the region . Florida's major 

surface water quality problems come from urban stormwater runoff, 

agricultural runoff, domestic wastewater, industry wastewater, and 

hydrological changes such as draining and filling wetlands . 

There are three sources of information on local water quality surrounding 

Bay County . First, the Federal Water Pollution Control Act requires the 

state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Bay County . 

Two indices are used in the 3o5(b) report for measuring surface water 

quality : the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen-demanding 

substances (BOD), nutrients, bacteria, and macroinvertebrate diversity . 

The TSI measures the potential for algal or aquatic weed growth . Although 

the present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality . 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Bay County, St . 

19 
Andrews Bay has been selected for a brief summary of the current state of 

water quality in this region of the study area (see Figure 1) . 

The St . Andrews Bay Basin is in the central region or the panhandle. 

Major pollution sources are from chemical processing, pulp and paper mills 

and urban runoff . Arizona Chemical and Stone Container are primarily 

responsible for the manufacturing wastewater . Panama City, a high-density 

population center, is responsible for the urban pollution. There are many 

other possible sources of pollution into the water in Bay County . The 

Majette Landfill is located in one bayou. Development along the shorelines 

and recreation activities also have negative effects . A recent study found 

high levels of lead, mercury, DDT, and PCB's in Watson Creek . 

The Panama City Beach area has water quality problems with decreased 

dissolved oxygen levels . The most significant threat is due to industrial 

rather than domestic waste . This problem has been addressed recently and 

improvements are expected . Other pollution sources include small, package 

plants and septic tanks which empty into ditches leading into St . Andrews 

Bay, highway and construction runoff and runoff from logging operations . 

The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . Table 16 indicates that in 

1994, two companies (Stone Container and Arizona Chemical) discharged toxic 

substances in and around the surface water of Bay County . The WQI and TSI 

for selected areas are listed in Table 17 . 

Shellfish harvesting has been closed in 35,149 acres in the St . Andrews 

Bay area, and opened conditionally in 37,359 acres in the same areas, 

indicating significant coliform levels in over 51s of the beds . 

Table 16 . Toxic Chemical Releases Into Surface Water by Firms Located in 

Bay County, Florida in 1994 . 

Company SIC Discharge Mainl 

1 . Stone Container 2,621 N/A 

(Pulp and Paper) 

2 . Arizona Chemical 2,824 N/A 

Total 

Leading chemical released based on pounds . 

Source : EPA Toxic Release Inventory, unpublished data, 1994 . 

20 
Table 17 . Water Quality Indices for Selected Areas of Bay County, Florida . 

II Water Areas : St . Andrews Bay Water Quality Indices* II 

Water Body Type : Estuary WOI TSI 

3 Walker Bay -- 52 

4 Direct Runoff -- 12 

6 East Bay (E) -- 32 

7 California Bayou -- 46 

8 East Bay (W) -- 36 

9 St . Andrews Bay (mouth) -- 31 

10 Pitts Bay -- 24 

11 Laird Bayou -- 43 

14 Massalina Bayou -- 37 

15 Parker Bay -- 41 

16 St . Andrews Bay -- 25 

17 Woodlawn Canal -- 37 

18 Watson Bayou -- 49 

19 Direct Runoff -- 35 

21 Pretty Bayou -- 37 

22 Robinson Bayou -- 28 

24 Mill Bayou -- 46 

25 Goose Bayou -- 53 

26 St . Andrews Bay (N) -- 35 

27 Beatty Bayou -- 55 

29 Direct Runoff -- 39 

30 North Bay (N) -- 37 

31 North Bay (N) -- 50 

33 West Bay -- 38 

35 Direct Runoff -- 48 

Water B ody Type : Lake 

34 Lake Powell -- 24 

44 Merial Lake -- 22 

48 L . Gap Pond -- 20 

49 Compass Lake Outlet -- 22 

Water B ody Type : Stream 

20 Galloway Creek 20 -- 

28 Bayou George Creek 34 -- 

32 Beefwood Branch 17 -- 

38 So . Fk . Little Bear Creek 20 -- 

40 Crooked Creek 24 -- 

42 Burnt Mill Creek 23 -- 

43 Bear Branch 1$ -- 

45 Little Bear Creek 18 -- 

46 Cedar Creek 18 -- 

47 Econfina Creek 15 -- 

* Higher values indicate lower water quality 

21 

Socioeconomic Components and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

CIT .l Introduction 

Citrus County is located in southeastern section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figure 2) . 

It contains 584 square miles of land, ranking it 47th among the 67 counties 

in Florida . In 1990, Citrus County had a population of 93,512, ranking it 

30th among Florida's counties . The population density was 173 people per 

square mile in 1990, ranking it 27th in Florida . Citrus County has a 

median age of 50 .8 years, very high when compared to the Florida-wide 

median of 36 .4 years . 

The population of Citrus County had a per capita income of $15,290 in 1992, 

35th of the 67 Florida counties and 23% below the state-wide average of 

$19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income, and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem . For example, a retirement community 

may produce less toxic chemical discharges into waterbodies compared to an 

area where income is earned at a local chemical plant . For Citrus County, 

an analysis of the sources of income will be discussed below, along with 

the interaction with the ecosystem . 

Citrus County had 8 .5% of the households below the poverty level in 1989, 

which was lower than the State of Florida average of 9 .0% . In 1993, the 

unemployment rate was also 8 .50 (relative to a statewide average of 7 .0%), 

indicating a slack labor market . 

CIT .2 Trends in Population Income and Emvloyment in Citrus County, 

1980-93 . 

Table 18 shows the trend in key economic variables in Citrus County from 

1980 through 1993 . Over this interval, resident population increased by 

83% (6 .4o annually), which was rapid when compared to 39 .5% for Florida as 

a whole . Population increases that were induced primarily by industrial 

structure (i .e ., job creation) and natural amenities of the region place 

additional pressure on the carrying capacity of both living (e .g ., coastal 

fishery stocks) and non-living natural resources (e .g ., beaches) . 

Nominal aggregate personal income increased by 364% from 1980 to 1993 . 

(Table 18) . Adjusted for inflation, real aggregate personal income 

increased by 130% (10% annually) . Since real income growth outstripped the 

population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

will have the financial resources to reduce negative externalities (e .g ., 

air and water pollution) which often accrue from population growth (Hall, 

1994) . 

23 
River 

GULF of 

PITHLACHASCOTEE 

ANCLOTE RIVER 

TAMPA BAY 

CANAL (SOUTH) 

ST JOE CREEK 

WATER QUALITY 

CRYSTAL RIVER TO ST. PETE GOOD 03100207 

THREATENED 

AVERAGE WATER QUALITY FAIR 

19841993 STORET DATA _ POOR WATERSHED ID NUMBERS LINK MAP TO TABLES 

INDICATES QUALITATIVE ASSESSMENT O UNKNOWN 

Figure 2 . Map of Citrus County, Florida, showing levels of water quality 

and areas of quality testing (Crystal river to St . Pete)[from 

Bureau of Surface Water Management (1994c)] . 

24 
Table 18 . Trends in Key Economic Aggregate Variables in Citrus County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

EmPloyment3 

1980 55,800 $385,897 $468,322 15,525 

1981 59,600 469,343 516,329 17,449 

1982 62,800 528,002 547,152 18,450 

1983 66,800 597,726 600,127 19,173 

1984 70,600 722,208 695,099 21,101 

1985 74,500 858,573 797,930 23,218 

1986 78,700 949,791 866,597 24,198 

1987 82,700 1,034,321 910,494 26,890 

1988 85,900 1,112,777 940,640 28,120 

1989 90,000 1,254,554 1,011,737 29,064 

1990 94,600 1,366,764 1,045,726 30,553 

1991 97,500 1,428,765 1,049,020 31,040 

1992 100,100 1,491,622 1,063,166 31,404 

1993 101,900 1,558,130 1,078,291 32,585 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Citrus County increased from 15,525 in 1980 to 32,585 

in 1993, a 110% increase . The growth of jobs is stimulated in a region by 

what is known as the export base . Simply put, a region's growth is 

determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region, income to retirees in Florida and injections 

of Federal dollars to sustain military bases such as Eglin Air Force Base 

in Okaloosa County . Through a multiplier process, this export income 

sustains both direct export jobs (e .g ., civilians working for the military) 

and indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Citrus County 

grew less rapidly than the measure of county output - real aggregate 

personal income - as local entrepreneurs introduced labor-saving 

technological devices to economize on the rising cost of labor . 

CIT .3 Trends in Various Welfare Measures in Citrus County , 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing. A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is likely to be more able 

to protect the ecosystem than one which is highly dependent on income 

maintenance and unemployment insurance, since the former is taxable while 

25 
the latter is not . In 1993, Citrus County derived 97 .9% of its personal 

income from earnings, retirement and capital income, compared to 98 .28 for 

the whole of Florida. Thus, the county is less likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem. The trends in the components of personal income per capita are 

shown for Citrus County in Table 19 . 

CIT .4 Industrial Base : Citrus County 

The "industrial base" for Citrus County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy . The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy . If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., l00) in an area, compared 

to the same percentage nationally (e .g ., 0 .50), assuming the nation 

Table 19 . Trends in Components of Personal Income in Citrus County, 

Florida, 1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $6,912 $2,207 $66 $19 $2,029 $2,096 

1981 7,870 3,030 69 18 2,313 2,440 

1982 8,403 3,230 73 34 2,582 2,484 

1983 8,953 3,332 75 37 2,816 2,695 

1984 10,225 3,768 67 29 2,994 3,367 

1985 11,528 4,424 64 22 3,210 3,808 

1986 12,066 4,432 66 24 3,290 4,253 

1987 12,514 4,875 71 22 3,396 4,150 

1988 12,959 4,949 85 30 3,508 4,386 

1989 13,932 5,235 101 33 3,657 4,907 

1990 14,442 5,558 120 48 3,777 4,939 

1991 14,650 5,625 156 78 4,033 4,731 

1992 14,901 5,920 210 116 4,225 4,429 

1993 15,295 6,149 215 97 4,406 4,428 

Source : BEA (1995) 

26 
consumes all it produces - no imports or exports . This is rather 

simplistic, but it does serve as an indicator of which industries are 

predominately export . This figure, the location quotient (LQ), would be : 

(1) LQ = 100/ .5% = 20 

Thus, 95g would be in export or 

(2) 1 - LQ-1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 20 shows the main identified export industries and their contribution 

to personal income in Citrus County . This county depends primarily on 

fishing, manufacturing, utilities and retirement for its economic survival . 

Some of the largest individual employers in Citrus County have, from time 

to time, had negative impacts on the ecosystem . For Citrus County, Table 

21 shows the top ten employers, along with the products they produce that 

may generate conflicts with the environment . Industries such as utilities 

and manufacturing must be rigorously controlled or they will reduce water 

and air quality . In 1993, the EPA reported that the companies in Citrus 

County discharged no toxic chemicals into surface water (Lester, 1995) . 

CIT .5 Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Citrus County, the industries shown in Table 22 fall into 

this category . 

The Citrus County economy is heavily based upon manufacturing . This 

economic activity creates various kinds of waste that is a point or 

nonpoint discharge into rivers and coastal waters . This industry is 

primarily involved in the export sector and therefore is critical to this 

coastal county . 

CIT .6 8cosvstem-Insensitive Industr 

As indicated by earnings, the economic base of Citrus County is primarily 

composed of ecosystem-insensitive industries, those which have relatively 

little impact on the environment . These are shown in Table 23 . 

In general, an industry such as retirement has a less adverse impact on 

local ecosystem health than other industries in Citrus County . Over the 

1969-93 period, the ecosystem-insensitive industries grew faster than the 

ecosystem-sensitive industries, meaning that the growth in the Citrus 

County economy is not in conflict with the environment . 

CIT .7 Commercial Fishery Landings in Citrus County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

27 
Table 20 . Major Export Industries in Citrus County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings 

(000) 

% of Personal 

Income 

LQ* 

Fishing $945 .06 1 .95 

Manufacturing 

Printing 4,179 .26 PJ* 

Chemicals 311 N/A Pi 

Lumber N/A N/A Pi 

Electrical Equipment N/A N/A Pi 

Transportation Equipment N/A N/A Pi 

Utilities (Crystal River Power N/A N/A PJ 

Plant) 

Retirement 315,763 20 Pi 

Construction 66,524 4 Pi 

*LQ = Location quotient . See Text . 

*PJ = Professional Judgment . 

Source : BEA (1995) 

Table 21 . Top Ten Employers in Citrus County, Florida and Products 

Produced, 1994 . 

Employer Employees 

1 . Florida Power Corporation, Utilities 1,279 

2 . Citrus Memorial Hospital, Health Care 903 

3 . Seven Rivers Hospital, Health Care 530 

4 . Winn-Dixie, Grocery 519 

5 . Sunshine Material Corporation, Contractor 330 

6 . WalMart, Retail Store 295 

7 . Publix, Grocery 283 

8 . Proline, Boat Manufacturing 265 

9 . Kash-N-Karry, Grocery 201 

10 . K-Mart, Retail Sales 197 

Sub-Total 4,802 

Total 32,585 

Percent of Total 15% 

Source : Florida Department of Commerce (1994) 

28 
Table 22 . Ecosystem-Sensitive Industries in Citrus County, Florida . 

Industry Earnings ($000) 

1 . Manufacturing $20,040 

2 . Utilities N/A 

3 . Construction 66,524 

Sub-Total $86,564 

Total Earnings (Non-Farm) $493,386 

Percent of Total 17 .58 

Source : BEA (1995) 

Table 23 . Ecosystem-Insensitive Industries in Citrus County, Florida . 

Industry Earnings ($000) 

1 . Retirement $315,763 

2 . Fisheries 945 

Sub-Total $316,708 

Total Earnings $1,558,130 

Percent of Total 200 

Source : Table 20 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Citrus County . 

Three categories of fishery products are found : (1) finfish; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $6 .5 million worth of commercial fishery 

products were landed in Citrus County at the ex vessel level (Table 24) . 

Finfish and shrimp account for 310 of this value. Among the finfish, red 

grouper was the leading species as measured by value. Stone crabs account 

for 609. of the total ex vessel value of the landings . Brown shrimp, which 

depends on wetlands during a phase of its life cycle, was the dominant 

shrimp species . 

Although the ex vessel value does not include value added in processing and 

distribution, commercial fishing is a relatively small component of the 

economic base of Citrus County, where aggregate personal income was $1 .5 

billion in 1993 . Over the last fourteen years, commercial fishery landing 

has increased by 7 .7% while the ex vessel value of the catch has increased 

by 2620 . When adjusted for inflation, the value of landings changed by 

102% (FDNR, 1980) . 

29 
Table 24 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Citrus County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Red Grouper 416,997 $733,914 .69 

Black Mullet 818,443 384,668 .22 

Black Grouper 53,314 110,359 .98 

Crevalle Jack 183,208 60,458 .64 

Spotted Sea Trout 44,766 53,719 .20 

Porgies 25,028 23,025 .76 

Sheepshead 22,437 10,281 .57 

Grunts 22,437 10,545 .39 

Permit 8,359 10,281 .57 

Ladyfish 23,325 9,330 .00 

All Others 126,492 83,735 . a 

( Total $1,491,869 .54 

Invertebrates 

Blue Crabs 932,220 $596,645 .69 

Stone Crabs 732,192 3,885,951 .30 

Octopus 2,919 2,714 .67 

Spanish Lobster 192 332 .16 

Total $4,485,703 .78 

Shrimp (Total) 214,055 489 .468 .61 

Grand Total $6,467,037 .93 

* State average ex vessel price used . 

Source : FDEP (1994) 

CIT .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently, 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively, that engage in saltwater recreational 

fishing in Florida . In Milon and Thunberg (1992), there is some regional 

breakdown embracing the present study area from Hernando County north to 

Escambia County . Such regions include both coastal and interior counties . 

As an approximation, these regional averages can be applied to the 

individual counties . Bell (1993) has only statewide averages for tourist 

saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

angler for Region I (i .e ., Escambia to Jefferson County) were about 40-50% 

higher than the statewide average . Thus, using the latest study of Bell 

(1993), statewide figures may be conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county . Citrus County had 11,685 resident anglers purchasing a one-year 

fishing license . It should be pointed out that purchase of a license in a 

county does not ensure that one is a resident of that county, but informal 

30 
conversations with Florida Dept . of Environmental Protection personnel 

suggest little bias is associated with that assumption . Nonresidents are 

those that purchased saltwater fishing licenses in non-coastal counties . 

Such licenses were pro-rated to coastal counties in close geographical 

proximity to each county, using personal judgment . This is shown in Table 

25 where nonresidents are shown in the second column . Finally, tourists 

must purchase a license, and the number is shown for the counties in the 

study area . This may underestimate tourist saltwater anglers since 

tourists may buy a license in an interior county and use it in one of the 

coastal counties . 

Table 26 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 25 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers, 

respectively . Citrus County showed a fishing effort of 188,747 days . 

Finally, Table 27 is derived from Table 25 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $11,227,755 in Citrus County in 1993-94 . Many assumptions 

were made to arrive at these estimates, however, these figures are believed 

to indicate an order of magnitude and relative ranking, and may actually be 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . Multiplier effects of nonresidents and 

tourists were not considered . 

Table 25 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents Nonresident2 Tourist3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11,685 6,926 5,312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

' Non-resident (out of state) saltwater fishing licenses for one year ; 

seven days and three days . 

31 
Table 26 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Tourist2 Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167,499 21"248 188 .747 

Total 952,605 377,480 1,330,085 

1 9 days per angler year and Table e . See Milon and Thunberg (1992) . 

Z 4 days per angler year and Table 8 . See Bell (1993) . 

Table 27 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Touristz Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8,890,475 2 .337,280 11,227,755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 9 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 8 multiplied by $440 .00 per angler . 

32 
If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing . There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Citrus County can be computed as follows : 

(value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 18,611 = $7 .0 million 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 5,312 = $1 .0 million . 

Thus, saltwater recreational fishing generates $8 .0 million per year in 

Citrus County with a capitalized value of $267 million using a 3% discount 

rate (i .e ., $8 million = .03) . 

CIT .9 Fisheries and wetlands 

wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing. The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property, where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets, such as 

residential development and agricultural use. Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated. This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 28 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch. 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

33 
Table 28 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

were estuarine-dependent. A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida at $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

34 
production elasticity of 0 .19) . Citrus County has 27,400 acres of salt 

marsh (NOAA, 1991), which would be worth $145 million ($5,316 x 27,400) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by Citrus County wetlands . 

CIT .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier . Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . The Citrus County coast is primarily 

saltwater marsh . The University of West Florida (1985b) reported one 

saltwater beach which is 0 .2 miles in length with 142,500 square feet . 

Since there is very little user information, and because of the relatively 

small importance of beaches in this county, the value was not estimated . 

Some ecological resources have been identified that are an asset to Citrus 

County and induce a considerable level of economic activity (Table 29) . 

CIT .11 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 30 is an 

inventory of these water-dependent facilities in Citrus County . Piers, 

boardwalks and jetties facilitate bank recreational fishing, beach use and 

other outdoor recreational activities . 

As an outdoor recreational activity, boating makes use of common property 

water resources . Expressed in 1994 dollars, Bell (1995) found that the 

user value per day is worth $3 .56 more if a marina is used (i .e ., $5 .02 

less $1 .48) rather than a boat ramp . These are Florida-wide values and may 

or may not be good estimates for Citrus County, but are used for purposes 

of illustration . 

Citrus County has 15 saltwater boat ramp lanes and 49 wet slips and dry 

racks, as shown in Table 30 . The number of private docks from which to 

launch pleasure craft is unknown . Combining data from Bell et al . (1982) 

and Bell (1995), the annual user value from boating in the Gulf of Mexico 

off Citrus County is estimated and shown in Table 31 . The annual user 

value for marine boating off Citrus County is about $ .99 million . 

35 
Table 29 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Citrus County, Florida . 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year 1 

Asset Value 

(Millions )2 

Commercial Fishing $6 .43 N/A N/A 

Recreational Fishing $11 .2' $8 .05 $1455 

Saltwater Marshs N/A .207 6 145 6 

Saltwater Beaches N/A6 N/A' N/A6 

Marine Boating' N/A $ .991' $33 .05' 

1 Nonmarket value per year 

z #1 divided by .03 = Asset Value 

Table 7, ex vessel price 

Table 10, retail price 

5 To commercial fishery landings only 

See text for discussion 

See Table 14 

Table 30 . An Inventory of Marine-Related Recreational Facilities in 

Citrus County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number 

b . Length (all) (LFT)* 170 

2 . Boardwalks/Catwalks 

a . Number 

b . Length (all) (LFT)* 0 

3 . Jetties 

(all) (LFT) * 200 

Boating 

1 . Boat Ramps 

a . Number 12 

b . Total Lanes 15 

2 . Marinas 

a . Total 

b . Slips/Moorings 49 

c . Dry Storage -- 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

36 
Table 31 . Estimation of the Annual User Value for Saltwater Boating Off 

Citrus County, Florida, 1993-94 . 

Facility 

Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$357,072 = $5 .021 x 11,6992 x .193 x 32' 

2 . Boat Rams 

$371,223 = $1 .481 x 11,699 x .674 x 32 

3 . Private Docks 

$263,106 = $5 .025 x 11,699 x .14 x 32 

Total Annual User Value = $991,401 

*Asset Value = 991,401 = .03 = $33 .05 million 

Bell (1995), Florida-wide value 

FDEP (1992), Citrus County 

Bell et al . (1982), northwest Florida 

Bell (1995), Citrus County 

Assumed $/day same for marinas and private docks 

Recreational boating in marine waters is rapidly growing in Citrus County . 

Such boating can affect coastal water quality (e .g ., inadequate pumping out 

facilities) as well as adding user value to those using coastal waters . 

From the FDEP (1983-1992) and Bell (1995), pleasure boat registrations in 

Citrus County grew as follows, with projected (P) numbers included : 

1983 7,998 

1984 8,427 

1985 8,772 

1986 9,157 

1987 9,658 

1988 10,190 

1989 10,979 

1990 11,771 

1991 11,808 

1992 11,818 

1993 11,445 

1994 11,699 

2000 15,373 (P) 

2005 17,791 (P) 

2010 20,590 (P) 

CIT .12 Water Quality, the Ecosystem and the economy 

The interaction of the local economy and the marine ecosystem is manifested 

in the water quality surrounding the region . Florida's major surface water 

quality problems come from urban stormwater runoff, agricultural runoff, 

domestic wastewater, industry wastewater, and hydrological changes such as 

draining and filling wetlands . There are three sources of information on 

37 
local water quality surrounding Citrus County . First, the Federal Water 

Pollution Control Act requires the state to prepare a 305(b) technical 

report on the status and trends in surface water quality. Second, the EPA 

Toxic Release Inventory (TRI) provides information on toxic and other 

chemical discharges by firms into surface water. Third, the acreage of 

shellfish harvesting that is prohibited from fishing is an indicator of 

high bacterial counts in the water. These three sources of information 

will give a profile of surface water conditions in Citrus County . 

Two indices are used in the 305(b) report for measuring surface water 

quality: the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen-demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity. The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI run from zero to 

100 with larger values indicating declining water quality. 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Citrus County, the 

Crystal River Basin has been selected for a brief summary of the current 

state of water quality in this region of the study area . 

The Crystal River Basin is unique from some of the other rivers in its 

vicinity, in that it has some tidal characteristics . The water in the area 

typically is clear and transparent, and is a common spot for diving . It 

also serves as a winter manatee refuge . The river is designated as an 

Outstanding Florida Water. The river typically has high nutrient input and 

occasionally has dense aquatic weed growths . The usual sources of these 

nutrients are waste water treatment plant discharge, septic tanks and 

runoff . There is a nuclear power plant in the basin, but it does not 

discharge waste into the water. The wQ2 and TSI for selected areas are 

listed in Table 32 . 

The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . In 1994, there were no 

companies that discharged toxic substances in and around the surface water 

of Citrus County . 

Shellfish harvesting has been closed in 4,534 acres, and opened in 42,432 . 

This would suggest that there are not any significant coliform problems in 

the water area . 

38 
Table 32 . Water Quality Indices for Selected Areas of Citrus County, 

Florida . 

Water Areas : Crystal River Basin Water Quality Indices* 

Water Body Type : Estuary W~. TSI 

73 Crystal River -- 36 

Water Body Type : Siring 

72 Homosassa Spring 27 -- 

A.* Higher values indicate lower water quality 

39 

rtl 

DIX .1 

Dixie County is located in the southeastern section of the study area, 

which ranges from Escambia to Citrus County in northwestern Florida . It 

contains 704 .1 square miles of land, ranking it 33rd among the 67 counties 

in Florida . In 1990, Dixie County had a population of 10,585, ranking it 

61st among Florida's counties . The population density was 17 people per 

square mile in 1990, a ranking of 63rd in Florida . Dixie County has an 

median age of 36 .8 years, which is approximately equal to the Florida-wide 

median of 36 .4 years . 

The population of Dixie County had a per capita income of $11,205 in 1992, 

65th of the 67 Florida counties and 43% below the state-wide average of 

$19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem . For example, a retirement community 

may produce less toxic chemical discharges into waterbodies compared to an 

area where income is earned at a local chemical plant . For Dixie County, 

an analysis of the sources of income will be discussed below, along with 

the interaction with the ecosystem . 

Dixie County had 21 .38 of the households below the poverty level in 1989, 

which was higher than the State of Florida average of 9 .0% . In 1993, the 

unemployment rate was 8 .7 0 (relative to a statewide average of 7 .Og), 

indicating a slack labor market . 

DIX .2 Trends in Population Income and Employment in Dixie County, 

1980-93 . 

Table 33 shows the trend in key economic variables in Dixie County from 

1980 through 1993 . Over this interval, resident population increased by 

46% (3 .6% annually), which was faster than the 39 .58 increase for Florida 

as a whole . Population increases that were induced primarily by industrial 

structure (i .e ., job creation) and natural amenities of the region place 

additional pressure on the carrying capacity of both living (e .g ., coastal 

fishery stocks) and non-living natural resources (e .g ., beaches) . 

Nominal aggregate personal income increased by 159% from 1980 to 1993 

(Table 33) . Adjusted for inflation, real aggregate personal income 

increased by 48% (3 .7% annually) . Since real income growth outstripped the 

population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

will have the financial resources to reduce negative externalities (e .g ., 

air and water pollution) which often accrue from population growth (Hall, 

1994) . 

41 
Table 33 . Trends in Key Economic Aggregate Variables in Dixie County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Income' 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

Employment3 

1980 7,800 $45,530 $55,256 $2,423 

1981 8,000 48,975 53,878 2,447 

1982 8,400 53,631 55,576 2,547 

1983 8,800 60,919 61,164 2,607 

1984 9,000 65,403 62,948 2,721 

1985 9,100 72,006 66,920 2,817 

1986 9,400 77,598 70,801 2,908 

1987 9,700 85,812 75,539 3,142 

1988 10,000 94,551 79,925 3,290 

1989 10,300 106,494 85,882 3,540 

1990 10,700 113,571 86,894 3,532 

1991 11,000 113,327 83,206 3,387 

1992 11,300 120,801 86,102 3,395 

1993 11,400 117,910 81,599 3,570 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Dixie County increased from 2,423 in 1980 to 3,570 in 

1993, a 47g increase . The growth of jobs is stimulated in a region by what 

is known as the export base . Simply put, a region's growth is determined 

by its ability to derive "export income" from outside the region . In 

Florida, such income may come from physically exporting goods such as 

electronic components or fish, but it is more likely to come from tourists 

visiting the region, income to retirees in Florida and injections of 

Federal dollars to sustain military bases such as Eglin Air Force Base in 

Okaloosa County . Through a multiplier process, this export income sustains 

both direct export jobs (e .g ., civilians working for the military) and 

indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Dixie County grew 

less rapidly than the measure of county output - real aggregate personal 

income - as local entrepreneurs introduced labor-saving technological 

devices to economize on the rising cost of labor . 

DIX .3 Trends in Various Welfare Measures in Dixie County . 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing . A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is likely to be more able 

to protect the ecosystem than one which is highly dependent on income 

42 
maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Dixie County derived 93 .7% of its personal 

income from earnings, retirement and capital income compared to 98 .28 for 

the whole of Florida . Thus, the county is less likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem . The trends in the components of personal income per capita are 

shown in Table 34 for Dixie County . 

DIX .4 Industrial Base : Dixie County 

The "industrial base" for Dixie County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy. The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county ; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy . If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., loo) in an area, compared 

to the same percentage nationally (e .g ., 0 .50) assuming the nation consumes 

Table 34 . Trends in Components of Personal Income in Dixie County, 

Florida, 1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $5,571 $3,638 $188 $26 $1,076 644 

1981 6,115 3,905 210 28 1,288 784 

1982 6,406 3,957 204 21 1,429 794 

1983 6,891 4,264 204 22 1,515 887 

1984 7,294 4,546 209 14 1,586 943 

1985 7,913 4,862 210 26 1,765 1,049 

1986 8,297 5,000 210 16 1,804 1,266 

1987 8,820 5,442 222 21 1,891 1,245 

1988 9,445 5,669 300 22 2,165 1,289 

1989 10,324 6,185 294 23 2,344 1,478 

1990 10,657 6,134 381 33 2,478 1,631 

1991 10,298 5,579 458 71 2,670 1,520 

1992 10,716 5,790 524 93 2,897 1,413 

1993 10,334 6,149 566 74 3,077 467 

Source : BEA (1995) 

43 
all it produces - no imports or exports . This is rather simplistic, but it 

does serve as an indicator of which industries are predominately export . 

This figure, the location quotient (LQ), is the following in this example : 

(1) LQ = lOg/ .5% = 20 

Thus, 95% would be in export or 

(2) 1 - LQ-1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 35 shows the main identified export industries and their contribution 

to personal income in Dixie County . This county depends primarily on 

forestry services, lumber and wood, textile manufacturing, local 

governments and fishing for its economic survival . Some of the largest 

individual employers in Dixie County have, from time to time, had negative 

impacts on the ecosystem . For Dixie County, Table 36 shows the top ten 

employers along with the products they produce that may generate conflicts 

with the environment . Products such as textiles and lumber must be 

rigorously controlled or they will reduce water and air quality . In 1993, 

the EPA reported that the companies in Dixie County discharged no toxic 

chemicals into surface water (tester, 1995) . 

DIX.5 Ecosystem-sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Dixie County, the industries shown in Table 37 fall into 

this category . 

The Dixie County economy is heavily based upon timber which is harvested 

and processed regionally into various paper-based products . All of these 

economic activities create various kinds of waste that is a point or 

nonpoint discharge into rivers and coastal waters . These industries are 

primarily involved in the export sector and therefore are critical to this 

coastal county . 

DIX .6 Ecosystem-insensitive Industries 

As indicated by earnings, the economic base of Dixie County is of mostly 

ecosystem-sensitive industries . The remainder, ecosystem-insensitive 

industries, have little impact on the ecosystem and are shown in Table 38 . 

In general, industries such as fishing and local government have a less 

adverse impact on local ecosystem health than other industries in the 

economics base for Dixie County . Over the 1969-93 period, the ecosysteminsensitive industries grew slower than the ecosystem-sensitive industries, 

meaning that the growth of the Dixie County economy is in conflict with the 

environment . 

44 
Table 35 . Major Export Industries in Dixie County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings 

(000) 

~ of Personal 

Income 

LQ* 

Forestry Services $612 .51 9 .1 

Fishing 1,151 .97 31 .5 

Lumber and Wood 13,239 11 .22 26 .2 

Textiles N/A N/A N/A 

Water Transportation 195 .16 1 .3 

State and Local Government 21,143 17 .93 2 .11 

Limited Tourism (Horseshoe N/A N/A PJ* 

Beach) 

*LQ = Location quotient . See Text . 

*PJ = Professional Judgment . 

Source : BEA (1995) 

Table 36 . Top Ten Employers in Dixie County, Florida and Products 

Produced, 1994 . 

Employer Employees 

1 . Georgia Pacific Corporation, Timber 200 

2 . Great Bear Industries, Textile 200 

3 . Suwannee Lumber Company, Timber 140 

4 . Rick's Seafood, Fishing 60 

5 . Cross City Veneer Company, Timber 40 

6 . Anderson-Columbia, Asphalt paving 40 

7 . Gulf Stream Crab Company, Fishing 30 

8 . Knights Sawmill, Timber 25 

9 . Joe C . Smith Trucking, Timber 20 

10 . Sand T Service, Construction ,`2 

Sub-Total 770 

Total 3,570 

Percent of Total 22% 

Source : Florida Department of Commerce (1994) 

45 
Table 37 . Ecosystem-Sensitive Industries in Dixie County, Florida . 

Industry Earnings ($000) 

1 . Forestry Services $612 

2 . Lumber and Wood 1,151 

3 . Textiles 13,239 

4 . Water Transportation N/A 

Sub-Total $15,002 

Total Earnings (Place of Work) $63,482 

Percent of Total 24% 

Source : BEA (1995) 

Table 38 . Ecosystem-Insensitive Industries in Dixie County, Florida . 

11 Industry Earnings ($000) 11 

1 . Fishing 

2 . State and Local Government 

3 . Tourism 

Sub-Total 

Total Earnings 

Percent of Total 

Source : Table 35 

DIX .7 Commercial Fishery Landings in Dixie County 

$1,151 

21,143 

N/A 

$22,294 

$63,482 

35% 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Dixie County . 

Three categories of fishery products are found : (1) finfish; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $2 .1 million worth of commercial fishery 

products were landed in Dixie County at the ex vessel level (Table 39) . 

Finfish and shrimp account for 32% of this value . Crabs accounted for 65% 

of the ex vessel value for the county . Brown shrimp, which depends on 

wetlands during a phase of its life cycle, was the dominant shrimp species . 

46 
Table 39 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Dixie County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Spotted Sea Trout 139,058 $166,869 .61 

Black Mullet 287,871 135,299 .38 

Shad 196,798 59,039 .40 

Grunts 107,134 50,352 .98 

Spanish mackerel 115,208 48,387 .36 

Sea Bass 56,401 25,944 .46 

Gag Grouper 5,659 12,619 .57 

Red Grouper 8,312 14,454 .88 

Black Grouper 7,938 16,431 .66 

Spot 30,102 12,040 .80 

All Others 147,436 82 .670 .00 

Total $624,110 .10 

Invertebrates 

Stone Crabs 134,702 781,065 .86 

Blue Crabs 857,404 578,480 .05 

Oysters 29,120 36,108 .80 

Clams 5,680 29,231 .35 

All Others 7,276 6,654 .12 

Total $1,431,540 .18 

Shrimp (Total) 23,757 45,495 .52 

Grand Total $2,101,145 .80 

* State average ex vessel price used . 

Source : FDEP (1994) 

Although the ex vessel value does not include value added in processing and 

distribution, commercial fishing is a relatively important component of the 

economic base of Dixie County, where aggregate personal income was $ .17 

billion in 1993 . Over the last fourteen years, commercial fishery landing 

has increased by 101% while the ex vessel value of the catch has increased 

by 2440 . When adjusted for inflation, the value of landings changed by 

91 .60 (FDNR, 1980) . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

the fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county (Table 40) . Dixie County had 2,892 resident anglers purchasing a 

one-year fishing license . It should be pointed out that purchase of a 

license in a county does not ensure that one is a resident of that county, 

but informal conversations with Florida Dept . of Environmental Protection 

personnel suggest little bias is associated with that assumption . 

Nonresidents are those that purchased saltwater fishing licenses in noncoastal counties . Such licenses were pro-rated to coastal counties in 

close geographical proximity to each county, using personal judgment, as 

shown in Table 40 . Finally, tourists must purchase a license, and the 

number is shown for the counties in the study area . This may underestimate 

47 
Table 40 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents Nonresident2 Tourist3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11,685 6 .926 5 .312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

Non-resident (out of state) saltwater fishing licenses for one year ; 

seven days and three days . 

tourist saltwater anglers since tourists may buy a license in an interior 

county and use it in one or more of the coastal counties . 

Table 41 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 40 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers, 

respectively . Dixie County showed a fishing effort of 84,719 days . 

Finally, Table 42 is derived from Table 40 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $5,178,169 in Dixie County in 1993-94 . Many assumptions were 

made to arrive at these estimates, however, these figures are believed to 

indicate an order of magnitude and relative ranking, and may actually be 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . Multiplier effects of nonresidents and 

tourists were not considered . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing . There is no organized market for recreational 

fisheries since they are common property resources . 

48 
Table 41 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Tourist Z Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167,499 21"248 188 .747 

Total 952,605 377,480 1,330,085 

9 days per angler year and Table 8 . See Milon and Thunberg (1992) . 

4 days per angler year and Table 8 . See Bell (1993) . 

Table 42 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

TouristZ Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8 .890 .475 2 .337 .280 11,227,755 

Total $50,562~157 $41,522,800 $92,038,955 

Figures in Table 8 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 8 multiplied by $440 .00 per angler . 

49 
Using the contingent value (CV) method, Bell, et al . (1982) have estimated 

the per day value of saltwater recreational fishing in northwest Florida at 

$41 .70 and $48 .67 for residents and tourists respectively (in 1994 

dollars) . The annual flow of value for Dixie County can be computed as 

follows : 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 7,011 = $2 .6 million 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 4,121 = $0 .8 million . 

Thus, saltwater recreational fishing generates $3 .6 million per year in 

Dixie County with a capitalized value of $120 million using a 3% discount 

rate (i .e ., $3 .6 million = .03) . 

DIX.8 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing . The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property, where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets, such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated . This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 43 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch. 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

50 
Table 43 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D .C . 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

51 
production elasticity of .19) . Dixie County has 20,300 acres (NOAA, 1991) 

of salt marsh which would be worth $108 million ($5,316 x 20,300) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by wetlands off the shore of 

Dixie County . 

DIX .9 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier . Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . Horseshoe Beach is the only major beach 

area in the county . Since no user information is available the estimated 

value of the beaches cannot be calculated (see Table 44) . 

DIX .10 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 45 

identifies ecological resources that are an asset to Dixie County and 

induce a considerable level of economic activity . Table 46 is an inventory 

of these water-dependent facilities in Dixie County . Piers, boardwalks and 

jetties facilitate bank recreational fishing, beach use and other outdoor 

recreational activities . 

Table 44 . Key Saltwater Beaches in Dixie County, Florida .* 

Western District 

Environmentally Endangered Lands 

Horseshoe Beach 

*In Dixie County alone, the University of West Florida (1985b) 

reported 2 individual saltwater beaches which were 1 mile in length 

and 132,000 square feet (public and private) . 

Source : University of West Florida(1985a) 

52 
Table 45 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Dixie County, Florida . 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year' 

Asset Value 

(Millions )2 

Commercial Fishing $2 .13 N/A N/A 

Recreational Fishing $5 .17' $3 .65 $1205 

Saltwater Marshs N/A .207 6 108 6 

Saltwater Beaches N/A6 N/A' N/A 6 

Marine Boating' N/A $ .138 $4 .63' 

Nonmarket value per year 

#1 divided by .03 = Asset Value 

Table 39, ex vessel price 

Table 42, retail price 

To commercial fishery landings only 

See text for discussion 

See Table 47 

Table 46 . An Inventory of Marine-Related Recreational Facilities 

in Dixie County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number --

b . Length (all) (LFT)* --

2 . Boardwalks/Catwalks 

a . Number 3 

b . Length (all) (LFT)* 485 

3 . Jetties 

a . Length (all) (LFT)* -- 

Boating 

1 . Boat Ramps 

a . Number 13 

b . Total Lanes 15 

2 . Marinas 

a . Total 6 

b . Slips/Moorings 80 

c . Dry Storage 36 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

As an outdoor recreational activity, boating makes use of common property 

water resources . Bell (1995) found that the user value per day, expressed 

in 1994 dollars, is worth $3 .56 more if a marina is used (i .e ., $5 .02 less 

$1 .48) rather than a boat ramp . These are Florida-wide values and may or 

53 
may not be good estimates for Dixie County, but are used for purposes of 

illustration . 

Dixie County has 15 saltwater boat ramp lanes and 116 wet slips and dry 

racks, as shown in Table 46 . The number of private docks from which to 

launch pleasure craft is unknown . Combining data from Bell et al . (1982) 

and Bell (1995), the annual user value from boating in the Gulf of Mexico 

off Dixie County is estimated and shown in Table 47 . This value is about 

$0 .14 million . 

Recreational boating in marine waters is rapidly growing in Dixie County . 

Such boating can affect coastal water quality (e .g ., inadequate pumping out 

facilities) as well as adding user value to those using coastal water 

resources . From the FDEP (1983-1992) and Bell (1995) studies, pleasure 

boat registrations in Dixie County grew as follows, with projected (P) 

numbers included : 

1983 1,046 

1984 1,160 

1985 1,223 

1986 1,233 

1987 1,269 

1988 1,361 

1989 1,365 

1990 1,407 

1991 1,398 

1992 1,496 

1993 1,544 (P) 

1994 1,639 (P) 

2000 2,488 (P) 

2005 3,242 (P) 

2010 4,226 (P) 

DIX.11 Water Quality, the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is manifested 

in the water quality surrounding the region . Florida's major surface water 

quality problems come from urban stormwater runoff, agricultural runoff, 

domestic wastewater, industry wastewater and hydrological changes such as 

draining and filling wetlands . 

There are three sources of information on local water quality surrounding 

Dixie County . First, the Federal Water Pollution Control Act requires the 

state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Dixie County . 

54 
Table 47 . Estimation of the Annual User Value for Saltwater 

Boating Off Dixie County, Florida, 1993-94 . 

Facility 

Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$50,024 = $5 .02' x 1,639' x .193 x 32' 

2 . Boat Rams 

$52,007 = $1 .481 x 1,639 x .674 x 32 

3 . Private Docks 

$36,860 = $5 .025 x 1,639 x .14 x 32 

',Total Annual User Value = $138,891 

*Asset Value = 138,891 = .03 = $4 .63 million 

Bell (1995), Florida-wide value 

FDEP (1992), Dixie County 

Bell et al . (1982), northwest Florida 

Bell (1995), Dixie County 

S Assumed $/day same for marinas and private docks 

Two indices used in the 305(b) report for measuring surface water quality : 

the stream water quality index (WQI), and the lake/estuary Trophic State 

Index (TSI) . Both are of interest to this study simply because streams 

flow into Gulf of Mexico estuaries . The TSI measures estuarine water 

quality that is critical to fish and wildlife . The WQI summarizes 

information from six categories including water clarity (turbidity and 

total suspended solids), dissolved oxygen, oxygen demanding substances 

(BOD), nutrients, bacteria and macroinvertebrate diversity . The TSI 

measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality . 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Dixie County, the 

Econfina Creek/Steinhatchee River Basin has been selected for a brief 

summary of the current state of water quality in this region of the study 

area . 

The water bodies in Dixie County are primarily smaller river systems that 

drain swampy lowlands and empty into marshes near the Gulf of Mexico . 

Water quality in this area has traditionally been very good because of 

55 
relatively low development . Sources of pollution include highway runoff 

and septic tank leakage . The wQI and TSI for selected areas are listed in 

Table 48 . 

The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . In 1994, there were no 

companies that discharged toxic substances in and around the surface water 

of Dixie County . Shellfish harvesting has been closed in 3,612 acres and 

restricted, conditionally or permanently, in another 35,588 acres . This 

leaves open over 90,000 acres, meaning that pollution levels in this area 

were not significant enough to prevent shellfish harvesting . 

Table 48 . Water Quality Indices for Selected Areas of Dixie 

County, Florida. 

Water Areas : Steinhatchee River Basin Water Quality Indices* 

Water Body Type : Stream WOI . TSI 

1 . Sand Hill Creek 34 -- 

2 . Steinhatchee River 35 -- 

4 . Steinhatchee River 41 -- 

5 . Eightmile Creek 47 -- 

7 . Steinhatchee River 44 -- 

A . * Higher values indicate lower water quality 

56 
)ccurri 

Marine 

ESC . I In 

Escambia County is located in the western section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figures 3 

and 4) . Escambia County contains 664 square miles of land, ranking it 38th 

among the 67 counties in Florida . In 1990, Escambia County had a 

population of 262,798, ranking it 15th among Florida's counties . The 

population density was 410 people per square mile in 1990, ranking it 12th 

in Florida . Escambia County has a relatively low median age of 32 .4 years, 

compared to the Florida-wide median of 36 .4 years . 

The population of Escambia County had a per capita income of $16,667 in 

1992, 28th of the 67 Florida counties and 16% below the Florida-wide 

average of $19,797 . This income was derived primarily from earnings from 

local industries, return on investment (rent, interest, dividends), 

retirement income, and transfer payments (e .g ., AFDC, food stamps, etc .) . 

The sources of income for a county may lead to a characterization of how 

that area interacts with the natural ecosystem . For example, a retirement 

community may produce less toxic chemical discharges into waterbodies, 

compared to an area where income is earned at a local chemical plant . For 

Escambia County, an analysis of the sources of income will be discussed 

below, along with the interaction with the ecosystem . 

Escambia County had 13 .3% of the households below the poverty level in 

1989, which was higher than the State of Florida average of 9 .0% . In 1993, 

the unemployment rate was 5 .3% in Escambia county (relative to a statewide 

average of 7 .0%-), indicating a slack labor market . 

ESC . 2 Trends 1I1 Pqgulation Income and Smvlovment in Sscambia County . 

1980-93 . 

Table 49 shows the trend in key economic variables in Escambia County from 

1980 through 1993 . Over this interval resident population increased by 

16 .40 (1 .3% annually), which was slow when compared to 39 .5% for Florida as 

a whole. Population increases that were induced primarily by industrial 

structure (i .e ., job creation) and natural amenities of the region place 

additional pressure on the carrying capacity of both living (e .g ., coastal 

fishery stocks) and non-living natural resources (e .g ., beaches) . 

Nominal aggregate personal income increased by 147% from 1980 to 1993 . 

(Table 49) . Adjusted for inflation, real aggregate personal income 

increased by 38 .20 (2 .9% annually) . Since real income growth outstripped 

the population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

have the financial resources to reduce negative externalities (e .g ., air 

and water pollution) which often accrue from population growth (Hall, 

1994) . 

57 
`tEIGHTMILE CREEK 

f~4 

9`' .. . 

r PERDIDO BAY 3 

y u- CUS 

ALABAMA 1 . . 

yD' 

t3 

r / r~> 

'6 

BIG LAGOON 

GULF OF MEXICO 

PERDIDO BAY BASIN WATER QUALITY 

03140107 

~ GOOD 

AVERAGE WATER QUALITY ~ THREATENED 

1984-1993 STORET DATA FAIR 

' WATERSHED ID NUMBERS LINK MAP TO TABLES POOR 

INDICATES QUALITATIVE ASSESSMENT ~ UNKNOWN 

Figure 3 . Map of Escambia County, Florida, showing levels of water 

quality and areas of quality testing (Perdido Bay Basin)[from 

Bureau of Surface Water Management (1994b)] . 

58 
lT0 B 

: 

AY 

ESCAMBIA BAY 

CARPENTER CREEK 

~ 

33.'r 

~ " .1 

BAYOU Gi1Cdr -- -a-r R BAY 

15 

3 

., o 7 S 6 

-+afi~ 

, v2 . W F 

GULF OF MEXICO 

PENSACOLA BAY BASIN WATER QUALITY 

03140105 GOOD 

~ THREATENED AVERAGE WATER QUALITY 

A FAIR 1984-1993 STORET DAT 

WAT R 

- 

E SHED ID NUMBERS LINK MAP TO TABLES POOR 

INDICATES QUALITATIVE ASSESSMENT D UNKNOWN 

Figure 4 . Map of Escambia County, Florida, showing levels of water 

quality and areas of quality testing (Pensacola Bay Basin)[from 

Bureau of Surface Water Management (1994b)] . 

59 
Table 49 . Trends in Key Economic Aggregate Variables in Escambia County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

Employment 3 

1980 235,600 $1,885,710 $2,288,483 113,101 

1981 239,700 2,150,728 2,366,037 117,742 

1982 243,200 2,323,311 2,407,576 117,905 

1983 245,800 2,514,014 2,524,110 119,578 

1984 249,000 2,723,858 2,621,615 126,114 

1985 250,600 2,400,021 2,695,187 130,400 

1986 255,000 3,104,779 2,832,828 135,195 

1987 258,200 3,275,173 2,883,074 137,782 

1988 258,000 3,433,251 2,883,075 137,753 

1989 260,200 3,677,887 2,966,038 138,852 

1990 263,300 3,952,498 3,024,099 140,547 

1991 266,600 4,143,803 3,042,440 139,586 

1992 270,200 4,408,297 3,142,051 142,954 

1993 270,400 4,569,565 3,162,329 143,673 

1 . Includes earnings, dividends, interest, rent and transfer payments . 

2 . Deflated by CPI where 1982-84 = 100 . 

3 . Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Escambia County increased from 113,101 in 1980 to 

143,673 in 1993, a 27% increase . The growth of jobs is stimulated in a 

region by what is known as the export base . Simply put, a region's growth 

is determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region; income to retirees in Florida and injections 

of Federal dollars to sustain military bases such as Eglin Air Force Base 

in Okaloosa County . Through a multiplier process, this export income 

sustains both direct export jobs (e .g ., civilians working for the military) 

and indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Escambia County 

grew less rapidly than the measure of county output - real aggregate 

personal income - as local entrepreneurs introduced labor-saving 

technological devices to economize on the rising cost of labor . 

ESC .3 Trends in Various welfare Measures in Escambia County. 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing . A county that depends on earnings, retirement income and income 

60 
from capital (i .e ., dividends, interest and rent) is likely to be more able 

to protect the ecosystem than one which is highly dependent on income 

maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Escambia County derived 97 .4% of its personal 

income from earnings, retirement and capital income, compared to 98 .28 for 

the whole of Florida . Thus, the county is equally likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem . The trends in the components of personal income per capita are 

shown in Table 50 for Escambia County . 

SSC.4 Industrial Base : Bscambia County 

The "industrial base" for Escambia County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy . The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county; however, location quotients and expert judgment can be used 

to identify such industries fairly accurately . If a given county is highly 

specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

Table 50 . Trends in Components of Personal Income in Escambia County, 

Florida, 1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $8,003 $5,622 $140 $15 $1,378 $847 

1981 8,974 6,207 148 13 1,581 1,024 

1982 9,555 6,531 147 22 1,748 1,107 

1983 10,277 6,926 153 21 1,888 1,238 

1984 10,938 7,412 146 15 1,945 1,421 

1985 11,574 7,728 148 25 2,124 1,549 

1986 12,176 8,050 159 22 2,221 1,723 

1987 12,687 8,402 169 23 2,359 1,733 

1988 13,306 8,725 190 22 2,536 1,833 

1989 14,137 8,996 215 21 2,786 2,118 

1990 15,011 9,494 256 26 3,063 2,172 

1991 15,544 9,737 312 37 3,356 2,103 

1992 16,316 10,265 396 59 3,589 2,008 

1993 16,899 10,486 386 51 3,870 2,106 

Source : BEA (1995) 

61 
from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., lOg) in an area, 

compared to the same percentage nationally (e .g ., 0 .5%), assuming the 

nation consumes all it produces - no imports or exports . This is rather 

simplistic, but it does serve as an indicator of which industries are 

predominately export . This figure, the location quotient (LQ), would be : 

(1) LQ = 10%/ .5t = 20 

Thus, 95t would be in export or 

(2) 1 - LQ-1 = .9S 

In reality, any manufacturing industries with a high LQ would most likely 

export all or most of its product outside the county (e .g ., Olin Company 

makes gunpowder in Wakulla County and sells none locally) . 

Table 51 shows the main identified export industries and their 

contribution to personal income in Escambia County . This county depends 

primarily on manufacturing, the Federal Government, water transportation, 

health services and tourism for its economic survival . Some of the largest 

individual employers in Escambia County, have, from time to time, had 

negative impacts on the ecosystem . For Escambia County, Table 52 shows the 

top ten employers, along with the products they produce that may generate 

conflicts with the environment . Products such as pulp and paper, 

chemicals, and utilities must be rigorously controlled or they will reduce 

water and air quality . Historically, Escambia County has had problems with 

industries located in this county . Terrebonne (1973) pointed out that the 

expansion of manufacturing firms in Escambia County (e .g ., paper mills and 

chemical plants) has been accompanied by deteriorating water quality which 

in turn resulted in loss to other sectors of the economic base . Shrimp 

caught in inland waters near Pensacola declined from a high of 1 .64 million 

pounds in 1968 to .77 million pounds in 1971 as a direct result of degraded 

conditions in local estuaries . Low dissolved oxygen and high bacteria 

counts present stresses that make shrimp more susceptible to other damaging 

factors . The oyster fishery also experienced severe losses as a result of 

water pollution . Virtually all oyster grounds in Escambia County were 

closed to shellfish harvesting over the 1951-1972 period according to 

Terrebonne (1973) . In sum, from 1962-1972, environmental losses in terms 

of lost income from shrimping, shellfish harvesting, tourism, outdoor 

recreation and decreased property value because of poor water quality was 

over $1 billion . In 1993, the EPA reported that the companies in Escambia 

County discharged 18,440 pounds of toxic chemicals into surface water, 

ranking it 4th in volume among Florida's counties (see Lester, 1995) . 

l3SC .5 Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Escambia County, the industries shown in Table 53 fall 

into this category . 

62 
Table 51 . Major Export Industries in Escambia County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings 

(000) 

% of Personal 

Income 

LQ* 

Manufacturing $362,315 10 .5 

Paper and Allied Products 1 .50 

Printing and Publishing 1 .50 

Stone, Clay and Glass Products 1 .58 

Water Transportation 194,425 5 .7 1 .44 

Federal Government, Civilian 384,120 11 .2 3 .52 

Military 296,766 8 .6 7 .05 

Health Services 466,890 13 .6 1 .60 

Tourism 103,456 3 .0 N/A M 

* LQ = Location quotient . See Text . 

Source : BEA (1995) 

Table 52 . Top Ten Employers in Escambia County, Florida and Products 

Produced, 1994 . 

Employer Employees 

1 . Baptist Healthcare, Health Care 2,846 

2 . Sacred Heart Hospital, Health Care 2,700 

3 . Monsanto Company, Nylon Fiber 2,300 

4 . Gulf Power, Utilities 1,587 

5 . HCA West Florida Regional Medical Center, Health Care 1,500 

6 . Lakeview Center, Health Care 1,300 

7 . Champion International Corporation, Paper Products 1,100 

8 . Medical Center Clinic, Health Care 980 

9 . Instrument Control Services, Inc ., Instrumentation 750 

10 . Pensacola Christian School, Private School/Publishing 724 

Sub-Total 15,787 

Total Jobs 143,673 

Percent of Total Jobs 11% 

Source : Florida Department of Commerce (1994) 

63 
Table 53 . Ecosystem-Sensitive Industries in Escambia County, Florida . 

Industry Earnings ($000) 

1 . Printing and Publishing $23,871 

2 . Paper and Allied Products 80,966 

3 . Lumber and Wood Products 4,407 

4 . Furniture and Fixtures 6,247 

5 . Fabricated Metals 17,005 

6 . Stone, Clay and Glass Products 25,369 

7 . Water Transportation 8,940 

8 . Federal Civilian/Military (Naval Base) 680 .886 

Sub-Total $847,691 

Total Earnings (Non-Farm) $2,381,390 

Percent of Total 36% N 

Source : BEA (1995) 

The Escambia County economy is heavily based upon timber which is harvested 

and processed regionally into various paper-based products . This county has 

a deep-water port and serves as a naval station for the U.S . military and a 

port for a variety of materials and products . All of these economic 

activities create various kinds of waste that is a point or nonpoint 

discharge into rivers and coastal waters . These industries are primarily 

involved in the export sector and therefore are critical to this coastal 

county . 

SSC .6 Ecosystem-Insensitive Industries 

As is indicated by earnings, the economic base of Escambia County is 

composed of primarily ecosystem-sensitive industries . The ecosysteminsensitive industries, which have less impact on the environment, are shown 

in Table 54 . 

In general, industries such as health services, tourism and retirement 

have a less adverse impact on local ecosystem health than other industries 

in Escambia County . Also, over the 1969-93 period, the ecosysteminsensitive industries were growing faster than the ecosystem-sensitive 

industries, meaning that the industrial structure is placing relatively 

less pressure on the marine ecosystem . Still, ecosystem-sensitive 

industries did grow in absolute terms and still place considerable stress 

on the ecosystem . 

SSC .7 Commercial Fishery Landings in Escambia County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Escambia County . 

64 
Table 54 . Ecosystem-Insensitive Industries in Escambia County, Florida . 

Industry Earnings ($000) 

1 . Health Services $466,890 

2 . Tourism and Retirement 

Construction 216,732 

Hotels/Motels 11,391 

Eating and Drinking 92,065 

Sub-Total $786,778 

Total Earnings 

Percent of Total 

Source : Table 51 

$2,381,390 

330 

Three categories of fishery products are found : (1) finfish ; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90%- of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's fisheries . 

In 1994, about $2 .5 million worth of commercial fishery products were 

landed in Bay County at the ex vessel level (Table 55) . Finfish and shrimp 

account for 97t of this value . Among the finfish, red snapper was by far 

the leading species as measured by quantity and value . Brown shrimp, which 

depends on wetlands during a phase of its life cycle, was the dominant 

shrimp species . Among the 13 counties in the study area, Escambia County 

ranked 8th in the ex vessel value of all commercial fishery landings . 

Although the ex vessel value does not include value added in processing 

and distribution, commercial fishing is a relatively small component of the 

economic base of Escambia County, where aggregate personal income was $4 .6 

billion in 1993 . Over the last fourteen years, commercial fishery landing 

has decreased by 91% while the ex vessel value of the catch has increased 

by 100. When adjusted for inflation, the value of landings changed by -380 . 

Compared to other economic trends in Escambia County, commercial fishery 

landings are a declining component of the local economy (FDNR, 1980) . 

ESC .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively, that engage in saltwater recreational 

fishing in Florida. In Milon and Thunberg (1992), there is some regional 

breakdown embracing the present study area from Hernando County north to 

Escambia County . These counties include both coastal and interior 

counties . As an approximation, these regional averages can be applied to 

the individual counties . Bell (1993) has only statewide averages for 

tourist saltwater anglers, which are also used as an approximation . In an 

earlier study, Bell et al . (1982) found that expenditures and days per 

tourist angler for Region I (i .e ., Escambia to Jefferson County) were about 

40-50% higher than the statewide average . Thus, using the latest study of 

Bell (1993), statewide figures may be conservative . 

65 
Table 55 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Escambia County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Vermilion Snapper 73,595 $178,099 .91 

Red Snapper 416,137 645,012 .31 

Black Mullet 335,843 157,846 .20 

Porgies 75,664 69,610 .88 

Amberjacks 48,249 46,801 .53 

Spanish Mackerel 94,791 39,812 .22 

Black Roe Mullet 3,319 39,064 .63 

Triggerfish 41,121 37,831 .32 

Gag Grouper 15,750 35,122 .50 

Yellowedge Grouper 13,962 29,180 .58 

All others 194,254 171 .493 .40 

Total $1,449,875 .49 

Invertebrates 

Blue Crabs 83,902 $53,810 .85 

Stone Crabs 240 1,123 .48 

Squid 17,329 6,411 .73 

Spiny Lobster 753 3 .222 .84 

Total $64,491 .45 

Shrimp (Total) 489,539 981 .593 .17 

Grand Total N/A $2,496,960 .11 

* State average ex vessel price used . 

Source : FDEP (1994) 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county (Table 56) . Escambia County had 11,004 resident anglers purchasing 

a one-year fishing license . It should be pointed out that purchase of a 

license in a county does not ensure that one is a resident of that county, 

but informal conversations with Florida Dept . of Environmental Protection 

personnel suggest little bias is associated with that assumption . 

Nonresidents are those that purchased saltwater fishing licenses in noncoastal counties . Such licenses were pro-rated to coastal counties in 

close geographical proximity to each county, using personal judgment, as 

shown in Table 56 . Finally, tourists must purchase a license, and the 

number is shown for the counties in the study area . This may underestimate 

tourist saltwater anglers since tourists may buy a license in an interior 

county and use it in one or more of the coastal counties . 

Table 57 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 56 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers 

respectively . Escambia County showed a fishing effort of 125,792 days . 

66 
Table 56 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents NonresidentZ Tourist 3 

$scambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11 .685 6 .926 5 .312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

Non-resident (out of state) saltwater fishing licenses for one year ; seven days 

and three days . 

Table 57 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresidents 

TouristZ Total 

gecambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167,499 21,248 188 .747 

Total 952,605 377,480 1,330 085 

9 days per angler year and Table 56 . See Milon and Thunberg (1992) . 

4 days per angler year and Table 56 . See Bell (1993) . 

67 
Finally, Table 58 is derived from Table 56 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $8 .1 million in Escambia County in 1993-94 . Many assumptions 

were made to arrive at these estimates, however, these figures are believed 

to indicate an order of magnitude and relative ranking, and may actually be 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing. There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Escambia County can be computed as follows : 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 11,152 = $4 .2 million 

Tourists 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 6,356 = $1 .2 million . 

Thus, saltwater recreational fishing generates $5 .4 million per year in 

Escambia County with a capitalized value of $180 million using a 3% 

discount rate (i .e ., $5 .4 million , .03) . 

SSC.9 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing. The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property, where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets, such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated. This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 59 . 

68 
Table 58 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Tourist2 Total 

Bscambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8,890 .475 2 .337,280 11 .227,755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 54 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 54 multiplied by $440 .00 per angler . 

Table 59 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

69 
Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch. 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch. The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 39. yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Escambia County has 1,300 acres of salt 

marsh (NOAA, 1991), which would be worth $6 .9 million ($5,316 x 1,300) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by Escambia County wetlands . 

$SC .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier. Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . It is difficult to separate Escambia 

County from neighboring Santa Rosa County since one beach runs into 

another . Table 60 lists the key beaches for these two counties . 

70 
Table 60 . Key Saltwater Beaches in Escambia County, Florida.* 

Western District 

Environmentally Endangered Lands : 

Perdido Key State Preserve #1 

Perdido Key State Preserve #2 

Gulf Islands National Seashore 

Perdido Key and Johnson Beach 

Perdido Key State Preserve 

Big Lagoon State Recreational Area 

Central District 

Gulf Islands National Seashore 

Fort Pickens and Langdon Beach 

Unnamed Beaches 

Quietwater Beach 

Casino Beach 

Pensacola Beach 

* In Escambia County alone, the University of West Florida (1985b) 

reported 37 individual saltwater beaches which were 50 .9 miles in 

length and 86 .6 million square feet (public and private) . 

Source : University of West Florida(1985a) 

In 1984, Bell and Leeworthy (1986) estimated expenditures per day of $12 

(1994 dollars) and $30 (1994 dollars) for residents and tourists, 

respectively, on saltwater beach-related costs such as lodging, food and 

drink, etc. in Pensacola, Florida. These estimates will be used for all 

counties in the study area as an approximation since no recent studies have 

been undertaken . 

Using the CV technique, Leeworthy, et al . found that Escambia, Franklin 

and Bay Counties had an averaged user value of about $3 .0 per day (in 1994 

dollars) for residents and tourists . In a comprehensive study of Florida 

beaches, the University of West Florida (1985b) projected that Escambia 

County would have 951,555 saltwater beach days per year in 1990 for the 

beaches listed in Table 60 . By multiplying the user value per day of $3 

times the estimated number of saltwater beach days, the annual flow of 

value is $2 .85 million. These are not actual expenditures, but an estimate 

of annual recreational benefits to beach users . The capitalized value of 

this value flow at a real discount rate of 3% is over $95 million - the 

asset value of the beach. Finally, beach-related spending in Escambia 

County in 1990 can be calculated in the following manner [with the 

percentage of residents and tourists taken from the University of West 

Florida (1985b) study] : 

Residents 

(% Residents) x (Beach Days/Yr.) x (Expenditures/day) 

.36 x 951,555 x $12 = $4 .11 million 

71 
(% Tourists) x (Beach Days/Yr .) x (Expenditures/day) 

.64 x 951,555 x $30 = $18 .3 million 

Combined, saltwater beaches in Escambia County attracted an estimated 

$22 .41 million in beach-related spending in 1990 with tourists accounting 

for 830 of this spending . 

Table 61 summarizes three ecological resources that are an asset to 

Escambia County and induce a considerable level of economic activity in 

this region . 

SSC.11 Man-Made Resources: Water Dependent 

As discussed above, many economic activities, such as fisheries and beaches, 

in the marine ecosystem are water-dependent such as fisheries and beaches . 

To take advantage of the marine ecosystem in terms of outdoor recreation 

which has considerable economic value, man-made facilities or resources 

have been constructed . The Growth Management Act of Florida mandates that 

counties should give preferences in land planning to water-dependent 

facilities . Table 62 is an inventory of these water-dependent facilities 

in Escambia County . Piers, boardwalks and jetties facilitate bank 

recreational fishing, beach use and other outdoor recreational activities . 

As an outdoor recreational activity, boating makes use of common property 

water resources . Bell (1995) found that the user value per day, expressed 

in 1994 dollars, is worth $3 .56 more if a marina is used (i .e ., $5 .02 less 

$1 .48) rather than a boat ramp . These are Florida-wide values and may or 

may not be good estimates for Escambia County, but are used for purposes of 

illustration . 

Table 61 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Escambia County, Florida. 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year' 

Asset Value 

(Millions)2 

Commercial Fishing $2 .53 N/A N/A 

Recreational Fishing $8 .14 $5 .45 $1805 

Saltwater Marshs N/A .207 6 6 .9 6 

Saltwater Beaches $22 .416 $2 .856 $95 .06 

Marine Boating' N/A $1 .15' $38 .45' 

1 Nonmarket value per year 

Z #1 divided by .03 = Asset Value 

Table 55, ex vessel price 

' Table 58, retail price 

5 To commercial fishery landings only 

See text for discussion 

See Table 63 

72 
Table 62 . An Inventory of Marine-Related Recreational Facilities in 

Escambia County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number 9 

b . Length (all) (LFT)* 10,410 

2 . Boardwalks/Catwalks 

a . Number 21 

b . Length (all) (LFT)* 11,065 

3 . Jetties 

a . Length (all) (LFT)* 0 

Boating 

1 . Boat Ramps 

a . Number 26 

b . Total Lanes 38 

2 . Marinas 

a . Total 28 

b . Slips/Moorings 1,383 

c . Dry Storage 515 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

Escambia County has 38 saltwater boat ramp lanes and 1,898 wet slips and 

dry racks as shown in Table 62 . The number of private docks from which to 

launch pleasure craft is unknown. Combining data from Bell et al . (1982) 

and Bell (1995), the annual user value from boating in the Gulf of Mexico 

off Escambia County is estimated and shown in Table 63 . This value is 

about $1 .15 million. 

Recreational boating in marine waters is rapidly growing in Escambia 

County . Such boating can affect coastal water quality (e .g ., inadequate 

pumping out facilities) as well as adding user value to those using coastal 

water resources . From the FDEP (1983-1992) and Bell (1995) studies, 

pleasure boat registrations in Escambia County grew as follows, with 

projected (P) numbers included : 

1983 13,495 

1984 13,892 

1985 14,204 

1986 14,542 

1987 14,898 

1988 15,325 

1989 15,944 

1990 15,790 

1991 15,432 

1992 15,558 

2000 17,460 (P) 

2005 19,066 (P) 

2010 20,803 (P) 

73 
Table 63 . Estimation of the Annual User Value for Saltwater Boating Off 

Escambia County, Florida, 1993-94 . 

Facility 

Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$415,498 = $5 .021 x 15,5582 x .193 x 284 

2 . Boat Rams 

$431,965 = $1 .481 x 15,558 x .67' x 28' 

3 . Private pocks 

$306,157 = $5 .025 x 15,558 x .14 x 28 

,Total Annual User Value = $1,153,620 

*Asset Value = 1,153,620 = .03 = $38 .45 million 

Bell (1995), Florida-wide value 

2 FDEP (1992), Escambia County 

Bell et al . (1982), northwest Florida 

' Bell (1995), Escambia County 

Assumed $/day same for marinas and private docks 

ESC.12 Water Quality, the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is 

manifested in the water quality surrounding the region . Florida's major 

surface water quality problems come from urban stormwater runoff, 

agricultural runoff, domestic wastewater, industry wastewater and 

hydrological changes such as draining and filling wetlands . 

There are three sources of information on local water quality surrounding 

Escambia County . First, the Federal Water Pollution Control Act requires 

the state to prepare a 305(b) technical report on the status and trends in 

surface water quality. Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water. These three sources of information will give a profile of surface 

water conditions in Escambia County . 

Two indices are used in the 305(b) report for measuring surface water 

quality : the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity. The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

74 
Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality. 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Escambia County, 

Perdido Bay and Pensacola Bay have been selected for a brief summary of the 

current state of water quality in this region of the study area (see 

Figures 3 and 4) . 

The Perdido Bay Basin is on the Florida-Alabama border, with Escambia 

County on the eastern side of this basin . Major pollution sources are from 

pulp and paper mills and urban runoff . Champion Paper Corp . (formerly the 

St . Regis Paper Company) is a good example of the former, while the City of 

Pensacola is a high density population center and a good example of the 

latter . The discharge from Champion Paper Corp . negatively effects many 

in-stream water quality parameters, particularly biological integrity, 

color, DO, BOD, nutrients, turbidity and solids . Complaints from 

individuals living around Elevenmile Creek below the paper mill are over 

low density, diversity and species richness values for benthic fauna. 

Also, dissolved oxygen violations were recorded for Perdido Bay and 

Elevenmile Creek during the spring of 1994 . EPA work on fish and dioxin 

concentrations resulted in advisories being issued urging no consumption of 

fish from Elevenmile Creek . Stormwater continues to be a pollution source 

to the bayou and the bay from a variety of non-point sources . The Florida 

side contributes mostly urban and construction stormwater, whereas the 

Alabama side has more agricultural runoff . The WQI and TSI for selected 

areas are listed in Table 64 . 

The Pensacola Bay Basin extends from Escambia County to Santa Rosa County . 

Urban runoff and wastewater treatment plant discharges are the major 

pollution sources . These latter sources are from well-defined points such 

as the University of West Florida WWTP, Monsanto industrial discharges, and 

Gulf Power thermal discharges that enter the Escambia River upstream of the 

mouth . Therefore, reduced DO concentrations, fish kills and bacteria 

problems have been evident around the mouth of the Escambia River . This 

portion of Escambia Bay also receives discharges from CYTEC and Air 

Products, two manufacturing plants . Both discharges have been found to be 

toxic in several bioassays . These companies discharge high levels of 

nitrogen and BOD . As outlined earlier in this report, the industrial 

structure of Escambia County is such that the ecosystem is under constant 

attack from many major industries in this area . This has manifested itself 

in fish kills (April, 1994), toxic bioassays and dirty foam near point 

source outfalls . Moving east in this basin, water quality improves, 

especially in Santa Rosa Sound . The WQI and TSI for important areas are 

also shown in Table 64 . 

75 
Table 64 . Water Quality Indices for Selected Areas of Escambia 

County, Florida. 

Water Areas : Perdido Bay Basin Water Quality Indices 

Water Body Type : Estuary WO.I . TSI 

3 Direct Runoff to Bay -- 50 

4 Big Lagoon -- 35 

5 Direct Runoff to Bay -- 46 

13 Perdido Bay -- 51 

Water B 

10 

ody Tyype : Stream 

Unnamed Stream 36 -- 

12 Bridge Creek 72 -- 

15 Marcus Creek 26 -- 

16 Bellshead Branch 18 -- 

19 Turner Creek 52 -- 

20 Unnamed Branch 29 -- 

21 Hurst Branch 41 -- 

22 Eight Mile Creek 41 -- 

23 Eleven Mile Creek 76* -- 

Water Areas : Pensacola Bay Basin Water Quality Indices 

Water Body Tyke : Estua ry 

2 Pensacola Bay (Mouth) --24 

3 Bayou Grande -- 44 

4 Pensacola Bay (Mid) -- 27 

13 Bayou Chico -- 52 

14 Pensacola Bay (N) -- 25 

18 Bayou Grande -- 44 

22 Texar Bayou -- 56* 

24 Escambia Bay (S) -- 41 

Water Body Type : Stream 

9 Jones Creek 56* --

15 Jackson Creek 49 --

1i29 Carpenter Creek 30 -- 

*Poor water quality . 

The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . Table 65 indicates that in 

1994, two companies (Champion and Monsanto) discharged toxic substances in 

and around the surface water of Escambia County . Of the 13 counties in the 

study area, Escambia County ranked fourth in pounds of toxic chemical 

discharges . These discharges may be highly variable from year to year . 

As of 1993, Perdido Bay had 6,887 acres closed to shellfishing (while 

3,050 acres were conditionally approved) . Of a larger magnitude, the 

Pensacola Bay System had 62,457 acres closed to shellfishing (43,474 acres 

conditionally approved) . Thus, in and around Escambia County, water 

quality is very poor for shellfishing (i .e ., high coliform counts) in that 

nearly 70,000 acres are closed . 

76 
Table 65 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Escambia County, Florida in 1994 . 

Company SIC Discharge Main' 

1 . Champion International 2,621 114,710 Ammonia 

(Pulp and Paper) 

2 . Monsanto (Chemicals) 2,824 799 Nickel/ 

Copper 

Total 115,509 

Leading chemical released based on pounds . 

Source : EPA Toxic Release Inventory, unpublished data, 1994 . 

77 

Socioeconomic Components and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

FRA.1 Introduction 

Franklin County is located in the central section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figures 5 

and 6) . It contains 534 square miles of land, ranking it 56th among the 67 

counties in Florida. In 1990, Franklin County had a population of 8,967, 

ranking it 64th among Florida's counties . The population density was 18 

people per square mile in 1990, a ranking of 62nd in Florida. Franklin 

County has a fairly high median age of 38 .9 years, compared to the Floridawide median of 36 .4 years . 

The population of Franklin County had a per capita income of $14,063 in 

1992, 45th of the 67 Florida counties and 28 .9% below the state-wide 

average of $19,797 . This income was derived primarily from earnings from 

local industries, return on investment (rent, interest, dividends), 

retirement income, and transfer payments (e .g ., AFDC, food stamps, etc .) . 

The sources of income for a county may lead to a characterization of how 

that area interacts with the natural ecosystem . For example, a retirement 

community may produce less toxic chemical discharges into waterbodies, 

compared to an area where income is earned at a local chemical plant . For 

Franklin County, an analysis of the sources of income will be discussed 

below, along with the interaction with the ecosystem . 

Franklin County had 23 .30 of the households below the poverty level in 

1989, which was considerably higher than the State of Florida average of 

9 .0% . In 1993, the unemployment rate was 4 .2% (relative to a statewide 

average of 7 .0%), indicating a slack labor market . 

FRA .2 Trends in Population Income and Samloyment in Franklin County . 

1980-93 . 

Table 66 shows the trend in key economic variables in Franklin County from 

1980 through 1993 . Over this interval, resident population increased by 

23% (1 .7g annually), which was slow when compared to 39 .5% for Florida as a 

whole . Population increases that were induced primarily by industrial 

structure (i .e ., job creation) and natural amenities of the region place 

additional pressure on the carrying capacity of both living (e .g ., coastal 

fishery stocks) and non-living natural resources (e .g ., beaches) . 

Nominal aggregate personal income increased by 1970 from 1980 to 1993 

(Table 66) . Adjusted for inflation, real aggregate personal income 

increased by 70% (5o annually) . Since real income growth outstripped the 

population growth discussed above, the average level of affluence increased. 

This usually is a positive trend for ecosystems since people will have the 

financial resources to reduce negative externalities (e .g ., air and water 

pollution) which often accrue from population growth (Hall, 1994) . 

79 
r 

. . 

y 

' l.y.Jy 

"1 ~ v ^~ Lf S. 

T VINCENT ApplAC,r~ BAY 

T 

r 

GULF OF MEXKA 

APALACHICOLA BAY BASIN 

03130014 

WATER QUALITY 

GOOD 

AVERAGE WATER QUALITY ~ THREATENED 

1984-1993 STORET DATA FAIR 

WATERSHED ID NUMBERS LINK MAP TO TABLES POOR 

INDICATES QUALITATIVE ASSESSMENT 0 UNKNOWN 

Figure S . Map of Franklin County, Florida, showing levels of water 

quality and areas of quality testing (Rpalachicola Bay 

Basin)[from Bureau of Surface Water Management (1994b)] . 

80 
QCY 

. .` ;Y 

NEW RIVER 

T~ . . . ,, 

~ Y CREEK 

i 

"Y- V t ~ j+S r± R C % 

's~ ~ .1 

C 

x~ . L .~} 

,s ~r~` ~. < -_*3 

~1i11VIPER CREEK 

J 

NEW RIVER 

D RIVER 

SO J~O 

GULF OF MEXICO 

NEW RIVER BASIN WATER QUALITY 

03130013 GOOD 

~ THREATENED 

AVERAGE WATER QUALITY FAIR 

1984-1993 STORET DATA POOR WATERSHED ID NUMBERS LINK MAP TO TABLES 

" SSMENT O UNKNOWN INDICATES QUALITATIVE ASSE 

Figure 6 . Map of Franklin County, Florida, showing levels of water 

quality and areas of quality testing (New River Basin)[from 

Bureau of Surface Water Management (1994b)] . 

61 
Table 66 . Trends in Key Economic Aggregate Variables in Franklin County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

Employment3 

1980 7,700 $46,007 $55,834 2,716 

1981 7,800 49,489 54,443 2,951 

1982 8,000 52,471 54,374 2,924 

1983 8,100 58,836 59,072 2,934 

1984 8,400 64,932 62,495 3,003 

1985 8,400 75,331 70,010 3,131 

1986 8,500 84,287 76,904 3,235 

1987 8,600 87,888 77,366 3,363 

1988 8,700 96,184 81,305 3,641 

1989 8,900 104,989 84,668 3,703 

1990 9,000 115,083 88,051 3,569 

1991 9,100 121,381 89,120 3,781 

1992 9,200 128,650 91,692 3,937 

1993 9,500 136,900 94,740 4,020 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Franklin County increased from 2,716 in 1980 to 4,020 

in 1993, a 48% increase . The growth of jobs is stimulated in a region by 

what is known as the export base . Simply put, a region's growth is 

determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region, income to retirees in Florida and injections 

of Federal dollars to sustain military bases such as Eglin Air Force Base 

in Okaloosa County . Through a multiplier process, this export income 

sustains both direct export jobs (e .g ., civilians working for the military) 

and indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Franklin County 

grew less rapidly than the measure of county output - real aggregate 

personal income - as local entrepreneurs introduced labor-saving 

technological devices to economize on the rising cost of labor . 

FRA .3 Trends 1n various welfare Measures in Franklin Counter 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing . A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is more likely to be able 

to protect the ecosystem than one which is highly dependent on income 

82 
maintenance and unemployment insurance, since the former is taxable while 

the latter is not. In 1993, Franklin County derived 960 of its personal 

income from earnings, retirement and capital income, compared to 98 .28 for 

the whole of Florida . Thus, the county is less likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem. The trends in the components of personal income per capita are 

shown for Franklin County in Table 67 . 

FRA.4 Industrial Base : Franklin County 

The "industrial base" for Franklin County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy . The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county ; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy . If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., 10%) in an area, compared 

Table 67 . Trends in Components of Personal Income in Franklin County, 

Florida, 1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents l i

1980 $5,984 $3,375 $241 $16 $1,427 $925 

1981 6,328 3,350 238 12 1,607 1,121 

1982 6,563 3,382 237 13 1,756 1,176 

1983 7,254 3,820 223 15 1,906 1,289 

1984 7,689 3,971 247 11 1,901 1,559 

1985 8,919 4,747 239 34 2,130 1,769 

1986 9,937 5,537 277 20 2,137 1,966 

1987 10,180 5,760 235 14 2,233 1,939 

1988 10,995 6,094 471 24 2,507 1,899 

1989 11,860 4,496 375 28 2,793 2,169 

1990 12,844 6,811 577 31 3,086 2,340 

1991 13,309 7,060 646 41 3,434 2,127 

1992 13,923 7,388 578 59 3,750 2,148 

1993 14,458 7,701 583 38 4,041 2,095 

Source : BEA (1995) 

83 
to the same percentage nationally (e .g ., 0 .5%) assuming the nation consumes 

all it produces - no imports or exports . This is rather simplistic, but it 

does serve as an indicator of which industries are predominately export . 

This figure, the location quotient (LQ), is the following in this example : 

(1) LQ = 10/ .5% = 20 

Thus, 95% would be in export or 

(2) 1 - LQ-1 = . 95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 68 shows the main identified export industries and their contribution 

to personal income in Franklin County . This county depends primarily on 

fishing, forestry, health services, tourism and retirement for its economic 

survival . Franklin County is interesting in that it is two separate parts . 

In the west, the cutting of timber and harvesting of oysters are very large 

industries . In the east, Dog Island and St . George Island host a tourismand retirement-based economy. This dichotomy has been in conflict in 

recent years . Some of the largest individual employers in Franklin County 

have, from time to time, had negative impacts on the ecosystem . Table 69 

shows the top ten employers for Franklin County, along with the products 

they produce that may generate conflicts with the environment . Products 

such as lumber, and in this county, residents, must be rigorously 

controlled or they will reduce water and air quality. 

Historically, Franklin County has had problems with industries located in 

this county . As stated earlier, the residents of Franklin County living on 

Dog Island and St . George Island have been accused by the fishing community 

of polluting the waters with waste from septic tanks . Since there is no 

paper or lumber mill, industrial waste is not a major concern in 

Appalachicola Bay . In 1993, the EPA reported that the companies in 

Franklin County discharged no toxic chemicals into surface water (Lester, 

1995) . 

FRA .5 Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Franklin County, the industries shown in Table 70 fall 

into this characterization . 

The Franklin County economy is heavily based upon timber which is harvested 

and processed in Gulf County into various paper-based products . This 

county is a fishing community and Apalachicola produces nearly 95 percent 

of all Florida oysters . All of these economic activities create various 

kinds of waste that is a point or nonpoint discharge into rivers and 

coastal waters . These industries are primarily involved in the export 

sector and therefore are critical to this coastal county . 

84 
Table 68 . Major Export Industries in Franklin County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings 

(000) 

% of Personal 

Income 

LQ* 

Fisheries $3,329 2 .4 78 .6 

Forestry 

Forestry Services 253 .18 3 .2 

Lumber and Wood Products 1,783 .42 3 .0 

Railroad Transportation 926 .67 2 .6 

Water Transportation 728 .53 4 .1 

Health Services 9,212 6 .7 1 .1 

Tourism/Retirement 

Building and Construction 2,303 1 .7 1 .0 

Food Stores 2,806 2 .0 1 .8 

Eating and Drinking Places 2,330 1 .7 1 .0 

Hotels and Lodging 1,545 1 .1 1 .6 

*LQ = Location quotient . See Text . 

Source : BEA (1995) 

Table 69 . Top Ten Employers in Franklin County, Florida and Products 

Produced, 1994 . 

Employer Employees 

1 . Leavins Seafood, Fishing 100 

2 . D . W . Wilson Seafood, Fishing 100 

3 . Annewakee, Private School 92 

4 . Bayside Shellfish, Fishing 90 

5 . Willis IGA, Grocery 70 

6 . Eastpoint Nursing Home, Health Services 47 

7 . Florida Power Corporation, utilities 35 

8 . Jr . Foods, Grocery 30 

9 . Gibson Inn, Hotel 30 

10 . Miller Trucking Company, Trucking 30 

Sub-Total 624 

Total 4,020 

Percent of Total 150 

Source : Florida Department of Commerce (1994) 

85 
Table 70 . Ecosystem-Sensitive Industries in Franklin County, Florida . 

II Industry Earnings ($000) II 

1 . Forestry 

Forestry Services 

Railroad Transportation 

Water Transportation 

Lumber/Wood 

2 . Tourism/Retirement (Dog Island, St . George Island) 

Building 

Food Stores 

Eating and Drinking Places 

Hotels 

Private Households 

Sub-Total 

Total Earnings (Non-Farm) 

Percent of Total 

$253 

926 

728 

1,783 

3,378 

2,806 

2,330 

1,545 

519 

$14,268 

$136,900 

109. 

Source : BEA (1995) 

FRA.6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of Citrus County is primarily 

composed of ecosystem-insensitive industries, those which have relatively 

little impact on the environment . These are shown in Table 71 . In 

general, industries such as health services and fishing have a less adverse 

impact on local ecosystem health than other industries in Franklin County . 

Over the 1969-93 period, the ecosystem-insensitive industries grew slower 

than the ecosystem-sensitive industries, meaning that new economic growth 

is in conflict with the environment . 

FR.A .7 Commercial Fishery Landings in Franklin County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Franklin County . 

Three categories of fishery products are found : (1) finfish; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 900 of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $12 .3 million worth of commercial fishery 

products were landed at the ex vessel level (Table 72) . Finfish and shrimp 

account for 77% of this value . Among the finfish, grouper was by far the 

leading species as measured by quantity and value . Oysters and scallops 

accounted for 21% of the ex vessel value. Brown shrimp, which depends on 

86 
Table 71 . Ecosystem-Insensitive Industries in Franklin County, Florida . 

Industry Earnings ($000) 

1 . Health Services $9,212 

2 . Fisheries 3,339 

Sub-Total 12,551 

Total Earnings $136,900 

Percent of Total 9g 

Source : Table 68 

Table 72 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Franklin County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Red Grouper 427,374 $752,178 .25 

Gag Grouper 232,216 517,891 .69 

Yellowedge Grouper 236,507 494,299 .62 

Swordfish 51,674 165,873 .55 

Black Mullet 308,078 144,796 .66 

Shark Fins 4,945 91,581 .40 

Shark 212,435 84,974 .00 

Tilefish 53,895 79,764 .60 

Pompano 20,005 67,616 .90 

Amberjack 57,399 55,677 .03 

All Others 439,340 472,559 .60 

A Total $2,927,163 .30 

Invertebrates 

Oysters 1,478,875 $1,833,805 .00 

Calico Scallops 1,245,048 714,807 .38 

'i Blue Crabs 362,407 293,844 .43 

Spanish Lobster 17,940 31,036 .20 

Clams 2,661 12,187 .38 

All others 11,499 2 .782 .45 

Total $2,888,462 .84 

Shrimp (Total) 2,938,079 6,578 .489 .85 

Grand Total $12,394,115 .99 

* State average ex vessel price used . 

Source : FDEP (1994) 

87 
wetlands during a phase of its life cycle, was the dominant shrimp species . 

Among the 13 counties in the study area, Franklin County ranked first in 

the ex vessel value of all commercial fishery landings . 

Although the ex vessel value does not include value added in processing and 

distribution, commercial fishing is a relatively large component of the 

economic base of Franklin County, where aggregate personal income was $136 

million in 1993 . Over the last fourteen years, commercial fishery landing 

has decreased by 37% while the ex vessel value of the catch has decreased 

by 3$ . When adjusted for inflation, the value of landings decreased by 

43% . Compared to other economic trends in Franklin County, commercial 

fishery landings are an important component of the local economy (FDNR, 

1980) . 

FRA .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively that engage in saltwater recreational 

fishing in Florida . In Milon and Thunberg (1992), there is some regional 

breakdown embracing the present study area from Hernando County north to 

Escambia County . Such regions include both coastal and interior counties . 

As an approximation, these regional averages can be applied to the 

individual counties . Bell (1993) has only statewide averages for tourist 

saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

angler for Region I (i .e ., Escambia to Jefferson County) were about 40-50%-

higher than the statewide average . Thus, using the latest study of Bell 

(1993), statewide figures may be conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county (Table 73) . Franklin County had 1,793 resident anglers purchasing a 

one-year fishing license . It should be pointed out that purchase of a 

license in a county does not ensure that one is a resident of that county, 

but informal conversations with Florida Dept . of Environmental Protection 

personnel suggest little bias is associated with that assumption . 

Nonresidents are those that purchased saltwater fishing licenses in noncoastal counties . Such licenses were pro-rated to coastal counties in 

close geographical proximity to each county, using personal judgment, as 

shown in Table 73 . Finally, tourists must purchase a license, and the 

number is shown for the counties in the study area . This may underestimate 

tourist saltwater anglers since tourists may buy a license in an interior 

county and use it in one or more of the coastal counties . 

Table 74 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 73 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers, 

respectively . Franklin County showed a fishing effort of 73,394 days . 

88 
Table 73 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents Nonresident 2 Tourist3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11,685 6 .926 5 .312 

Total 76383 29462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

Non-resident (out of state) saltwater fishing licenses for one year ; 

seven days and three days . 

Table 74 . Estimated Number of Saltwater Recreational Days (Fishing Effort) 

in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresidents 

Tourist2 Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167,499 21,248 188 .747 

Total 952,605 377,480 1,330,085 

9 days per angler year and Table 73 . See Milon and Thunberg (1992) . 

4 days per angler year and Table 73 . See Bell (1993) . 

89 
Finally, Table 75 is derived from Table 73 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $6,502,628 in Franklin County in 1993-94 . Many assumptions 

were made to arrive at these estimates, however, these figures are believed 

to indicate the order of magnitude and relative ranking, and may actually 

be conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) Counties are the top two counties for saltwater 

recreational fishing expenditures . Multiplier effects of nonresidents and 

tourists were not considered . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing. There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Franklin County can be computed as follows : 

Residents 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 7,011 = $2 .6 million 

Tourists 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 4,121 = $0 .8 million . 

Thus, saltwater recreational fishing generates $3 .37 million per year in 

Franklin County with a capitalized value of $112 million using a 3% 

discount rate (i .e ., $3 .37 million = .03) . 

FR.A .9 Fisheries and Wetlan 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing . The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated . This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 76 . 

90 
Table 75 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

TouristZ Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8 .890,475 2,337,280 11,227,755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 73 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 73 multiplied by $440 .00 per angler . 

Table 76 . Economic Value of wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic valuation of wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

91 
Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch . 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Franklin County has 18,400 acres of salt 

marsh (NOAA, 1991), which would be worth $98 million ($5,316 x 18,400) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by Franklin County wetlands . 

FRA.10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier . Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . Table 77 lists the key beaches for this 

county . 

92 
Table 77 . Key Saltwater Beaches in Franklin County, Florida .* 

Western District 

Environmentally Endangered Lands : 

St . Vincent National Wildlife Refuge 

Eastern District 

St . George Island 

Dr . Julian G . Bruce State Park/St . George Island 

Carrabelle Beach 

Dog Island 

*In Franklin County alone, the University of West Florida(1985b) 

reported 26 individual saltwater beaches which were 40 .5 miles in 

length and 187 million square feet (public and private) . 

Source : University of West Florida (1985a) 

In 1984, Bell and Leeworthy (1986) estimated expenditures per day of $12 

(1994 dollars) and $30 (1994 dollars) for residents and tourists, 

respectively, on saltwater beach-related costs such as lodging, food and 

drink, etc . in Pensacola, Florida . These estimates will be used for all 

counties in the study area as an approximation since no recent studies have 

been undertaken . 

Using the CV technique, Leeworthy, et al . (1989) found that Escambia, 

Franklin and Bay Counties had an averaged user value of about $3 .0 per day 

(in 1994 dollars) for residents and tourists . In a comprehensive study of 

Florida beaches, the University of West Florida (1985b) projected that 

Franklin County would have 30,660 saltwater beach days per year in 1990 for 

the beaches listed in Table 77 . By multiplying the user value per day of 

$3 times the estimated number of saltwater beach days, the annual flow of 

value is $91,980 . These are not actual expenditures, but an estimate of 

annual recreational benefits to beach users . The capitalized value of this 

value flow at a real discount rate of 3% is over $3 million - the asset 

value of the beach . 

Finally, beach-related spending in Franklin County in 1990 can be 

calculated in the following manner [with the percent of residents and 

tourists taken from the University of West Florida (1985b) study] : 

(% Residents) x (Beach Days/Yr .) x (Expenditures/day) 

.36 x 30,660 x $12 = $132,451 

(o Tourists) x (Beach Days/Yr.) x (Expenditures/day) 

.64 x 30,660 x $30 = $588,672 

93 
Combined, saltwater beaches in Franklin County attracted an estimated $0 .72 

million in beach-related spending in 1990, with tourists accounting for 830 

of this spending . 

Table 78 identifies three ecological resources that are an asset to 

Franklin County and induce a considerable level of economic activity in 

this region . 

FRA.11 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 79 is an 

inventory of these water-dependent facilities in Franklin County . Piers, 

boardwalks and jetties facilitate bank recreational fishing, beach use and 

other outdoor recreational activities . 

As an outdoor recreational activity, boating makes use of common property 

water resources . Bell (1995) found that the user value per day, expressed 

in 1995 dollars, is worth $3 .56 more if a marina is used (i_e ., $5 .02 less 

$1 .48) rather than a boat ramp . These are Florida-wide values and may or 

may not be good estimates for Franklin County, but we shall use these 

values for purposes of illustration . 

Franklin County has 19 saltwater boat ramp lanes and 624 wet slips and dry 

racks, as shown in Table 79 . The number of private docks from which to 

launch pleasure craft is unknown. Combining data from Bell et al . (1982) 

and Bell (1995), the annual user value from boating in the Gulf of Mexico 

off Franklin County is shown in Table 80 . This value is about $0 .13 

million. 

Table 78 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Franklin County, Florida. 

Resource/Activity Spending User Value Asset Value 

II (Millions) Per Year' (Millions )2 II 

Commercial Fishing $12 .33 N/A N/A 

Recreational Fishing $6 .5' $3 .375 $1125 

Saltwater Marshs N/A .207 6 986 

Saltwater Beaches $ .726 $ .096 $3 .06 

Marine Boating' N/A $ .131' $4 .4' 

I Nonmarket value per year 

Z #1 divided by .03 = Asset Value 

Table 72, ex vessel price 

Table 75, retail price 

5 To commercial fishery landings only 

See text for discussion 

See Table 80 

94 
Table 79 . An Inventory of Marine-Related Recreational Facilities in 

Franklin County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number 

b . Length (all) (LFT)* 2,000 

2 . Boardwalks/Catwalks 

a . Number 27 

b . Length (all) (LFT)* 630 

3 . Jetties 

a . Length (all) (LFT)* 1,100 

Boating 

1 . Boat Ramps 

a . Number 19 

b . Total Lanes 25 

2 . Marinas 

a . Total 11 

b . Slips/Moorings 304 

c . Dry Storage 320 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

Table 80 . Estimation of the Annual User Value for Saltwater Boating Off 

Franklin County, Florida, 1993-94 . 

Facility 

Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

I1 . Marinas 

$47,522 = $5 . 021 x 1, 5572 x .193 x 32' 

I2 . Boat Ramps 

$49,405 = $1 .481 x 1,557 x .67' x 32 

I3 . Private Docks 

$35,016 = $5 .025 x 1,557 x .14 x 32 

II Total Annual User Value = $131,943 

*Asset Value = 131,943 = .03 = $4 .4 million 

Bell (1995), Florida-wide value 

FDEP (1992), Franklin County 

Bell et al . (1982), northwest Florida 

° Bell (1995), Franklin County 

Assumed $/day same for marinas and private docks 

95 
Recreational boating in marine waters is rapidly growing in Franklin 

County . Such boating can affect coastal water quality (e .g ., inadequate 

pumping out facilities) as well as adding user value to those using coastal 

water resources . From the FDEP (1983-1992) and Bell (1995) studies, 

pleasure boat registrations in Franklin County grew as follows, with 

projected (P) numbers included : 

1983 886 

1984 957 

1985 1,010 

1986 1,033 

1987 1,068 

1988 1,074 

1989 1,128 

1990 1,185 

1991 1,309 

1992 1,366 

1993 1,424 

1994 1,557 

2000 1,850 (P) 

2005 2,496 (P) 

2010 3,237 (P) 

FRA.12 Water Quality, the Ecosystem and the $conomv 

The interaction of the local economy and the marine ecosystem is manifested 

in the water quality surrounding the region . Florida's major surface water 

quality problems come from urban stormwater runoff, agricultural runoff, 

domestic wastewater, industry wastewater and hydrological changes such as 

draining and filling wetlands . 

There are three sources of information on local water quality surrounding 

Franklin County . First, the Federal Water Pollution Control Act requires 

the state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Franklin County . 

Two indices are used in the 305(b) report for measuring surface water 

quality : the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen-demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity . The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

96 
Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality. 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Franklin County, 

Apalachicola Bay and New River have been selected for a brief summary of 

the current state of water quality in this region of the study area (Table 

81) . 

The Apalachicola Bay Basin contains approximately 200 square miles of 

estuary area . The bay is defined by a stretch of barrier islands including 

St . George Island, Cape St . George and St . Vincent Islands . The entire bay 

has been declared an Outstanding Florida Water . The most serious threats 

to the bay are direct stormwater runoff and runoff from fish-houses . The 

fish-houses create high BOD levels and some waste from boats docking and 

refueling. In the southern section of the bay, leakage from failing septic 

tanks has caused problems . 

The New River Basin covers low wet forests between the Ochlockonee and 

Apalachicola Rivers . There is very little development in the basin . The 

only sources of pollution are near Carrabelle, where the city used to 

discharge treated wastewater directly into St . George Sound . This problem 

has since been addressed, but marinas and shellfishing continue to threaten 

the water quality . 

Shellfish harvesting has been closed in 1,028 acres during the summer 

months . During the winter, the entire Apalachicola Bay, which is a major 

source of shellfish for the state, is open for harvesting . 

Table 81 . Water Quality Indices for Selected Areas of Franklin 

County, Florida . 

IlWater Areas : Apalachicola Bay Water Quality Indices 

Water Body Type : Estuary 

1 Apalachicola Bay 

2 Apalachicola Bay 

2 St . George Sound 

WOI TSI 

58 

64 

40 

Water Areas : New River Basin 

Water Body Tyke : Estuary 

4 Alligator Harbor 

Water Bodes Tune : Stream 

2 New River 

3 Crooked River 

-- 64 

44 --

43 -- 

97 

Socioeconomic Components and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

GIIL .1 Introduction 

Gulf County is located in the central section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figure 7) . 

It contains 565 .1 square miles of land, ranking it 52nd among the 67 

counties in Florida . In 1990, Gulf County had a population of 11,504, 

ranking this county 57th among Florida's counties . The population density 

was 22 people per square mile in 1990, a ranking of 59th . Gulf County has 

a median age of 35 .7 years, slightly lower than the Florida-wide median of 

36 .4 years . 

The population of Gulf County had a per capita income of $13,840 in 1992, 

48th of the 67 Florida counties and 30%- below the state-wide average of 

$19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income, and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem . For example, a retirement community 

may produce less toxic chemical discharges into waterbodies compared to an 

area where income is earned at a local chemical plant . For Gulf County, an 

analysis of the sources of income will be discussed below, along with the 

interaction with the ecosystem . 

Gulf County had 13 .78 of the households below the poverty level in 1989, 

which was higher than the State of Florida average of 9 .00 . In 1993, the 

unemployment rate was 7 .30 (relative to a statewide average of 7 .Og), 

indicating a tight labor market . 

GIIL .2 Trends in Population . Income and Employment in Gulf County, 1980-93 . 

Table 82 shows the trend in key economic variables in Gulf County from 1980 

through 1993 . Over this interval, resident population increased by 12% 

(0 .9g annually), which was very low when compared to 39 .5% for Florida as a 

whole . Population increases that were induced primarily by industrial 

structure (i .e ., job creation) and natural amenities of the region place 

additional pressure on the carrying capacity of both living (e .g ., coastal 

fishery stocks) and non-living natural resources (e .g ., beaches) . 

Nominal aggregate personal income increased by 141% from 1980 to 1993 . 

(Table 82) . Adjusted for inflation, real aggregate personal income 

increased by 37% (3% annually) . Since real income growth outstripped the 

population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

will have the financial resources to reduce negative externalities (e .g ., 

air and water pollution) which often accrue from population growth . (Hall, 

1994) . 

99 
a 

v 

CONFINA CREE 

~ ~' I~ ~"- , , E O sy BRANCH 

.. 4`t 

To 

GE CREEK 

LAKE POWELL 

*3 

. :. 

n 

K .C i.4 

ST. ANDREWS =~cir 

ATAPPO 

,e.. yl 

w 

GULF OF MEXICO ;:ANTHER SWAMP 

ST. ANDREWS BAY BASIN WATER QUALITY 

03140101 

~ GOOD 

AVERAGE WATER QUALITY ~ THREATENED 

1984-1993 STORET DATA FAIR 

WATERSHED ID NUMBERS LINK MAP TO TABLES POOR 

INDICATES QUALITATIVE ASSESSMENT (~ UNKNOWN 

Figure 7 . Map of Gulf County, Florida, showing levels of water quality 

and areas of quality testing (St . Andrews Bay Basin)[from 

Bureau of Surface Water Management (1994b)] . 

100 
Table 82 . Trends in Key Economic Aggregate Variables in Gulf County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

Employment' 

1980 10,700 $72,191 $87,610 3,795 

1981 10,600 80,528 88,590 3,909 

1982 10,700 86,821 89,970 3,996 

1983 10,800 93,290 93,665 4,071 

1984 10,900 100,804 97,020 4,046 

1985 11,100 105,645 98,183 4,016 

1986 11,100 113,979 103,995 4,107 

1987 11,200 117,544 103,472 4,218 

1988 11,300 124,685 105,397 4,251 

1989 11,400 132,476 106,835 4,371 

1990 11,500 141,834 105,519 4,440 

1991 11,600 150,105 110,209 4,301 

1992 11,700 161,599 115,181 4,424 

1993 12,000 174,258 120,594 4,692 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Gulf County increased from 3,795 in 1980 to 4,692 in 

1993, a 24% increase . The growth of jobs is stimulated in a region by what 

is known as the export base . Simply put, a region's growth is determined 

by its ability to derive "export income" from outside the region . In 

Florida, such income may come from physically exporting goods such as 

electronic components or fish, but it is more likely to come from tourists 

visiting the region ; income to retirees in Florida and injections of 

Federal dollars to sustain military bases such as Eglin Air Force Base in 

Okaloosa County . Through a multiplier process, this export income sustains 

both direct export jobs (e .g ., civilians working for the military) and 

indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Gulf County grew 

less rapidly than the measure of county output - real aggregate personal 

income - as local entrepreneurs introduced labor-saving technological 

devices to economize on the rising cost of labor . 

GIIL .3 Trends in Various Welfare Measures in Gulf County . 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing . A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is more likely to be able 

to protect the ecosystem than one which is highly dependent on income 

101 
maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Gulf County derived 960 of its personal 

income from earnings, retirement and capital income, compared to 98 .20 for 

Florida as a whole . Thus, the county is more likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem. The trends in the components of personal income per capita are 

shown for Gulf County in Table 83 . 

GIIL .4 Industrial Base : Gulf County 

The "industrial base" for Gulf County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy. The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county ; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy. If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., 10%) in an area, 

compared to the same percentage nationally (e .g ., 0 .50), assuming the 

Table 83 . Trends in Components of Personal Income in Gulf County, Florida, 

1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends. 

(Nominal) Maintenance Interest, 

Rents 

1980 $6,765 $4,723 $190 $28 $1,157 $666 

1981 7,630 5,175 194 29 1,413 819 

1982 8,094 5,335 199 53 1,596 912 

1983 8,673 5,667 210 71 1,727 998 

1984 9,268 6,045 224 34 1,820 1,146 

1985 9,533 6,170 215 33 1,984 1,132 

1986 10,244 6,537 216 31 2,111 1,350 

1987 10,503 6,816 203 35 2,204 1,244 

1988 11,082 7,058 270 28 2,366 1,360 

1989 11,651 7,161 266 31 2,699 1,493 

1990 12,329 7,356 341 38 3,016 1,579 

1991 12,988 7,410 413 59 3,412 1,694 

1992 13,832 7,776 480 107 3,747 1,722 

1993 14,482 8,188 464 87 3,990 1,753 

Source : BEA (1995) 

102 
nation consumes all it produces - no imports or exports . This is rather 

simplistic, but does serve as a barometer of which industries are 

predominately export . This figure, the location quotient (LQ), would be : 

(1) LQ = lOg/ .5% = 20 

Thus, 95% would be in export or 

(2) 1 - LQ-1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 84 shows the main identified export industries and their contribution 

to personal income in Gulf County . This county depends primarily on 

forestry, paper products, fishing and chemical production for its economic 

survival . The county's largest employers are St . Joe Forest Products and 

two other forestry-related companies . Raffield Fisheries also is based in 

Gulf County . Other major employers in the county include two chemical 

companies and Apalachicola Northern Railroad . In this county, tourism is 

not a major industry . Some of the largest individual employers in Gulf 

County have, from time to time, had negative impacts on the ecosystem. 

Table 85 shows the top employers in Gulf County, along with the products 

they produce that may generate conflicts with the ecosystem. Products such 

as chemicals, lumber and paper products must be rigorously controlled or 

they will reduce water and air quality. Gulf County has had problems with 

industries located in this county ; Arizona Chemical and St . Joe paper mill 

both discharge large quantities of chemicals to the City of Port St . Joe 

Waste Water Treatment Plant which are then released into the surface water . 

GIIL .5 Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Gulf County, the industries shown in Table 86 fall into 

this category . 

The Gulf County economy is heavily based upon timber which is harvested and 

processed regionally into various paper-based products . Fishing is also a 

very important export, and Port St . Joe serves as a major port for shipping 

these products . All of these economic activities create various kinds of 

waste that is a point or nonpoint discharge into rivers and coastal waters . 

These industries are primarily involved in the export sector and therefore 

are critical to this coastal county . 

GIIL .6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of 

primarily of ecosystem-sensitive industries . 

insensitive industries, have relatively little 

and are shown in Table 87 . 

Gulf County is composed 

The remainder, ecosystemimpact on the environment 

103 
Table 84 . Major Export Industries in Gulf County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings 

(000) 

o of Personal 

Income 

LQ* 

Forestry $200 .11 2 .00 

Lumber N/A 

Paper Products (Manufacturing) 35,961 

Railroad Transportation 2,717 1 .55 6 .10 

Fishing 388 .22 7 .17 

Chemicals (Manufacturing) 5,827 

*LQ = Location quotient . See Text . 

Source : BEA (1995) 

Table 85 . Top Employers in Gulf County, Florida and Products Produced, 1994 . 

Employer Employees 

1 . St . Joe Forest Products, Paper 900 

2 . Raffield Fisheries, Fishing 160 

3 . Arizona Chemicals, Chemicals 126 

4 . Premier Services, Chemicals 106 

5 . whitfield Timber Company, Lumber and Millwork 100 

6 . Apalachicola Northern Railroad, Railroad Services 98 

7 . St . Joe Container, Paper Products 87 

8 . Material Transfer, Coal 15 

Sub-Total 1,592 

Total 4,692 

Percent of Total 34% 

Source : Florida Department of Commerce (1994) 

Table 86 . Ecosystem-Sensitive Industries in Gulf County, Florida . 

Industry Earnings ($000) 

1 . Lumber/Forestry/Paper Products $3,700 

2 . Railroad Transportation 2,717 

3 . Chemicals 5 .000 

Sub-Total $43,748 

Total Earnings (Non-Farm) 174,258 

Percent of Total 26% 

Source : BEA (1995) 

104 
Table 87 . Ecosystem-Insensitive Industries in Gulf County, Florida . 

Industry Earnings ($000) 

1 . Fisheries $388 

Sub-Total 388 

Total Earnings $174,258 

Source : Talbe 84 

In general, industries such as fisheries have a less adverse impact on 

local ecosystem health than other industries in Gulf County . Over the 

1969-93 period, ecosystem-insensitive industries were growing slower than 

ecosystem-sensitive industries, meaning that the economic base of Gulf 

county is in direct conflict with the environment . 

GUL .7 Commercial Fishery Landings in Gulf County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Gulf County . 

Three categories of fishery products are found : (1) finfish; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $3 .8 million worth of commercial fishery 

products were landed in Gulf County at the ex vessel level (Table 88) . 

Finfish and shrimp account for 90% of this value . Among the finfish, 

ladyfish and menhaden were the leading species as measured by quantity and 

value . Brown shrimp, which depends on wetlands during a phase of its life 

cycle, was the dominant shrimp species . Among the 13 counties in the study 

area, Gulf County ranked 5th in the ex vessel value of all commercial 

fishery landings . Although the ex vessel value does not include value 

added in processing and distribution, commercial fishing is a relatively 

important component of the economic base of Gulf County, where aggregate 

personal income was $174 million in 1993 . Over the last fourteen years, 

commercial fishery landing has increased by 91% while the ex vessel value 

of the catch has increased by 154% . When adjusted for inflation, the value 

of landings changed by 41% . 

GIIL .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively, that engage in saltwater recreational 

fishing in Florida . In Milon and Thunberg (1992), there is some regional 

105 
Table 88 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Gulf County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Ladyfish 1,467,167 $586,866 .81 

Menhaden 5,059,917 556,590 .88 

Misc . Foot Fish 763,755 450,615 .44 

Misc . Industrial Fish 2,815,391 450,462 .56 

Little Tuna 931,336 232,834 .00 

Spanish Sardines 815,968 122,395 .20 

Round Scad 424,314 110,321 .63 

Goatfishes 54,321 63,545 .04 

Black Mullet 126,018 59,228 .46 

Baitfish 413,158 45,447 .38 

All Others 593,933 146 .587 .45 

Total $2,888,232 .17 

Invertebrates 

Calico Scallops 633,536 $361,115 .50 

Clams 5,104 9,864 .52 

Blue Crabs 10,182 6,516 .48 

Squid 10,771 3,985 .27 

Oysters 2,529 3,135 .96 

All others 34,899 3 .501 .13 

Total $388,118 .86 

Shrimp (Total) 267,329 500 .270 .15 

Grand Total $3,756,621 .18 

* State average ex vessel price used . 

Source : FDEP (1994) 

breakdown embracing the present study area from Hernando County north to 

Escambia County . Such regions include both coastal and interior counties . 

As an approximation, these regional averages can be applied to the 

individual counties . Bell (1993) has only statewide averages for tourist 

saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

angler for Region 2 (i .e ., Escambia to Jefferson County) were about 40-50% 

higher than the statewide average . Thus, using the latest study of Bell 

(1993), statewide figures may be conservative . 

Construction of an approximation to the number of anglers, fishing days 

(i .e ., fishing effort) and fishing expenditures by county in the present 

study area started with the 1993-94 saltwater fishing licenses sold in each 

county (Table 89) . Gulf County had 3,316 resident anglers purchasing a 

one-year fishing license . It should be pointed out that purchase of a 

license in a county does not ensure that one is a resident of that county, 

but informal conversations with Florida Dept . of Environmental Protection 

personnel suggest little bias is associated with that assumption . 

Nonresidents are those that purchased saltwater fishing licenses in noncoastal counties . Such licenses were pro-rated to coastal counties in 

106 
Table 89 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents Nonresident 2 Tourist 3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11 .685 6,926 5,312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

' Non-resident (out of state) saltwater fishing licenses for one year ; seven days 

and three days . 

close geographical proximity to each county, using personal judgment, as 

shown in Table 89 . Finally, tourists must purchase a license, and the 

number is shown for just the counties in the study area . This may 

underestimate tourist saltwater anglers since tourists may buy a license in 

an interior county and use it in one or more of the coastal counties . 

Table 90 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 89 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers, 

respectively . Gulf County showed a fishing effort of 49,520 days . 

Finally, Table 91 is derived from Table 89 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $3,748,413 in Gulf County in 1993-94 . Many assumptions were 

made to arrive at these estimates, however, these figures are believed to 

indicate an order of magnitude and relative ranking, and may actually be 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . Multiplier effects of nonresidents and 

tourists were not considered . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

107 
Table 90 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

TouristZ Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167 .499 21 .248 188 .747 

Total 

u 

952,605 377,480 1,330,085 

~i 

1 9 days per angler year and Table 89 . See Milon and Thunberg (1992) . 

2 4 days per angler year and Table 89 . See Bell (1993) . 

Table 91 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Tourist2 Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8,890 .475 2 .337,280 11 .227 .755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 89 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 89 multiplied by $440 .00 per angler . 

108 
recreational fishing. There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Gulf County can be computed as follows : 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 3,316 = $1 .2 million 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 4,919 = $ .95 million . 

Thus, saltwater recreational fishing generates $2 .1 million per year in 

Gulf County with a capitalized value of $70 million using a 3% discount 

rate (i .e ., $21 million = .03) . 

GIIL .9 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing. The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property, where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets, such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated. This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 92 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida. This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch. 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent. A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

109 
Table 92 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D .C . 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Gulf County has 2,800 acres (NOAA, 1991) 

110 
of salt marsh which would be worth $14 .9 million ($5,314 x 2,800) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by wetlands off the shore of 

Gulf County . 

GIIL .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier. Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . 

In 1984, Bell and Leeworthy (1986) estimated expenditures per day of $12 

(1994 dollars) and $30 (1994 dollars) for residents and tourists, 

respectively, on saltwater beach-related costs such as lodging, food and 

drink, etc . in Pensacola, Florida . These estimates will be used for all 

counties in the study area as an approximation since no recent studies have 

been undertaken . 

Using the CV technique, Leeworthy, et al . (1989) found that Escambia, 

Franklin and Bay Counties had an averaged user value of about $3 .0 per day 

(in 1994 dollars) for residents and tourists . In a comprehensive study of 

Florida beaches, the University of West Florida (1985b) projected that Gulf 

County would have 103,860 saltwater beach days per year in 1990 for the 

beaches listed in Table 93 . By multiplying the user value per day of $3 

times the estimated number of saltwater beach days, the annual flow of 

value is $3 .11 million . These are not actual expenditures, but an estimate 

of annual recreational benefits to beach users . The capitalized value of 

this value flow at a real discount rate of 3% is over $10 million - the 

asset value of the beach . 

Finally, beach-related spending in Gulf County in 1990 can be calculated in 

the following manner [with the percentage of residents and tourists taken 

from the University of West Florida (1985b) study] : 

(% Residents) x (Beach Days/Yr.) x (Expenditures/day) 

36 x 103,860 x $12 = $ .44 million 

(o Tourists) x (Beach Days/Yr.) x (Expenditures/day) 

.64 x 103,860 x $30 = $2 .0 million 

111 
Table 93 . Key Saltwater Beaches in Gulf County, Florida.* 

Western District 

Environmentally Endangered Lands : 

Beacon Hill Public Beach 

St . Joe Beach 

St . Joe Beach - Port St . Joe 

Port St . Joe City Park 

Indian Pass 

Cape San Blas 

St . Joseph Peninsula State Park 

*In Gulf County alone, the University of West Florida (1985b) reported 

12 individual saltwater beaches which were 16 .4 miles in length and 

6 .4 million square feet (public and private) . 

Source : University of West Florida (1985a) 

Combined, saltwater beaches in Gulf County attracted an estimated $2 .44 

million in beach-related spending in 1990 with tourists accounting for 83% 

of this spending . Table 94 identifies three ecological resources that are 

an asset to Gulf County and induce a considerable level of economic 

activity in this region . 

GIIL .11 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Piers, 

boardwalks and jetties facilitate bank recreational fishing, beach use and 

other outdoor recreational activities . 

Table 94 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Gulf County, Florida. 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year' 

Asset Value 

(Millions )Z 

Commercial Fishing $3 .83 N/A N/A 

Recreational Fishing $3 .7' $2 .15 $705 

Saltwater Marshs N/A .207 6 14 .9 6 

Saltwater Beaches $2 .446 $3 .116 $10 .06 

Marine Boating' N/A $ .169' $5 .64' 

i Nonmarket value per year 

2 #1 divided by .03 = Asset Value 

Table 88, ex vessel price 

Table 91, retail price 

5 To commercial fishery landings only 

6 See text for discussion 

'See Table 95 

112 
As an outdoor recreational activity, boating makes use of common property 

water resources . Bell (1995) found that the user value per day, expressed 

in 1994 dollars, is worth $3 .56 more if a marina is used ($5 .02 less $1 .48) 

rather than a boat ramp . These are Florida-wide values and are used for 

purposes of illustration . 

Gulf County has 5 saltwater boat ramp lanes and 121 wet slips and dry 

racks . The number of private docks from which to launch pleasure craft is 

unknown. Combining data from Bell et al . (1982) and Bell (1995), the 

annual user value from boating in the Gulf of Mexico off Gulf County is 

estimated and is shown in Table 95 . This value is about $ .17 million . 

Recreational boating in marine waters is rapidly growing in Gulf County . 

Such boating can affect coastal water quality (e .g ., inadequate pumping out 

facilities) as well as adding user value to those using coastal water 

resources . From the FDEP (1983-1992) and Bell (1995) studies, pleasure 

boat registrations grew as follows, with projected (P) numbers included : 

1983 1,352 

1984 1,492 

1985 1,537 

1986 1,672 

1987 1,735 

1988 1,821 

1989 1,883 

1990 1,883 

1991 1,836 

1992 1,917 

1993 1,866 

1994 1,996 

2000 2,763 (P) 

2005 3,461 (P) 

2010 4,334 (P) 

GIIL .12 Water Quality . the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is manifested 

in the water quality surrounding the region . Florida's major surface water 

quality problems come from urban stormwater runoff, agricultural runoff, 

domestic wastewater, industry wastewater and hydrological changes such as 

draining and filling wetlands . 

There are three sources of information on local water quality surrounding 

Gulf County . First, the Federal Water Pollution Control Act requires the 

state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Gulf County . 

113 
Table 95 . Estimation of the Annual User Value for Saltwater Boating Off 

Gulf County, Florida, 1993-94 . 

Facility 

(Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$60,921 = $5 .021 x 1,9962 x .193 x 324 

2 . Boat Rams 

$63,335 = $1 .481 x 1,996 x .67' x 32 

3 . Private pocks 

$44,8889 = $5 .025 x 1,996 x .14 x 32 

Total Annual User Value = $169,415 

*Asset Value = 169,415 = .03 = $5 .64 million 

Bell (1995), Florida-wide value 

2 FDEP (1992), Gulf County 

Bell et al . (1982), northwest Florida 

' Bell (1995), Gulf County 

Assumed $/day same for marinas and private docks 

Two indices are used in the 305(b) report for measuring surface water 

quality: the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity. The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality. 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Gulf County, we have 

selected St . Andrews Bay for a brief summary of the current state of water 

quality in this region of the study area (Figure 7) . 

The portion of the St . Andrews Bay Basin that lies in Gulf County includes 

Panther Creek, St . Joseph Bay, and Watappo . The major sources of pollution 

in these areas are from St . Joe Forest Products and the Premier Services 

Corporation . Both of these companies discharge into the Gulf County Canal 

near the St . Joseph Bay, where the pollution becomes diluted with cleaner 

bay water . This, however, has changed the water quality near the canal for 

114 
the worse . Sediments are mucky, not sandy, and seagrass coverage has 

decreased . High pH and TSS levels are becoming larger problems for the 

bay. The WQI and TSI for selected areas are listed in Table 96 . 

The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . Table 97 indicates that in 

1994, two companies (Arizona Chemical and St . Joe Paper) discharged toxic 

substances to the wastewater treatment plant in the City of Port St . Joe . 

These discharges may be highly variable from year to year . Shellfish 

harvesting has been closed in 6,088 acres, while still being allowed in 

34,137 acres . Gulf County is the second largest oyster-producing county in 

the state . 

Table 96 . Water Quality Indices for Selected Areas of Gulf County, 

Florida. 

Water Areas : St . Andrews Bay Basin Water Quality Indices* 

Water Body Type : Estuary ~ TSI 

1 St . Joseph Bay -- 52 

2 Panther Swamp -- 56 

Water Body Tyge : Stream 

5 Watappo 22 -- 

* Higher values indicate lower water quality 

Table 97 . Toxic Chemical Releases Into Surface Water by Firms Located in 

Gulf County, Florida in 1994 . 

Company SIC Discharge Main" 

1 . Port St . Joe Forest 2,621 101,250 Methanol 

Products (Pulp and Paper) 

2 . Arizona Chemicals 2,957 16 .173 Biphenyl 

Total 117,423 

Leading chemical released based on pounds . 

Source : EPA Toxic Release Inventory, unpublished data, 1994 . 

115 

Socioeconomic Components and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

JEF .1 Introduction 

Jefferson County is located in eastern section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figure 8) . 

It contains 597 .8 square miles of land, ranking it 45th among the 67 

counties in Florida. In 1990, Jefferson County had a population of 11,296, 

ranking it 58th among Florida's counties . The population density was 22 

people per square mile in 1990, a ranking of 59th in Florida . Jefferson 

County has a relatively low median age of 33 .8 years, compared to the 

Florida-wide median of 36 .4 years . 

The population of Jefferson County had a per capita income of $13,739 in 

1992, 49th of the 67 Florida counties and 44% below the state-wide average 

of $19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income, and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem . For example, a retirement community 

may produce less toxic chemical discharges into waterbodies compared to an 

area where income is earned at a local chemical plant . For Jefferson 

County, an analysis of the sources of income will be discussed below, along 

with the interaction with the ecosystem . 

Jefferson County had 17 .50 of the households below the poverty level in 

1989, which was considerably higher than the State of Florida average of 

9 .0% . In 1993, the unemployment rate was 4 .90 (relative to a statewide 

average of 7 .Og), indicating a slack labor market . 

JEF .2 Trends in Population, Income and Employment in Jefferson County, 

1980-93 . 

Table 98 shows the trend in key economic variables in Jefferson County from 

1980 through 1993 . Over this interval resident population increased by 9% 

(0 .7% annually), which was slow when compared to 39 .5% for Florida as a 

whole. Population increases that were induced primarily by industrial 

structure (i .e ., job creation) and natural amenities of the region place 

additional pressure on the carrying capacity of both living (e .g ., coastal 

fishery stocks) and non-living natural resources (e .g ., beaches) . 

Nominal aggregate personal income increased by 152% from 1980 to 1993 . 

(Table 98) . Adjusted for inflation, real aggregate personal income 

increased by 44% (3 .4% annually) . Since real income growth outstripped 

population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

will have the financial resources to reduce negative externalities (e .g ., 

air and water pollution) which often accrue from population growth . (Hall, 

1994) . 

117 
I WACISSA 

AUCILLA RIVER BASIN 

03110103 

AVERAGE WATER QUALITY 

1984-1993 STORET DATA 

WATERSHED ID NUMBERS LINK MAP TO TABLES 

INDICATES QUALITATIVE ASSESSMENT 

WATER QUALITY 

GOOD 

THREATENED 

FAIR 

POOR 

UNKNOWN 

Figure 8 . Map of Jefferson County, Florida, showing levels of water 

quality and areas of quality testing (Aucilla River Basin)[from 

Bureau of Surface Water Management (1994a)] . 

118 
Table 98 . Trends in Key Economic Aggregate Variables in Jefferson County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

gnployment3 

1980 10,800 $68,094 $82,638 3,903 

1981 10,900 72,968 80,273 3,788 

1982 11,000 80,433 83,350 3,764 

1983 11,100 84,442 84,781 3,837 

1984 11,200 89,667 86,301 3,801 

1985 11,100 96,807 89,969 3,684 

1986 11,000 104,040 94,927 3,683 

1987 11,100 111,501 98,152 3,850 

1988 11,200 121,051 102,325 3,993 

1989 11,200 131,364 105,939 3,888 

1990 11,400 145,054 110,982 4,163 

1991 11,600 155,938 114,492 4,281 

1992 11,700 165,579 118,018 4,402 

1993 

11 

11,800 172,176 119,153 4,453 

J 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Jefferson County increased from 3,903 in 1980 to 

4 .453 in 1993, a 14%- increase . The growth of jobs is stimulated in a 

region by what is known as the export base . Simply put, a region's growth 

is determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region, income to retirees in Florida and injections 

of Federal dollars to sustain military bases such as Eglin Air Force Base 

in Okaloosa County . Through a multiplier process, this export income 

sustains both direct export jobs (e .g ., civilians working for the military) 

and indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Jefferson County 

grew less rapidly than the measure of county output - real aggregate 

personal income - as local entrepreneurs introduced labor-saving 

technological devices to economize on the rising cost of labor . 

JEF .3 Trends in Various Welfare Measures in Jefferson County, 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing. A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is more likely to be able 

to protect the ecosystem than one which is highly dependent on income 

119 
maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Jefferson County derived 95 .69. of its personal 

income from earnings, retirement and capital income, compared to 98 .28 for 

the whole of Florida . Thus, the county is less likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem. The trends in the components of personal income per capita are 

shown for Jefferson County in Table 99 . 

JEF.4 Industrial Base : Jefferson County 

The 'industrial base" for Jefferson County refers to the industries that 

are primarily export in nature as discussed above . These industries drive 

the local economy . The rest of the industries in the county are "nonexport industries" that depend, for the most part, on what happens inside 

the region . These are called non-basic industries . For small areas such 

as counties, agriculture, fisheries, mining, manufacturing, transportation 

and service-oriented industries for tourists are likely to be export 

industries while wholesale and retail trade, finance, services and local 

government are likely to be non-basic industries . No data are available on 

exports from a county ; however, location quotients and expert judgment can 

be used to identify such industries with some accuracy . If a given county 

is highly specialized relative to the nation in the production of a 

particular commodity, the product is presumed to be an export item (e .g ., 

automobiles from Detroit) . The specialization is measured by computing the 

percentage of personal income generated by an industry (e .g ., 10%) in an 

area, compared to the same percentage nationally (e .g ., 0 .5%), assuming the 

Table 99 . Trends in Components of Personal Income in Jefferson County, 

Florida, 1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $6,325 $4,417 $253 $9 $930 $716 

1981 6,712 4,517 268 10 1,065 852 

1982 7,288 4,776 273 20 1,180 1,040 

1983 7,633 4,958 279 21 1,281 1,095 

1984 7,979 5,197 298 14 1,327 1,142 

1985 8,754 5,619 311 19 1,508 1,296 I 

1986 9,439 6,136 299 13 1,618 1,373 

1987 10,066 6,676 296 12 1,713 1,364 

1988 10 , 851 7 , 208 333 10 1,823 1,476 

1989 11 , 717 7,429 360 13 2 067 1,849 

1990 12,767 7,974 425 18 2,289 2,060 

1991 13,501 8,215 506 28 2,581 2,171 

1992 14,105 8,596 661 43 2,849 1,955 

1993 14,575 8,854 606 34 3,074 2,007 

Source : BEA (1995) 

120 
nation consumes all it produces - no imports or exports . This is rather 

simplistic, but it does serve as an indicator of which industries are 

predominately export . This figure, the location quotient (LQ), would be : 

(1) LQ = 10%/ .5a = 20 

Thus, 95g would be in export or 

(2) 1 - LQ-1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 100 shows the main identified export industries and their 

contribution to personal income in Jefferson County . This county depends 

primarily on agricultural services, lumber manufacturing, apparel 

manufacturing, utilities and local government for its economic survival . 

Some of the largest individual employers in Jefferson County have, from 

time to time, had negative impacts on the ecosystem . For Jefferson County, 

Table 101 shows the top ten employers, along with the products they produce 

that may generate conflicts with the environment . Industries such as 

logging, lumber and wood products, and utilities must be rigorously 

controlled or they will reduce water and air quality . In 1993, the EPA 

reported that the companies in Jefferson County discharged no toxic 

chemicals into surface water (Lester, 1995) . 

JEF .S Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Jefferson County, the industries shown in Table 102 fall 

into this category . 

Table 100 . Major Export Industries in Jefferson County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings 

(000) 

% of Personal 

Income 

LQ* 

Agricultural Services $3,867 2 .2 5 .6 

Manufacturing 

Apparel 1,624 .94 2 .5 

Lumber and wood 3,607 2 .1 4 .9 

Utilities 3,798 2 .2 2 .2 

State and Local Government 20,215 11 .7 1 .4 

*LQ = location quotient . See Text . 

Source : BEA (1995) 

121 
Table 101 . Top Ten Employers in Jefferson County, Florida and Products 

Produced, 1994 . 

Employer Employees 

1 . Command Enterprises, Apparel 145 

2 . Simpson Nursery, Plants 125 

3 . Brynwood Center, Nursing Home 105 

4 . Bassett's Dairy, Food Products 50 

5 . Winn-Dixie, Grocery 46 

6 . Florida Power Corporation, Utilities 45 

7 . Farmers and Merchants Bank, Financial Services 34 

8 . Monticello Foodway, Grocery 28 

9 . Kaleidoscope Limited 20 

10 . Jefferson County Kennel Club, Dog Racing 79 

Sub-Total 617 

Total 4,453 

Percent of Total 14% 

Source : Florida Department of Commerce (1994) 

Table 102 . Ecosystem-Sensitive Industries in Jefferson County . 

11 Industry Earnings ($000) 11 

1 . Agricultural Services 

2 . Apparel 

3 . Lumber and wood 

4 . Utilities 

Sub-Total 

Total Earnings (Non-Farm) 

Percent of Total 

Source : BEA (1995) 

$3,867 

1,624 

3,607 

3,798 

$12,896 

69,470 

19%. 

The Jefferson County economy is heavily based upon agricultural services . 

Lumber and wood products also are large components of the Jefferson County 

economy. All of these economic activities create various kinds of waste 

that is a point or nonpoint discharge into rivers and coastal waters . 

These industries are primarily involved in the export sector and therefore 

are critical to this coastal county . 

JEF .6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of Jefferson County is 

composed of primarily ecosystem-sensitive industries . The remainder are 

ecosystem-insensitive industries, which have relatively little impact on 

the environment and are shown in Table 103 . 

122 
Table 103 . Ecosystem-Insensitive Industries in Jefferson County . 

11 Industry Earnings ($000) 

1 . State and Local Government 20 .215 

Sub-Total $20,215 

Total Earnings 69,470 

Percent of Total 290 

Source : Table 100 And 102 

In general, an industry such as government has a less adverse impact on 

local ecosystem health than other industries in Jefferson County . Over the 

1969-93 period, the ecosystem-insensitive industries grew faster than the 

ecosystem-sensitive industries, meaning that the growth of the Jefferson 

County economy is not in conflict with the environment . 

JEF.7 Commercial Fishery Landings in Jefferson County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Jefferson County . 

Three categories of fishery products are found : (1) finfish; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90g of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . Jefferson County only had $1,000 of fishery landings in 1994 

(Table 104) ; with very little coastal area, fisheries are a relatively 

insignificant part of the economy. Among the 13 counties in the study 

area, Jefferson County ranked 13th in the ex vessel value of all commercial 

fishery landings . 

JEF .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively, that engage in saltwater recreational 

fishing in Florida . In Milon and Thunberg (1992), there is some regional 

breakdown embracing the present study area from Hernando County north to 

Escambia County . Such regions include both coastal and interior counties . 

As an approximation, these regional averages can be applied to the 

individual counties . Bell (1993) has only statewide averages for tourist 

saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

123 
Table 104 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Jefferson County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Porgies 287 $264 .04 

Gag Grouper 78 173 .94 

Cobia 63 111 .51 

Grunts 228 107 .16 

Flounder 36 62 .28 

Sea Bass 66 30 .36 

Red Snapper 10 24 .20 

Triggerfish 18 16 .56 

Other Jack 26 11 .44 

Total $801 .49 

Invertebrates 

Blue Crabs 270 172 .80 

Total 172 .80 

Shrimp (Total) o o .oo 

Grand Total $974 .29 

* State average ex vessel price used . 

Source : FDEP (1994) 

angler for Region 2 (i .e ., Escambia to Jefferson County) were about 40-50% 

higher than the statewide average . Thus, using the latest study or Bell 

(1993) statewide figures may be very conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county (Table 105) . Jefferson County had 250 resident anglers purchasing a 

one-year fishing license . It should be pointed out that purchase of a 

license in a county does not ensure that one is a resident of that county, 

but informal conversations with Florida Dept . of Environmental Protection 

personnel suggest little bias is associated with that assumption . 

Nonresidents are those that purchased saltwater fishing licenses in noncoastal counties . Such licenses were pro-rated to coastal counties in 

close geographical proximity to each county, using personal judgment, as 

shown in Table 105 . Finally, tourists must purchase a license, and the 

number is shown for the counties in the study area . This may underestimate 

tourist saltwater anglers since tourists may buy a license in an interior 

county and use it in one or more of the coastal counties . 

Table 106 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 105 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers 

respectively . Jefferson County showed a fishing effort of 15,277 days . 

124 
Table 105 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents Nonresident 2 Tourist3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11,685 6 .926 5"312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

Non-resident (out of state) saltwater fishing licenses for one year; 

seven days and three days . 

Table 106 . Estimated Number of Saltwater Recreational Days 

(Fishing Effort) in the Thirteen County Study Area, 

1993-94 . 

County Resident + 

Nonresidents 

Tourist2 Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167,499 21"248 188 .747 

Total 952,605 377,480 1,330 085 

9 days per angler year and Table 105 . See Milon and Thunberg (1992) . 

4 days per angler year and Table 105 . See Bell (1993) . 

125 
Finally, Table 107 is derived from Table 105 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $872,573 in Jefferson County in 1993-94 . Many assumptions 

were made to arrive at these estimates, however, these figures are believed 

to indicate an order of magnitude and relative ranking, and may actually be 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing. There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41.70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Jefferson County can be computed as follows : 

Residents 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 1,577 = $ .59 million 

Tourists 

(Value/day) x (days/angler) x ( :W Anglers) : 

$48 .67 x 4 x 271 = $ .05 million . 

Table 107 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

TouristZ Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8 .890 .475 2 .337,280 11 .22 .755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 105 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 105 multiplied by $440 .00 per angler . 

126 
Thus, saltwater recreational fishing generates $ .64 million per year in 

Jefferson County with a capitalized value of $21 million using a 3g 

discount rate (i .e ., $ .64 million = .03) . 

JEF.9 Fisheries and wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export, 

rather than wetlands for grazing . The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property, where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets, such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated . This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 108 . 

Table 108 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized value 

($/acre at 

5°s discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

127 
Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch . 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Jefferson County has 3,800 acres of salt 

marsh (NOAA, 1991), which would be worth $20 .2 million ($5,316 x 3,800) in 

fishery production alone . Negative ecological factors, such as dredging 

or oil spills would threaten the value provided by Jefferson County 

wetlands . 

JEF .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier. Second, beaches provide user 

value to residents and tourists . Although a beach's user value is not 

traded in a traditional market for services, it can still be measured 

through such techniques as the travel cost method (TCM) and/or the 

contingent value (CV) method . Saltwater beaches are an integral part of 

128 
the marine ecosystem which can be damaged by erosion, debris, oil spills 

and other toxic discharges into coastal waters . Jefferson County, much 

like the eastern Gulf panhandle counties, does not have any significant 

beach areas . Ecological resources that are an asset to Jefferson County 

and induce a considerable level of economic activity in the region are 

summarized in Table 109 . 

JSF .11 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Piers, 

boardwalks and jetties facilitate bank recreational fishing, beach use and 

other outdoor recreational activities . There are no such facilities in 

Jefferson County . 

As an outdoor recreational activity, boating makes use of common property 

water resources . Expressed in 1994 dollars, Bell (1995) found that the 

user value per day is worth $3 .56 more if a marina is used (i .e ., $5 .02 

less $1 .48) rather than a boat ramp . These are Florida-wide values and may 

or may not be good estimates for Jefferson County, but are used for 

purposes of illustration . 

Jefferson County has no saltwater boat ramp lanes, wet slips or dry racks . 

The number of private docks from which to launch pleasure craft is unknown . 

Combining data from Bell et al . (1982) and Bell (1995), the annual user 

value from boating in the Gulf of Mexico off Jefferson County is estimated 

and shown in Table 110 . This value is about $40,345 . 

Table 109 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Jefferson County, Florida. 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year' 

Asset Value 

(Millions)2 

Commercial Fishing $03 N/A N/A 

Recreational Fishing $ .874 $ .645 $215 

Saltwater Marsh s N/A .207 6 20 .2 6 

Saltwater Beaches N/A" N/A 6 N/A 6 

Marine Boating' N/A $ .040' $1 .34' 

Nonmarket value per year 

#1 divided by .03 = Asset Value 

Table 104, ex vessel price 

° Table 107, retail price 

To commercial fishery landings only 

See text for discussion 

See Table 110 

129 
Table 110 . Estimation of the Annual User Value for Saltwater Boating Off 

Jefferson County, Florida, 1993-94 . 

Facility 

'Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$4,072 = $5 .021 x 6692 x .193 x 32' 

2 . Boat Ramns 

$21,228 = $1 .481 x 669 x .67' x 32 

3 . Private Docks 

$15,045 = $5 .025 x 669 x .14 x 32 

Total Annual User Value = $40,345 

*Asset Value = 40,345 = .03 = $1 .34 million 

Bell (1995), Florida-wide value 

FDEP (1992), Jefferson County 

Bell et al . (1982), northwest Florida 

Bell (1995), Jefferson County 

5 Assumed $/day same for marinas and private docks 

Recreational boating in marine waters is rapidly growing in Jefferson 

County . Such boating can affect coastal water quality (e .g ., inadequate 

pumping out facilities) as well as adding user value to those using coastal 

water resources . From the FDEP (1983-1992) and Bell (1995) studies, 

pleasure boat registrations in Jefferson County grew as follows, with 

projected (P) numbers included : 

1983 505 

1984 524 

1985 556 

1986 569 

1987 612 

1988 621 

1989 616 

1990 597 

1991 576 

1992 659 

1993 669 

1994 669 

2000 928 (P) 

2005 1,115 (P) 

2010 1,340 (P) 

JEF .12 Water Quality, the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is 

manifested in the water quality surrounding the region . Florida's major 

surface water quality problems come from urban stormwater runoff, 

agricultural runoff, domestic wastewater, industry wastewater and 

hydrological changes such as draining and filling wetlands . 

130 
There are three sources of information on local water quality surrounding 

Jefferson County . First, the Federal Water Pollution Control Act requires 

the state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water. Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Jefferson County . 

Two indices are used in the 305(b) report for measuring surface water 

quality : the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity . The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality . 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Jefferson County, we 

have selected the Aucilla River Basin for a brief summary of the current 

state of water quality in this region of the study area . The WQI and TSI 

for important areas are shown in Table 111 . 

The Aucilla River extends approximately 70 miles into Florida and Georgia 

from the Gulf of Mexico . Both the Aucilla and Wacissa Rivers are 

considered very pristine waters . The headwaters are a series of swamps, 

lakes, sinkholes and natural springs which contain very few pollution 

sources . The pH is naturally low in the Aucilla River, but improves when 

the stream becomes more defined. Overall, the whole basin is thought to 

have very good water quality. 

Table 111. Water Quality Indices for Selected areas of Jefferson 

County, Florida. 

Water Areas : Aucilla River Basin 

Water B ody Type : Stream 

1 Aucilla River 

5 Aucilla River 

7 Wacissa River 

46 Aucilla River 

Water Quality Indices* 

WOI TSI 

25 --

28 --

25 --

35 -- 

* Higher values indicate lower water quality 

131 
A.The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . In 1994, there were no 

companies that discharged toxic substances in and around the surface water 

of Jefferson County . Shellfish is not harvested in significant numbers in 

the waters near Jefferson County, so information on closed areas is 

limited. 

132 
Socioeconomic Components and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

LSV .1 Introduction 

Levy County is located in Southeastern section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figure 9) . 

It contains 1,118 square miles of land, ranking it 9th among the 67 

counties in Florida . In 1990, Levy County had a population of 25,912, 

ranking it 46th among Florida's counties . The population density was 25 

people per square mile in 1990, ranking it 54th in Florida . Levy County 

has a relatively high median age of 38 .5 years, compared to the Floridawide median of 36 .4 years . 

The population of Levy County had a per capita income of $12,766 in 1992, 

60th of the 67 Florida counties and 35% below the state-wide average of 

$19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income, and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem . For example, a retirement community 

may produce less toxic chemical discharges into waterbodies compared to an 

area where income is earned at a local chemical plant . For Levy County, an 

analysis of the sources of income will be discussed below, along with the 

interaction with the ecosystem . 

Levy County had 16 .68 of the households below the poverty level in 1989, 

which was higher than the State of Florida average of 9 .0% . In 1993, the 

unemployment rate was 6 .7 %- (relative to a statewide average of 7 .0%), 

indicating a slack labor market . 

LEV .2 Trends in Population. Income and Employment in Levy County, 1980-93 . 

Table 112 shows the trend in key economic variables in Levy County from 

1980 through 1993 . Over this interval, resident population increased by 

40% (3% annually), which was approximately equal to the 39 .5% increase for 

Florida as a whole . Population increases that were induced primarily by 

industrial structure (i .e ., job creation) and natural amenities of the 

region place additional pressure on the carrying capacity of both living 

(e .g ., coastal fishery stocks) and non-living natural resources (e .g ., 

beaches) . 

Nominal aggregate personal income increased by 182 from 1980 to 1993 . 

(Table 112) . Adjusted for inflation, real aggregate personal income 

increased by 61% or 4 .6% annually . Since real income growth outstripped 

the population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

will have the financial resources to reduce negative externalities (e .g ., 

air and water pollution) which often accrue from population growth (Hall, 

1994) . 

133 
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ENMILE CREEK 

CEDAR KEY 

p SPRING RUN 

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WACCASASSA RIVER BASIN 

0311010 WATER QUALITY 

GOOD 

AVERAGE WATER QUALITY ~ THREATENED 

1984-1993 STORET DATA FAIR 

WATERSHED ID NUMBERS LINK MAP TO TABLES POOR 

" INDICATES QUALITATIVE ASSESSMENT 0 UNKNOWN 

Figure 9 . Map of Levy County, Florida, showing levels of water quality 

and areas of quality testing (Waccasassa River Basin)[from 

Bureau of Surface Water Management (1994a)] . 

134 
Table 112 . Trends in Key Economic Aggregate Variables in Levy County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

Mmployment3 

1980 20,100 $130,350 $158,191 5,852 

1981 20,900 146,915 161,623 5,805 

1982 21,800 161,738 167,604 6,193 

1983 22,200 174,198 174,898 6,115 

1984 22,700 191,097 183,924 6,522 

1985 23,300 211,196 196,279 6,846 

1986 23,900 228,299 208,302 7,133 

1987 24,200 242,815 213,745 7,454 

1988 24,600 265,294 224,255 7,724 

1989 25,300 286,779 231,273 8,212 

1990 26,100 305,711 233,903 8,333 

1991 26,600 327,803 240,678 8,454 

1992 27,100 349,080 248,810 8,591 

1993 28,100 367,523 254,341 9,021 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Levy County increased from 5,852 in 1980 to 9,021 in 

1993, a 54% increase . The growth of jobs is stimulated in a region by what 

is known as the export base . Simply put, a region's growth is determined 

by its ability to derive "export income" from outside the region . In 

Florida, such income may come from physically exporting goods such as 

electronic components or fish, but it is more likely to come from tourists 

visiting the region, income to retirees in Florida and injections of 

Federal dollars to sustain military bases such as Eglin Air Force Base in 

Okaloosa County . Through a multiplier process, this export income sustains 

both direct export jobs (e .g ., civilians working for the military) and 

indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Levy County grew 

less rapidly than the measure of county output - real aggregate personal 

income - as local entrepreneurs introduced labor-saving technological 

devices to economize on the rising cost of labor . 

LEV .3 Trends in various welfare measures in Levy County, 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing. A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is more likely to be able 

135 
to protect the ecosystem than one which is highly dependent on income 

maintenance and unemployment insurance since the former is taxable while 

the latter is not . In 1993, Levy County derived 96 .5% of its personal 

income from earnings, retirement and capital income, compared to 98 .2% for 

the whole of Florida . Thus, the county is less likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem . The trends in the components of personal income per capita are 

shown for Levy County in Table 113 . 

LSV .4 Industrial Base : Levy County 

The "industrial base" for Levy County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy . The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county ; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy . If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., 10%) in an area, 

Table 113 . Trends in Components of Personal Income in Levy County, 

Florida, 1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

( Nominal) Maintenance Interest, 

Rents 

1980 $6,481 $4,011 $140 $18 $1,242 $1,070 

1981 7,045 4,165 147 17 1,426 1,289 

1982 7,429 4,376 149 26 1,590 1,287 

1983 7,849 4,371 150 30 1,717 1,581 

1984 8,424 4,841 152 20 1,810 1,601 

1985 9,066 5,165 152 21 2,010 1,717 

1986 9,561 5,346 163 20 2,108 1,923 

1987 10,022 5,608 170 21 2,226 1,997 

1988 10,771 5,897 212 24 2,310 2,328 

1989 11,330 6,189 222 20 2,546 2,354 

1990 11,715 6,276 275 27 2,780 2,357 

1991 12,341 6,508 338 42 3,097 2,356 

1992 12,863 6,793 408 72 3,326 2,265 

1993 13,062 6,989 395 56 3,479 2,142 

Source : BEA (1995) 

136 
compared to the same percentage nationally (e .g ., 0 .5g), assuming the 

nation consumes all it produces - no imports or exports . This is rather 

simplistic, but it does serve as a barometer of which industries are 

predominately export . This figure, known as the location quotient (LQ), 

would be : 

(1) LQ = 10%/ .5$ = 20 

Thus, 95g would be in export or 

(2) 1 - LQ-1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 114 shows the main identified export industries and their 

contribution to personal income in Levy County . This county depends 

primarily on boat manufacturing, lumber and wood, fisheries, and machinery 

for its economic survival . Some of the largest individual employers in 

Levy County have, from time to time, had negative impacts on the ecosystem . 

Table 115 shows the top ten employers for Levy County, along with the 

products they produce that may generate conflicts with the environment . 

Products such as lumber and manufacturing must be rigorously controlled or 

they will reduce water and air quality . In 1993, the EPA reported that the 

companies in Levy County did not discharge any toxic chemicals into surface 

water (Lester, 1995) . 

LEV.S Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health, are referred to as ecosystem-sensitive 

industries . For Levy County, these industries are shown in Table 116 . 

The Levy County economy is heavily based upon timber which is harvested and 

processed regionally into various paper-based products . Local and state 

governments also contribute about one-quarter of total earnings by place of 

work . All of these economic activities create various kinds of waste that 

is a point or nonpoint discharge into rivers and coastal waters . These 

industries are primarily involved in the export sector and therefore are 

critical to this coastal county . 

LSV.6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of Citrus County is primarily 

composed of ecosystem-insensitive industries, those which have relatively 

little impact on the environment . These are shown in Table 117 . 

In general, retirement has a less adverse impact on local ecosystem health 

than other industries in Levy County . Over the 1969-93 period, the 

ecosystem-insensitive industries were growing faster than the ecosystemsensitive industries, meaning that the new economic growth is not 

threatening the ecosystem . 

137 
Table 114 . Major Export Industries in Levy County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings 

(000) 

% of Personal 

Income 

LQ* 

Fishing $838 .22 7 .3 

Manufacturing 71,019 4 .5 PJ* 

Lumber and Wood 3,993 1 .1 2 .5 

Machinery 323 .09 Pi 

Boats N/A N/A Pi 

Limited Tourism (Cedar Key) N/A N/A Pi 

Retirement 44,672 12 .15 N/A 

Agricultural Services 3,359 .91 2 .3 

*LQ = Location quotient . See Text . 

*PJ = Professional Judgment . 

Source : BEA (1995) 

Table 115 . Top Ten Employers in Levy County, Florida and Products 

Produced, 1994 . 

Employer Employees 

1 . White Construction Company, Construction/Auto 250 

2 . Oakview Care Center, Health Care 159 

3 . WalMart, Retail Sales 135 

4 . Winn-Dixie, Grocery 100 

5 . Central Florida Electric Co-op, Utilities 95 

6 . Nature Coast Regional Hospital, Health Care 76 

7 . V .E . Whitehurst & Sons, Cattle/Construction 75 

8 . Levy County State Bank, Finance 66 

9 . Limerock Industries, Limerock 60 

10 . J-Mak Inc ., Fiberglass 5.Q 

Sub-Total 1,066 

Total 9,021 

Percent of Total 12% 

Source : Florida Department of Commerce (1994) 

Table 116 . Ecosystem-Sensitive Industries in Levy County . 

Industry Earnings ($000) 

1 . Manufacturing (Lumber and Wood, Machinery) $7,203 

2 . Agricultural Services 3,359 

Sub-Total 10,562 

Total Earnings (Place of Work) 145,228 

Percent of Total 5 .2% 

Source : BEA (1995) 

138 
Table 117 . Ecosystem-Insensitive Industries in Levy County . 

Industry Earnings ($000) 

1 . Fishing $838 

2 . Retirement 57 .250 

Sub-Total 58,088 

Total Earnings 367,523 

Percent of Total 15 .8 

Source : Table 114 

LEV.7 Commercial Fishery Landings in Lew County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Levy County . 

Three categories of fishery products are found : (1) finfish; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $3 .1 million worth of commercial fishery 

products were landed in Levy County at the ex vessel level (Table 118) . 

Finfish and shrimp account for 55% of this value . Among the finfish, 

grouper was the leading species as measured by value . Crabs accounted for 

45% of the ex vessel value of the landings . Brown shrimp, which depends on 

wetlands during a phase of its life cycle, was the dominant shrimp species . 

Among the 13 counties in the study area, Levy County ranked 8th in the ex 

vessel value of all commercial fishery landings . 

Although the ex vessel value does not include value added in processing and 

distribution, commercial fishing is a relatively important component of the 

economic base of Levy County where aggregate personal income was $ .367 

billion in 1993 . Over the last fourteen years, commercial fishery landing 

has decreased by 41% while the ex vessel value of the catch has increased 

by 2690 . When adjusted for inflation, the value of landings changed by 

1059. (FDNR, 1980) . 

LEV.8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently, 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively, that engage in saltwater recreational 

fishing in Florida . In Milon and Thunberg (1992), there is some regional 

breakdown embracing the present study area from Hernando County north to 

139 
Table 118 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Levy County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Red Grouper 140,729 $247,683 .03 

Gag Grouper 86,411 192,696 .53 

Black Mullet 297,365 139,761 .55 

Spotted Sea Trout 15,278 18,333 .60 

Pompano 5,094 17,217 .72 

Crevalle Jack 37,661 12,428 .13 

Shark Fins 560 10,371 .20 

Grunts 21,532 10,120 .04 

Sheepshead 18,308 9,520 .16 

All Others 72,141 49 .807 .47 

Total $726,037 .44 

Invertebrates 

Stone Crabs 156,238 846,138 .91 

Blue Crabs 581,185 422,067 .68 

Oysters 74,174 91,975 .76 

Clams 10,803 57,643 .01 

Octopus 74,174 3 .319 .17 

Total 1,421,144 .53 

Shrimp (Total) 515,257 1 .024 .812 .41 

Grand Total $3,171,994 .38 

* State average ex vessel price used . 

Source : FDEP (1994) 

Escambia County . Such regions include both coastal and interior counties . 

As an approximation, these regional averages can be applied to the 

individual counties . Bell (1993) has only statewide averages for tourist 

saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

angler for Region I (i .e ., Escambia to Jefferson County) were about 40-50% 

higher than the statewide average . Thus, using the latest study of Bell 

(1993), statewide figures may be conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county . Levy County had 6,447 resident anglers purchasing a one-year 

fishing license. It should be pointed out that purchase of a license in a 

county does not ensure that one is a resident of that county, but informal 

conversations with Florida Dept . of Environmental Protection personnel 

suggest little bias is associated with that assumption . Nonresidents are 

those that purchased saltwater fishing licenses in non-coastal counties . 

Such licenses were pro-rated to coastal counties in close geographical 

140 
proximity to each county, using personal judgment, as shown in Table 119 . 

Finally, tourists must purchase a license, and the number is shown for the 

counties in the study area . This may underestimate tourist saltwater 

anglers since tourists may buy a license in an interior county and use it 

in one or more of the coastal counties . 

Table 120 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers 

in Table 119 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers, 

respectively . Levy County showed a fishing effort of 141,304 days . 

Finally, Table 121 is derived from Table 119 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $8,182,713 in Levy County in 1993-94 . Many assumptions were 

made to arrive at these estimates, however, these figures are believed to 

indicate an order of magnitude and relative ranking, and may actually be 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . Multiplier effects of nonresidents and 

tourists were not considered . 

Table 119 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents Nonresident Tourist 3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11,685 6 .926 5"312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

Non-resident (out of state) saltwater fishing licenses for one year; 

seven days and three days . 

141 
Table 120 . Estimated Number of Saltwater Recreational Days 

(Fishing Effort) in the Thirteen County Study Area, 

1993-94 . 

County Resident + 

Nonresident) 

Tourist Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167 .499 21,248 188,747 

Total 952,605 377,480 1,330 085 

1 9 days per angler year and Table 119 . See Milon and Thunberg (1992) . 

Z 4 days per angler year and Table 119 . See Bell (1993) . 

Table 121 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Tourist2 Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8,890,475 2,337 .280 11,227,755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 119 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 119 multiplied by $440 .00 per angler . 

142 
If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing. There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Levy County can be computed as follows : 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 14,368 = $5 .4 million 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 2,998 = $ .6 million . 

Thus, saltwater recreational fishing generates $6 .0 million per year in 

Levy County with a capitalized value of $200 million using a 3% discount 

rate (i .e ., $6 million = .03) . 

LEV .9 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing . The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated . This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 122 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch. 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch. The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

143 
Table 122 . Economic Value of Wetlands . 

(Wetland Function 

( 

Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

were estuarine-dependent. A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

144 
acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Levy County has 35,400 acres of salt marsh 

(NOAA, 1991), which would be worth $188 million ($5,316 x 35,400) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by Levy County wetlands . 

LSV .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier. Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . Levy County, much like the rest of the 

eastern panhandle, has very little beach area (Table 123) . The coastal 

areas are primarily saltwater marsh. Since little information is available 

about user demand, the value of the saltwater beaches could not be 

estimated. Table 124 identifies ecological resources that are an asset to 

Levy County and induce a considerable level of economic activity in the 

region . 

LEV .11 Man-Made Resources : Water D 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 125 is 

an inventory of these water-dependent facilities in Levy County . Piers, 

boardwalks and jetties facilitate bank recreational fishing, beach use and 

other outdoor recreational activities . 

Table 123 . Key Saltwater Beaches in Levy County, Florida .* 

Western District 

Environmentally Endangered Lands : 

Cedar Keys 

*In Levy County alone, the University of West Florida (1985b) 

reported 4 individual saltwater beaches which were .3 miles in 

length and 38,000 square feet (public and private) . 

Source : University of West Florida (1985a) 

145 
Table 124 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Levy County, Florida . 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year' 

Asset Value 

(Millions)2 

Commercial Fishing $3 .13 N/A N/A 

Recreational Fishing $8 .14 $6 .05 $2005 

Saltwater Marshs N/A .207 6 188 6 

Saltwater Beaches N/A6 N/A6 N/A 6 

Marine Boating' N/A $ .198' $6 .6' 

1 Nonmarket value per year 

#1 divided by .03 = Asset Value 

Table 118, ex vessel price 

Table 121, retail price 

5 To commercial fishery landings only 

See text for discussion 

See Table 126 

Table 125 . An Inventory of Marine-Related Recreational Facilities in 

Levy County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number 2 

b . Length (all) (LFT)* 400 

2 . Boardwalks/Catwalks 

a . Number --

b . Length (all) (LFT)* --

3 . Jetties 

a . Length (all) (LFT)* -- 

Boating 

1 . Boat Ramps 

a . Number 5 

b . Total Lanes 7 

2 . Marinas 

a . Total 3 

b . Slips/Moorings 96 

c . Dry Storage -- 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

146 
As an outdoor recreational activity, boating makes use of common property 

water resources . Bell (1995) found that the user value per day, expressed 

in 1994 dollars, is worth $3 .56 more if a marina is used (i .e ., $5 .02 less 

$1 .48) rather than a boat ramp . These are Florida-wide values and may or 

may not be good estimates for Levy County, but are used for illustrative 

purposes . 

Levy County has 7 saltwater boat ramp lanes and 96 wet slips and dry racks 

as shown in Table 125 . The number of private docks from which to launch 

pleasure craft is unknown . Combining data from Bell et al . (1982) and Bell 

(1995), the annual user value from boating in the Gulf of Mexico off Levy 

County is estimated and shown in Table 126 . This value is about $0 .2 

million . 

Recreational boating in marine waters is rapidly growing in Levy County . 

Such boating can affect coastal water quality (e .g ., inadequate pumping out 

facilities) as well as adding user value to those using coastal water 

resources . From the FDEP (1983-1992) and Bell (1995) studies, pleasure 

boat registrations in Levy County grew as follows, with projected (P) 

numbers included : 

1983 1,530 

1984 1,588 

1985 1,667 

1986 1,715 

1987 1,720 

1988 1,870 

1989 1,889 

1990 1,916 

1991 1,998 

1992 2,154 

1993 2,162 

1994 2,337 

2000 2,802 (P) 

2005 3,239 (P) 

2010 3,743 (P) 

LEV.12 Water Quality. the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is 

manifested in the water quality surrounding the region . Florida's major 

surface water quality problems come from urban stormwater runoff, 

agricultural runoff, domestic wastewater, industry wastewater, and 

hydrological changes such as draining and filling wetlands . 

There are three sources of information on local water quality surrounding 

Levy County . First, the Federal Water Pollution Control Act requires the 

state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Levy County . 

147 
Table 126 . Estimation of the Annual User Value for Saltwater Boating Off 

Levy County, Florida, 1993-94 . 

Facility 

Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$71,329 = $5 .021 x 2,3372 x .193 x 32' 

2 . Boat Ramps 

$74,156 = $1 .481 x 2,337 x .67' x 32 

3 . Private Docks 

$52,558 = $5 .025 x 2,337 x .14 x 32 

Total Annual User Value = $198,043 

*Asset Value = 198,043 = .03 = $6 .6 million 

Bell (1995), Florida-wide value 

2 FDEP (1992), Levy County 

Bell et al . (1982), northwest Florida 

Bell (1995), Levy County 

Assumed $/day same for marinas and private docks 

Two indices are used in the 305(b) report for measuring surface water 

quality: the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen-demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity. The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality. 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Levy County, the 

Waccasassa River Basin has been selected for a brief summary of the current 

state of water quality in this region of the study area . 

The Waccasassa River Basin stretches through 936 square miles of forest 

and wetlands in Levy County . The river has the blackwater color typical of 

those whose headwaters are primarily swamp and woodland drainage . There is 

very little development in the basin, so the only sources of pollution may 

be highway runoff or pollution from logging operations . Cedar Key, at the 

mouth of the river in the Gulf, is the only developed area, but has a waste 

water treatment plant . The WQI and TSI for selected areas are listed in 

(Table 127) . 

148 
Table 127 . Water Quality Indices for Selected Areas of Levy County, 

Florida . 

Water Areas : Waccasassa River Basin Water Quality Indices* 

Water Body Type : EstuarX WOI TSI 

3 Waccasassa River -- 38 

Water 

8 

Body Type : Lake 

Unnamed Slough -- 37 

Water 

4 

Body Type : Spring 

Wekiva River 36 -- 

Water Body Type : Stream 

1 Tenmile Creek 38 -- 

2 Horsehole Creek 56 -- 

5 Mule Creek 33 -- 

6 Otter Creek 48 -- 

7 Waccasassa River 27 -- 

9 Little Waccasassa River 58 -- 

* Higher values indicate lower water quality 

The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . In 1994, there were no 

discharged toxic substances in and around the surface water of Levy County . 

Shellfish harvesting has been closed in 18,847 acres due to high coliforms . 

This is a small percentage of the 344,153 total acres of possible 

harvesting area . 

149 

_Socioeconomic Components and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

ORA .1 Introduction 

Okaloosa County is located in western section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figures 10 

and 11) . It contains 936 square miles of land, ranking it 19th among the 

67 counties in Florida. In 1990, Okaloosa County had a population of 

143,777, ranking this county 23rd among Florida's counties . The population 

density was 165 people per square mile in 1990, ranking it 28th in Florida. 

Relative to other Florida counties, Okaloosa County has a low median age of 

31 .5 years, as compared to the Florida-wide median of 36 .4 years . 

The population of Okaloosa County had a per capita income of $18,060 in 

1992, 18th of the 67 Florida counties and loo below the Florida-wide 

average of $19,797 . This income was derived primarily from earnings from 

local industries, return on investment (rent, interest, dividends), 

retirement income, and transfer payments (e .g ., AFDC, food stamps, etc .) . 

The sources of income for a county may lead to a characterization of how 

that area interacts with the natural ecosystem . For example, a retirement 

community may produce less toxic chemical discharges into waterbodies 

compared to an area where income is earned at a local chemical plant . For 

Okaloosa County, an analysis of the sources of income will be discussed 

below along with the interaction with the ecosystem . 

Okaloosa County had 7 .80 of the households below the poverty level in 1989, 

which was below the State of Florida average of 9 .0% . In 1993, the 

unemployment rate was 6 .2% (relative to a statewide average of 7 .0%), 

indicating a slack labor market . 

OKA .2 Trends in Population . Income and Smvloyment in Ok 

1980-93 . 

Table 128 shows the trend in key economic variables in Okaloosa County from 

1980 through 1993 . Over this interval, resident population increased by 

410 (3 .1g annually), which was slightly lower than the 39 .50 for Florida as 

a whole . Population increases that were induced primarily by industrial 

structure (i .e ., job creation) and natural amenities of the region place 

additional pressure on the carrying capacity of both living (e .g ., coastal 

fishery stocks) and non-living natural resources (e .g ., beaches) . 

Nominal aggregate personal income increased by 2270 from 1980 to 1993 

(Table 128) . Adjusted for inflation, real aggregate personal income 

increased by 86% (6 .6% annually) . Since real income growth outstripped the 

population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

will have the financial resources to reduce negative externalities (e .g ., 

air and water pollution) which often accrue from population growth (Hall, 

1994) . 

151 
ESCAMMA BAY 

BAYOU 

GULF OF MEXICO 

PENSACOLA BAY BASIN 

03140105 

AVERAGE WATER QUALITY 

1984-1993 STORET DATA 

WATERSHED ID NUMBERS LINK MAP TO TABLES 

INDICATES QUALITATIVE ASSESSMENT 

WATER QUALITY 

GOOD 

THREATENED 

FAIR 

_ POOR 

0 UNKNOWN 

BAY 

Figure 10 . Map of Okaloosa County, Florida, showing levels of water 

quality and areas of quality testing (Pensacola Bay Basin)[from 

Bureau of Surface Water Management (1994b)] . 

152 
CHOCTAWHATCHEE BAY BASIN 

0314002 

WATER QUALITY 

GOOD 

AVERAGE WATER QUALITY 

1984-1993 STORET DATA 

WATERSHED ID NUMBERS LINK MAP TO TABLES 

INDICATES QUALITATIVE ASSESSMENT 

THREATENED 

FAIR 

~ POOR 

D UNKNOWN 

Figure 11 . Map of Okaloosa County, Florida, showing levels of water 

quality and areas of quality testing (Choctawhatchee Bay 

Basin)[from Bureau of Surface Water Management (1994b)] . 

153 
Table 128 . Trends in Key Economic Aggregate Variables in Okaloosa County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

Mmployment3 

1980 110,900 $876,247 $1,063,407 53,990 

1981 113,100 1,036,674 1,140,455 57,235 

1982 116,000 1,139,650 1,180,984 59,154 

1983 120,400 1,267,972 1,273,064 62,496 

1984 124,100 1,403,349 1,350,673 67,168 

1985 127,900 1,538,055 1,429,419 69,486 

1986 131,700 1,679,589 1,532,472 73,174 

1987 135,400 1,838,302 1,618,224 77,106 

1988 138,000 1,982,962 1,677,060 79,779 

1989 141,000 2,158,726 1,740,908 81,605 

1990 144,500 2,332,543 1,784,654 83,231 

1991 148,000 2,508,389 1,841,695 84,191 

1992 152,900 2,711,442 1,932,603 86,537 

1993 157,300 2,863,026 1,981,333 89,337 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Okaloosa County increased from 53,990 in 1980 to 

89,337 in 1993, a 65% increase . The growth of jobs is stimulated in a 

region by what is known as the export base . Simply put, a region's growth 

is determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region, income to retirees in Florida and injections 

of Federal dollars to sustain military bases such as Eglin Air Force Base 

in this county . Through a multiplier process, this export income sustains 

both direct export jobs (e .g ., civilians working for the military) and 

indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Okaloosa County 

grew less rapidly than the measure of county output - real aggregate 

personal income - as local entrepreneurs introduced labor-saving 

technological devices to economize on the rising cost of labor . 

ORA.3 Trends in VarQUS Welfare Measures in Okaloosa Countv, 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but the components of personal income are sometimes more 

revealing. A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is likely to be more able 

to protect the ecosystem than one which is highly dependent on income 

154 
maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Okaloosa County derived 98 .6% of its personal 

income from earnings, retirement and capital income, compared to 98 .2% for 

the whole of Florida . Thus, the county is slightly more likely to tax 

residents, compared to the state as a whole, to protect threats to the 

marine ecosystem. The trends in the components of personal income per 

capita are shown for Okaloosa County in Table 129 . 

ORA.4 Industrial Base : Okaloosa County 

The "industrial base" for Okaloosa County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy . The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county ; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy . If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., 10%) in an area, 

Table 129 . Trends in Components of Personal Income in Okaloosa County, 

Florida, 1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $7,901 $5,301 $84 $18 $1,585 $913 

1981 9,165 6,082 89 17 1,817 1,161 

1982 9,825 6,475 83 20 2,024 1,223 

1983 10,532 6,903 82 25 2,152 1,369 

1984 11,304 7,454 79 16 2,177 1,579 

1985 12,030 7,783 77 25 2,409 1,735 

1986 12,749 8,285 74 21 2,512 1,856 

1987 13 , 581 8 , 915 73 22 2 , 659 1 , 912 

1988 14,375 9,312 86 22 2,805 2,150 

1989 15,310 9,727 100 22 3,046 2,415 

1990 16,144 10,163 120 30 3,305 2,526 

1991 16,946 10,555 145 45 3,583 2,619 

1992 17,738 11,067 184 74 3,784 2,629 

1993 18,202 11,291 179 68 3,989 2,675 

Source : BEA (1995) 

155 
compared to the same percentage nationally (e .g ., 0 .5%), assuming the 

nation consumes all it produces - no imports or exports . This is rather 

simplistic, but it does serve as an indicator of which industries are 

predominately export . This figure, the location quotient (LQ), would be : 

(1) LQ = 10/ .50 = 20 

Thus, 95% would be in export or 

(2) 1 - LQ-1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 130 shows the main identified export industries and their 

contribution to personal income in Okaloosa County . This county depends 

primarily on the military, tourism, manufacturing, retirement and 

commercial fishing for its economic survival . Some of the largest 

individual employers in Okaloosa County have, from time to time, had 

negative impacts on the ecosystem . For Okaloosa County, Table 132 shows 

the top ten employers, along with the products they produce that may 

generate conflicts with the environment . Products such as textiles, lumber 

and printing must be rigorously controlled or they will reduce water and 

air quality . In 1993, the EPA reported that none of the companies in 

Okaloosa County discharged toxic chemicals into surface water . 

ORA .5 Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Okaloosa County, the industries shown in Table 131 fall 

into this characterization . 

The Okaloosa County economy is heavily based upon manufacturing . The 

county has an Air Force base for the U .S . military . All of these economic 

activities create various kinds of waste that is a point or nonpoint 

discharge into rivers and coastal waters . These industries are primarily 

involved in the export sector and therefore are critical to this coastal 

county . 

ORA .6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of Citrus County is primarily 

composed of ecosystem-insensitive industries, those which have relatively 

little impact on the environment . These are shown in Table 133 . 

In general, industries such as the military, tourism and retirement have a 

less adverse impact on local ecosystem health than other industries in 

Okaloosa County . Over the 1969-93 period, the ecosystem-insensitive 

industries were growing slower than the ecosystem-sensitive industries, 

meaning that there may be relatively more stress on the marine ecosystem 

from recent economic growth . 

156 
Table 130 . Major Export Industries in Okaloosa County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings % of Personal LQ* 

(000) Income 

Commercial Fishing $2,222 .077 2 .5 

Tourism 

Hotels 21,084 .73 1 .07 

Eating and Drinking 69,974 244 1 .5 

Building Materials 13,118 .45 1 .2 

Amusement 25,664 .83 1 .1 

Retirement/Tourism 

General Building 23,558 .87 PJ* 

Real Estate 28,144 .98 1 .4 

Engineering Services 119,802 4 .2 1 .6 

Military/Federal Government 704,335 24 .6 7 .4 

(Eglin Air Force Base) 

Manufacturing 

Printing 6,302 .22 Pi 

Apparel 9,061 .31 PJ 

Lumber and Wood 7,490 .26 Pi 

Machinery 3,560 .12 Pi 

Electrical Machinery 16,695 .58 Pi 

Transportation Equipment 36,008 1 .3 1 .5 

Instruments 15,161 .53 PJ 

Total $1,102,178 38 .5 

*LQ = Location quotient . See Text . 

*PJ = Professional Judgment . 

Source : BEA (1995) 

Table 131 . Ecosystem-Sensitive Industries in Okaloosa County, Florida . 

Industry Earnings ($000) 

1 . Manufacturing 106,315 

Total Earnings 2,863,492 

Percent of Total 3 .7% 

Source : BEA (1995) 

157 
Table 132 . Top Ten Employers in Okaloosa County, Florida and Products 

Produced, 1994 . 

Employer Employees 

1 . Vitro Services Corporation, Instrumentation 1,400 

2 . Metric Systems, Radar Systems 780 

3 . Russell Corporation, Sports Clothing 430 

4 . Sverdrup Technology, Technical Engineering 400 

5 . Keltec Florida, Electronics 300 

6 . Gulf Power Company, Utilities 163 

7 . Tybrin Corporation, Scientific Data Processing 150 

8 . NW Florida Daily News, Newspaper 145 

9 . RMS Technologies, Engineering Services 110 

10 . Rainbow Koolers, Sportswear - 78 

Sub-Total 3,956 

Total 89,337 

Percent of Total 4$ 

Source : Florida Department of Commerce (1994) 

Table 133 . Ecosystem-Insensitive Industries in Okaloosa County, Florida 

Industry Earnings ($000) 

1 . Tourism $129,840 

2 . Retirement 171,504 

3 . Military/Government 704,335 

4 . Commercial Fishing 2 .222 

Sub-Total 1,007,901 

Total Earnings $2,863,086 

Percent of Total 350 

Source : Table 130 

OKA .7 Commercial F18t12M~ ~Landings in Okaloosa County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

158 
here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Okaloosa County . 

Three categories of fishery products are found : (1) finfish ; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $6 million worth of commercial fishery products 

were landed in Okaloosa County at the ex vessel level (Table 134) . Finfish 

and shrimp account for 99% of this value . Among the finfish, swordfish and 

vermilion snapper were by far the leading species as measured by value . 

Brown shrimp (which depends on wetlands during a phase of its life cycle) 

was the dominant shrimp species . Among the 13 counties in the study area, 

Okaloosa County ranked 4th in the ex vessel value of all commercial fishery 

landings . 

Although the ex vessel value does not include value added in processing and 

distribution, commercial fishing is a relatively small component of the 

economic base of Okaloosa County, where aggregate personal income was $2 .9 

billion in 1993 . Over the last fourteen years, commercial fishery landing 

has decreased by 62% while the ex vessel value of the catch has increased 

by 73%. When adjusted for inflation, the value of landings changed by 420 . 

Compared to other economic trends in Okaloosa County, commercial fishery 

landings are a small component of the local economy (FDNR, 1980) . 

ORA .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently, 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively, that engage in saltwater recreational 

fishing in Florida. In Milon and Thunberg (1992), there is some regional 

breakdown embracing the present study area from Hernando County north to 

Escambia County . Such regions include both coastal and interior counties . 

As an approximation, these regional averages can be applied to the 

individual counties . Bell (1993) has only statewide averages for tourist 

saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

angler for Region I (i .e ., Escambia to Jefferson County) were about 40-50t 

higher than the statewide average . Thus, using the latest study of Bell 

(1993), statewide figures may be conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county . Okaloosa County had 9,622 resident anglers purchasing a one-year 

fishing license . It should be pointed out that purchase of a license in a 

county does not ensure that one is a resident of that county, but informal 

conversations with Florida Dept . of Environmental Protection personnel 

suggest little bias is associated with that assumption . Nonresidents are 

those that purchased saltwater fishing licenses in non-coastal counties . 

Such licenses were pro-rated to coastal counties in close geographical 

proximity to each county, using personal judgment . This is shown in 

159 
Table 134 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Okaloosa County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Swordfish 68,922 $2,214,649 .75 

Vermilion Snapper 873,374 1,353,729 .62 

Ladyfish 1,033,055 413,222 .00 

Red Snapper 161,187 390,072 .56 

King Mackerel 119,899 170,256 .58 

Round Scad 575,560 149,645 .59 

Porgies 152,499 140,299 .08 

Amberjacks 123,960 120,241 .20 

Shark 253,198 101,279 .20 

Gag Grouper 33,854 75,494 .42 

All Others 915,091 577,968 .70 

Total $5,706,858 .70 

Invertebrates 

Blue Crabs 654,246 $41,774 .06 

Stone Crabs 184 1,189 .70 

Spanish Lobster 5,817 10,063 .41 

Spiny Lobster 380 1,626 .40 

Squid 3,050 1 .128 .50 

Total $56,230 .33 

Shrimp (Total) 145,746 296 .183 .51 

Grand Total $6,059,272 .54 

* State average ex vessel price used . 

Source : FDEP (1994) 

Table 135 where nonresidents are shown in the second column . Finally, 

tourists must purchase a license, and the number is shown for the counties 

in the study area . This may underestimate tourist saltwater anglers since 

tourists may buy a license in an interior county and use it in one of the 

coastal counties . 

Table 136 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 135 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers, 

respectively . Okaloosa County showed a fishing effort of 138,694 days . 

Finally, Table 137 is derived from Table 135 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $10,251,169 in Okaloosa County in 1993-94 . Many assumptions 

were made to arrive at these estimates, however, these figures are believed 

to indicate an order of magnitude and relative ranking, and may actually be 

160 
Table 135 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents NonresidentZ Tourist3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11,685 6,926 5 .312 

Total 

I,I 

76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

Non-resident (out of state) saltwater fishing licenses for one year ; 

seven days and three days . 

Table 136 . Estimated Number of Saltwater Recreational Days 

(Fishing Effort) in the Thirteen County Study Area, 

1993-94 . 

County Resident + 

Nonresidents 

TouristZ Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167,499 21 .248 188,747 

Total 952,605 377,480 1,330,085 

9 days per angler year and Table 135 . See Milon and Thunberg (1992) . 

4 days per angler year and Table 135 . See Bell (1993) . 

161 
Table 137 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

TouristZ Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8 .890 .475 2 .337 .280 11 .227,755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 135 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 135 multiplied by $440 .00 per angler . 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . Multiplier effects of nonresidents and 

tourists were not considered . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing . There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Okaloosa County can be computed as follows : 

Residents 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 9,770 = $3 .7 million 

Tourists 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 12,691 = $2 .5 million . 

Thus, saltwater recreational fishing generates $6 .2 million per year in 

Okaloosa County with a capitalized value of $207 million using a 3% 

discount rate (i .e ., $6 .2 million = .03) . 

162 
OKA .9 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing . The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated . This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 138 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch . 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows : (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

163 
Table 138 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5`k discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Okaloosa County has 300 acres of salt 

marsh (NOAH, 1991) which would be worth $1 .6 million ($5,316 x 300) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by Okaloosa County wetlands . 

OKA .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier. Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . Table 139 lists the key beaches for this 

county . 

164 
Table 139 . Key Saltwater Beaches in Okaloosa County, Florida.* 

Western District 

Environmentally Endangered Lands : 

Liza Jackson Park 

Central District 

Garnier Beach 

Santa Rosa Island/Okaloosa County Beach Access 

Ross Marler Park 

Newman Brackin Wayside Park/Okaloosa Island Pier 

John C. Beasley Park 

Gulf Islands National Seashore 

Burney Henderson Beach State Recreation Area 

Silver Beach Wayside Park 

*In Okaloosa County alone, the University of West Florida (1985b) 

reported 45 individual saltwater beaches which were 18 .9 miles in 

length and 11 .5 million square feet (public and private) . 

Source : University of West Florida (1985a) 

In 1984, Bell and Leeworthy (1986) estimated expenditures per day of $12 

(1994 dollars) and $30 (1994 dollars) for residents and tourists, 

respectively, on saltwater beach-related costs such as lodging, food and 

drink, etc . in Pensacola, Florida . These estimates will be used for all 

counties in the study area as an approximation since no recent studies have 

been undertaken . 

Using the CV technique, Leeworthy, et al . found that Okaloosa, Franklin 

and Bay Counties had an averaged user value of about $3 .0 per day (in 1994 

dollars) for residents and tourists . In a comprehensive study of Florida 

beaches, the University of West Florida (1985b) projected that Okaloosa 

County would have 904,470 saltwater beach days per year in 1990 for the 

beaches listed in Table 139 . By multiplying the user value per day of $3 

times the estimated number of saltwater beach days, the annual flow of 

value is $2 .71 million . These are not actual expenditures, but an estimate 

of annual recreational benefits to beach users . The capitalized value of 

this value flow at a real discount rate of 3% is over $90 million - the 

asset value of the beach. 

Finally, beach-related spending in Okaloosa County in 1990 can be 

calculated in the following manner [with the percentage of residents and 

tourists taken from University of West Florida (1985b) study] : 

Residents 

(o Residents) x (Beach Days/Yr .) x (Expenditures/day) 

.36 x 904,470 x $12 = $3 .91 million 

Tourists 

(% Tourists) x (Beach Days/Yr .) x (Expenditures/day) 

.64 x 904,470 x $30 = $17 .4 million 

165 
Combined, we estimate that saltwater beaches in Okaloosa County attracted 

$21.31 million in beach-related spending in 1990 . Tourists accounted for 

83 percent of this spending . 

Three ecological resources that are an asset to Okaloosa County and induce 

a considerable level of economic activity in this region have been 

identified and are summarized in Table 140 . 

ORA .11 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 141 is 

an inventory of these water-dependent facilities in Okaloosa County . 

Piers, boardwalks and jetties facilitate bank recreational fishing, beach 

use and other outdoor recreational activities . 

As an outdoor recreational activity, boating makes use of common property 

water resources . Bell (1995) found that the user value per day, expressed 

in 1994 dollars, is worth $3 .56 more if a marina is used (i .e ., $5 .02 less 

$1 .48) rather than a boat ramp . These are Florida-wide values and may or 

may not be good estimates for Okaloosa County, but are used for purposes of 

illustration . 

Okaloosa County has 37 saltwater boat ramp lanes and 2,482 wet slips and 

dry racks, as shown in Table 141 . The number of private docks from which 

to launch pleasure craft is unknown. Combining data from Bell et al . 

(1982) and Bell (1995), the annual user value from boating in the Gulf of 

Mexico off Okaloosa County is estimated and shown in Table 142 . This value 

is about $ .85 million. 

Recreational boating in marine waters is rapidly growing in Okaloosa 

County . Such boating can affect coastal water quality (e .g ., inadequate 

pumping out facilities) as well as adding user value to those using coastal 

water resources . From the FDEP (1983-1992) and Bell (1995) studies, 

pleasure boat registrations in Okaloosa County grew as follows, with 

projected (P) numbers included : 

1983 8,385 

1984 9,030 

1985 9,277 

1986 9,828 

1987 10,080 

1988 10,572 

1989 11,222 

1990 11,765 

1991 12,158 

1992 12,767 

2000 15,175 (P) 

2005 16,516 (P) 

2010 17,943 (P) 

166 
Table 140 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Okaloosa County, Florida . 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year' 

Asset Value 

(Millions)2 

Commercial Fishing $6 .03 N/A N/A 

Recreational Fishing $10 .2' $6 .25 $2075 

Saltwater Marshs N/A .207 6 $1 .66 

Saltwater Beaches $21 .316 $2 .716 $90 .06 

Marine Boating N/A $ .845' $28 .2' 

Nonmarket value per year 

#1 divided by .03 = Asset Value 

Table 134, ex vessel price 

° Table 137, retail price 

To commercial fishery landings only 

See text for discussion 

See Table 142 

Table 141 . An Inventory of Marine-Related Recreational Facilities in 

Okaloosa County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number 6 

b . Length (all) (LFT)* 1,658 

2 . Boardwalks/Catwalks 

a . Number 24 

b . Length (all) (LFT)* 2,606 

3 . Jetties 

a . Length (all) (LFT)* 720 

Boating 

1 . Boat Ramps 

a . Number 37 

b . Total Lanes 41 

2 . Marinas 

a . Total 30 

b . Slips/Moorings 1,449 

c . Dry Storage 1,033 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

167 
Table 142 . Estimation of the Annual User Value for Saltwater Boating Off 

Okaloosa County, Florida, 1993-94 . 

Facility 

Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$304,429 = $5 .021 x 12,7672 x .193 x 324 

2 . Boat Rams 

$316,494 = $1 .481 x 12,767 x .67' x 32 

3 . Private Docks 

$224,316 = $5 .025 x 12,767 x .14 x 32 

Total Annual User Value = $845,239 

*Asset Value = 845,239 = .03 = $28 .2 million 

Bell (1995), Florida-wide value 

Z FDEP (1992), Okaloosa County 

Bell et al . (1982), northwest Florida 

° Bell (1995), Okaloosa County 

5 Assumed $/day same for marinas and private docks 

OKA.12 Water Ouality, the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is 

manifested in the water quality surrounding the region . Florida's major 

surface water quality problems come from urban stormwater runoff, 

agricultural runoff, domestic wastewater, industry wastewater, and 

hydrological changes such as draining and filling wetlands . 

There are three sources of information on local water quality surrounding 

Okaloosa County . First, the Federal Water Pollution Control Act requires 

the state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water. These three sources of information will give a profile of surface 

water conditions in Okaloosa County . 

Two indices are used in the 305(b) report for measuring surface water 

quality : the stream water quality index (WQI), and the lake/estuary Trophic 

State Index (TSI) . Both are of interest to this study simply because 

streams flow into Gulf of Mexico estuaries . The TSI measures estuarine 

water quality that is critical to fish and wildlife . The WQI summarizes 

information from six categories including water clarity (turbidity and 

total suspended solids), dissolved oxygen, oxygen-demanding substances 

(BOD), nutrients, bacteria and macroinvertebrate diversity . The TSI 

measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

168 
Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes. The WQI and TSI are constructed so 

they run from zero to 100 ; larger values indicate declining water quality. 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Okaloosa County, 

Pensacola Bay and Choctawhatchee Bay have been selected for a brief summary 

of the current state of water quality in this region of the study area . 

The WQI and TSI for important areas are shown in Table 143 . 

The Pensacola Bay Basin extends from Escambia County to Okaloosa County . 

Urban runoff and wastewater treatment plant discharges are the major 

pollution sources . These latter sources are from well-defined points such 

as the University of West Florida WWTP, Monsanto industrial discharges, and 

Gulf Power thermal discharges that enter the Escambia River upstream of the 

mouth . Therefore, reduced DO levels, fish kills and bacteria problems have 

been evident around the mouth of the Escambia River . This portion of 

Escambia Bay also receives discharges from CYTEC and Air Products, two 

Table 143 . Water Quality Indices for Selected Areas of Okaloosa 

County, Florida . 

Water Areas : Pensacola Bay Water Quality Indices* 

Water Body Type : Estuary W~.~ TSI 

19 East River Bay -- 37 

Water Body Type : Stream 

25 Prairie Creek 15 --

31 Live Oak Creek 19 --

39 Turtle Creek 12 -- 

Water Areas : Choctawhatchee Bay 

Water B ody TyBe : Estuary 

21 Choctawhatchee Bay -- 30 

24 Cinco Bayou -- 25 

25 Choctawhatchee Bay -- 36 

27 Carnier Bayou -- 37 

35 Poquito Bayou -- 12 

43 Boggy Bayou -- 38 

48 Rocky Bayou -- 42 

Water Body Type : Stream 

49 Toms Creek 23 -- 

50 Lightwood Knot Creek 10 -- 

51 Garnier Creek 10 -- 

58 Turkey Creek 10 -- 

68 Juniper Creek 13 -- 

79 Turkey Creek 11 -- 

* Higher values indicate lower water quality 

169 
manufacturing plants whose discharges have been found to be toxic in 

several bioassays, with high levels of nitrogen and BOD . As outlined 

earlier in this report, the industrial structure of Okaloosa County is such 

that the ecosystem is under constant attack from many major industries in 

this area . This has manifested itself in fish kills (April, 1994), toxic 

bioassays and dirty foam near point-source outfalls . Finally, moving east 

in this basin, water quality improves, especially in Santa Rosa Sound. 

The TRI is an annual summary of discharges to surface water as well as 

other kinds of discharges (e .g ., airborne) . In 1994 there were no toxic 

substances reported that were discharged in or around the surface waters of 

Okaloosa County . 

Shellfish harvesting has been closed in 27,488 acres, and opened 

(conditional) in 68,077 acres of Choctawhatchee Bay, indicating somewhat 

cleaner conditions than those existing in the counties west of Okaloosa 

(i .e ., Escambia and Santa Rosa) . 

170 
Socioeconomic Components and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

SR .1 Introduction 

Santa Rosa County is located in the western section of the study area, 

which ranges from Escambia to Citrus County in northwestern Florida (Figure 

12) . It contains 1,016 square miles of land, ranking it 16th among the 67 

counties in Florida . In 1990, Santa Rosa County had a population of 

81,608, ranking it 33rd among Florida's counties . The population density 

was 89 people per square mile in 1990, ranking it 33rd in Florida . Santa 

Rosa County has a relatively low median age of 32 .5 years, compared to the 

Florida-wide median age of 36 .4 years . 

The population of Santa Rosa County had a per capita income of $16,167 in 

1992, 31st of the 67 Florida counties and 22%- below the state-wide average 

of $19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem. For example, a retirement community 

may produce less toxic chemical discharges into waterbodies, compared to an 

area where income is earned at a local chemical plant . For Santa Rosa 

County, an analysis of the sources of income will be discussed below, along 

with the interaction with the ecosystem. 

Santa Rosa County had 11 .5% of the households below the poverty level in 

1989, which was higher than the State of Florida average of 9 .Oo . In 1993, 

the unemployment rate was 5 .10 (relative to a statewide average of 7 .Og), 

indicating a slack labor market . 

SR .2 Trends in Population . Income and Employment in Santa Rosa County, 

1980-93 . 

Table 144 shows the trend in key economic variables in Santa Rosa County 

from 1980 through 1993 . Over this interval, resident population increased 

by 62%, (4 .8% annually), which was rapid when compared to 39 .5% for Florida 

as a whole . Population increases that were induced primarily by the 

industrial structure (i .e ., job creation) and natural amenities of the 

region place additional pressure on the carrying capacity of both living 

(e .g ., coastal fishery stocks) and non-living natural resources (e .g ., 

beaches) . 

Nominal aggregate personal income increased by 260% from 1980 to 1993 

(Table 144) . Adjusted for inflation, real aggregate personal income 

increased by 105% (8 .1% annually) . Since real income growth outstripped 

the population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

will have the financial resources to reduce negative externalities (e .g ., 

air and water pollution) which often accrue from population growth (Hall, 

1994) . 

171 
=~` 

,~ TTO BAY 

4+l 

ESCAMBIA SAY l Am"; 

,~7n 7 Cd 

CARPENTER 

ur 

BAYOU CWC~- I A 

~. 

~e~.. 

g . ."" "6 

3 

. t'- 

GULF OF MEXICO 

PENSACOLA BAY BASIN 

03140105 

WATER QUALITY 

GOOD 

AVERAGE WATER QUALITY ~ THREATENED 

1984-1993 STORET DATA 

~ 

FAIR 

WATERSHED ID NUMBERS LINK MAP TO TABLES POOR 

INDICATES QUALITATIVE ASSESSMENT ~ UNKNOWN 

Figure 12 . Map of Santa Rosa County, Florida, showing levels of water 

quality and areas of quality testing (Pensacola Bay Basin)[from 

Bureau of Surface Water Management (1994b)] . 

172 
Table 144 . Trends in Key Economic Aggregate Variables in Santa Rosa 

County, Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

gmployment3 

1980 56,500 $434,336 $527,107 18,011 

1981 59,000 506,770 557,503 17,852 

1982 60,900 567,070 587,637 18,520 

1983 63,000 640,001 642,571 19,470 

1984 65,600 712,494 685,750 20,395 

1985 68,000 774,130 719,452 21,300 

1986 70,400 843,764 816,019 22,271 

1987 73,600 922,304 811,887 23,835 

1988 76,000 1,002,118 847,099 24,991 

1989 79,000 1,094,767 882,877 26,091 

1990 82,200 1,221,088 934,268 27,847 

1991 85,400 1,336,838 981,526 29,179 

1992 90,100 1,462,337 1,042,293 30,169 

1993 94,500 1,564,823 1,082,922 30,741 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Santa Rosa County increased from 18,011 in 1980 to 

30,741 in 1993, a 70% increase . The growth of jobs is stimulated in a 

region by what is known as the export base . Simply put, a region's growth 

is determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region, income to retirees in Florida and injections 

of Federal dollars to sustain military bases such as Eglin Air Force Base 

in Okaloosa County . Through a multiplier process, this export income 

sustains both direct export jobs (e .g ., civilians working for the military) 

and indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Santa Rosa County 

grew less rapidly than the measure of county output - real aggregate 

personal income - as local entrepreneurs introduced labor-saving 

technological devices to economize on the rising cost of labor . 

SR .3 Trends in Various Welfare Measures in Santa Rosa County. 1980-93 

Per capita income is a general overall measure of how well-off a community 

is in economic terms, but components of personal income are sometimes more 

revealing . A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is likely to be more able 

173 
to protect the ecosystem than one which is highly dependent on income 

maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Santa Rosa County derived 99%- of its personal 

income from earnings, retirement and capital income, compared to 98 .2 for 

the whole of Florida . Thus, the county is more likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem. The trends in the components of personal income per capita are 

shown for Santa Rosa County in Table 145 . 

SR .4 The Industrial Base : Santa Rosa County 

The "industrial base" for Santa Rosa County refers to the industries that 

are primarily export in nature as discussed above . These industries drive 

the local economy. The rest of the industries in the county are "nonexport industries" that depend, for the most part, on what happens inside 

the region . These are called non-basic industries . For small areas such 

as counties, agriculture, fisheries, mining, manufacturing, transportation 

and service-oriented industries for tourists are likely to be export 

industries while wholesale and retail trade, finance, services and local 

government are likely to be non-basic industries . No data are available on 

exports from a county ; however, location quotients and expert judgment can 

be used to identify such industries with some accuracy . If a given county 

is highly specialized relative to the nation in the production of a 

particular commodity, the product is presumed to be an export item (e .g ., 

automobiles from Detroit) . The specialization is measured by computing the 

percentage of personal income generated by an industry (e .g ., lOg) in an 

Table 145 . Trends in Components of Personal Income in Santa Rosa County, 

Florida, 1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $7,687 $5,561 $104 $16 $1,178 $828 

1981 8,558 6,131 108 13 1,347 989 

1982 9,318 6,556 106 19 1,489 1,148 

1983 10,158 7,240 108 22 1,609 1,179 

1984 10,859 7,730 102 18 1,661 1,349 

1985 11,390 8,070 100 28 1,791 1,401 

1986 11,985 8,485 109 27 1,878 1,486 

1987 12,529 8,886 109 23 1,971 1,541 

1988 13,194 9,272 120 25 2,170 1,607 

1989 13,862 9,640 131 22 2,324 1,744 

1990 14,861 10,314 157 28 2,474 1,889 

1991 15,657 10,784 189 38 2,644 2,002 

1992 16,237 11,231 238 61 2,782 1,925 

1993 16,556 11,445 229 50 2,891 1,951 

Source : BEA (1995) 

174 
area, compared to the same percentage nationally (e .g ., 0 .5%), assuming the 

nation consumes all it produces - no imports or exports . This is rather 

simplistic, but it does serve as an indicator of which industries are 

predominately export . This figure, the location quotient (LQ), would be : 

(1) LQ = 10%/ .5g = 20 

Thus, 95% would be in export or 

(2) 1 - LQ-1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 146 shows the main identified export industries and their 

contribution to personal income in Santa Rosa County . This county 

primarily depends on military, manufacturing, textiles and chemicals, and 

acts as a bedroom community to Escambia County for its economic survival . 

Some of the largest individual employers in Santa Rosa County have, from 

time to time, had negative impacts on the ecosystem. For Santa Rosa 

County, Table 147 shows the top ten employers, along with the products they 

produce that may generate conflicts with the ecosystem. Products such as 

textiles, chemicals and lumber must be rigorously controlled or they will 

reduce water and air quality. In 1993, the Florida Department of 

Environmental Protection reported that the companies in Santa Rosa County 

discharged 243,490 pounds of toxic chemicals into surface water, ranking it 

second in volume among Florida's counties . 

SR .S Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health, are referred to as ecosystem-sensitive 

industries . For Santa Rosa County, the industries shown in Table 148 fall 

into this category . 

The Santa Rosa County economy is partly based upon timber which is 

harvested and processed in this region into various kinds of paper-based 

products . This county serves as part of an air base for the U .S . Military . 

Many of these economic activities create various kinds of waste that is a 

point or nonpoint discharge into rivers and coastal waters . These 

industries are primarily involved in the export sector and therefore are 

critical to this coastal county . 

SR .6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of Citrus County is primarily 

composed of ecosystem-insensitive industries, those which have relatively 

little impact on the environment . These are shown in Table 149 . In 

general, industries such as an Air Force base (Eglin), tourism and being a 

"bedroom community" for Escambia County are less toxic to animals in the 

ecosystem than are other industries in Santa Rosa County . Over the 1969-93 

period, ecosystem-insensitive industries grew faster than the ecosystemsensitive industries, meaning that the relative impact of industrial growth 

has been less hazardous to the fragile marine environment . 

175 
Table 146 . Major Export Industries in Santa Rosa County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings 

(000) 

% of Personal 

Income 

LQ* 

Manufacturing $71,019 4 .5 PJ* 

Food 3 .9 

Textiles N/A 

Paper & Printing, Lumber, Pi 

Furniture 

Chemicals 2 .2 

Machinery Pi 

Stone, Clay, Glass Pi 

Tourism (Meals & Motels) 19,208 1 .2 Pi 

Military 65,927 4 .2 4 .5 

Federal, Civilian 25,245 1 .6 Pi 

Bedroom Community to Escambia 

County Plus Construction 539,546 N/A gyp 

Aggregate Personal Income $1,564,823 ? ? 

*LQ = Location quotient . See Text . 

*PJ = Professional Judgment . 

Source : BEA (1995) 

Table 147 . Top Ten Employers in Santa Rosa County, Florida and Products 

Produced, 1994 . 

Employer Employees 

1 . Vanity Fair Mills, Clothing 850 

2 . Beech Aerospace, Aircraft Maintenance 360 

3 . Santa Rosa Medical Center, Health Care 350 

4 . Air Products and Chemicals, Chemicals/Fertilizer 343 

5 . Cytec, Inc ., Acrylic Fibers 320 

6 . Russell Corporation, Sportswear 

7 . UNC Support Services, Helicopter Services 250 

8 . Mold-Ex Rubber Company, Rubber Products 200 

9 . South-Tek International, Military Drop Systems 80 

10 . Fabbro Marine Group, Boat Manufacturers 75 

Sub-Total 3,128 

Total 30,741 

Percent of Total 11% 

Source : Florida Department of Commerce (1994) 

176 
Table 148 . Ecosystem-Sensitive Industries in Santa Rosa County, Florida . 

Industry Earnings ($000) 

1 . Food N/A 

2 . Textiles N/A 

3 . Chemicals $40,056 

4 . Paper & Printing 2,321 

5 . Stone, Clay & Glass 1,371 

Sub-Total $43,748 

Total Earnings (Non-Farm) ??? 

Percent of Total ??? 

Source : BEA (1995) 

Table 149 . Ecosystem-Insensitive Industries in Santa Rosa County, Florida . 

Industry Earnings ($000) 

1 . Military and Federal Employees, Civilian $91,172 

2 . Tourism 19,208 

Eating and Drinking ??? 

Hotels/Motels ??? 

3 . Bedroom Community 488 .438 

Sub-Total $488,438 

Total Earnings ??? 

Percent of Total ??? 

Source : Table 146 

SR .7 Commercial Fishery Landings in Santa Rosa County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Santa Rosa County . 

Three categories of fishery products are found : (1) finfish; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $1 .24 million worth of commercial fishery 

products were landed in Santa Rosa County at the ex vessel level (Table 

150) . Finfish and shrimp account for 65% of this value . Among finfish, 

menhaden, an industrial fish, was by far the leading species as measured by 

quantity and value . Blue crabs were the leading species overall in 

177 
Table 150 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Santa Rosa County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Menhaden 1,635,190 $179,870 .91 

Black Mullet 183,797 86,384 .59 

Red Snapper 26,477 64,074 .34 

Yellowfin Tuna 22,882 56,060 .90 

Vermilion Snapper 32,038 49,658 .90 

Tilefish 33,155 49,069 .40 

Yellowedge Grouper 22,411 46,838 .99 

Round Scad 149,130 38,773 .80 

Ladyfish 83,792 33,516 .80 

Triggerfish 20,345 18,717 .40 

All Others 284,046 158 .383 .84 

Total $781,349 .90 

Invertebrates 

Blue Crabs 572,781 $367,277 .88 

Stone Crabs 0 0 

Oysters 56,402 69,938 .48 

Squid 729 269 .73 

All Others 0 0 

Total $437,486 .09 

Shrimp (Total) 12,741 25,874 .52 

Grand Total $1,244,710 .51 

* State average ex vessel price used . 

Source : FDEP (1994) 

quantity and value . Nearly all of the shrimp were of the brown species 

that depends on wetlands for a habitat during a phase of its life cycle . 

Among the 13 counties in the study area, Santa Rosa County ranked 11th in 

the ex vessel value of all commercial fishery landings . 

Although the ex vessel value does not include value added in processing 

and distribution, commercial fishing is a relatively small component of the 

economic base of Santa Rosa County, where aggregate personal income was 

$1 .56 billion in 1993 . Over the last fourteen years, commercial fishery 

landing has increased by 34% while the ex vessel value of the catch has 

increased by 4250 . When adjusted for inflation, the value of landings 

changed by 66% (FDNR, 1980) . 

SR .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently, 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively, that engage in saltwater recreational 

fishing in Florida. In Milon and Thunberg (1992), there is some regional 

breakdown embracing the present study area from Hernando County north to 

178 
Escambia County . Such regions include both coastal and interior counties . 

As an approximation, these regional averages can be applied to the 

individual counties . Bell (1993) has only statewide averages for tourist 

saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

angler for Region I (i .e ., Escambia to Jefferson County) were about 40-500 

higher than the statewide average. Thus, using the latest study of Bell 

(1993), statewide figures may be conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county. Santa Rosa County had 6,863 resident anglers purchasing a one-year 

fishing license . It should be pointed out that purchase of a license in a 

county does not ensure that one is a resident of that county, but informal 

conversations with Florida Dept . of Environmental Protection personnel 

suggest little bias is associated with that assumption . Nonresidents are 

those that purchased saltwater fishing licenses in non-coastal counties . 

Such licenses were pro-rated to coastal counties in close geographical 

proximity to each county, using personal judgment . 

This is shown in Table 151 where nonresidents are shown in the second 

column . Finally, tourists must purchase a license, and the number is shown 

for the counties in the study area . This may underestimate tourist 

saltwater anglers since tourists may buy a license in an interior county 

and use it in one of the coastal counties . 

Table 152 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 151 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers, 

respectively . Santa Rosa County showed a fishing effort of 79,583 days . 

Finally, Table 153 is derived from Table 151 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $5,162,394 in Santa Rosa County in 1993-94 . 

Many assumptions were made to arrive at these estimates, however, these 

figures are believed to indicate an order of magnitude and relative 

ranking, and may actually be conservative . That is, it is not surprising 

that Bay (Panama City) and Citrus (Crystal River) counties are the top two 

counties for saltwater recreational fishing expenditures . Multiplier 

effects of nonresidents and tourists were not considered . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing . There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value 

179 
Table 151 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents Nonresident2 Tourist 3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

1 0kaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 

I 

1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11 .685 6,926 5,312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

Non-resident (out of state) saltwater fishing licenses for one year ; 

seven days and three days . 

Table 152 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresidents 

Tourist2 Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167,499 21 .248 188 .747 

Total 952,605 377,480 1,330,085 

1 9 days per angler year and Table 151 . See Milon and Thunberg (1992) . 

2 4 days per angler year and Table 151 . See Bell (1993) . 

180 
Table 153 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Touristz Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3~349~154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8,890 .475 2 .337 .280 11 .227,755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 151 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 151 multiplied by $440 .00 per angler . 

of saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Santa Rosa County can be computed as follows : 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 7,011 = $2 .6 million 

Tourists 

(value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 4,121 = $0 .8 million . 

Thus, saltwater recreational fishing generates $3 .4 million per year in 

Santa Rosa County with a capitalized value of $113 million using a 3% 

discount rate (i .e ., $3 .4 million , .03) . 

SR .9 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export, 

rather than wetlands for grazing. The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

181 
property, where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets, such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated . This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 154 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch . 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch. The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product. Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

Table 154 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

182 
estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Santa Rosa County has 6,500 acres of salt 

marsh (NOAA, 1991), which would be worth $34 million ($5,316 x 6,500) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by Santa Rosa County wetlands . 

SR .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier . Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . It is difficult to separate Escambia 

County from neighboring Santa Rosa County since one beach runs into 

another . Table 155 lists the key beaches for these two counties . 

In 1984, Bell and Leeworthy (1986) estimated expenditures per day of $12 

(1994 dollars) and $30 (1994 dollars) for residents and tourists, 

respectively, on saltwater beach-related costs such as lodging, food and 

drink, etc . in Pensacola, Florida . These estimates will be used for all 

counties in the study area as an approximation since no recent studies have 

been undertaken . 

183 
Table 155 . Key Saltwater Beaches in Santa Rosa County, Florida* 

(none) 

Gulf Islands National Seashore 

Fort Pickens and Langdon Beach 

Unnamed Beaches 

Quietwater Beach 

Casino Beach 

Pensacola Beach 

Eastern District 

Gulf Islands National Seashore/ 

Santa Rosa Recreational Facility 

Navarre Beach Public Access 

Navarre Beach Fishing Pier 

Shoreline Park 

*In Santa Rosa County alone, the University of West Florida (1985b) 

reported 17 individual saltwater beaches which were 9 .5 miles in 

length and 2 .5 million square feet (public and private) . 

Source : University of West Florida (1985a) 

Using the CV technique, Leeworthy, et al . found that Escambia, Franklin 

and Bay Counties had an averaged user value of about $3 .0 per day (in 1994 

dollars) for residents and tourists . In a comprehensive study of Florida 

beaches, the University of West Florida (1985b) projected that Santa Rosa 

County would have 951,555 saltwater beach days per year in 1990 for the 

beaches listed in Table 155 . By multiplying the user value per day of $3 

times the estimated number of saltwater beach days, the annual flow of 

value is $2 .85 million . Remember, these are not actual expenditures, but 

an estimate of annual recreational benefits to beach users . The 

capitalized value of this value flow at a real discount rate of 3$ is over 

$95 million - the asset value of the beach . 

Finally, beach-related spending in Santa Rosa County in 1990 can be 

calculated in the following manner [with the percentage of residents and 

tourists taken from the University of West Florida (1985b) study] : 

Residents 

(% Residents) x (Beach Days/Yr .) x (Expenditures/day) 

.36 x 951,555 x $12 = $4 .11 million 

Tourists 

(% Tourists) x (Beach Days/Yr .) x (Expenditures/day) 

.64 x 951,555 x $30 = $18 .3 million 

184 
Combined, saltwater beaches in Santa Rosa County attracted an estimated 

$22 .41 million in beach-related spending in 1990 with tourists accounting 

for 83 percent of this spending . 

Three ecological resources have been identified that are an asset to Santa 

Rosa County and induce a considerable level of economic activity in this 

region . Such values are summarized in Table 156 . 

SR .11 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 157 is 

an inventory of these water-dependent facilities in Santa Rosa County . 

Piers, boardwalks and jetties facilitate bank recreational fishing, beach 

use and other outdoor recreational activities . 

As an outdoor recreational activity, boating makes use of common property 

water resources . Bell (1995) found that the user value per day, expressed 

in 1994 dollars, is worth $3 .56 more if a marina is used (i .e ., $5 .02 less 

$1 .48) rather than a boat ramp . These are Florida-wide values and may or 

may not be good estimates for Santa Rosa County, but are used for purposes 

of illustration . 

Santa Rosa County has 19 saltwater boat ramp lanes and 276 wet slips and 

dry racks, as shown in Table 157 . The number of private docks from which 

to launch pleasure craft is unknown. Combining data from Bell et al . 

(1982) and Bell (1995), the annual user value from boating in the Gulf of 

Mexico off Santa Rosa County is estimated and shown in Table 158 . This 

value is about $ .39 million. 

Table 156 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Santa Rosa County, Florida . 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year l 

Asset Value 

(Millions )2 

Commercial Fishing $1 .243 N/A N/A 

Recreational Fishing $5 .14 $3 .45 $1135 

Saltwater Marshs N/A .207 6 346 

Saltwater Beaches $22 .416 $2 .856 $95 .06 

Marine Boating' N/A $ .390' $13 .02' 

Nonmarket value per year 

#1 divided by .03 = Asset Value 

' Table 150, ex vessel price 

Table 153, retail price 

To commercial fishery landings only 

See text for discussion 

See Table 158 

185 
Table 157 . An Inventory of Marine-Related Recreational Facilities in 

Santa Rosa County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number 6 

b . Length (all) (LFT)* 10,318 

2 . Boardwalks/Catwalks 

a . Number 9 

b . Length (all) (LFT)* 1,020 

3 . Jetties 

a. Length (all) (LFT)* 120 

Boating 

1 . Boat Ramps 

a . Number 17 

b . Total Lanes 19 

2 . Marinas 

a . Total 4 

b . Slips/Moorings 96 

c . Dry Storage 180 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

Table 158 . Estimation of the Annual User Value for Saltwater Boating Off 

Santa Rosa County, Florida, 1993-94 . 

Facility 

N Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$140,663 = $5 .021 x 5,2672 x .193 x 28' 

2 . Boat Rams 

$146,237 = $1 .481 x 5,267 x .674 x 28 

3 . Private Docks 

$103,646 = $5 .025 x 5,267 x .14 x 28 

Total Annual User Value = $390,546 

*Asset Value = 390,546 = .03 = $13 .02 million 

Bell (1995), Florida-wide value 

2 FDEP (1992), Santa Rosa County 

Bell et al . (1982), northwest Florida 

° Bell (1995'), Santa Rosa County 

Assumed $/day same for marinas and private docks 

186 
Recreational boating in marine waters is rapidly growing in Santa Rosa 

County . Such boating can effect coastal water quality (e .g ., inadequate 

pumping out facilities) as well as adding user value to those using coastal 

water resources . From the FDEP (1983-1992) and Bell (1995) studies, 

pleasure boat registrations in Santa Rosa County grew as follows, with 

projected (P) numbers included : 

1983 5,267 

1984 5,413 

1985 5,711 

1986 5,933 

1987 5,881 

1988 6,301 

1989 6,730 

1990 6,727 

1991 6,731 

1992 6,927 

2000 10,988 (P) 

2005 15,605 (P) 

2010 22,160 (P) 

SR .12 Water Quality, the Ecosystem and the Econ 

The interaction of the local economy and the marine ecosystem is 

manifested in the water quality surrounding the region . Florida's major 

surface water quality problems come from urban stormwater runoff, 

agricultural runoff, domestic wastewater, industry wastewater, and 

hydrological changes such as draining and filling wetlands . 

There are three sources of information on local water quality surrounding 

Santa Rosa County . First, the Federal Water Pollution Control Act requires 

the state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Santa Rosa County . 

Two indices are used in the 305(b) report for measuring surface water 

quality: the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen-demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity. The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality. 

187 
The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Santa Rosa County, 

Pensacola Bay has been selected for a brief summary of the current state of 

water quality in this region of the study area . 

The Pensacola Bay Basin extends from Escambia County to Santa Rosa County . 

Urban runoff and wastewater treatment plant (WWTP) discharges are the 

major pollution sources . These latter sources are from well-defined 

points such as the University of West Florida WWTP, Monsanto industrial 

discharges and Gulf Power thermal discharges that enter the Escambia River 

upstream of the mouth . As a result, reduced DO levels, fish kills and 

bacteria problems have been evident around the mouth of the Escambia River . 

This portion of Escambia Bay also receives discharges from CYTEC and Air 

Products, two manufacturing plants . Both discharges have been found to be 

toxic in several bioassays . These companies discharge high levels of 

nitrogen and BOD . As outlined earlier in this report, the industrial 

structure of Santa Rosa County is such that the ecosystem is under 

constant attack from many major industries in this area . This has 

manifested itself in fish kills (April, 1994), toxic bioassays and dirty 

foam near point source outfalls . Finally, further east, water quality 

improves especially in Santa Rosa Sound . The WQI and TSI for important 

areas are shown in Table 159 . 

Table 159 . Water Quality Indices for Selected Areas of Santa Rosa 

County, Florida . 

Water Areas : Pensacola Bay Water Quality Indices* 

Water Body Type : Estuary WOI TSI 

7 Direct Runoff to Gulf -- 12 

8 Santa Rosa Sound -- 18 

10 Direct Runoff to Bay -- 23 

17 Direct Runoff to Bay -- 45 

21 East Bay -- 46 

30 Trout Bayou -- 43 

32 Blackwater Bay -- 34 

33 Indian Bayou -- 45 

37 Escambia Bay (N) -- 48 

42 Mulatto Bayou -- 55 

44 Judges Bayou -- 53 

45 Blackwater Bay -- 32 

Water Body Tyke : Stream 

47 Pace Mill Creek 40 -- 

* Higher vales indicate lower water quality 

188 
The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . Table 160 indicates that in 

1994, two companies (Westlake and Cytec) discharged toxic substances in and 

around the surface water of Santa Rosa County . Of the 13 counties in the 

study area, Santa Rosa County ranked second in pounds of toxic chemical 

discharges . The reader should be warned that such discharges may be highly 

variable from year to year . 

Shellfish harvesting has been closed in 70,448 acres of Pensacola Bay, 

Blackwater River, Santa Rosa Sound and the East Bay River, and opened 

(conditional) in 64,233 acres in these same areas, indicating significant 

coliform count problems in over 500 of the shellfish beds . 

Table 160 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Santa Rosa County, Florida in 1994 . 

Company SIC Discharge Main' 

1 . Westlake PVC 219,500 Ammonium 

Nitrate 

12 . Cytec Industries 23 .990 Ammonia/ 

Copper 

Total 243,490 

Leading chemical released based on pounds . 

Source : EPA Toxic Release Inventory, unpublished data, 1994 . 

189 

Socioeconomic Components and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

TAY .1 Introduction 

Taylor County is located in the eastern-central section of the study area, 

which ranges from Escambia to Citrus County in northwestern Florida 

(Figures 13 and 14) . It contains 1,042 square miles of land, ranking it 

13th among the 67 counties in Florida . In 1990, Taylor County had a 

population of 17,111, ranking it 52nd among the States' 67 counties . The 

population density was 17 people per square mile in 1990, a ranking of 63rd 

in Florida . Taylor County has a relatively low median age of 33 .5 years, 

compared to the Florida-wide median of 36 .4 years . 

The population of Taylor County had a per capita income of $13,951 in 1992, 

47th of the 67 Florida counties and 30% below the state-wide average of 

$19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income, and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem . For example, a retirement community 

may produce less toxic chemical discharges into waterbodies, compared to an 

area where income is earned at a local chemical plant . For Taylor County, 

an analysis of the sources of income will be discussed below, along with 

the interaction with the ecosystem . 

Taylor County had 16 .1% of the households below the poverty level in 1989, 

which was higher than the State of Florida average of 9 .0% . In 1993, the 

unemployment rate was 14 .5% (relative to a statewide average of 7 .0%), 

indicating a tight labor market . 

TAY .2 Trends in Population. Income and hmloyment in T 

1980-93 . 

Table 161 shows the trend in key economic variables in Taylor County from 

1980 through 1993 . Over this interval, resident population increased by 

3 .6% (0 .3% annually), which was extremely slow when compared to 39 .5% for 

Florida as a whole . Population increases that were induced primarily by 

industrial structure (i .e ., job creation) and natural amenities of the 

region place additional pressure on the carrying capacity of both living 

(e .g ., coastal fishery stocks) and non-living natural resources (e .g ., 

beaches) . 

Nominal aggregate personal income increased by 102% from 1980 to 1993 . 

(Table 161) . Adjusted for inflation, real aggregate personal income 

increased by 15 .20 (1 .2% annually) . Since real income growth outstripped 

the population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

will have the financial resources to reduce negative externalities (e .g ., 

air and water pollution) which often accrue from population growth (Hall, 

1994) . 

191 
AUCILLA RIVER BASIN 

03110103 

AVERAGE WATER QUALITY 

1984-1993 STORET DATA 

WATERSHED ID NUMBERS LINK MAP TO TABLES 

" INDICATES QUALITATIVE ASSESSMENT 

WATER QUALITY 

GOOD 

THREATENED 

FAIR 

POOR 

UNKNOWN 

Figure 13 . Map of Taylor County, Florida, showing levels of water quality 

and areas of quality testing (Aucilla River Basin)[from Bureau 

of Surface Water Management (1994a)] . 

192 
i 

r 

~a~r 

ECONFINA RI 17 . . . . ." ,. ., _Y 

NHOLLOWAY ABOVE PULP MILL 

. ~ ~ Warrior C w-- ; 

FENHOLLOWAY R 

i 

n:.Z.~.I&TMILE .: CREEK 

. ~ , r. . 

v ,Q 

-seF' 

GULF OF ~ ~:~ ::~Hl('(2:1-IEE RIVER 

MEXICO 

SANDERS CREEK 

ECONFINA CREEK/STEINHATCHEE RIVER BASIN WATER QUALITY 

03110102 GOOD 

AVERAGE WATER QUALITY ~ THREATENED 

1984-1993 STORET DATA FAIR 

WATERSHED ID NUMBERS LINK MAP TO TABLES POOR 

INDICATES QUALITATIVE ASSESSMENT 0 UNKNOWN 

Figure 14 . Map of Taylor County, Florida, showing levels of water quality 

and areas of quality testing (Ecofina Creek/Steinhatchee River 

Basin)[from Bureau of Surface Water Management (1994a)] . 

193 
Table 161 . Trends in Key Economic Aggregate Variables in Taylor County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

Employment3 

1980 16,700 $116,910 $141,881 6,999 

1981 16,800 134,917 148,424 7,322 

1982 16,900 147,122 152,458 7,466 

1983 16,800 152,730 153,343 7,439 

1984 16,800 162,707 156,600 7,815 

1985 16,800 170,593 158,544 7,637 

1986 17,000 183,941 167,829 7,843 

1987 17,000 186,190 163,900 7,957 

1988 16,900 199,153 168,346 8,161 

1989 17,000 210,482 169,743 8,042 

1990 17,200 220,812 168,946 8,113 

1991 17,400 226,248 166,114 7,225 

1992 17,300 241,816 172,356 7,812 

1993 17,300 236,255 163,498 7,541 

Includes earnings, dividends, interest, rent and transfer payments . 

2 Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Taylor County increased from 6,999 in 1980 to 7,541 

in 1993, a 7 .7% increase . The growth of jobs is stimulated in a region by 

what is known as the export base . Simply put, a region's growth is 

determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region, income to retirees in Florida and injections 

of Federal dollars to sustain military bases such as Eglin Air Force Base 

in Okaloosa County . Through a multiplier process, this export income 

sustains both direct export jobs (e .g ., civilians working for the military) 

and indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Taylor County 

grew less rapidly than the measure of county output - real aggregate 

personal income - as local entrepreneurs introduced labor-saving 

technological devices to economize on the rising cost of labor . 

TAY .3 Trends in Various Welfare Measures in Taylor County, 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but the components of personal income are sometimes more 

revealing. A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is more likely to be able 

to protect the ecosystem than one which is highly dependent on income 

194 
maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Taylor County derived 95 .10 of its personal 

income from earnings, retirement and capital income, compared to 98 .2% for 

the whole of Florida . Thus, the county is less likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem . The trends in the components of personal income per capita are 

shown for Taylor County in Table 162 . 

TAY.4 Industrial Base : Taylor County 

The "industrial base" for Taylor County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy . The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy . If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., 10%) in an area, 

compared to the same percentage nationally (e .g ., 0 .50), assuming the 

Table 162 . Trends in Components of Personal Income in Taylor County, 

Florida, 1980-93 . 

Per Capita 

Year Income 

3. Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $7,019 $5,097 $181 $26 $1,046 $669 

1981 8,029 5,830 182 22 1,204 791 

1982 8,712 6,191 182 42 1,364 932 

1983 9,067 6,383 190 34 1,469 990 

1984 9,668 6,776 205 22 1,548 1,118 

1985 10,133 7,054 201 31 1,716 1,131 

1986 10,847 7,547 194 24 1,845 1,237 

1987 10,933 7,538 184 28 1,954 1,230 

1988 11,765 8,028 215 37 2,138 1,348 

1989 12,386 8,231 252 43 2,368 1,490 

1990 12,868 8,425 310 65 2,574 1,493 

1991 13,024 8,193 389 108 2,856 1,478 

1992 13,988 8,728 527 142 3,144 1,446 

1993 13,690 8,685 514 148 3,433 909 

Source : BEA (1995) 

195 
nation consumes all it produces - no imports or exports . This is rather 

simplistic, but it does serve as an indicator of which industries are 

predominately export . This figure, the location quotient (LQ), would be : 

(1) LQ = 10$/ .5°s = 20 

Thus, 95% would be in export or 

(2) 1 - LQ~1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 163 shows the main identified export industries and their 

contribution to personal income in Taylor County . This county depends 

primarily on fishing, lumber and wood products, chemicals, and local 

governments for its economic survival . Some of the largest individual 

employers in Taylor County have, from time to time, had negative impacts on 

the ecosystem . Table 164 shows the top employers in Taylor County, along 

with the products they produce that may generate conflicts with the 

environment . Products such as lumber and chemicals must be rigorously 

controlled or they will reduce water and air quality . In 1993, the EPA 

reported that the companies in Taylor County discharged 16,470 pounds of 

toxic chemicals into surface water, ranking it 5th in volume among 

Florida's counties (Lester, 1995) . 

TAY .S Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Taylor County, the industries shown in Table 165 fall into 

this category . 

The Taylor County economy is heavily based upon timber which is harvested 

and processed regionally into various paper-based products . All of these 

economic activities create various kinds of waste that is a point or 

nonpoint discharge into rivers and coastal waters . These industries are 

primarily involved in the export sector and therefore are critical to this 

coastal county . 

TAY .6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of Taylor County is composed of 

primarily ecosystem-sensitive industries . The remainder are ecosysteminsensitive industries, which have relatively little impact on the 

environment, and are shown in Table 166 . 

In general, lumber accounts for the greatest portion of earnings and nearly 

all manufacturing revenue . This industry usually has adverse effects on 

local ecosystems . Over the 1969-93 period, the ecosystem-insensitive 

industries were growing slower than the ecosystem-sensitive industries, 

meaning that the growth in the Taylor County economy is in direct conflict 

with the environment . 

196 
Table 163 . Major Export Industries in Taylor County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings 

(000) 

% of Personal 

Income 

LQ* 

Fisheries $573 .24 7 .81 

Manufacturing 

Lumber and Wood 11,387 4 .8 11 .25 

Fabricated Metals 6,833 2 .9 3 .15 

Electronics N/A N/A N/A 

Chemicals N/A N/A N/A 

State and Local Government 3,169 1 .34 2 .21 

*LQ = Location quotient . See Text . 

Source : BEA (1995) 

Table 164 . Top Employers in Taylor County, Florida and Products Produced, 

1994 . 

Employer Employees 

1 . Buckeye Florida, Cellulose 1,007 

2 . Watkins Engineering, Construction 250 

3 . Martin Electronics, Pyrotechnics 232 

4 . Doctor's Memorial Hospital, Health Care 123 

5 . Tom's Snack Food, Food 98 

6 . Perry Lumber Company, Lumber 83 

7 . Consolidated Forest Products, Lumber Products 54 

Sub-Total 1,724 

Total 7,541 

Percent of Total 23% 

Source : Florida Department of Commerce (1994) 

Table 165 . Ecosystem-Sensitive Industries in Taylor County, Florida . 

Industry Earnings ($000) 

1 . Manufacturing 

Lumber and Wood $11,387 

Fabricated Metals 6,833 

Paper and Allied Products 50, 000 (est . ) 

Sub-Total $68,220 

Total Earnings (Non-Farm) $170,156 

Percent of Total 40% 

Source : BEA (1995) 

197 
Table 166 . Ecosystem-Insensitive Industries in Taylor County, Florida . 

Industry Earnings ($000) 

1 . Fisheries $573 

2 . Food Stores 3,169 

3 . State and Local Government ?.4,483 

Sub-Total $28,225 

Total Earnings $170,156 

Percent of Total 16% 

Source : Table 163 

TAY.7 Commercial Fishery Landings in Taylor County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Taylor County . 

Three categories of fishery products are found : (1) finfish; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $1 .3 million worth of commercial fishery 

products were landed in Taylor County at the ex vessel level (Table 167) . 

Finfish and shrimp account for 70g of this value. Among the finfish, sea 

bass was the leading species as measured by quantity and value. Brown 

shrimp, which depends on wetlands during a phase of its life cycle, was the 

dominant shrimp species . Among the 13 counties in the study area, Taylor 

County ranked 10th in the ex vessel value of all commercial fishery 

landings . 

Although the ex vessel value does not include value added in processing and 

distribution, commercial fishing is a relatively small component of the 

economic base of Taylor County, where aggregate personal income was $236 

million in 1993 . Over the last fourteen years, commercial fishery landing 

has increased by 539. while the ex vessel value of the catch has increased 

by 316 . When adjusted for inflation, the value of landings changed by 

1320 (FDNR, 1980) . 

TAY .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently, 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively, that engage in saltwater recreational 

fishing in Florida. In Milon and Thunberg (1992), there is some regional 

198 
Table 167 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Taylor County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Sea Bass 311,227 $143,164 .42 

Grunts 301,925 141,904 .75 

Red Grouper 64,475 113,476 .00 

Black Mullet 230,035 108,116 .45 

Spotted Sea Trout 85,198 102,237 .60 

Gag Grouper 27,147 60,537 .81 

Spanish mackerel 103,475 43,459 .50 

MisC . Food Fish 37,876 22,346 .84 

Sand Sea Trout 22,389 13,209 .51 

All Others 99,748 97,140 .73 

Total $866,877 .81 

Invertebrates 

Stone Crabs 35,368 $194,987 .72 

Blue Crabs 267,009 171,013 .17 

Octopus 16,405 15,256 .65 

Oysters 571 708 .04 

Total $381,965 .58 

Shrimp (Total) 9,466 22 .397 .42 

Grand Total $1,271,240 .81 

* State average ex vessel price used . 

Source : FDEP (1994) 

breakdown embracing the present study area from Hernando County north to 

Escambia County . Such regions include both coastal and interior counties . 

As an approximation, these regional averages can be applied to the 

individual counties . Bell (1993) has only statewide averages for tourist 

saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

angler for Region I (i .e ., Escambia to Jefferson County) were about 40-50% 

higher than the statewide average . Thus, using the latest study of Bell 

(1993), statewide figures may be conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county . Taylor County had 4,583 resident anglers purchasing a one-year 

fishing license . It should be pointed out that purchase of a license in a 

county does not ensure that one is a resident of that county, but informal 

conversations with Florida Dept . of Environmental Protection personnel 

suggest. little bias is associated with that assumption . Nonresidents are 

those that purchased saltwater fishing licenses in non-coastal counties . 

Such licenses were pro-rated to coastal counties in close geographical 

proximity to each county, using personal judgment . This is shown in Table 

199 
168 where nonresidents are shown in the second column . Finally, tourists 

must purchase a license and the number is shown for the counties in the 

study area . This may underestimate tourist saltwater anglers since 

tourists may buy a license in an interior county and use it in one of the 

coastal counties . 

Table 169 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 168 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers, 

respectively . Taylor County showed a fishing effort of 98,271 days . 

Finally, Table 170 is derived from Table 168 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $7,347,174 in Taylor County in 1993-94 . Many assumptions 

were made to arrive at these estimates, however, these figures are believed 

to indicate an order of magnitude and relative ranking, and may actually be 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . Multiplier effects of nonresidents and 

tourists were not considered . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing. There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Taylor County can be computed as follows : 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 6,759 = $2 .5 million 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 9,360 = $1 .8 million . 

Thus, saltwater recreational fishing generates $4 .3 million per year in 

Taylor County with a capitalized value of $143 million using a 3% discount 

rate (i .e ., $4 .3 million = .03) . 

TAY .9 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing . The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

200 
Table 168 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents NonresidentZ Tourist 3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11 .685 6 .926 5"312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

Non-resident (out of state) saltwater fishing licenses for one year ; 

seven days and three days . 

Table 169 . Estimated Number of Saltwater Recreational Days (Fishing 

Effort) in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresidents 

Tourist2 Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167 .499 21 .248 188,747 

Total 952,605 377,480 1,330,085 

9 days-per angler year and Table 168. See Milon and Thunberg (1992) . 

4 days per angler year and Table 168 . See Bell (1993) . 

201 
Table 170 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Tourist2 Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118 400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8,890 .475 2 .337,280 11 .227 .755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 168 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 168 multiplied by $440 .00 per angler . 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated . This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 171 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida. This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch . 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of 'the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

202 
Table 171 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

West Florida at $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

203 
production elasticity of 0 .19) . Taylor County has 21,800 acres of salt 

marsh (NOAA, 1991), which would be worth $115 .8 million ($5,316 x 21,800) 

in fishery production alone . Negative ecological factors such as dredging 

or oil spills would threaten the value provided by Taylor County wetlands . 

TAY .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier. Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . Taylor County only has one significant 

beach (Keaton Beach), and no visitor information is currently available, so 

the value of beaches cannot be estimated . Table 172 identifies ecological 

resources that are an asset to Taylor County and induce a considerable 

level of economic activity in the region . 

TAY .11 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 173 is 

an inventory of these water-dependent facilities in Taylor County . Piers, 

boardwalks and jetties facilitate bank recreational fishing, beach use and 

other outdoor recreational activities . 

As an outdoor recreational activity, boating makes use of common property 

water resources . Bell (1995) found that the user value per day, expressed 

in 1994 dollars, is worth $3 .56 more if a marina is used (i .e ., $5 .02 less 

$1 .48) rather than a boat ramp . These are Florida-wide values and may or 

may not be good estimates for Taylor County, but are used for purposes of 

illustration . 

Taylor County has 8 saltwater boat ramp lanes and 312 wet slips and dry 

racks, as shown in Table 173 . The number of private docks from which to 

launch pleasure craft is unknown . Combining data from Bell et al . (1982) 

and Bell (1995), the annual user value from boating in the Gulf of Mexico 

off Taylor County is estimated and shown in Table 174 . The annual user 

value for marine boating off Taylor County is about $ .22 million . 

Recreational boating in marine waters is rapidly growing in Taylor County . 

Such boating can affect coastal water quality (e .g ., inadequate pumping out 

facilities) as well as adding user value to those using coastal water 

204 
Table 172 . Spending, Annual User Value and Asset value of Selected 

Ecological Resources in Taylor County, Florida. 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year' 

Asset Value 

(Millions )2 

Commercial Fishing $1 .33 N/A N/A 

Recreational Fishing $7 .3' $4 .35 $1435 

Saltwater Marshs N/A .207 6 115 .8 6 

Saltwater Beaches N/A' N/A6 N/A6 

Marine Boating' N/A $ .219' $7 .3' 

1 Nonmarket value per year 

z #1 divided by .03 = Asset Value 

Table 167, ex vessel price 

° Table 170, retail price 

5 To commercial fishery landings only 

See text for discussion 

See Table 174 

Table 173 . An Inventory of Marine-Related Recreational Facilities in 

Taylor County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number -- 

b . Length (all) (LFT)* -- 

2 . Boardwalks/Catwalks 

a . Number 5 

b . Length (all) (LFT)* 470 

3 . Jetties 

a . Length (all) (LFT)* 50 

Boating 

1 . Boat Ramps 

a . Number 10 

b . Total Lanes 8 

2 . Marinas 

a . Total 5 

b . Slips/Moorings 195 

c . Dry Storage 117 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

205 
Table 174 . Estimation of the Annual User Value for Saltwater Boating Off 

Taylor County, Florida, 1993-94 . 

Facility 

(Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$78,868 = $5 .021 x 2,5842 x .193 x 324 

2 . Boat Ramps 

$81,993 = $1 .481 x 2,584 x .67° x 32 

3 . Private pocks 

$58,113 = $5 .025 x 2,584 x .14 x 32 

Total Annual User Value = $218,974 

*Asset Value = 218,974 = .03 = $7 .3 million 

Bell (1995), Florida-wide value 

2 FDEP (1992), Taylor County 

Bell et al .(1982), northwest Florida 

° Bell (1995), Taylor County 

5 Assumed $/day same for marinas and private docks 

resources . From the FDEP (1983-1992) and Bell (1995) studies, pleasure 

boat registrations in Taylor County grew as follows, with projected (P) 

numbers included : 

1983 1,639 

1984 1,731 

1985 1,787 

1986 1,810 

1987 1,917 

1988 1,967 

1989 1,944 

1990 2,099 

1991 2,298 

1992 2,391 

1993 2,399 

1994 2,584 

2000 3,298 (P) 

2005 4,074 (P) 

2010 4,988 (P) 

TAY .12 Water Quality, the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is 

manifested in the water quality surrounding the region . Florida's major 

surface water quality problems come from urban stormwater runoff, 

agricultural runoff, domestic wastewater, industry wastewater, and 

hydrological changes such as draining and filling wetlands . 

206 
There are three sources of information on local water quality surrounding 

Taylor County . First, the Federal Water Pollution Control Act requires the 

state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Taylor County . 

Two indices are used in the 305(b) report for measuring surface water 

quality: the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen-demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity. The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality . 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Taylor County, we 

have selected the Aucilla River and Econfina Creek/Steinhatchee River 

Basins for a brief summary of the current state of water quality in this 

region of the study area . 

The Aucilla River is considered one of Florida's most outstanding waters . 

The river originates in Georgia in a series of lakes, swamps, sinkholes and 

underground passages . The water is characterized by tea-colored water due 

to natural substances . The overall water quality is considered very good, 

and will most likely stay that way, because of few pollution sources and 

very little development in the basin . 

The Econfina Creek/Steinhatchee River Basin covers the coastal lowlands in 

Taylor County . A series of small rivers drain swampy lowlands and empty 

into the Gulf of Mexico . There are very few threats to most of these 

smaller rivers because of the surrounding wetlands . The exception is the 

Fenholloway River, which is the only waterbody in the state used for 

navigation, utility and industrial use . Discharges from the Buckeye 

Florida paper mill have severely affected water quality, and at times make 

up the river's entire flow . The mill also withdraws large quantities of 

water from the river, which also reduces the flow . Investigations near the 

river show that most of the nearby wells have been contaminated . At the 

mouths of the other estuaries, the water quality is considerably better and 

even supports commercial fishing. Other non-point discharges include 

septic tank leakage and poor drainage . The WQI and TSI for selected areas 

are listed in Table 175 . 

207 
Table 175 . Water Quality Indices for Selected Areas of Taylor County, 

Florida. 

II Water Areas: Aucilla River Water Quality Indices* II 

Water Body Type : Stream WOI T I 

5 Aucilla River 28 --

8 Aucilla River 35 -- 

(Water Areas : Bconfina Creek/Fenholloway 

River 

Water Body Type : Estuary -- 

10 Spring Warrior (at mouth) 57 

Water B ody Type : Stream 

3 Bevins (Boggy) Creek 

4 Steinhatchee River 

6 California (Rocky) Creek 

9 Spring Warrior Creek 

11 Weaver Warrior Creek 

12 Fenholloway River (at mouth) 

13 Fenholloway River (below pulp) 

14 Spring Creek 

16 Fenholloway River (at pulp) 

17 Rocky Creek 

18 Econfina River 

54 --

41 --

40 --

43 --

48 --

66 --

69 --

44 --

43 --

55 --

32 -- 

* Higher values indicate lower water quality 

The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . Table 176 indicates that in 

1994, one company, Buckeye Florida, discharged toxic substances in and 

around the surface water of Taylor County . Of the 13 counties in the study 

area, Taylor County ranked third in pounds of toxic chemical discharges . 

These discharges may be highly variable from year to year . 

Table 176 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Taylor County, Florida in 1994 . 

Company SIC Discharge Main' 

1 . Buckeye Florida 2,823 10,997 Ammonia 

Leading chemical released based on pounds . 

A.Source : EPA Toxic Release Inventory, unpublished data, 1994 . 

208 
County Name : Wakulla . Florida 

Socioeconomic Components and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

WAR .1 Introduction 

Wakulla County is located in the western section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figures 15 

and 16) . It contains 606 .7 square miles of land, ranking it 43rd among the 

67 counties in Florida. In 1990, Wakulla County had a population of 

14,202, ranking it 56th among Florida's counties . The population density 

was 25 people per square mile in 1990, a ranking of 54th in Florida . 

Wakulla County has a relatively low median age of 34 .2 years, compared to 

the Florida-wide median of 36 .4 years . 

The population of Wakulla County had a per capita income of $14,718 in 

1992, 41st of the 67 Florida counties and 269. below the state-wide average 

of $19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income, and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem . For example, a retirement community 

may produce less toxic chemical discharges into waterbodies, compared to an 

area where income is earned at a local chemical plant . For Wakulla County, 

an analysis of the sources of income will be discussed below, along with 

the interaction with the ecosystem . 

wakulla County had 11 .1% of the households below the poverty level in 1989, 

which was higher than the State of Florida average of 9.0% . In 1993, the 

unemployment rate was 4 .5 % (relative to a statewide average of 7 .0%), 

indicating a slack labor market . 

WAK.2 Trends in Population, Income and Employment in Wakulla County. 

1980-93 . 

Table 177 shows the trend in key economic variables in Wakulla County from 

1980 through 1993 . Over this interval, resident population increased by 

47 .7% (3 .7% annually), which was greater than the 39 .5 increase for 

Florida as a whole. Population increases that were induced primarily by 

industrial structure (i .e ., job creation) and natural amenities of the 

region place additional pressure on the carrying capacity of both living 

(e .g ., coastal fishery stocks) and non-living natural resources (e .g ., 

beaches) . 

Nominal aggregate personal income increased by 2509. from 1980 to 1993 . 

(Table 177) . Adjusted for inflation, real aggregate personal income 

increased by 99 .6s (7 .6% annually) . Since real income growth outstripped 

the population growth discussed above, the average level of affluence 

increased . This usually is a positive trend for ecosystems since people 

will have the financial resources to reduce negative externalities (e .g ., 

air and water pollution) which often accrue from population growth (Hall, 

1994) . 

209 
GEORGIA 

V 

C:

;` I ., 

l?- 

r 1 

rELocw CREEK ~ 1 ~ . . LAKE JACKSON 

Lake Talqun 

V 

. ~= : . ~ 

t r 

YELLOW CREEK`' 12 ~ 

,, SOPCHOPPY RIVER 

... . OCHLOCKONEE . . 

r :5 ::i' 

j 

,, 

w~ .

ti` 

f 

HLOCKONEE BAY 

OCHLOCKONEE RIVER BASIN WATER QUALITY 03120003 P-R~9 GOOD 

AVERAGE WATER QUALITY ~ THREATENED 

1984-1993 STORET DATA FAIR 

WATERSHED ID NUMBERS LINK MAP TO TABLES POOR 

INDICATES QUALITATIVE ASSESSMENT 0 UNKNOWN 

Figure 15 . Map of Wakulla County, Florida, showing levels of water quality 

and areas of quality testing (Ochlockonee River Basin)[from 

Bureau of Surface Water Management (1994b)] . 

210 
Lake 

LOST 

APALACHEE BAY 

ST. (NARKS RIVER BASIN 

03120001 

AVERAGE WATER QUALITY 

1984-1993 STORET DATA 

WATERSHED ID NUMBERS LINK MAP TO TABLES 

INDICATES QUALITATIVE ASSESSMENT 

WATER QUALITY 

GOOD 

THREATENED 

FAIR 

- POOR 

0 UNKNOWN 

LLOYD CREEK 

Figure 16 . Map of Wakulla County, Florida, showing levels of water quality 

and areas of quality testing (St . Marks River Basin)[from 

Bureau of Surface Water Management (1994b)] . 

211 
Table 177 . Trends in Key Economic Aggregate Variables in Wakulla County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

gmployment3 

1980 10,900 $68,207 $82,775 2,731 

1981 11,000 77,275 85,011 2,769 

1982 11,400 82,942 85,850 2,942 

1983 11,900 92,671 93,043 2,945 

1984 12,400 100,022 96,268 3,025 

1985 12,800 112,427 104,486 3,195 

1986 12,900 127,380 116,223 3,288 

1987 13,100 136,033 119,747 3,428 

1988 13,600 153,948 130,134 3,711 

1989 13,900 171,908 138,635 3,908 

1990 14,400 189,247 144,795 3,986 

1991 14,900 204,247 149,961 4,307 

1992 15,400 219,925 156,753 4,413 

1993 16,100 238,807 164,264 4,581 

Includes earnings, dividends, interest, rent and transfer payments . 

2 Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Wakulla County increased from 2,731 in 1980 to 4,581 

in 1993, a 68% increase . The growth of jobs is stimulated in a region by 

what is known as the export base . Simply put, a region's growth is 

determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region, income to retirees in Florida and injections 

of Federal dollars to sustain military bases such as Eglin Air Force Base 

in Okaloosa County . Through a multiplier process, this export income 

sustains both direct export jobs (e .g ., civilians working for the military) 

and indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in Wakulla County 

grew less rapidly than the measure of county output - real aggregate 

personal income - as local entrepreneurs introduced labor-saving 

technological devices to economize on the rising cost of labor . 

WAK .3 Trends in Various Welfare Measure in Wakulla County , 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing . A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is likely to be more able 

to protect the ecosystem than one which is highly dependent on income 

212 
maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Wakulla County derived 97 .4% of its personal 

income from earnings, retirement and capital income, compared to 98 .2% for 

the whole of Florida. Thus, the county is less likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem. The trends in the components of personal income per capita are 

shown for Wakulla County in Table 178 . 

WAR .4 Industrial Base : Wakulla Countv 

The "industrial base" for Wakulla County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy . The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy . If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., 10%) in an area, 

compared to the same percentage nationally (e .g ., 0 .5°s), assuming the 

Table 178 . Trends in Components of Personal Income in Wakulla County, 

Florida, 1980-93 . 

Per Capita 

Year Income' Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $6,243 $4,408 $159 $12 $960 $704 

1981 7,038 4,850 167 12 1,088 922 

1982 7,299 4,986 154 15 1,197 947 

1983 7,820 5,323 148 17 1,249 1,084 

1984 8,089 5,687 159 9 1,248 986 

1985 8,813 6,206 160 17 1,372 1,058 

1986 9,839 6,991 165 14 1,467 1,202 

1987 10,349 7,497 158 17 1,561 1,116 

1988 11,314 8 , 019 207 15 1,754 1,319 

1989 12,354 8,646 218 12 1,939 1,539 

1990 13,168 9,088 281 15 2,111 1,674 

1991 13,768 9,486 334 26 2,306 1,616 

1992 14,255 9,881 354 37 2,468 1,516 

1993 14,816 10,341 346 29 2,595 1,505 

Source : ._BEA (1995) 

213 
nation consumes all it produces - no imports or exports . This is rather 

simplistic, but it does serve as an indicator of which industries are 

predominately export . This figure, the location quotient (LQ), would be : 

(1) LQ = lOg/ .5$ = 20 

Thus, 95% would be in export or 

(2) 1 - LQ-1 = .95 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 179 shows the main identified export industries and their 

contribution to personal income in Wakulla County . This county depends 

primarily on fishing and manufacturing, and acts as a bedroom community for 

Leon County . The counties' largest employer is Olin Corporation, a 

producer of gun powder . There is also some logging and a small trace of 

tourism in the county economy . Some of the largest individual employers in 

Wakulla County have, from time to time, had negative impacts on the 

ecosystem . For Wakulla County, Table 180 shows the top employers, along 

with the products they produce that may generate conflicts with the 

environment . Products such as chemicals and gun propellants must be 

rigorously controlled or they will reduce water and air quality. In 1993, 

the EPA reported that the companies in Wakulla County discharged 1,017 

pounds of toxic chemicals into surface water (Lester, 1995) . 

WAR .5 Ecosystem-Sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Wakulla County, the industries shown in Table 181 fall 

into this category . 

The Wakulla County economy is heavily based upon the Olin Corporation, 

which produces gun powder . The county also acts as a bedroom community for 

Leon County . All of these economic activities create various kinds of 

waste that is a point or nonpoint discharge into rivers and coastal waters . 

These industries are primarily involved in the export sector and therefore 

are critical to this coastal county . 

WAR .6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of Wakulla County is composed 

of primarily ecosystem-sensitive industries . The remainder are known as 

ecosystem-insensitive industries, which have relatively little impact on 

the environment and are shown in Table 182 

In general, industries such as health services, tourism and retirement have 

a less adverse impact on local ecosystem health than other industries in 

Wakulla County . Over the 1969-93 period, the ecosystem-insensitive 

industries grew more rapidly than the ecosystem-sensitive industries, 

meaning that the recent economic growth is not threatening to the marine 

environment . 

214 
Table 179 . Major Export Industries in Wakulla County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings % of Personal LQ* 

(000) Income 

Fisheries $1,176 .49 15 .87 

Manufacturing 

Food and Kindred Products 1,735 .72 .72 

Petroleum Products 415 .17 .92 

Chemicals D* N/A N/A 

Water Transportation 402 .16 1 .3 

Tour ism (Minor) 

I, Food Stores 2,858 1 .19 1 .1 II 

*LQ = Location quotient . See Text . 

*D = Disclosure 

Source : BEA (1995) 

Table 180 . Top Employers in Wakulla County, Florida and Products Produced, 

1994 . 

Employer Employees 

1 . Olin Corporation, Ball Powder 400 

2 . Wakulla Manor Nursing Home, Health Care 150 

3 . Wakulla County State Bank, Banking 

Sub-Total 600 

Total 4,581 

Percent of Total 13% 

Source : Florida Department of Commerce (1994) 

Table 181 . Ecosystem-Sensitive Industries in Wakulla County, Florida. 

Industry Earnings ($000) 

1 . Manufacturing 22,134 

Food and Kindred Products 

Petroleum Products 

Chemicals 

2 . Water Transportation 402 

Sub-Total 22,536 

Total Earnings (Non-Farm) 238,907 

Percent of Total 90 

Source : BEA (1995) 

215 
Table 182 . Ecosystem-Insensitive Industries in Wakulla County, Florida . 

11 Industry Earnings ($000) 11 

1 . Fisheries 1,176 

2 . Food Stores (tourism) 2,858 

Sub-Total 4,034 

Total Earnings 238,807 

Percent of Total 2% 

Source : Table 179 

WAR .7 Commercial Fishery Landings in Wakulla County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Wakulla County . 

Three categories of fishery products are found : (1) finfish ; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $2 .8 million worth of commercial fishery 

products were landed in Wakulla County at the ex vessel level (Table 183) . 

Finfish and shrimp account for 40% of this value . Among the finfish, black 

mullet was the leading species as measured by quantity and value . Brown 

shrimp, which depends on wetlands during a phase of its life cycle, was the 

dominant shrimp species . Crabs accounted for 60% of the ex vessel value . 

Among the 13 counties in the study area, Wakulla County ranked 7th in the 

ex vessel value of all commercial fishery landings . 

Although the ex vessel value does not include value added in processing and 

distribution, commercial fishing is a relatively important component of the 

economic base of Wakulla County, where aggregate personal income was $ .23 

billion in 1993 . Over the last fourteen years, commercial fishery landing 

has increased by loo while the ex vessel value of the catch has increased 

by 2858 . When adjusted for inflation, the value of landings changed by 

113% (FDNR, 1980) . 

WAK .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently, 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively that engage in saltwater recreational 

fishing in Florida. In Milon and Thunberg (1992), there is some regional 

breakdown embracing the present study area from xernando County north to 

216 
Table 183 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Wakulla County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Black Mullet 763,653 $358,916 .91 

Red Grouper 162,382 285,792 .31 

Gag Grouper 75,847 169,138 .81 

Grunts 168,748 79,311 .56 

Sea Bass 126,980 58,410 .80 

Spotted Sea Trout 16,177 19,412 .40 

Flounder 7,070 12,231 .10 

Gray Snapper 3,877 6,784 .75 

Spot 16,096 6,438 .40 

Porgies 6,415 5,901 .80 

All Others 60,921 41 .051 .65 

Total $1,043,390 .49 

Invertebrates 

Stone Crabs 150,562 $835,362 .92 

Blue Crabs 1,227,580 786,321 .53 

Oysters 51,841 64,282 .84 

All Others 13,250 10 .336 .49 

Total $1,696,303 .78 

Shrimp (Total) 26,806 57,769 .11 

Grand Total $2,797,463 .38 

n 

* State average ex vessel price used . 

Source : FDEP (1994) 

Escambia County . Such regions include both coastal and interior counties . 

These regional averages can be applied to the individual counties as an 

approximation . Bell (1993) has only statewide averages for tourist 

saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

angler for Region I (i .e ., Escambia to Jefferson County) were about 40-50% 

higher than the statewide average. Thus, using the latest study of Bell 

(1993), statewide figures may be conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county . Wakulla County had 4,629 resident anglers purchasing a one-year 

fishing license. It should be pointed out that purchase of a license in a 

county does not ensure that one is a resident of that county, but informal 

conversations with Florida Dept . of Environmental Protection personnel 

suggest little bias is associated with that assumption . Nonresidents are 

those that purchased saltwater fishing licenses in non-coastal counties . 

Such licenses were pro-rated to coastal counties in close geographical 

217 
proximity to each county, using personal judgment . This is shown in Table 

184 where nonresidents are shown in the second column . Finally, tourists 

must purchase a license, and the number is shown for the counties in the 

study area . This may underestimate tourist saltwater anglers since 

tourists may buy a license in an interior county and use it in one of the 

coastal counties . 

Table 185 shows an estimate of fishing effort (in days) for resident/ 

nonresident and tourist anglers . This was done by using the days fished 

per year by an angler and multiplying by the number of estimated anglers in 

Table 184 . The Milon and Thunberg (1992) and Bell (1993) estimates are 

shown as nine and four days (per year) for residents and tourist anglers, 

respectively . Wakulla County showed a fishing effort of 81,406 days . 

Finally, Table 186 is derived from Table 184 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $5,902,377 in Wakulla County in 1993-94 . Many assumptions 

were made to arrive at these estimates, however, these figures are believed 

to indicate an order of magnitude and relative ranking, and may actually be 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . Multiplier effects of nonresidents and 

tourists were not considered . 

Table 184 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents Nonresident2 Tourist 3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11 .685 6 .926 .5,312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident nne year saltwater fishing license from interior counties . 

' Non-resident (out of state) saltwater fishing licenses for one year ; 

seven days and three days . 

218 
Table 185 . Estimated Number of Saltwater Recreational Days 

(Fishing Effort) in the Thirteen County Study Area, 

1993-94 . 

County Resident + 

Nonresident) 

TouristZ Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167 .499 21"248 188 .747 

Total 952,605 377,480 1,330,085 

9 days per angler year and Table 184 . See Milon and Thunberg (1992) . 

4 days per angler year and Table 184 . See Bell (1993) . 

Table 186 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

TouristZ Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783,640 1,528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8,890 .475 2,337,280 11,227,755 

Total $50,562,157 $41,522,800 $92,038,955 

Figured in Table 184 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Figures in Table 184 multiplied by $440 .00 per angler . 

219 
If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing . There is no organized market for recreational 

fisheries since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of value for Wakulla County can be computed as follows : 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 5,958 = $22 million 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 6,946 = $1 .35 million . 

Thus, saltwater recreational fishing generates $3 .55 million per year in 

Wakulla County with a capitalized value of $118 million using a 3% discount 

rate (i .e ., $3 .55 million = .03) . 

WAK .9 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing. The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property, where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets, such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated. This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 187 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch. 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price peopre are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

220 
Table 187 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows (at the means) : 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of- the marginal acre of salt marsh to the commercial fisheries of 

west Florida at $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Wakulla County has 18,600 acres of salt 

221 
marsh (NOAA, 1991), which would be worth $98 .8 million ($5,316 x 18,600) 

in fishery production alone . Negative ecological factors such as 

dredging or oil spills would threaten the value provided by Wakulla 

County wetlands . 

WAR .10 Non-Livina Resources : Saltwater 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well-organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects. First, they draw 

tourists into the local community, thereby becoming an important component 

of the economic base discussed earlier . Second, beaches provide user value 

to residents and tourists . Although a beach's user value is not traded in 

a traditional market for services, it can still be measured through such 

techniques as the travel cost method (TCM) and/or the contingent value (CV) 

method . Saltwater beaches are an integral part of the marine ecosystem 

which can be damaged by erosion, debris, oil spills and other toxic 

discharges into coastal waters . Wakulla County does not have any major 

beach areas, therefore, no value to the economy can be calculated . 

WAR .11 Man-Made Resources : Water Dependent 

As discussed above, many economic activities, such as fisheries and 

beaches, in the marine ecosystem are water-dependent . To take advantage of 

the marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 188 

identifies ecological resources that are an asset to Wakulla County and 

induce a considerable level of economic activity in the region . Table 189 

is an inventory of these water-dependent facilities in Wakulla County . 

Piers, boardwalks and jetties facilitate bank recreational fishing, beach 

use and other outdoor recreational activities . 

As an outdoor recreational activity, boating makes use of common property 

water resources . Expressed in 1994 dollars, Bell (1995) found that the 

user value per day is worth $3 .56 more if a marina is used (i .e ., $5 .02 

less $1 .48) rather than a boat ramp . These are Florida-wide values and may 

or may not be good estimates for Wakulla County, but are used for purposes 

of illustration . 

Wakulla County has 14 saltwater boat ramp lanes and 550 wet slips and dry 

racks as shown in Table 189. The number of private docks from which to 

launch pleasure craft is unknown. Combining data from Bell et al . (1982) 

and Bell (1995), the annual user value from boating in the Gulf of Mexico 

off Wakulla County is estimated and shown in Table 190 . This value is 

about $0 .3 million. 

Recreational boating in marine waters is rapidly growing in Wakulla County . 

Such boating can affect coastal water quality (e .g ., inadequate pumping out 

facilities) as well as adding user value to those using coastal water 

222 
Table 188 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Wakulla County, Florida. 

Resource/Activity Spending 

(Millions) 

User Value 

Per Year' 

Asset Value 

(Millions )2 

Commercial Fishing $2 .83 N/A N/A 

Recreational Fishing $5 .94 $3 .555 $1185 

Saltwater Marshs N/A .2p7 s 98 .8s 

Saltwater Beaches __s __s __s 

Marine Boating' N/A $ .305' $10 .2' 

Nonmarket value per year 6 See text for discussion 

#1 divided by .03 = Asset Value ' See Table 190 

Table 183, ex vessel price 

Table 186, retail price 

To commercial fishery landings only 

Table 189 . An Inventory of Marine-Related Recreational Facilities 

in Wakulla County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Beaches 

1 . Number 6 

2 . Length (all) (miles) 1 .4 

3 . Area (all) (sq . ft .) 143,700 

Fishing 

1 . Piers 

a. Number -- 

b. Length (all) (LFT)* -- 

2 . Boardwalks/Catwalks 

a . Number 1 

b . Length (all) (LFT)* 2,110 

3 . Jetties 

a. Length (all) (LFT)* -- 

Boating 

1 . Boat Ramps 

a . Number 13 

b . Total Lanes 14 

2 . Marinas 

a . Total 6 

b . Slips/Moorings 359 

c . Dry Storage 191 

*LFT = Linear Feet 

Source : bureau of Recreation and Parks (1995) 

223 
Table 190 . Estimation of the Annual User Value for Saltwater 

Boating Off Wakulla County, Florida, 1993-94 . 

Facility 

Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

1 . Marinas 

$110,152 = $5 .021 x 3,6092 x .193 x 32' 

2 . Boat Rams 

$114,518 = $1 .481 x 3,609 x .67' x 32 

3 . Private pocks 

$81,165 = $5 .025 x 3,609 x .14 x 32 

Total Annual User Value = $305,835 

*Asset Value = 305,835 = .03 = $10 .2 million 

Bell (1995), Florida-wide value 

Z FDEP (1992), Wakulla County 

Bell et al . (1982), northwest Florida 

° Bell (1995), Wakulla County 

5 Assumed $/day same for marinas and private docks 

resources . From the FDEP (1983-1992) and Bell (1995) studies, pleasure 

boat registrations in Wakulla County grew as follows, with projected (P) 

numbers included : 

1983 1,420 

1984 1,663 

1985 1,752 

1986 1,785 

1987 1,845 

1988 1,991 

1989 2,126 

1990 2,157 

1991 2,243 

1992 2 .874 

1993 3,321 

1994 3,609 

2000 3,866 (P) 

2005 4,620 (P) 

2010 5,521 (P) 

WAK.12 Water Quality, the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is 

manifested in the water quality surrounding the region . Florida's major 

surface water quality problems come from urban stormwater runoff, 

agricultural runoff, domestic wastewater, industry wastewater and 

hydrological changes such as draining and filling wetlands . 

224 
There are three sources of information on local water quality surrounding 

Wakulla County . First, the Federal Water Pollution Control Act requires 

the state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Wakulla County . 

Two indices are used in the 305(b) report for measuring surface water 

quality : the stream water quality index (wQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen-demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity . The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality . 

The geographical analysis of 

basins, but this analysis is 

because of this study's emph~ 

ecosystem interacts with the 

have selected the Ochlocknee 

summary of the current state 

area . 

the 305(b) report is formulated by river 

restricted to bays and some critical rivers 

Isis on the marine environment and how this 

economy of the area . For Wakulla County, we 

River and St . Marks River Basins for a brief 

of water quality in this region of the study 

The Ochlocknee River originates in Georgia and enters Florida north of 

Tallahassee . The river enters Wakulla County near Wakulla . The overall 

water quality in this basin is good . The Lower Ochlocknee and Sopchoppy 

Rivers both traditionally have very good water quality. There are 

relatively few pollution sources entering the water in this basin and, 

because of the relatively low county population, there appear to be no 

immediate threats to it . The St . Marks River begins in Georgia and drains 

into the Gulf of Mexico . The river widens and clarity begins to improve 

near the Wakulla County line due to water input from natural springs . The 

Wakulla River meets the St . Marks approximately three miles north of the 

Gulf of Mexico . Both rivers have very good water quality, and in some 

areas are protected by the St . Marks National Wildlife Refuge . The lower 

part of the St . Marks River, however, has in the past had problems with 

water quality. There are pumping stations for oil barges, a few small 

marinas, which have seen some oil spills in the past, and there are 

sediments coated with oil in the area . The lower portion of the Wakulla 

River is now being threatened by increased development and discharge from 

Olin Corporation into Boggy Branch . The WQI and TSI for selected areas are 

listed in Table 191. 

225 
Table 191 . Water Quality Indices for Selected Areas of Wakulla 

County, Florida . 

Water Areas: Ochlocknee River Basin Water Quality Indices* 

Water Body Type : Estuary WOI TSI 

1 Ochlocknee Bay -- 47 

Water Body Type : Stream 

2 Ochlocknee River 26 -- 

3 Buckhorn Creek 22 -- 

4 Syprett Creek 42 -- 

5 Otter Creek 46 -- 

7 Monkey Creek 42 -- 

8 Smith Creek 34 -- 

9 Sopchoppy River 22 -- 

Water Areas : St . Marks River 

Water Body Type : Stream 

4 Big Boggy Branch 41 --

5 Wakulla River 19 --

10 St . Marks River 34 -- 

* Higher values indicate lower water quality 

The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . Table 192 indicates that in 

1994, a single company, Olin Ordnance, discharged toxic substances in and 

around the surface water of Wakulla County . These discharges may be highly 

variable from year to year . 

Shellfish harvesting has been closed in 1,592 acres and conditional in 

6,042 acres in the Ochlocknee Bay and Wakulla County . This means that 300 

of the shellfish beds have been closed due to poor water quality. 

Table 192 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Wakulla County, Florida in 1994 . 

Company SIC Discharge Main' 

1 . Olin Ordnance 2,892 1,017 Nitroglycerin 

Leading chemical released based on pounds . 

A.Source: EPA Toxic Release Inventory, unpublished data, 1994 . 

226 
County Name : Walton . Florida 

Socioeconomic Comflonents and Processes Occurring in the 

Northeastern Gulf of Mexico Coastal and Marine Ecosystem 

WAL .1 Introduction 

Walton County is located in the central section of the study area, which 

ranges from Escambia to Citrus County in northwestern Florida (Figures 17 

and 18) . It contains 1,058 square miles of land, ranking it 11th among the 

67 counties in Florida. In 1990, Walton County had a population of 27,759, 

ranking it 44th among Florida's counties . The population density was 29 

people per square mile in 1990, a ranking of 53rd in Florida. Walton 

County has an median age of 37 .8 years, somewhat higher than the Floridawide median of 36 .4 years . 

The population of Walton County had a per capita income of $13,531 in 1992, 

51st of the 67 Florida counties and 32% below the state-wide average of 

$19,797 . This income was derived primarily from earnings from local 

industries, return on investment (rent, interest, dividends), retirement 

income, and transfer payments (e .g ., AFDC, food stamps, etc .) . The sources 

of income for a county may lead to a characterization of how that area 

interacts with the natural ecosystem . For example, a retirement community 

may produce less toxic chemical discharges into waterbodies compared to an 

area where income is earned at a local chemical plant . For Walton County, 

an analysis of the sources of income will be discussed below, along with 

the interaction with the ecosystem . 

Walton County had 15 .1% of the households below the poverty level in 1989, 

which was higher than the State of Florida average of 9 .0% . In 1993, the 

unemployment rate was 5 .8$ (relative to a statewide average of 7 .0%) 

indicating a slack labor market . 

WAL .2 Trends in Population. Income and Mrmloyment in Walt 

1980-93 . 

Table 193 shows the trend in key economic variables in Walton County from 

1980 through 1993 . Over this interval, resident population increased by 

41 .4 (3 .2% annually), which was comparable to the 39 .5% increase for 

Florida as a whole . Population increases that were induced primarily by 

industrial structure (i .e ., job creation) and natural amenities of the 

region place additional pressure on the carrying capacity of both living 

(e .g ., coastal fishery stocks) and non-living natural resources (e .g ., 

beaches) . 

Nominal aggregate personal income increased by 233 from 1980 to 1993 (Table 

193) . Adjusted for inflation, real aggregate personal income increased by 

90% (6 .9% annually) . Since real income growth outstripped the population 

growth discussed above, the average level of affluence increased . This 

usually is a positive trend for ecosystems since people will have the 

financial resources to reduce negative externalities (e .g ., air and water 

pollution) which often accrue from population growth (Hall, 1994) . 

227 
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CHOCTAWHATCHEE BAY BASIN 

03140102 

WATER QUALITY 

GOOD 

~ THREATENED AVERAGE WATER QUALITY 

~ 

FAIR 1984-1993 STORET DATA 

T POOR WA ERSHED 

INDICATES 

ID NUMBERS 

QUALITATIVE 

LINK 

ASSESSMENT 

MAP TO TABLES 

- O UNKNOWN 

Figure 17 . Map of Walton County, Florida, showing levels of water quality 

and areas of quality testing (Choctawhatchee Bay Basin)[from 

Bureau of Surface Water Management (1994b)] . 

228 
BRANCH 

LAKE POWELL 

ST. ANDREWS 

CREEK 

l 

GULF OF MEXICO ~ qN7HER SWAMP 

ST. ANDREWS BAY BASIN 

03140101 

AVERAGE WATER QUALITY 

1984-1993 STORET DATA 

WATERSHED ID NUMBERS LINK MAP TO TABLES 

" INDICATES QUALITATIVE ASSESSMENT 

WATER QUALITY 

GOOD 

THREATENED 

Q FAIR 

_ POOR 

UNKNOWN 

I 

Figure 18 . Map of Walton County, Florida, showing levels of water quality 

and areas of quality testing (St . Andrews Bay Basin)[from 

Bureau of Surface Water Management (1994b)] . 

229 
Table 193 . Trends in Key Economic Aggregate Variables in Walton County, 

Florida, 1980-93 . 

Year Resident 

Population 

Personal 

Incomes 

(nominal) 

(000) 

Real 

Personal 

Income 

(000) 

gmployment3 

1980 21,500 $128,838 $156,375 6,052 

1981 21,900 146,630 161,309 6,126 

1982 22,600 160,964 166,802 6,109 

1983 23,100 177,162 177,873 6,389 

1984 24,000 203,246 195,617 7,321 

1985 24,900 224,020 208,197 8,374 

1986 25,700 245,483 223,981 8,793 

1987 26,200 254,699 224,207 9,174 

1988 26,600 277,526 234,595 9,569 

1989 27,200 303,526 244,779 9,978 

1990 27,800 333,677 255,300 10,658 

1991 28,600 368,994 270,921 10,787 

1992 29,500 398,400 283,963 11,160 

1993 30,400 429,411 297,170 11,652 

Includes earnings, dividends, interest, rent and transfer payments . 

Deflated by CPI where 1982-84 = 100 . 

Full and part-time wages and salary and proprietors' employment . 

Source : BEA (1995) 

The number of jobs in Walton County increased from 6,052 in 1980 to 11,652 

in 1993, a 93% increase . The growth of jobs is stimulated in a region by 

what is known as the export base . Simply put, a region's growth is 

determined by its ability to derive "export income" from outside the 

region . In Florida, such income may come from physically exporting goods 

such as electronic components or fish, but it is more likely to come from 

tourists visiting the region, income to retirees in Florida and injections 

of Federal dollars to sustain military bases such as Eglin Air Force Base 

in Okaloosa County . Through a multiplier process, this export income 

sustains both direct export jobs (e .g ., civilians working for the military) 

and indirect or support jobs for those in export industries (e .g ., barber 

shops, grocery stores and shopping malls) . Job growth in walton County 

grew less rapidly than the measure of county output - real aggregate 

personal income - as local entrepreneurs introduced labor-saving 

technological devices to economize on the rising cost of labor. 

WAL .3 Trends in various welfare Measures in Walton County, 1980-93 

Per capita income is an overall measure of how well off a community is in 

economic terms, but components of personal income are sometimes more 

revealing . A county that depends on earnings, retirement income and income 

from capital (i .e ., dividends, interest and rent) is more likely to be able 

to protect the ecosystem than one which is highly dependent on income 

230 
maintenance and unemployment insurance, since the former is taxable while 

the latter is not . In 1993, Walton County derived 97% of its personal 

income from earnings, retirement and capital income, compared to 98 .2% for 

the whole of Florida . Thus, the county is less likely to tax residents, 

compared to the state as a whole, to protect threats to the marine 

ecosystem. The trends in the components of personal income per capita are 

shown for Walton County in Table 194 . 

WAL .4 Industrial Base : walton County 

The "industrial base" for Walton County refers to the industries that are 

primarily export in nature as discussed above . These industries drive the 

local economy . The rest of the industries in the county are "non-export 

industries" that depend, for the most part, on what happens inside the 

region . These are called non-basic industries . For small areas such as 

counties, agriculture, fisheries, mining, manufacturing, transportation and 

service-oriented industries for tourists are likely to be export industries 

while wholesale and retail trade, finance, services and local government 

are likely to be non-basic industries . No data are available on exports 

from a county ; however, location quotients and expert judgment can be used 

to identify such industries with some accuracy . If a given county is 

highly specialized relative to the nation in the production of a particular 

commodity, the product is presumed to be an export item (e .g ., automobiles 

from Detroit) . The specialization is measured by computing the percentage 

of personal income generated by an industry (e .g ., 10%) in an area, 

compared to the same percentage nationally (e .g ., 0 .50), assuming the 

Table 194 . Trends in Components of Personal Income in Walton County, 

Florida, 1980-93 . 

Per Capita 

Year Incomes Earnings Income Unemployment Retirement Dividends, 

(Nominal) Maintenance Interest, 

Rents 

1980 $6,004 $3,563 $164 $18 $1,415 $843 

1981 6,710 3,866 173 19 1,653 999 

1982 7,128 3,965 176 23 1,880 1,084 

1983 7,657 4,240 180 26 2,020 1,191 

1984 8,470 4,899 172 16 2,060 1,325 

1985 8,993 5,166 164 27 2,259 1,377 

1986 9,552 5,479 166 30 2,313 1,564 

1987 9,704 5,616 165 27 2,417 1,479 

1988 10,434 6,003 190 30 2,682 1,528 

1989 11,159 6,352 204 27 2,889 1,688 

1990 11,999 6,804 237 34 3,189 1,734 

1991 12,889 6,973 286 48 3,659 1,925 

1992 13,527 7,395 374 58 3,960 1,740 

1993 14,128 7,741 355 53 4,214 1,764 

Source : SEA (1995) 

231 
nation consumes all it produces - no 

simplistic, but it does serve as an 

predominately export . This figure, 

(1) LQ = 10%/ .5% = 20 

Thus, 95% would be in export or 

(2) 1 - L4-1 = .95 

imports or exports . This is rather 

indicator of which industries are 

the location quotient (LQ), would be : 

In reality, any manufacturing industries with a high LQ would most likely 

export all of its product outside the county (e .g ., Olin Company makes 

gunpowder in Wakulla County and sells none locally) . 

Table 195 shows the main identified export industries and their 

contribution to personal income in Walton County . This county depends 

primarily on tourism, retirement and manufacturing for its economic 

survival . Some of the largest individual employers in Walton County have, 

from time to time, had negative impacts on the ecosystem . Table 196 shows 

the top ten employers in Walton County, along with the products they 

produce that may generate conflicts with the environment . Products such as 

lumber and wood, apparel and other manufacturing must be rigorously 

controlled or they will reduce water and air quality . In 1992, the EPA 

reported that the companies in Walton County discharged 10 pounds of toxic 

chemicals into surface water (Lester, 1995) . 

WAL .S Ecosystem-sensitive Industries 

Those industries that, if left unchecked, may be a threat to environmental 

quality and ecosystem health are referred to as ecosystem-sensitive 

industries . For Walton County, the industries shown in Table 197 fall into 

this category . 

The Walton County economy is heavily based upon manufacturing and tourism . 

The county's largest employer is a food processing plant . All of these 

economic activities create various kinds of waste that is a point or 

nonpoint discharge into rivers and coastal waters . These industries are 

primarily involved in the export sector and therefore are critical to this 

coastal county . 

WAL .6 Ecosystem-Insensitive Industries 

As indicated by earnings, the economic base of Citrus County is primarily 

composed of ecosystem-insensitive industries, those which have relatively 

little impact on the environment . These are shown in Table 198 . 

In general, industries such as tourism and retirement have a less adverse 

impact on local ecosystem health than other industries in Walton County . 

Over the 1969-93 period, the ecosystem-insensitive industries grew faster 

than the ecosystem-sensitive industries, meaning that the growth of the 

economy for Walton County is not a threat to the natural resources of the 

county . 

232 
Table 195 . Major Export Industries in Walton County, Florida and Their 

Contribution to Aggregate Personal Income, 1993 . 

Industry Earnings % of Personal LQ* 

(000) Income 11 

( Tourism 

Construction $15,691 3 .64 1 .02 

Real Estate 4,400 1 .02 1 .42 

Manufacturing 

Lumber/Wood 1,259 .29 .68 

Transportation Equipment 1,511 .35 .41 

Apparel 1,896 .44 1 .27 

Food and Kindred Products N/A N/A N/A 

Tourism 

Food Stores 8,234 1 .91 1 .73 

Eating and Drinking Places 9,097 2 .11 1 .30 

Hotels 22,014 5 .12 7 .48 

*LQ = Location quotient . See Text . 

Source : BEA (1995) 

Table 196 . Top Ten Employers in Walton County, Florida and Products 

Produced, 1994 . 

Employer Employees 

1 . Showell Farms of Florida, Poultry Processing 800 

2 . Sandestin Beach Resort, Resort 500 

3 . Topsail Beach and Racquet Resort, Resort 150 

4 . Walton Regional Hospital, Health Care 140 

5 . Seascape Resort, Resort 120 

6 . Walton County Convalescent Center, Health Care 115 

7 . Wal-Mart, Retail Sales 115 

8 . Professional Products, Orthopedic wear 110 

9 . Continental Apparel, Ladies wear 106 

10 . CHELCO, Electric Utility 99 

Sub-Total 2,255 

Total 11,652 

Percent of Total 190 

Source : Florida Department of Commerce (1994) 

233 
Table 197 . Ecosystem-Sensitive Industries in Walton County, Florida. 

Industry Earnings ($000) 

1 . Manufacturing $26,126 

Food and Kindred Products 16,000* 

Apparel and Other Textiles 1,558 

Lumber and Wood 1,259 

Transportation Equipment 1,511 

Sub-Total $46,454 

Total Earnings (Non-Farm) $425,192 

Percent of Total 10 .90 

Source : BEA (1995) 

Table 198 . Ecosystem-Insensitive Industries in Walton County, Florida. 

II Industry Earnings ($000) II 

2 . Tourism 

Food Stores 

Eating and Drinking Places 

Hotels 

Sub-Total 

Total Earnings 

Percent of Total 

$8,234 

9,097 

$39,345 

$425,192 

9 .2% 

Source : Table 195 

WAL .7 Commercial Fishery Landings in Walton County 

Commercial fishery products are landed at the ex vessel level . At this 

level, processors, wholesalers and dealers purchase various species from 

the fishermen for food and industrial (e .g ., fish meal) uses . Thus, the ex 

vessel value only reflects what the fishermen receive for their catch and 

not the value added in processing and distribution . All landings discussed 

here refer to marine or saltwater fisheries products caught somewhere in 

the Gulf of Mexico and landed for sale in Walton County . 

Three categories of fishery products are found : (1) finfish; (2) 

invertebrates (e .g ., crabs, lobsters, oysters) and (3) shrimp . It has been 

estimated that over 90% of commercially important species in the Gulf of 

Mexico are estuary-dependent during some part of their life . Wetlands 

habitat is thus important to the continued viability of Florida's 

fisheries . In 1994, about $87,000 worth of commercial fishery products 

were landed in Walton County at the ex vessel level (Table 199) . Finfish 

and shrimp account for 84s of this value . Among the finfish, shark and 

black mullet were the leading species landed as by value and quantity, 

respectively . Brown shrimp, which depends on wetlands during a phase of 

its life cycle, was the dominant shrimp species . Among the 13 counties in 

the study area, Walton County ranked 12th in the ex vessel value of all 

commercial fishery landings . 

234 
Table 199 . Ex Vessel Landings and Value of Commercial Fishery 

Landings in Walton County, Florida, 1994 . 

Quantity (lb .) Total Value 

Finfish 

Shark Fins 2,357 $43,651 .64 

Black Mullet 6,388 3,002 .36 

Flounder 954 1,650 .42 

Spotted Seatrout 917 1,100 .40 

Silver Mullet 474 170 .64 

Other Snapper 69 109 .71 

Triggerfish 96 88 .32 

Gag Grouper 39 86 .97 

Porgies 58 53 .36 

Misc . Food Fish 3 1 .77 

All Others 16 1 .58 

Total $49,917 .06 

Invertebrates 

Blue Crabs 14,747 $9,562 .73 

Oysters 2,973 3,686 .52 

Spanish Lobster 156 269 .88 

Squid 11 4 .07 

Total $13,523 .20 

Shrimp (Total) 12,111 23 .932 .95 

Grand Total 87,373 .21 

* State average ex vessel price used . 

Source : FDEP (1994) 

Although the ex vessel value does not include value added in processing 

and distribution, commercial fishing is a relatively small component of the 

economic base of Walton County, where aggregate personal income was $429 

million in 1993 . Over the last fourteen years, commercial fishery landing 

has decreased by 55% while the ex vessel value of the catch has increased 

by 64% . When adjusted for inflation, the value of landings changed by 54% . 

(FDNR, 1980) . 

WAL .8 Recreational Fishing 

Recreational fishing data are not collected on a county level . Recently, 

Milon and Thunberg (1992) and Bell (1993) estimated economic parameters for 

residents and tourists, respectively, that engage in saltwater recreational 

fishing in Florida . In Milon and Thunberg (1992), there is some regional 

breakdown embracing the present study area from Hernando County north to 

Escambia County . Such regions include both coastal and interior counties . 

As an approximation, these regional averages can be applied to the 

individual counties . Bell (1993) has only statewide averages for tourist 

235 
saltwater anglers, which are also used as an approximation . In an earlier 

study, Bell et al . (1982) found that expenditures and days per tourist 

angler for Region I (i .e ., Escambia to Jefferson County) were about 40-50% 

higher than the statewide average . Thus, using the latest study of Bell 

(1993), statewide figures may be conservative . 

Construction of an estimate of the number of anglers, fishing days (i .e ., 

fishing effort) and fishing expenditures by county in the present study 

area started with the 1993-94 saltwater fishing licenses sold in each 

county. Walton County had 1,531 resident anglers purchasing a one-year 

fishing license . It should be pointed out that purchase of a license in a 

county does not ensure that one is a resident of that county, but informal 

conversations with Florida Dept . of Environmental Protection personnel 

suggest little bias is associated with that assumption . Nonresidents are 

those that purchased saltwater fishing licenses in non-coastal counties . 

Such licenses were pro-rated to coastal counties in close geographical 

proximity to each county, using personal judgment . Finally, tourists must 

purchase a license, and the number is shown for the counties in the study 

area . This may underestimate tourist saltwater anglers since tourists may 

buy a license in an interior county and use it in one of the coastal 

counties . 

Table 200 shows the estimated number of fishermen in each of the counties 

within the study area . Then, Table 201 shows an estimate of fishing effort 

(in days) for resident/ nonresident and tourist anglers . This was done by 

using the days fished per year by an angler and multiplying by the number 

of estimated anglers in Table 200 . The Milon and Thunberg (1992) and Bell 

(1993) estimates are shown as nine and four days (per year) for residents 

and tourist anglers respectively . Walton County showed a fishing effort of 

21,164 days . 

Finally, Table 202 is derived from Table 200 using the Milon and Thunberg 

(1992) and Bell (1993) estimates of annual saltwater fishing expenditures 

per angler of $477 .70 and $440 .00 for residents and tourists, respectively . 

The calculations indicate that saltwater recreational fishermen spent 

approximately $1,528,852 in Walton County in 1993-94 . Many assumptions 

were made to arrive at these estimates, however, these figures are believed 

to indicate an order of magnitude and relative ranking, and may actually be 

conservative . That is, it is not surprising that Bay (Panama City) and 

Citrus (Crystal River) counties are the top two counties for saltwater 

recreational fishing expenditures . Multiplier effects of nonresidents and 

tourists were not considered . 

If this fishery were damaged due to pollution or other adverse ecological 

factors, it would be important to know the nonmarket or user value of 

recreational fishing. There is no organized market for recreational 

fisheries, since they are common property resources . Using the contingent 

value (CV) method, Bell et al . (1982) have estimated the per day value of 

saltwater recreational fishing in northwest Florida at $41 .70 and $48 .67 

for residents and tourists, respectively (in 1994 dollars) . The annual 

flow of vague for Walton County can be computed as follows : 

236 
Table 200 . Estimated Number of Recreational Saltwater Fishermen in 

the Thirteen County Study Area, 1993-94 . 

County Residents NonresidentZ Tourist3 

Escambia 11,004 148 6,356 

Santa Rosa 6,863 148 4,121 

Okaloosa 9,622 148 12,691 

Walton 1,383 177 1,781 

Bay 13,265 1,349 25,172 

Gulf 1,967 1,349 4,919 

Franklin 1,793 1,273 11,450 

Wakulla 4,629 1,329 6,946 

Jefferson 250 1,327 271 

Taylor 4,583 2,176 9,360 

Dixie 2,892 5,191 2,993 

Levy 6,447 7,921 2,998 

Citrus 11 .685 6,926 5"312 

Total 76,383 29,462 94,370 

Resident one year saltwater fishing license . 

Resident one year saltwater fishing license from interior counties . 

Non-resident (out of state) saltwater fishing licenses for one year ; 

seven days and three days . 

Table 201 . Estimated Number of Saltwater Recreational Days 

(Fishing Effort) in the Thirteen County Study Area, 

1993-94 . 

County Resident + 

Nonresidents 

Tourist2 Total 

Escambia 100,368 25,424 125,792 

Santa Rosa 63,099 16,484 79,583 

Okaloosa 87,930 50,764 138,694 

Walton 14,040 7,124 21,164 

Bay 131,526 100,688 232,214 

Gulf 29,844 19,676 49,520 

Franklin 27,594 45,800 73,394 

Wakulla 53,622 27,784 81,406 

Jefferson 14,193 1,084 15,277 

Taylor 60,831 37,440 98,271 

Dixie 72,747 11,972 84,719 

Levy 129,312 11,992 141,304 

Citrus 167 .499 21"248 188,747 

Total 952,605 377,480 1,330,085 

9 days per angler year and Table 200 . See Milon and Thunberg (1992) . 

4 days per angler year and Table 200 . See Bell (1993) . 

237 
Table 202 . Estimated Expenditures by Saltwater Recreational 

Fishermen in the Thirteen County Study Area, 1993-94 . 

County Resident + 

Nonresident) 

Tourist Z Total 

Escambia $5,327,310 $2,796,640 $8,123,950 

Santa Rosa 3,349,154 1,813,240 5,162,394 

Okaloosa 4,667,129 5,584,040 10,251,169 

Walton 745,212 783 640 1 528,852 

Bay 6,981,108 11,075,680 18,056,788 

Gulf 1,584,053 2,164,360 3,748,413 

Franklin 1,464,628 5,038,000 6,502,628 

Wakulla 2,846,137 3,056,240 5,902,377 

Jefferson 753,333 119,240 872,573 

Taylor 3,228,774 4,118,400 7,347,174 

Dixie 3,861,249 1,316,920 5,178,169 

Levy 6,863,593 1,319,120 8,182,713 

Citrus 8 .890 .475 2 .337 .280 11 .227,755 

Total $50,562,157 $41,522,800 $92,038,955 

Figures in Table 200 multiplied by $477 .70 per angler per year . See 

Milon and Thunberg (1992) . 

Z Figures in Table 200 multiplied by $440 .00 per angler . 

(Value/day) x (days/angler) x (# Anglers) : 

$41 .70 x 9 x 1,531 = $ .57 million 

(Value/day) x (days/angler) x (# Anglers) : 

$48 .67 x 4 x 1,781 = $ .35 million . 

Thus, saltwater recreational fishing generates $0 .92 million per year in 

Walton County with a capitalized value of $307 million using a 3% discount 

rate (i .e ., $ .92 million = .03) . 

WAL.9 Fisheries and Wetlands 

Wetlands provide the carrying capacity for many fishery stocks . The main 

link between estuarine wetlands and marine life is through detrital export 

rather than wetlands for grazing. The literature indicates few attempts to 

link statistically marine fishery catch with estuarine wetlands . Attempts 

by others have suggested such a link, but in many cases failed to consider 

fishing effort . For the most part, estuarine wetlands are quasi-common 

property where actual owners cannot capture the implied rental value of 

such wetlands . This produces a market failure and a great incentive to 

convert wetlands to uses consistent with organized markets, such as 

residential development and agricultural use . Although estuarine wetlands 

perform many and varied functions useful to society, the lack of a market 

238 
for such services produces a conflict between the owners and the general 

public . One important contribution is to stimulate such a market where the 

economic value of an estuarine wetland acre can be estimated . This 

establishes a monetary rationale for government purchase or intervention in 

preserving wetlands . Such functions and estimated values of wetlands are 

shown in Table 203 . 

Bell (1989) employed the marginal productivity theory of estuarine wetland 

valuation to the west coast of Florida . This theory looks at the 

incremental contribution of estuarine wetlands to the marine fishery catch . 

It is recognized that estuarine wetlands together with fishing effort 

produce a marine fishery catch . The marginal product of an acre of 

estuarine wetlands, holding all other factors constant, is valued by the 

price people are willing to pay for the fishery product . Since this 

marginal value can flow into perpetuity, one may estimate the capitalized 

value of this flow by dividing by the discount rate . In 1984, ninety-five 

percent of the value of commercial fishery landings on Florida's west coast 

were estuarine-dependent . A production function was estimated for eight 

estuarine-dependent species including blue crab, grouper, red snapper, 

oyster, spiny lobster, shrimp and black mullet . The result indicated a 

strong statistical link between catch and fishing effort as it interacts 

with salt marsh land . This link was established using a salt marsh time 

series over the 1952-1976 period on Florida's west coast for seven of the 

eight species, with grouper being the only exception to the empirical 

results . The value of the marginal products (1994 dollars) for an acre of 

saltwater marsh was as follows : (at the means) 

Blue Crab $ .37 

Stone Crab .37 

Spiny Lobster 1 .31 

Red Snapper 10 .60 

Oyster .69 

Black Mullet 3 .41 

Shrimp 10 .60 

All other species 3 .10 

Total $30 .29 

Capitalizing this flow into perpetuity at a discount rate of 3% yields a 

value of the marginal acre of salt marsh to the commercial fisheries of 

west Florida of $1,010 at the ex vessel level . The value of the average 

acre for saltwater marsh is $5,316 (i .e ., marginal value divided by its 

production elasticity of 0 .19) . Walton County has 2,700 acres of salt 

marsh (NOAA, 1991), which would be worth $14 .3 million ($5,316 x 2,700) in 

fishery production alone . Negative ecological factors such as dredging or 

oil spills would threaten the value provided by wetlands off the shore of 

Walton County . 

WAL .10 Non-Living Resources : Saltwater Beaches 

As in the case of recreational fisheries and wetlands discussed earlier, 

beaches do not have well organized markets for their recreational services . 

As with fisheries, beaches are common property resources . However, beaches 

provide a resource that produces two economic effects . 

239 
Table 203 . Economic Value of Wetlands . 

Wetland Function Value 

($/acre/year) 

Capitalized Value 

($/acre at 

5% discount rate) 

Flood conveyance $191 $3,820 

Erosion, wind, and wave 

barriers $0 .44 $9 

Flood storage N/A N/A 

Sediment replenishment N/A N/A 

Fish and shellfish habitat $32, $66 $700-$1,320 

Waterfowl habitat $167 $3,340 

Mammal and reptile habitat $12 $240 

Recreation $6, $25, $76, $120, $500, $1,520, 

$70 $1,400 

Water supply N/A N/A 

Timber N/A N/A 

Historic and archaeological 

use $323 $6,480 

Educational and research 

use $6 $120 

Water quality improvement N/A N/A 

Source : Robert Anderson and Mark Rockel, 1991, Economic Valuation of Wetlands, 

Discussion Paper No . 065, American Petroleum Institute, Washington, D.C . 

First, they draw tourists into the local community, thereby becoming an 

important component of the economic base discussed earlier . Second, 

beaches provide user value to residents and tourists . Although a beach's 

user value is not traded in a traditional market for services, it can still 

be measured through such techniques as the travel cost method (TCM) and/or 

the contingent value (CV) method . Saltwater beaches are an integral part 

of the marine ecosystem which can be damaged by erosion, debris, oil spills 

and other toxic discharges into coastal waters . Table 204 lists the key 

beaches for this county . 

In 1984, Bell and Leeworthy (1986) estimated expenditures per day of $12 

(1994 dollars) and $30 (1994 dollars) for residents and tourists, 

respectively, on saltwater beach-related costs such as lodging, food and 

drink, etc . in Pensacola, Florida . These estimates will be used for all 

counties in the study area as an approximation since no recent studies have 

been undertaken . 

Using the CV technique, Leeworthy, et al . (1989) found that Escambia, 

Franklin and Bay Counties had an averaged user value of about $3 .0 per day (in 

1994 dollars) for residents and tourists . In a comprehensive study of Florida 

beaches, the University of West Florida (1985b) projected that Walton County 

would have 239,440 saltwater beach days per year in 1990 for the beaches 

listed in table 204 . By multiplying the user value per day of $3 times the 

estimated number of saltwater beach days, the annual flow of value is 

$718,320 . These are not actual expenditures, but an estimate of annual 

recreational benefits to beach users . The capitalized value of this value 

240 
Table 204 . Key Saltwater Beaches in Walton County, Florida.* 

Western District 

Environmentally Endangered Lands : 

Miramar Beach 

Four Mile Village 

Beach Highlands 

Dune Allen Beach 

Blue Mountain Beach 

Eastern District 

Grayton Beach State Recreational Area 

Seagrove Beach 

Phillips Inlet Area 

*In Walton County alone, the University of West Florida (1985b) 

reported 17 individual saltwater beaches which were 3 miles in 

length and 1 .2 million square feet (public and private) . 

Source : University of West Florida (1985a) 

flow at a real discount rate of 3% is over $23 .4 million - the asset value 

of the beach . Finally, beach-related spending in Walton County in 1990 can 

be calculated in the following manner [with the percentage of residents and 

tourists taken from the University of West Florida (1985b) study] : 

Residents 

(o Residents) x (Beach Days/Yr .) x (Expenditures/day) 

.36 x 239,440 x $12 = $1 .03 million 

Tourists 

(% Tourists) x (Beach Days/Yr .) x (Expenditures/day) 

.64 x 239,440 x $30 = $4 .6 million 

Combined, it is estimated that saltwater beaches in Walton County attracted 

$5 .63 million in beach-related spending in 1990 . Tourists accounted for 

82% of this spending . 

Three ecological resources have been identified that are an asset to 

Walton County and induce a considerable level of economic activity in this 

region . These values are summarized in Table 205 . 

WAL .11 Man-Made Resources : Water D 

As discussed above, many economic activities such as fisheries and beaches 

in the marine ecosystem are water-dependent . To take advantage of the 

marine ecosystem in terms of outdoor recreation which has considerable 

economic value, man-made facilities or resources have been constructed . 

The Growth Management Act of Florida mandates that counties should give 

preferences in land planning to water-dependent facilities . Table 14 is an 

inventory of these water-dependent facilities in Walton County . Piers, 

boardwalks and jetties facilitate bank recreational fishing, beach use and 

other outdoor recreational activities . 

241 
Table 205 . Spending, Annual User Value and Asset Value of Selected 

Ecological Resources in Walton County, Florida . 

Resource/Activity Spending User Value Asset Value 

II (Millions) Per Year' (Millions )2 II 

Commercial Fishing $ .093 N/A N/A 

Recreational Fishing $1 .5' $ .925 $30 .75 

Saltwater Marshs N/A .207 6 14 .3 6 

Saltwater Beaches $5 .636 $ .7186 $23 .46 

Marine Boating' N/A $ .156' $5 .2' 

1 Nonmarket value per year 

Z #1 divided by .03 = Asset Value 

' Table 199, ex vessel price 

Table 202, retail price 

5 To commercial fishery landings only 

See text for discussion 

See Table 207 

Table 206 . An Inventory of Marine-Related Recreational Facilities in 

Walton County, Florida, 1995 (Public and Private) . 

Facilities Inventory 

Fishing 

1 . Piers 

a . Number 1 

b . Length (all) (LFT)* 300 

2 . Boardwalks/Catwalks 

a . Number 5 

b . Length (all) (LFT)* 1,025 

3 . Jetties 

a . Length (all) (LFT)* 0 

Boating 

1 . Boat Ramps 

a . Number 10 

b . Total Lanes 12 

2 . Marinas 

a . Total 4 

b . Slips/Moorings 223 

c . Dry Storage 168 

*LFT = Linear Feet 

Source : Bureau of Recreation and Parks (1995) 

Walton County has 12 saltwater boat ramp lanes and 391 wet slips and dry 

racks, as shown in Table 206 . The number of private docks from which to 

launch pleasure craft is unknown . Combining data from Bell et al . (1982) 

and Bell (1995), the annual user value from boating in the Gulf of Mexico 

off Walton County is estimated and shown in Table 207 . This value is about 

$0 .16 million . 

242 
Table 207 . Estimation of the Annual User Value for Saltwater Boating Off 

Walton County, Florida, 1993-94 . 

Facility 

Annual User Value = $/day x Pleasure Craft x Percent Use x Days Boated/Yr . (Marine) 

l . Marinas 

$55,608 = $5 .021 x 2,3742 x .193 x 254 

2 . Boat Rams 

$58,851 = $1 .481 x 2,374 x .674 x 25 

3 . Private Docks 

$41,711 = $5 .025 x 2,374 x .14 x 25 

Total Annual User Value = $156,170 

*Asset Value = 156,170 = .03 = $5 .2 million 

Bell (1995), Florida-wide value 

2 FDEP (1992), Walton County 

Bell et al . (1982), northwest Florida 

Bell (1995), Walton County 

5 Assumed $/day same for marinas and private docks 

Recreational boating in marine waters is rapidly growing in Walton County . 

Such boating can affect coastal water quality (e .g ., inadequate pumping out 

facilities) as well as adding user value to those using coastal water 

resources . From the FDEP (1983-1992) and Bell (1995) studies, pleasure 

boat registrations in Walton County grew as follows, with projected (P) 

numbers included : 

1983 2,104 

1984 2,043 

1985 2,062 

1986 2,176 

1987 2,276 

1988 2,357 

1989 2,449 

1990 2,365 

1991 2,276 

1992 2,374 

2000 3,010 (P) 

2005 3,587 (P) 

2010 4,274 (P) 

WAL .12 Water Quality, the Ecosystem and the Economy 

The interaction of the local economy and the marine ecosystem is 

manifested in the water quality surrounding the region . Florida's major 

surface water quality problems come from urban stormwater runoff, 

agricultural runoff, domestic wastewater, industry wastewater, and 

hydrological changes such as draining and filling wetlands . 

243 
There are three sources of information on local water quality surrounding 

Walton County . First, the Federal Water Pollution Control Act requires the 

state to prepare a 305(b) technical report on the status and trends in 

surface water quality . Second, the EPA Toxic Release Inventory (TRI) 

provides information on toxic and other chemical discharges by firms into 

surface water . Third, the acreage of shellfish harvesting that is 

prohibited from fishing is an indicator of high bacterial counts in the 

water . These three sources of information will give a profile of surface 

water conditions in Walton County . 

Two indices are used in the 305(b) report for measuring surface water 

quality: the stream water quality index (WQI), and the lake/estuary 

Trophic State Index (TSI) . Both are of interest to this study simply 

because streams flow into Gulf of Mexico estuaries . The TSI measures 

estuarine water quality that is critical to fish and wildlife . The WQI 

summarizes information from six categories including water clarity 

(turbidity and total suspended solids), dissolved oxygen, oxygen-demanding 

substances (BOD), nutrients, bacteria and macroinvertebrate diversity. The 

TSI measures the potential for algal or aquatic weed growth . Although the 

present emphasis is on the marine environment, the TSI can be used in 

Florida estuaries to describe their water quality, even though the TSI is 

more widely used for freshwater lakes . The WQI and TSI are constructed so 

they run from zero to 100 with larger values indicating declining water 

quality. 

The geographical analysis of the 305(b) report is formulated by river 

basins, but this analysis is restricted to bays and some critical rivers 

because of this study's emphasis on the marine environment and how this 

ecosystem interacts with the economy of the area . For Walton County, 

Choctawhatchee Bay and St . Andrews Bay Basin have been selected for a brief 

summary of the current state of water quality in this region of the study 

area . 

The Choctawhatchee Bay lies within the peninsula, south of Walton County . 

There is little interaction between the Gulf of Mexico and the bay, with 

only one inlet, East Pass, which is on the western side of the bay . Major 

populations include Eglin Air Force Base in the northern area of the basin, 

Ft . Walton Beach on the eastern shore and Destin on East Pass . Major 

pollution sources are primarily from the rapid growth of the county along 

the peninsula . Highway runoff, ditching and drainage of wetlands, and 

discharges from waste water treatment plants also contribute to the 

deterioration of water quality . Water quality has traditionally been good, 

but a few occurrences of fish kills and some grass bed die-offs have been 

reported . One endangered species of fish, the Okaloosa Darter, lives in 

the streams which drain into some of the county's bayous . 

The St . Andrews Bay Basin only has three of its sites in Walton County, 

with Lake Powell being the most significant of the three . This lake is 

considered interesting because it contains both freshwater and saltwater 

characteristics . Recently it was designated as an Outstanding Florida 

Water . The rest of the basin lies in Bay County . The WQI and TSI for 

selected areas in the county are listed in Table 208 . 

244 
The TRI is an annual summary of discharges to surface water, as well as 

other kinds of discharges (e .g ., airborne) . Table 209 indicates that in 

1994 there was one company, Showell Farms, which was discharging toxic 

substances in and around the surface water of Walton County . These 

discharges may be highly variable from year to year . Shellfish harvesting 

has been closed in 27,488 acres, and opened conditionally in 68,007 acres, 

in the Choctawhatchee Bay, indicating that there have been significant 

coliform counts in almost 30% of the shellfish beds . 

Table 208 . Water Quality Indices for Selected Areas of Walton County, 

Florida . 

Water Areas : Pensacola Bay Water Quality Indices* 

Water Body Tyke : Estuary WOI TSI 

14 Indian Bayou -- 47 

17 Choctawhatchee Bay -- 38 

18 Joe's Bayou -- 52 

23 Choctawhatchee Bay -- 35 

37 Alaqua Creek Outlet -- 46 

41 Alaqua Bayou -- 50 

44 Basin Bayou -- 45 

Water Body Type : Lake 

10 Lake Oyster -- 51 

Water Body Type : Stream 

28 Lagrange Bayou 33 -- 

52 Lafayette Creek 24 -- 

70 Magnolia Creek 11 -- 

74 Watering Creek 17 -- 

75 Alaqua Creek 34 -- 

86 Rocky Creek 23 -- 

89 Little Alaqua Creek 22 -- 

Water Areas : St . Andrews Bay Basin 

Water Body Type : Lake 

34 Lake Powell -- 24 

41 Western Lake Outlet -- 26 

Water Body Type : Stream 

37 Direct Runoff to Bay 31 -- 

* Higher values indicate lower water quality 

Table 209 . Toxic Chemical Releases Into Surface Water by Firms 

Located in Walton County, Florida in 1994 . 

Company SIC Discharge Main' 

1 . Showell Farms 2,015 10 Chlorine 

Leading chemical released based on pounds . 

A.Source: EPA Toxic Release Inventory, unpublished data, 1994 . 

245 

Bell, F . W . 1995 . Estimation of the Present and Projected Demand and 

Supply of Boat Ramps for Florida's Coastal Regions and Counties . 

Florida Sea Grant College Program . TP-77 . 

Bell, F . W . 1993 . Current and Projected Tourist Demand for Saltwater 

Recreational Fisheries in Florida . Florida Department of Natural 

Resources and Florida Sea Grant College Program . 

Bell, F . W . 1989 . Application of Wetland Valuation Theory to Florida 

Fisheries . Florida Sea Grant College Report . SGR-95 . 

Bell, F . W . and V . R . Leeworthy. 1986 . An Economic Analysis of the 

Importance of Saltwater Beaches in Florida . Florida Sea Grant College 

Report . SGR-82 . 

Bell, F . W ., P . E . Sorensen and V . R . Leeworthy . 1982 . The Economic 

Impact and Valuation of Saltwater Recreational Fisheries in Florida . 

Florida Sea Grant College Report . SGR-47 :118 . 

Bureau of Economic Analysis (BEA) . 1995 . Unpublished computer runs, 1969-

93 . U .S . Department of Commerce . Washington, DC . 

Bureau of Recreation and Parks . 1995 . Unpublished Computer Printout . 

Florida Department of Environmental Protection (FDEP) . 

Bureau of Surface Water Management . 1994a . Northeast Florida District 

Water Quality Assessment, 1994 305(b) Technical Appendix . Florida 

Department of Environmental Protection (FDEP) . 114pp . 

Bureau of Surface Water Management . 1994b . Northwest Florida District 

Water Quality Assessment, 1994 305(b) Technical Appendix . Florida 

Department of Environmental Protection (FDEP) . 157pp . 

Bureau of Surface Water Management . 1994c . Southwest Florida District 

Water Quality Assessment, 1994 305(b) Technical Appendix . Florida 

Department of Environmental Protection (FDEP) . 122pp . 

Florida Department of Commerce . 1994 . Florida County Profiles . Division 

of Economic Development, Bureau of Economic Analysis . 

Florida Department of Environmental Protection (FDEP) . 1994 . Unpublished 

Commercial Fishery Landings . Tallahassee, Florida . 

Florida Department of Environmental Protection (FDEP) . 1992 . Unpublished 

Registered Pleasure Craft by County . Tallahassee, Florida . 

Florida Department of Natural Resources (FDNR) . 1980 . Florida Commercial 

Marine Landings . Tallahassee, Florida . 

Hall, R . 1994 . "Gold and Green : Can We Have Good Jobs and a Healthy 

Environment?" Institute for Southern Studies Publications . Durham, 

North Carolina . 

247 
Leeworthy, V . R ., N . F . Meade, K . Drazek and D . Schruefer . 1989 . A 

Socioeconomic Profile of Recreationists at Public Outdoor Recreation 

Sites in Coastal Areas : Volume 3 . NOAA, U .S . Department of Commerce . 

Lester, W . 1995 . "Toxic Troubles" A Five Part Series by the Associated 

Press . Tallahassee Democrat, November . 

Milon, J. W. and E . M. Thunberg . 1992 . A Regional Analysis of Current and 

Future Florida Resident Participation in Marine Recreational Fishing. 

Florida Department of Natural Resources and Florida Sea Grant 

College . 

NOAA . 1991 . Coastal Wetlands of the United States, A Special NOAA 20th 

Anniversary Report . U .S . Department of Commerce . Washington, D .C . 

Terrebonne, P .R . 1973 . The Economic Losses from Water Pollution in the 

Pensacola Area . The Florida Naturalist . 165(7) :21-26 . 

University of West Florida . 1985a . Sandy Beaches of Florida . University 

Presses of Florida . 218pp . 

University of West Florida . 1985b . Unpublished report on saltwater beach 

statistics in Florida for Florida Department of Environmental 

Protection . 

248 
U .S . Department of the Interior 

U .S. Geological Survey 

Biological Resources Division 

As the Nation's principal conservation 

agency, the Department of the Interior has 

responsibility for most of our nationally owned 

public lands and natural resources . This 

responsibility includes fostering the sound 

use of our lands and water resources ; 

protecting our fish, wildlife, and biological 

diversity; preserving the environmental and 

cultural values of our national parks and 

historical places; and providing for enjoyment 

of live through outdoor recreation. The 

Department assesses our energy and mineral 

resources and works to ensure that their 

development is in the best interests of all our 

people by encouraging stewardship and 

citizen participation in their care. The 

Department also has a major responsibility 

for American Indian reservation communities. 

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