Energy analysis and ecological evaluation of a coastal power plant


Material Information

Energy analysis and ecological evaluation of a coastal power plant
Physical Description:
xx, 560 leaves : ill. ; 28 cm.
Kemp, W. Michael ( William Michael ), 1947-
Publication Date:


Subjects / Keywords:
Nuclear power plants -- Environmental aspects -- Mathematical models -- Florida -- Crystal River   ( lcsh )
bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )


Thesis--University of Florida.
Includes bibliographical references (leaves 463-493).
Statement of Responsibility:
by William Michael Kemp.
General Note:
General Note:

Record Information

Source Institution:
University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
aleph - 000184720
notis - AAV1295
oclc - 03319312
lcc - TD195.E4 K45 1977a
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Full Text








I am deeply indebted to my major professor, H.T. Odum, for the

enthusiasm, insight and inspiration that he has provided during this

study. Many special acknowledgements go to my supervisory committee:

P. Brezonik, J. Ewel, C. Kylstra and S. Snedaker for their patience and


Research was supported by two contracts between the Florida Power

Corporation and the University of Florida Department of Environmental

Engineering Sciences, Systems Ecology Program, H.T. Odum, principal

investigator. (Contract No. DEC-159 918-200-188.19, entitled Models

and Measurements for Determining the Role of Power Plants and Cooling

Alternatives at Crystal River, Florida; and Contract No. GEC-183

entitled Models and Energy calculations for Determining the Role of a

Power Plant in its Environment at Anclote, Florida.) Additional sup-

port was provided by a contract between the State of Florida Department

of Pollution Control and University of Florida Center for Wetlands,

H.T. Odum and S.E. Bayley, Co-principal investigators.

I wish to express special appreciation to friends, fellow students

and associates, for stimulating interactions and stabilizing encourage-

ment, particularly to S. Bayley, W. Boynton, B. Walker and J. Zucchetto.

Mark Homer collaborated in field studies and calculations of energy

quality of estuarine animals. As project assistants, F. Ramsey and

L. Gunderson contributed many hours in field work and assembling data.

Many others also helped in the field, including W. Smith, A. Merriam

and T. Dolan.

Dr. S. Snedaker authorized use of data, nets, and equipment.

Zooplankton data were provided by W. Ingram, and fish population studies

by D. Dorman and S. Sutton. W. Trowel was pilot and maintained boats

and engines.

L. Arrington drafted figures and maps; J. Breeze typed reports.





ABSTRACT . . . .


Hierarchical Scales of Study . .

Power Plants in the Coastal Zone . .

Interface Ecosystems and Environmental Technology .

Questions on Roles of Coastal Power Plants .

Previous Studies of Interactions Between Power Plants
and Estuaries . . .

Review of Methods for Environmental Planning
and Evaluation . . .

Description of the Study Area . .

Previous Research at Crystal River . .


Modeling Methods . .

Ecological Field Measurements.. .

Calculations of Energy Cost . .


Energy Analysis of Powershed Region .. ...

Ecological and Energy Effects of Power Plant.


. 52

. 55

. 85

. 104

. 104

. 150

Economic and Energetic Costs of Alternative Cooling
Systems . . ... ... .. .. 210




.. xi







S. 26

S. .40

. 49



Field Measurements of Canal Ecosystems. . ... 220

Quality of Natural Energies at Crystal River. 301

Simulation of Estuarine Ecosystem Model ... 351

DISCUSSION. . . . 405

Cooling Water Canals as Interface Ecosystems. 405

Energy Quality Relationships. ....... ... 418

Energy Effectiveness of Environmental Technology ..... .423

Energy Signatures of Crystal River Estuary ........ 431

Recommended Procedure for Energy Analysis of
Environmental Impacts ............. .. 445

Energy Basis for a Coastal Power Plant in its
Regional Economy ............... ...... 451


REFERENCES. . . . 463


A. Species composition and distribution for major plant
communities in canal ecosystems at Crystal River. .494

B. Detailed data to describe benthic animal communities in
canal ecosystems at Crystal River ......... .. 501

C. Detailed data to describe nekton community in power plant
canal ecosystems at Crystal River . .. 517

D. Derivation of formula for estimating blue crab populations
at Crystal River, taking migration into account .. .531

E. Derivation of model equation to account for temperature
effects on productivity .... 537

F. Detailed information for computer model of estuarine
ecosystem . . . 541

G. Detailed tables of data used for calculating energy
qualities of estuarine animals. . ... 553

BIOGRAPHICAL SKETCH ................... 560



Table Page

1. Some major coastal and estuarine power plants in U.S.
utilizing cooling water canal systems. . ... 12

2. Fish entrapment on intake screens at several coastal
power plants in the United States ........... 24

3. Example of computation for flow time, T, between dis-
charge canal stations 5 and 6 on 1-2 July, 1974. ... 62

4. Portion of computation table for analysis of rate-of-
change of dissolved oxygen between stations 5 and 6
on 1-2 July, 1974, and example calculation corres-
ponding to data given in Fig. 6 and Table 3. .. 67

5. Energy quality ratios used to compare various kinds
of energy in terms of their ability to do work ...... 88

6. Summary of ecosystem areas and productivities in
powershed. . . ... ..... .116

7. Summary of annual inputs of natural energy to power
plant region . . ... .121

8. Electric power generation and fossil fuel consumption
by power plants in study region for 1973 ......... 126

9. Fuel consumption patterns for Florida, 1973. .. .127

10. Summary of economic and energy flows into and out from
the Anclote power plant region for 1973 ........ 131

11. Estimated portions of goods annually manufactured in
Florida which are exported from the state and raw
materials for manufacturing which are imported from
outside the state ................... 140

12. Estimated portions of annual retail sales of various
goods originating from within Florida. . ... 142

13. Loss of energy value associated
with plankton entrainment at Crystal River, considering
the role of plankton in the estuarine ecosystem. ... .165


Table Page

14. Loss of energy value associated with meroplankton
entrainment at Crystal River considering survival
to adulthood and the role of adult organisms in
the ecosystem. . . 167

15. Loss of energy value associated with meroplankton
entrainment at Crystal River, considering economic
value of surviving adults. . ... 170

16. Loss of energy value associated with juvenile fish
entrainmenf at Crystal River power plant, considering
trophic role of the juveniles in estuarine ecosystem 177

17. Loss of energy value associated with entrainment
of juvenile fish at Crystal River power plant con-
sidering survival to adulthood and the role of adult
organisms in the ecosystem . .... 180

18. Energy calculation of value loss resulting from impinge-
ment of nekton at the cooling water intake of the Crystal
River power plant, considering the trophic roles of
organisms in the estuarine ecosystem . .. 185

19. Energy calculation of value loss resulting from entrap-
ment of nekton at the cooling water intake of the Crystal
River power plant, considering the direct monetary value
to the regional economy. . .... 189

20. Estimates of the energetic impact of discharges from
Crystal River power plant Units 1 and 2 on the surround-
ing ecosystems, as indicated by changes in community
gross primary productivity . .... 197

21. Estimated size of discharge plume from Crystal River
power plant. . . ... ... 199

22. Estimates of the energetic impact of discharges from
Crystal River power plant Units 1, 2 and 3 on surrounding
ecosystems, as indicated by changes in community gross
primary productivity . .... 200

23. Estimates of energetic impact of displacing and replacing
ecosystems by construction associated with power plant
at Crystal River . . ... ... .202

24. Summary of cost estimates for cooling water management
alternatives at Crystal River power plant. ... 211


Table Page

25. Effects of salt spray deposition on terrestrial eco-
systems for alternative cooling water management schemes
for Cyrstal River power plant Units 1-3. ... 214

26. Comparative energetic costs of alternative cooling water
management schemes: economic investments and terrestrial
ecological impact for Crystal River power plant Units 1-3. 219

27. Productivity and respiration data for total ecosystems in
discharge and intake canals. . ... 223

28. Productivity and respiration of plankton in discharge (D)
and intake (I) canal ecosystems measured by light-dark
bottles. . . ... ..... ..238

29. Light extinction in waters of intake and discharge
canals at Crystal River power plant. . ... 248

30. Summary of monthly blue crab catch data for estimate of
canal population using Schnabel-type comulative mark-
recapture analysis . .... .280

31. Summary estimates of population density of polkadot
batfish, Ogcocephalus radiatus, in the intake canal
ecosystem at Crystal River . .... 282

32. Summary of gill-netting estimates of nekton populations in
canal ecosystems at Crystal River power plant ...... 285

33. Summary of trophic habits observed for selected fish
caught by gill net in canals at Crystal River power plant. 288

34. Summary of beach nourishment projects sponsored by U.S.
Corps of Engineers and comparison of local wave energies
with dredging costs. .. . .302

35. Summary of data comparing'tidal energies to net energy
output from the electric power plant at La Rance, France
and from a proposed plant on the Bay of Fundy, Maine 318

36. Summary of desalination data for selected, cost-effective
plants . . . 329

37. Summary of mean annual values of stocks and flows of
organic matter for major components in control salt marsh
creek ecosystem. . . ... ... .334

38. Energy quality ratios for various trophic levels in a
food web for an estuarine ecosystem on the Gulf Coast
of Florida . . ... .. ... 346



Table Page

39. General trophic habits of organisms considered in
energetic analysis of Crystal River power plant and its
effects on nearby estuary ................ 348

40. Summary of results from empirical sensitivity analysis
of estuarine ecosystem model. .. . .396

41. Summary of energy costs involved in construction and
operation of cooling eater canals at Crystal River 419

42. Summary of ecological and energetic costs to the Crystal
River estuarine and regional systems resulting from power
plant operation. . . .... 424

43. Comparison of energetic and economic costs to the
Crystal River power plant region for three alternative
cooling water management schemes for 3 power plant units
operating . . ... 427

44. The balance of energies supporting regional systems: a
comparison of the Crystal River powershed with the U.S.,
Florida and other regions. . ... 454

Al. Summary of dominant benthic plant species encountered in
canals at Crystal River power plant for samples taken on
8 February and 25 June 1975 .............. 495

Bl. List of benthic marine animal species collected in canals
at Crystal River power plant, 1974-1975. ... 502

B2. Seasonal trends of abundance, biomass and diversity for
benthic animal communities inhabiting the intertidal zone
of intake (I) and discharge (D) canal ecosystems at
Crystal River power plant, Florida . .... 507

B3. Seasonal trends of abundance and biomass for adult oysters
and spat in benthic intertidal animal communities of the
intake (I) and discharge (D) canal ecosystems. ... 510

B4. Seasonal trends of crab abundance and biomass for benthic
intertidal communities of intake and discharge canal
ecosystems .. ... .. ... ... 512

B5. Seasonal trends of abundance and biomass for barnacles,
mussels and serpulids in the benthic intertidal communi-
ties of the intake (I) and discharge (D) canal ecosystems. 514

Cl. List of nekton species caught by gill net in canal
ecosystems in March and June 1975. . ... 518


Table Page

C2. Mark-recapture data for estimating population density of
polkadot batfish, Ogcocephalus radiatus, in intake
canal at Crystal River power plant. . ... 521

C3. SCUBA census data for estimating population density of
the polkadot batfish, Ogcocephalus radiatus, in intake
canal at Crystal River power plant. . ... 522

C4. Measurements of nekton populations in power plant canal
ecosystems at Crystal River . ... 523

C5. Analyses of stomach contents of selected fish caught on
gill nets at Crystal River power plant. . ... 527

Fl. Differential equations describing model of estuary
receiving waste discharges from Crystal River power plant 542

F2. Data sources for flows and storage used in model of
estuary receiving waste discharges from Crystal River
power plant . . ... ..... .544

F3. Calculation and assumptions for pathway rate coefficients
used in model of estuary receiving waste discharges from
Crystal River power plant . .. 548

F4. Computer program of model used to simulate estuarine
ecosystem at Crystal River, Florida . ... 551

Gl. Partial feeding coefficients calculated for food web
consumers . . ... ..... 554

G2. Example calculations for apportioning organism stocks
and flows into trophic function categories, using second
level detritus branch of control marsh as illustrative
case. . . ... .... 557


Figure Page

1. Diagram of the general chain of interactions between
regional economy, power plant, canal ecosystems, and
estuary. . . ... 4

2. Energy diagrams and maps of Crystal River Power region
showing three hierarchical scales studied. . 6

3. Map showing some geographic features of region served
by Florida Power Corporation . .... 42

4. Estuary adjacent to Crystal River power plant showing
intake and discharge canals, and locations of field
sampling stations. . .... 46

5. Diagram of discharge canal illustrating the physical
parameters involved in calculating flow time, T, between
stations 5 and 6 . . ... ... 61

6. Typical diurnal variations in measured parameters for
stations 5 and 6 on 1-2 July 1974. . ... 66

7. Diagram illustrating pertinent processes affecting
oxygen concentration in two layers of the intake canal 71

8. Oxygen return to a nitrogen-filled plastic dome in
experiments to measure oxygen diffusion coefficients
(k, g 02/m2/hr at 100% stauration deficit) ... 74

9. Example of light penetration data measured with submarine
photometer on 19 Nov. 1975 at Sta. 6 in the vertically
well-mixed discharge canal . .... .79

10. Illustration of gill net placement for fish sampling in
the canal ecosystem. Diagram was adapted from a drawing
in Nugent (1970) . . ... ... 83

11. Diagrams showing three methods for calculating energy
quality ratios . .... ..... 92

12. Energy diagram of regional study area (powershed of
Florida Power Corporation) depicting energy and economic
budgets. . . ... ..... .106

13. Reduced copy of vegetation and land use map of powershed
regional study area for 1973 . .... .. 108


Figure Page

14. Map of rainfall and topography developed for calculating
the potential energy of elevated water from rainfall on
the landscape in powershed region . .. 110

15. Map of rainfall and riverflow developed for calculating the
chemical potential energy of freshwater relative to sea-
water in powershed region . ... 112

16. Map of mean wind speeds, tidal range and wave height in
regional study area developed for calculating the energy
inputs from these sources to the powershed regional system. 114

17. Unit model with details of energy budget for human systems
depicted in Fig. 12 and listed in Table 10. ..... 129

18. Annual trends in economic (constant 1967 dollars) and
energy parameters for Cyrstal River Power Plant Region
from 1958-1974. . . ... .145

19. Generalized model of Cyrstal River estuarine ecosystem
depicting major effects of power plant. ... 152

20. Total copepod standing stocks at three stations in Crystal
River study . . .. 155

21. Proportion of entrained copepods killed and estimated
mortality numbers per m3 of cooling water flow at the
Crystal River power plant . .... 157

22. Abundance of chaetognaths and medusae in intake and
discharge canals at Crystal River power plant ...... 159

23. Total meroplankton abundance in intake and discharge
canals at Crystal River power plant . .... 161

24. Total abundance of fish eggs and larvae in intake and
discharge canals at Crystal River power plant .. 163

25. Estimated rates of juvenile fish entrinment at Crystal
Tiver power plant and monthly occurrence (in nearly salt-
marsh creek) of such juveniles which are susceptible to
this entrainment. . . ... ... .176

26. Rate of impingement of nekton at power plant intake
screens. Large open bars are mean weekly impingement rate. 184

27. Gross primary productivity estimates for (a) inner and
(b) outer bay ecosystems at Crystal River, as inferred
from measurements of diurnal changes in dissolved oxygen. 193



Figure Page

28. Net and gross primary productivity estimates for salt
marsh ecosystems at Crystal River, Juncus (a) and
Spartina (b). . . ... ..... 196

29. Time series of current measurements at Crystal River com-
paring areas away from and within the influence of canal
spoil banks . . ... ... 206

30. Effects of salt spray deposition on growth of various
kinds of vegetation . .... .217

31. Generalized energy diagram illustrating major aggregated
components of intake and discharge canal ecosystems as
they interact with adjacent bays and offshore systems and
are interposed by the Crystal River power plant .. .222

32. Daytime net productivity and night respiration of total
ecosystems in canals at Crystal River power plant for
1974-75 . . ... . .228

33. Seasonal trends for net productivity and respiration of
canal ecosystems at Crystal River power plant for 1974
and 1975. . . ... ...... 230

34. Seasonal trends for gross productivity of total ecosystem
in canals at Crystal River power plant for 1974 and 1975. 232

35. Seasonal trends for P/R ratio of total ecosystems in
canals at Crystal River power plant for 1974 and 1975 234

36. Seasonal trends for gross productivity of the plankton
communities (as measured by light-dark 02 bottles) in
canals at Crystal River power plant for 1974 and 1975 241

37. Seaonsal trends of carbon-14 productivity for plankton
communities in canals at Crystal River power plant for
1974. . . ... .... 244

38. Seasonal trends of P/R ratios of plankton metabolism in
canals at Crystal River power plant for 1974 and 1975 .247

39. Extinction of solar radiation by water in canals at
Crystal River power plant, 1972-1975 . ... 252

40. Graph of vertical salinity gradient (AS) versus difference
in extinction coefficient (Ak) between the intake and dis-
charge canals at Crystal River power plant for 1974 and
1975 ... . .. .255



Figure Page

41. Chlorophyll-a measurements of live plankton in canals at
Crystal River power plant for 1974. . .... 257

42. Total organic carbon of seston in canals at Crystal River
power plant for 1974. . . ... 259

43. Total inorganic nitrogen in canals at Crystal River power
plant for 1974. . . ... .261

44. Phosphate-P in canals at Crystal River power plant
for 1974. . ... ... .263

45. Abundance (a) and biomass (b) of animals inhabiting the
littoral zone of canal ecosystems at Crystal River plant
for 1974 and 1975 . . ... ... .267

46. Species diversity of animal communities in littoral zone
of canals at Crystal River power plant for 1974 and 1975. 269

47. Oyster spat density (a) and adult oyster biomass in lit-
toral zone of canals at Crystal River power plant for
1973-1975 . . ... .... .273

48. Abundance (a) and biomass (b) of crabs in littoral zone
of canals at Crystal River power plant for 1973-1975. .. 275

49. Abundance (a) and biomass (b) of barnacles in littoral
zone of canals at Crystal River power plant for 1973-1975 277

50. Detailed energy diagrams illustrating primary components
of intake and discharge canal ecosystems interacting with
power plant and external estuary. . ... 291

51. Diagrammatic model of major interactions involved in the
counter-current processes of natural longshore transport
of sand and mechanical nourishment of eroded beaches. 308

52. (a) Regression of longshore wave energy, EA, versus
littoral drift. (b) Relationship between the alongshore
wave energy needed to transport a given quantity of sand
and the energy cost of dredging to return same amount of
sand at same rate . . ... ... .311

53. (a) Scatter diagram showing very weak inverse relationship
between alongshore wave energy, EA, and the ratio of
dredging costs to EA. (b) Diagram showing relationship
between the amount of transport work accomplished per unit
of wave energy and tht total wave energy involved ... .313


Figure Page

54. Diagram summarizing data to indicate the relative energy
inputs required from coastal waves and from fossil fuel
based dredging to accomplish the same sediment transport
work. . . .. ...... .316

55. Major economic and energetic processes involved in con-
struction and operation of tidal generated electric power
plant . . ... . 321

56. Diagram summarizing data to indicate the net output from
tidal electric power plants compared to input energy of
tides, (a) for operating plant at La Rance, France,
(b) for proposed plant at Bay of Fundy, Maine ....... 325

57. Major economic and energetic processes involved in
construction and operation of desalination plant. ... .328

58. Diagrams summarizing the energe used in selected de-
salination plants compared to chemical energy stores in
the process . ... ..... .333

59. Energy diagram indicating web of trophic relationships in
saltmarsh creek ecosystem at Cyrstal River. ... 341

60. Generalized energy diagram depicting relationships between
functional trophic groups in saltmarsh creek ecosystem at
Crystal River . . ... .... .343

61. Energy circuit diagram of estuarine ecosystem receiving
waste discharges from power plant ............. 353

62. Explanation of diagrammatic configurations and mathematical
expressions used in conceptualizing the model of an
estuarine ecosystem shown in Fig. 65.
(a) Plant biomass. . .... .355
(b) Detritus . . ... 357
(c) Nitrogen . . ... 359
(d) Benthic invertebrates. . ... 361
(e) Nekton . .... ... .. 363

63. Energy and material input forcing functions for model of
estuarine ecosystem shown in Fig. 61 . 365

64. Behavior of estuarine model (Fig. 61) under conditions
simulating the control ecosystem, unaffected by power
plant discharges . . ... ... .369

65. Behavior of estuarine model (Fig. 61) under conditions
simulating the ecosystem receiving waste discharges from
Cyrstal River units 1 and 2. . ... 372


Figure Page

66. Model response to increased temperature and turbidity. .. 377

67. Model response to extreme temperatures and turbidities
for conditions simulating Crystal River Units 1-3
operating. . . ... ..... 379

68. Model response to productivity coefficient, k1 ..... 382

69. Model response to limiting factor "saturation constant,"
k . . . 384
70. Sensitivity of model behavior to plant death rate coef-
ficient, k6. ................... 386

71. Sensitivity of model behavior to plant respiration
coefficient, k7 .................. .. 388

72. Sensitivity of model behavior to detrital respiration
coefficient, kl9 .................. .. 390

73. Sensitivity of model behavior to nekton respiration
coefficient, kl4 ............. 392

74. Sensitivity of model behavior to benthic respiration
coefficient, k16 ............. 394

75. Model behavior under conditions simulating the shallow
bay estuarine ecosystem receiving waste discharges from
the Crystal River power plant with 3 units operating 399

76. Model behavior under conditions simulating the shallow
bay estuarine ecosystem near the Crystal River power
plant, with plant using closed-cycle cooling ..... 402

77. Oyster spat density versus crab abundance in littoral
zone of canals at Crystal River power plant for 1973-1975. 413

78. Energy signature for estuarine ecosystems at Crystal
River. . . ... .... 434

79. Annual cycles of forcing functions which comprise the
energy signature for Crystal River estuary given in
Fig. 14. . . ... ..... 441

80. Generalized model of decision-making process suggested
for environment evaluation . .... 450



Figure Page

81. Energy diagram of regional study area (powershed)
depicitng energy-economic budget for 1973 ... 453

Al. Spatial distribution of major plant communities in the
(a) intake canal and (b) discharge canal ecosystems at
Crystal River . .. 499

Dl. Energy diagram of major system components and processes
for estimating blue crab populations in the intake canal
at Crystal River power plant, taking crab migration into
account . .. .. 534


Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the Requirements
for the Degree of Doctor of Philosophy



William Hichai1l Kemp

March 1977

Chairman: H.T. Odum
Major Department: Environmental Engineering Sciences

The energy basis and ecological interactions of a coastal power

plant near Crystal River, Florida were evaluated at three hierarchical

scales of study: the power plant region (powershed); the broad mosaic

of coastal ecosystems interacting with the power plant; and the eco-

systems of the cooling water canals at the interface between estuary and

power plant. Information was developed from model studies, computer

simulations, field measurements, compilations of data from project re-

ports, maps of land use, and energy analysis.

The Crystal River powershed was supported by a diverse array of

energy inputs. About 1.9 times as much energy was contributed from

fossil fuels as from natural (solar-based) sources. The ratio of fossil

fuels to natural energy inputs for this region was about 30% lower

than the national average (2.7), indicating the region might be rela-

tively undeveloped. However, the proportion of fossil fuels invested


in electric power generation in the powershed (0.52) was 67% higher than

the national average (0.27) and 7% higher than the Florida average (0.42).

Thus, there has been large investment in power plants for this region,

possibly in anticipation of further economic development.

The Crystal River power plant has had substantial impact on adjacent

estuarine ecosystems. Major areas of impact included entrainment

mortalities inflicted on meroplankton and juvenile fish, as well as

inhibition of productivity in the ecosystems receiving power plant dis-

charges. These effects were documented and evaluated in coal equivalent

(CE) energy units. The total annual cost to the estuaries and region

resulting from power plant construction and operation was estimated to

be 7.7 x 10 kcal CE/yr (equivalent to about $385,000/yr).

A simulation model of the estuarine ecosystems receiving thermal

wastes was used to predict the effects of adding a third generating unit.

A parabolic relationship between temperature and productivity, derived

as a simplification of theoretically based functions, produced model

behavior which closely matched field data. It was estimated that the

ecological effects of a 3-unit power plant (13.8 x 109 kcal CE/yr) would

be almost 80% greater than for the 2-unit plant. The costs of using

technological measures to ameliorate these ecological impacts were com-

pared to the ecological impacts themselves. The cheapest closed-cycle

cooling system would cost about $17 x 106/yr (350 x 10 kcal CE/yr),

which was about 25 times greater than the estimated damage to the


The power plant's effects on stocks of estuarine organisms were

evaluated in terms of equivalent amounts of primary productivity needed

to support these organisms. A model was developed to do this by

describing generalized functional relationships between trophic levels

in an estuarine ecosystem at Crystal River. Detailed data from a salt-

marsh creek ecosystem were used to evaluate stocks and energy flows in

the trophic web. For example, the model indicated that a kilocalorie

of mullet (Mugil cephalus) and jack (Caranx hippos) production would

require 20 and 300 kilocalories, respectively, of gross productivity.

'The cooling water canals were observed to be viable interface eco-

systems characterized by high productivities and large standing stocks

of animals. Mean levels of gross primary productivity in the canals

(7.8 02/ were 33% higher than adjacent bay ecosystems. Standing

stocks of benthic animals and nekton in the canals (31.2 g organic/m2
and 3.2 g dry/m2, respectively) were about 4.5 and 2 (respectively)

times higher than in the bays. The intake canal provided a habitat to

grow certain nekton species which were impinged at the power plant

intake, but overall, it served only as a channel to direct fish from

outside the canal to the power plant.


Understanding the combined systems of man and nature is a major

need in studying the ecology of large scale systems. In this dis-

sertation the ecological, economic and energy relationships of a steam

electric power generating plant in a coastal zone region are investi-

gated. Economic data, energy budgets, and maps of land use and energy

density are developed to consider relationships between the availability

of natural energy resources and the growth of electric power industries

in a coastal zone.

Information developed by many investigators in a coordinated

research project sponsored by Florida Power Corporation is synthesized

using energy analysis. Effects of power plant operation on estuarine

ecosystems are measured and compared in energetic terms to the cost of

mitigating them with environmental technology such as cooling towers.

Computer models simulating ecosystem behavior are developed and used

to predict potential effects of alternative cooling water schemes on

the estuary and its subsystems. Field measurements of ecosystems in

the power plant canals are used to evaluate the energy interactions and

ecological character of these unique systems at the interface between

power plant and estuary.

Hierarchical Scales of Study

Relationships between various components of this study are


depicted in Fig. 1, which shows the general chain of interactions

between regional economy, power plant, canal ecosystems and estuary.

From a spatial point of view, the power plant functions at several

levels within its region of influence. To understand the structure of

power plant systems, three hierarchical scales of size were identified

for modeling. Diagrams that were highly detailed initially were

aggregated and condensed until the hierarchical structure of the system

clearly emerged. In this way the smallest scale models could include

much detail without the study losing its holistic point of view. Since

each subsystem was a component in a larger system, information gleaned

from examination at one level could be effectively transferred to study

at other levels (see Simon, 1965; Pattee,1973).

Relationships between the three hierarchical levels of focus for

the present study are illustrated in Fig. 2. Diagrams show the aggre-

gated system components and interactions at each scale. The dashed

lines between subsystem diagrams indicate the manner in which lower

levels are nested into higher level systems. Maps of successively

smaller scales paralleling the diagrams are presented to suggest two-

dimensional spatial relationships.

Power Plants in the Coastal Zone

In the past century western technological societies have become

critically dependent on fossil fuels which have nurtured an accelerated

growth. Because of its versatility as a means of distributing energy,

electricity has become an integral part of the technological system,

so that presently about 27% of the fossil-fuel-based energy consumed

01- o *

o o
*H to

(cin 0

0 0

orl og

U 0U
4-4 H



* 0 o




Figure 2. Energy diagrams and maps of Crystal River
Power region showing three hierarchical scales
studied. For explanation of symbols see H.T.
Odum (1971).


(See Fig 12)

(See F~g 19)

(See Fig 31)




in the U.S. is involved in electric power generation (Smith, 1975).

In the United States electric power production has increased some 200

fold in the last 60 yrs while population has barely doubled during the

same period (Rainwater, 1968; Mihursky et al., 1970; Smith, 1975). At

present, over 80% of the electricity consumed is generated by fossil

fuel fired steam electric plants, and the remainder is produced by

hydroelectric and nuclear plants (Federal Power Commission, 1971; Smith,


During this time of rapid growth the availability of fuels to

support our complex human systems was seldom questioned, and the value

of nature in providing man's life-support system was little recognized.

However, the "energy crisis" of 1973 dramatically emphasized the

limited nature of fossil fuel supplies and the dependence of regional

economies on these energies. The ability of a regional system to make

effective use of its energy resources may determine the pattern of that

system which ultimately survives (Lotka, 1922; Odum, 1973).

Coastal zones that include man, like all regional systems, are

supported by a compatible influx of natural and purchased energies.

As fossil fuel supplies dwindle natural energy resources of the coast

become even more important. The coast is a junction between land and

sea; it is here that energy flows originating from inland sources (such

as river waters with their kinetic and chemical energies) mix with wave

and tidal energies from the ocean. The shallow aspect of estuaries

tends to concentrate these energies for utilization in ecological and

geological work processes.

These highly productive coastal areas, with their well-flushed

waters and scenic vistas, have generally attracted dense human


settlements. More than 50% of the population of the United States is

located in counties bordering the oceans and Great Lakes (Ketchum,

1972). Power plants require large volumes of water for condenser

cooling, and the Federal Power Commission (1971) has indicated that

some 374,000 m /min (220,000 cfs) of cooling water would be needed in

the U.S. for power plant cooling in 1975. Since coastal regions offer

an abundant supply of cooling water and have attracted much of the

urban development that demands electricity, power plants have been

sited with increasing frequency along the coastline. At least 30% of

the water pumped through steam electric power plants is coastal water

(Federal Power Commission, 1971).

Estuarine ecosystems contiguous to these electric generating

stations are subjected to new conditions that result from pumping of

cooling water, thermal discharges and other influences associated with

the power plants. After a transition period the affected ecosystems

are modified or replaced in adaptation to these altered energy con-

ditions. In planning for a compatible coupling of power plants and

estuaries, it is necessary to understand the character of these new


Interface Ecosystems and Environmental Technology

A choice exists between developing technological systems or

interface ecosystems to connect power plants and estuaries.

Interface Ecosystems

At the interface between areas of human activity and natural

environments are a variety of new ecosystems, which couple the energies

of nature with those of man. These ecotonal regions have unique

characteristics arising from the special combination of natural and

fossil fuel-based energies which drive them. Odum et al. (1977) have

termed this general category of systems as "interface ecosystems."

These systems channel and transform energies eminating from human

processes so that they can be exploited by natural systems, and they

may buffer downstream ecosystems from the stress of man's wastes.

Reciprocally, the interface ecosystems can concentrate natural energies

for use by man.

Some of the organisms in the ecosystems receiving these wastes

are stressed and may be eliminated from the system. However, through

the trial-and-error process of self-design, other species are intro-

duced and become component parts of the interface system, adapted to

tolerate and use the energies in these waste discharges. Thus, new

systems, with specialized complements of biotic components and other

properties intermediate between the wastes and original environment,

emerge at the boundaries between man and nature. For the coastal zones

of the U.S. Odum et al. (1974b) have categorized and described some of

these interface ecosystems. Recently, a number of projects have been

undertaken in attempts to identify and domesticate ecosystems for waste

recycling and other purposes so that they could be utilized system-

atically to reduce environmental impact and save money (Odum et al.,

1970; Ryther et al., 1972; Kuenzler et al., 1973; Valiela et al., 1975;

Odum and Ewel, 1974).



Power Plant Canals as Interfaces

Large canals which carry cooling waters to and from the power

stations are often associated with estuarine and coastal electric power

plants. The ecological systems that develop in canals are important

components at the interface between power plant and estuary. They allow

the plant buildings to be set-back from the shoreline area, and may

separate cooling water intake and discharge points so as to minimize

recirculation. Intake canals may extend into offshore waters which are

cooler in the summer, thus allowing condenser-turbine systems to be

more economically designed for lower back-pressure, but such protrusions

into open water can cause alterations of local hydrographic patterns.

Canals may also function as channels and ports for fuel barges. Cooling

water canals are generally 50-100 m wide. They are usually deeper

than adjacent aquatic ecosystems, but have a larger shoreline to sur-

face area ratio. Rip-rap or talus materials often line the periphery

of the canals to prevent bank erosion, and this substrate can provide

a good habitat for benthic communities. The constant flow of cooling

water contributes to the metabolism of canal ecosystems, keeping them

well flushed and generally well fed.

Heated effluent canals often attract nekton communities during

cooler months, and are noted for excellent sport fishing (Nugent, 1970;

Landry and Strawn, 1973; Moore et al., 1973; AEC, 1973a). Incurrent

canals, however, channel fish to their death on the rotating screens

which filter the cooling water before it flows into the plant. Extreme

summer temperatures often exclude fish from the effluent canal (Nugent,

1970; Clark and Brownell, 1973; AEC, 1973a),while unexpected shut-downs


of power plants in winter can cause cold-shock mortality to fish (in

the canal) which would normally migrate to warmer, offshore waters in

the autumn (Young, 1973; Raney, 1971; Clark and Brownell, 1973). Table

1 lists some of the major coastal power plants in the U.S. with cooling

canal systems. These canals range in length from <1km to nearly 10 km.

Environmental Technology

In the past 50 yrs in the U.S., large sums of money and energy

have been invested in waste treatment technology to alleviate some of

the adverse environmental effects of human waste products. The simplest

of these treatment schemes are themselves ecosystems (such as sewage

lagoons) and involve only small flows of money and fossil-fuel-based

energies to subsidize natural recycling processes. These interface

ecosystems are often highly successful and economically sound (Bartsch

and Allum, 1957). However, during the recent period of growth in the

U.S., the trend has been to bui.'d m're sophisticated, more expensive

technological treatment plants, which s.i stitute fossil fuel energies

for the energies of nature to acceler;ct 'jaste recycling. In some of

these "environmental technologies" :.uch as tertiary sewage treatment,

natural nutrient materials may be virtually removed from biogeochemical


Electric power generating plants are high-energy nodes in the

network of human activities. Construction and operation of power

plants constitute a major energy and economic investment in a region

resulting in large waste energy residuals. In planning for coastal

power plants, alternatives of technological cooling should be compared


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with the alternative of using ecosystems which develop in power plant

cooling water canals as ecological interfaces. To make wise use of a

region's natural resources, it may be necessary to determine what is

the best mix of natural and fossil fuel energies in "interface" areas.

Questions on Roles of Coastal Power Plants

The following questions are addressed in this study.

1) What are the useful environmental planning techniques for

optimizing power plant designs toward a viable regional


2) What are the major effects of an existing two-unit power plant

on the nearby coastal ecosystem? How can these be evaluated

in energy terms for comparison?

3) What additional effects are likely to occur with the expansion

of present power plant facilities to include a third generating


4) What are the main characteristics of cooling water canals as

interface ecosystems?

5) What are the relative trade-offs between the ecological modi-

fications resulting from human activities and the environmental

technologies which attempt to ameliorate such modifications?

Is investment of capital into these environmental technologies

a competitive use of energy resources?

6) Defining an "energy quality ratio" as the energy cost of

transforming one energy form to another divided by the heat

calories in the original energy flow, what are the relative

"qualities" of natural energies supporting a coastal region?


7) What are the relative qualities of energy processed by higher

trophic-level organisms? How can energy quality calculations

be used as a scale to evaluate the effects of power plants on


8) What are major energy sources supporting a coastal power plant's

region? How does the addition of new capital inputs to the

region (in the form of cooling towers or expanded generating

capacity) affect the balance between fossil fuels and natural

energies therein?

Other more specific questions are also investigated.

9) What are the effects of temperature, turbidity and current on

ecosystems in the discharge canal at Crystal River? How will

these effects be altered when the third generating unit becomes


10) Does the intake canal serve as a major habitat for nekton

which are impinged on the power plant intake screens? Does

the canal act to concentrate nekton from adjacent estuaries?

How will this be affected by operation of the third unit?

11) Can a two-station diurnal oxygen method for measuring com-

munity metabolism be used to estimate tidally influenced,

stratified coastal systems?

Before reporting results of the study of these questions, literature

and unpublished reports are reviewed on environmental effects associ-

ated with coastal power plants in the U.S.


Previous Studies of Interactions Between
Power Plants and Estuaries

In recent years much information has been provided, documenting

and describing the effects of power plants on adjacent aquatic eco-

systems, although a large portion is in contract reports. Much of the

work describes the effects of elevated temperatures on the physiology

and behavior of particular species, and only recently has there been a

major effort to characterize power plant effects at the ecosystem

level. Indices of plankton and community metabolism may best indicate

the health of an ecosystem (Odum, 1967). The overall energy response

of estuaries to power plant discharges can be described with produc-

tivity and respiration field measurements. In addition, several

investigators (Tarzwell, 1972; Clark and Brownell, 1973) have suggested

that ecological problems resulting from thermal discharges may be less

significant than problems of plankton entrainment and nekton impinge-

ment at the cooling water intake. A brief review of the accessible

literature on community metabolism, zooplankton entrainment and nekton

impingement follows.

Power Plant Effluents and Community Metabolism

Eppley (1972) reviewed a large number of papers investigating the

effects of temperature on metabolism and growth of phytoplankton in the

sea and indicated that with increasing temperatures photosynthesis

increased up to about 30-350C and thereafter decreased. The effect of

temperature on photosynthesis was reduced greatly under conditions of

limited light and nutrients. In a review of studies at various thermal


springs, Brock (1970) showed that extreme temperature inhibited the

functioning of even these steady-state climax systems. Maximum algal

net production occurred at slightly higher temperatures than for gross

production, probably because animal grazers were excluded at the very

high temperatures.

A general pattern observed for seasonal responses of photosynthesis

to power plant operation in temperate climates is a wintertime stimula-

tion of metabolic rates in discharge areas, with suppression of produc-

tivity occurring in the warmer months. Warinner and Brehmer (1966)

using both carbon-14 (C-14) productivity and oxygen bottle methods

described this pattern at the York River estuary in Virginia. Smith

et al. (1974a),Brooks (1974) and Brooks et al. (1974) reported C-14

measurements of phytoplankton at four mid-Atlantic power plants (3

estuarine sites) and concluded that productivity was generally increased

by almost half in the colder months (daily mean temperature < 200C), but

decreased by 30-50% during the summer. Similarly, Carpenter et al.

(1974a)found that C-14 productivity of discharge waters was about 75%

less than controls in the summer and 35% less in the spring, but 110%

greater in the winter and 15% greater in the autumn. M.C. Miller et al.

(1976) observed up to 48% decrease in C-14 productivities during summer

but slight stimulation in the winter. Lauer et al. (1974), again

using net C-14 uptake as an index, measured a 40-67% decline in photo-

synthesis of phytoplankton as they passed through the Indian Point

power plant on the Hudson River in the summer and spring, whereas no

change was detectable in the winter.

Previous studies, however, did not always indicate beneficial

effects in winter and detrimental effects in summer. At two estuarine


power plants in Maryland, for instance, Mihursky (1971) measured

a small (13%) reduction in net phytoplankton productivity in the summer,

whereas Flemer (1974) found marked photosynthetic depressions (on the

order of 95-98%) resulting from power plant operation in September.

Gurtz and Weiss (1974) observed reduced C-14 production of heated

samples in all seasons. A simulation model by P.C. Miller et al. (1976)

indicated about 10% decrease in net productivity accompanying a 100C

temperature increase for mangroves. Morgan and Stross (1969) indicated

a 15% decline in summer phytoplankton production at Chalk Point,

Maryland (for temperatures 230C) while winter photosynthesis was un-

affected. However, photosynthetic rates for laboratory incubations at

80C above control at winter temperatures were increased by half,

possibly indicating mechanical or chlorine stress to entrained phyto-

plankton (in addition to temperature effects). Fox and Moyer (1973 and

1975) reported results which indicate a possible buffering effect of

discharge canals. They found a small decrease in productivity across

the Crystal River power plant condensers, in April and June, but by the

time the thermal effluent had traversed the length of the discharge

canal, C-14 productivity was well above the level at the intake station.

M.C. Miller et al. (1976) showed similar recovery trends in the dis-

charge canal at the James Stewart generating station on the Ohio River.

Hiroyama and Hirano (1970), Grayum (1973) and Tilly (1974) found

virtually no effect of temperature on C-14 phytoplankton productivity.

Tilly measured oxygen consumption of concentrated samples and found

higher rates of plankton respiration in heated discharge waters.

Metabolism of benthic plants and whole communities affected by

power plant effluents have been reported for a few cases. Cory (1974)


found a slight increase in community productivity and a 70% increase in

total respiration before and after initial operation of the Chalk Point

plant, but factors other than the power plant (such as increased sewage

input) may have contributed to this change. Jacobson (1976) found

productivities in the Connecticut Yankee discharge canal almost two-

thirds higher than in the adjacent estuary near the power plant intake,

especially during winter months. The only other field measurements of

ecosystem metabolism at a power plant were done at Crystal River,

Florida, where Smith (1976) found a 50% reduction in total productivity

in the shallow bay near the discharge plume, and McKellar (1975)

observed consistently higher turn-over rates and found a significant

15% decrease in total metabolism of the heated outer bay in the Fall.

Young (1974a)found a slight stimulation of net productivity in the

thermally affected salt marsh near the discharge, but decreased gross


Thorhaug (1974) measured reductions of turtle grass net production

ranging from 50-100% in an area (3x 105 m2) adjacent to the Turkey Point

discharge. This community has apparently been partially replaced by

another benthic plant assemblage, but its production has not been

reported (Thorhaug, 1974). Vadas et al. (1976a) found macrophytic

algal standing stocks reduced by about 76% since initial operation of

the Maine Yankee power plant, but growth rates were not significantly

affected. They (Vadas et al., 1976b) also observed both biomass and

net production of Spartina alterniflora decreased by about 44% in the

areas affected by power plant discharge. Using the seagrass growth and

branch-density data of Ford et al. (1975), Kemp (1976) estimated

benthic productivity for the estuary near the Anclote power plant in


Florida. Summer net production in the effluent area was depressed by

22% and winter production increased by about 35%.

Several microcosm studies of thermal effects on aquatic ecosystems

have been published. Beyers (1962, 1963) observed that pond microcosms

with production and respiration balanced and closed mineral cycles

showed little effect of short-term 70C temperature elevations. Phinney

and Mclntire (1965), however, found that community respiration of

nutrient rich laboratory streams varied directly with temperature, and

gross productivity also increased with temperature, as long as adequate

light was available. With insufficient light no temperature effect was

found, and it may be that the added thermal energy in heated ecosystems

can be exploited only if light and nutrients are also readily avail-

able. Kelley (1971) studied microcosms adapted to different tempera-

tures and also found a direct relationship between mean temperature and

microcosm metabolism over the temperature ranges of his experiments.

Copeland and Davis (1972) reported an anomalous pattern of increased

community metabolism of heated pools in spring and summer, but decreased

in winter. For the same microcosms Copeland et al. (1974) measured

increased net algal production throughout the year, and Davis (1971)

found a direct relationship between temperature and community respira-

tion up to 300C.

Zooplankton Entrainment

Numerous investigators have reported mortalities incurred to

zooplankters as they pass through power plant condenser systems. The

level of mortality was a function of type and standing stocks of


zooplankton, temperature rise across the condensers, maximum temperature

experienced, length of time held at elevated temperature, and other

factors, including exposure to chlorine and mechanical shear. Mortality

rates varied, but at a given site summer values were generally highest.

Davies and Jensen (1974) observed copepod mortality rates between

0 and 70%, while Gonzalez (1973) found two congeneric species of

Acartia having mean summer mortality rates of 35 and 71%, with the more

tolerant species being naturally dominant in the estuary during warmer

months. Mean annual rates of zooplankton kill were 18.3 and 25.5% at

two Lake Ontario plants (Storr, 1974). Very low mean rates of about

6% were reported by Lackey (1974) for the Turkey Point plant in Florida

and by Icanberry and Adams (1974) for four coastal power plants in

California. Heinle (1969) and Heinle et al. (1974) measured no sig-

nificant copepod mortalities except during plant chlorination cycles.

Carpenter et al. (1974 a, b), on the other hand, have measured annual

mean rates of holoplankton kill at 70% and they attribute this primarily

to a mechanical stress as inferred from tests with circulating water

being pumped when the power plant was not operating. Similar inferences

have been drawn by others (Industrial Bio-test, 1972; Benda et

al., 1975). Carpenter and colleagues calculated that 0.5% of the

zooplankton production in all of Long Island Sound is cropped by power

plants, while Polgar et al. (1976) estimated 2% loss of zooplankton due

to entrainment at power plants on the Potomac River. For the Crystal

River plant Alden et al. (1976) reported about 10% copepod mortality

during most of the year, but this rate increased to 80% at mid-summer,

and this agrees well with the summer mortality rates described by

Reeve (1970) and Reeve and Cosper (1970) at Turkey Point. Benda and


Gulvas (1976) observed direct relationship between mortality rate and

ambient temperature, with mortality ranging from 6-15% when temperature

< 340C but ranging from 75-90% when temperature > 340C. Drew (1975),

continuing the earlier work of Fox and Moyer (1973) at Crystal River

power plant, showed that adenosine-triphosphate (ATP) changes between

intake and discharge were an adequate index of long-term trends of

zooplankton entrainment effects, although they did not correspond well

with daily mortality rates as measured by Alden (1976).

Entrainment mortality inflicted on meroplankton (larvae of larger

animals) appears to be generally higher than for copepods. Kennedy

et al. (1974 a, b) found that bivalve larvae suffered 63-100% losses

at laboratory temperature elevations of 10-120C for about 1 hr, while

Nelson (1973) indicated about 80% mortality for larvae of the Pacific

oyster. Neomysis shrimp were killed at a rate of 30-50% at Indian

Point in spring and summer (Lauer et al., 1974) and at rates up to 67%

throughout the year at a plant in the San Joaquin Delta of California

(Chadwick, 1974). Marcy (1971, 1974) measured extremely high levels

of mortality (93-100%) for fish larvae and juveniles passing through

the Connecticut Yankee cooling system from May to August, and 80% of

this loss was due to mechanical stress. He calculated that this

mortality represented about 4% of the total populations flowing past

the plant intake. Menhaden and river herring juveniles were entrained

at an estimated rate of 7-165 million per day at Brayton Point in the

summer of 1971 with complete mortality, and most of these had been

physically mascerated (EPA, 1972). Chadwick (1974) found striped bass

larvae mortality rates at 5-58% in the laboratory for a temperature

rise of 60C and ambient spring or fall conditions.


Nekton Impingement on Intake Screens

Very little published information exists regarding the rates and

types of fish which are killed by impingement on power plant intake

screens. Most of the existing information is in the form of environ-

mental impact statements and supporting research reports. Clark and

Brownell (1973) summarized some of this unpublished literature and

found impingement rates ranging from 350,000-6 million fish per year

including a variety of species such as white perch, menhaden and river


Table 2 summarizes impingement data available for coastal and

estuarine plants in the U.S., and there appears to be a general trend

for maximum impingement rates to occur during the winter, even though

estuarine nekton populations probably tend to be greater in the summer.

Landry and Strawn (1974) sampled the intake screens at the P.H. Robinson

plant on Galveston Bay and found that impingement rates corresponded

well with fish stocks measured in the intake canal by otter trawl. The

nekton impinged were predominantly menhaden, croaker, anchovy and blue

crab, and even though screened fish were sluiced into the discharge

canal, mortality rates appeared to be high. Grimes (1971, 1975) made

monthly observations of impingement at the Crystal River plant in 1969

and 1970, while Snedaker (1974b)continued to do weekly sampling for

1972 and 1973 at this same plant. In both studies mid-winter peaks in

entrapment were observed, but Grimes' data, although consistent between

years, indicated substantially fewer fish killed than did Snedaker's

data. This difference is possibly attributable in part to the more

comprehensive sampling techniques of Snedaker.


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Clark (in Clark and Brownell, 1973) made experimental observations

at the Indian Point Plant on the Hudson River under varied pumping

conditions. Impingement rates increased markedly when intake water

current exceeded velocities of about 18.3 m/min (1 fps). Based on life

history information and certain assumptions about impingement susceptibil-

ity, Lawler et al. (1974) and C.A.S. Hall (1975) developed simulation models

to predict the impact of power plant entrainment mortalities on the

striped bass population in the Hudson River. The impacts of larval

entrainment on adult populations predicted by these models range from

virtually none in the former to a 50-60% decrease in Hall's model under

conditions with all planned power plants in operation.

Review of Methods for Environmental Planning and Evaluation

Rational decisions between alternative sites for power plants and

alternative thermal (and other) waste management schemes require:

first, a method for predicting the effects of each option on the

regional systems and on the adjacent ecosystems; and second, a technique

for comparative evaluation of economic and ecological effects to facil-

itate selection of the best plans. Techniques which have been used in

decision-making processes for environmental planning and impact

assessment are reviewed under the following headings: evaluation

techniques; predictive models; and methods that couple evaluation and


Evaluation with Economic Analysis

The method of comparative costs is used to choose between


alternative economic designs for human systems, where the option having

the lowest total monetary cost is considered preferable. Burnham

et al. (1968) employed the technique for power plant siting in the

Pacific Northwest and considered environmental effects only in terms of

cost to mitigate them. A multi-objective form of this technique was

modified by Isard et al. (1972) to select between various recreation-

complex options, where environmental costs in adjacent estuaries were

compared in terms of economic cost of equivalent fishery loss.

A more complex version of cost analysis is the benefit-cost analy-

sis (BCA), widely used by the Corps of Engineers, Soil Conservation

Service, Bureau of Land Management and others for public water resource

project evaluation. BCA attempts to achieve so-called optimum resource

allocation where a given resource is distributed such that the economic

output value of the particular use (marginal product) is greater than

or equal to that of any other potential use. The objective of most BCA

is to maximize economic efficiency and/or net economic output. Dollar

benefits and costs projected for the future are put in terms of

"present economic worth," based on the notion that, in an expanding

economy, money in the present can earn money in the future. The

relationship between benefits and costs can be expressed either as a

ratio (Eq. 1) or a difference (Eq. 3):

n B
B t=O (1 + R)t
ratio = (1)
n C

t=0 (1 + R)t

n B C
N t t (2)
t=0 (1 + R)



N = net benefits,

Bt = benefits at time, t,

Ct = costs at time, t,

t = time,

R = discount rate.

There is considerable controversy as to the proper discount rate to use

in converting time series of benefits and costs to present worth.

Larger discount rates favor economic events closer to the present, so

that future dollars are worth less than present dollars. Most federal

water resource projects are conceived with costs in the present and

benefits in the future, and the low discount rates which are commonly

used thus tend to increase the B/C ratio. Environmental costs (at

present or in the future) are seldom considered with this method.

The details of the BCA method are summarized in Howe (1971), James

and Lee (1971) and Prest and Turvey (1966). Maass (1966) suggested

that multiple objectives other than short-term maximization of economic

efficiency should be considered for this method. Haveman (1965) showed

the extreme effects of slight changes in the discount rate assumption,

and he calculated that over 50% of the federal project funds spent in

the southern U.S. between 1946 and 1962 would,.under one set of

reasonable assumptions, have been spent on projects with B/C ratio

< 1.0. A major criticism of this technique for environmental decision-

ing, however, is its inability to quantify environmental costs, which

are by definition external to traditional economic models. Etzold

(1973) contended that the willingness of consumers to pay for


environmental amenities is a measure of environmental values in the BCA.

However, MUller (1974) rejected this proposition on the grounds that

prices and values do not reflect the interrelationships between environ-

ment and economy, and that consumers operate primarily with short-term

interests in mind.

Evaluation with Subjective and Mixed Units

The National Environmental Policy Act (NEPA, 1969) established as

a national objective the development of cost-benefit methodologies which

consider ecological and economic values in environmental impact assess-

ment. In response to this, the former Atomic Energy Commission (AEC,

1972a) developed a benefit-cost technique for use in environmental

impact statements for nuclear power plants and other AEC regulated

projects. This method calls for the tabulation of effects both to

people and to nature for various project alternatives. Evaluations

are done in terms of different units of measurement ranging from

pounds/year, to acres, to rems/year, to hours/year, to dollars/year,

to qualitatively descriptive words, thus making a decision between

alternatives difficult because different kinds of effects are not

directly comparable.

Several methods have been suggested using a subjective common

parameter for comparison of environmental values with economic.

Helliwell (1969) proposed a technique which categorizes wildlife

resources into four classifications (production, potential production,

education, and recreation) and assigns an arbitrary index for these

which is based on such parameters as species diversity. The numerical


index, then, is subjectively convertible to monetary units. Cairns

(1976) indicated a similar subjective rating scheme to evaluate the

vulnerability of ecosystems to power plant effects. He used the

following criteria for this index: 1) susceptibility to irreversible

damage; 2) elasticity; 3) inertia; 4) resiliency.

Leopold et al. (1971) proposed the use of a large evaluation matrix

with natural system components as matrix rows and categories of impact

as column headings. The matrix is used by assigning subjective numbers

to each category at the intersections of rows and columns in the matrix

to indicate the relative magnitude and importance of each impact on a

system component. However, intersections of the Leopold matrix do not

consider chains of interactions between environmental variables and

feedback properties. Nonlinear responses such as synergistic or

internally-damped behavior can not be taken into account. Only environ-

mental effects are considered, and no format is offered for comparing

various economic and environmental factors.

A modification to this basic matrix evaluation technique is the

"Delphi process" proposed by Dee et al. (1973), which employs an

interdisciplinary "panel of experts" to decide on the functional rela-

tionships and relative importance of matrix categories. The method

allows consideration of interactions between parameters, but suffers

from its subjective nature. Thus it would not be too surprising if

one group of "experts" were to develop a system of functional relation-

ships (for each position on the matrix) that was vastly different from

that developed by another group of "experts" (depending on their

interests, biases, and points-of-view). Cordara and Malloy (1973) used

a similar method to evaluate potential coastal power plant sites on

Long Island.


Evaluation with Maps of Spatial Parameters

Another qualitative technique which introduces spatial relation-

ships for environmental, social and economic parameters between sub-

systems has been developed by McHarg (1969 a, b). Here, natural and

urban lands are inventoried and categorized by present and potential

land uses. Separate overlay maps are made with varied shading to

indicate compatibility of given lands for development alternatives

according to estimated effect of, and on, each of several factors such

as soils, hydrology, topography, vegetation, economic activities,

cultural uses, and public health. Thus, the most suitable areas for

given land use are those with darkest (or lightest) shading from a

composite of overlaid maps. Zieman (1971) used a modified ver-

sion of this procedure to evaluate eight highway alignment alternatives

in north Georgia, and they employed a random error-weighting scheme for

these parameters, the effects on which are not precisely calculable, to

indicate sensitivity of analysis. They found that their evaluations

for each of the four best routes were not statistically differ-

ent. Murray (1972) and Niemann and Miller (n.d.) have employed a

computerized mapping technique for highway location planning based on

the "McHarg concept" where spatial cells were defined with dimensions

of 4 and 102 ha (10 and 250 ac) respectively. Subjective weighting

scales for various parameters and various degrees of impact are pro-

grammed into computer mapping routines which use 10-12 grades of

shading. These techniques allow the introduction of spatial factors in

environmental planning; however, they require subjective weighting

scales and do not consider interactions between land-use factors.


Evaluation with Operations Research Methods

The optimization techniques of operations research have found

several applications in environmental planning, and Swartzman (1972)

reviewed the concepts and utility of these methods for ecosystem manage-

ment. The most versatile and commonly used method is the linear

programming version. This is a static methodology which maximizes or

minimizes an objective function, F (within a given set of physical

constraints), linearly relating system variables at a given time.

Solution techniques generally employ algorithms which search for that

vertex on the boundary determined by constraint equations which maxi-

mizes the objective. This can be expressed mathematically in subscript


maximize (min) F = c. x (3)


a. x < b (4)
i=l 1i 1 -- j


x. > 1 for all i
1 -


a., = coefficients of constraint functions

b. = limits of constraint
ci = coefficients relating variables in objective function

x. = system variables.

The major problems with this procedure are that it is limited to the
The major problems with this procedure are that it is limited to the


use of linear relationships between variables, and that time is not an

explicit independent variable. As commonly applied, objective functions

are formulated in monetary terms and do not consider all environmental

values (although this could be done). Rothschild and Balsiger (1971)

have used this method to allocate salmon harvest among the days of the

salmon run to maximize the value of catch while providing sufficient

escape from harvest to maintain fishery stocks. Wardle (1965) used

linear programming to maximize net, discounted revenue from harvest of

mixed hardwood and conifer forests by optimizing planting and cutting


Non-linear and stochastic optimization programming methods are

available; however, solution techniques for even simple non-linear

systems are limited. Probabilistic systems often require solution via

Monte Carlo techniques which are expensive and not necessarily repro-

ducible. Dynamic programs enable optimization over a time course which

may be subjected to model policy decisions at each stage in the process.

A basic, though not necessarily realistic, assumption underlying all

dynamic optimization programming is the Markovian property that, at each

step of a process, the next optimum stage is a function only of the

present stage and not of the previous history of steps. Dynamic pro-

grams are nearly impossible to solve for detailed, non-linear functions.

Swartzman (1972) developed a very large linear optimization program to

maximize deer harvest within a given state without overkilling the

population. Swartzman (1972) also conceptualized (but did not solve)

a non-linear optimization model utilizing the subjective environmental

quality units of Dee et al. (1973) for watershed management.


Predictive Models: Input-Output

Wilson (1968) and Bishop et al. (1974) reviewed some of the models

which have been used in urban and regional environmental planning. An

accounting model procedure developed for economic analysis by Leontieff

(1970) has found some application in environmental planning. This

input-output method allows examination of general steady-state con-

ditions of production, and has often been used to estimate the impact

on all system sectors arising from a change in final economic demand

in one or more sectors. In vector form this is expressed as:

Q = A Q + F (5)


Q = vector of output value for all sectors

F = vector of final demand (i.e., inputs which are not
strictly a function of output)

A = matrix of input value coefficients.

This expression is then solved for Q so that,

Q = (I A)-1 F (6)


I = identity matrix.

Isard et a. (1972) developed an input-output matrix which couples

ecological processes (as monetary value of fisheries) to economic

sectors and evaluates recreation alternatives in terms of economic

efficiency. Wilen (1973) constructed a similar, general input-output

model linking an ecological submodel to an economic submodel with

energy and material exchanges between the two. He suggested that


using models such as this to estimate the impact of changes in the

economic sector on ecological productivity (in energy units) and com-

paring this to the modified economic productivity (in money units).

The main drawback of input-output models is that they must assume

linear functions, and calculations can only be done for static condi-

tions. Wilson (1968) also pointed out that the final demand sector

involves complex processes which should, themselves, be modeled. The

input-output technique does not explicitly consider external energies

which drive the production processes in each sector and therefore is

limited in addressing questions which pertain to these external factors.

Simulation Models for Prediction

Simulation models describe systems as sets of differential, dif-

ference, integral or summation equations. They simulate temporal

dynamics, with time as an independent variable. They can be made to

simulate spatial characteristics, either aggregating state variables

into clustered subunits of dependent variables, or as independent

spatial variables, portrayed with partial differential equations. The

use of simulation models for describing ecosystem dynamics has become

relatively widespread (e.g., Patten, 1971; 1972a,b; 1975a), but a

recent comprehensive review by Wiegert (1975) indicates that only a

limited number of these are finding specific application to environ-

mental planning. A few highlights of those ecological models used in

decision making are mentioned here.

Chen and Orlob (1975) developed aquatic ecosystem models to predict

effects of alternative sites for sewage treatment facilities in the San


Francisco Bay San Joaquin Delta region, and to study management

alternatives for Lake Washington. Kelley (1976) reported on a model

which predicts the effects of waste discharges on the Delaware River

estuarine ecosystem. O'Connor et al. (1975) described several appli-

cations of their plankton model which relates waste discharges to

eutrophication processes, and Park et al. (1975) have developed a com-

plex model to study resource management problems in Lake George, N.Y.

The EPA has been long involved in water quality modeling for basin

planning impact assessment, and a guidelines publication (EPA, 1971)

listed several of the commonly employed "prepackaged" models. At

present, a large portion of the models for ecosystem understanding and

management are being developed under the auspices of the International

Biological Program (IBP), and most of these are included in Wiegert's

review and are reported in the proceedings of a symposium series edited

by Patten (1971a, 1972a,1975). Proceedings from two other symposia

directed more at modeling for management problems are also available

(Russell, 1976; Middlebrooks et al., 1974).

Mar and Newell (1973) have provided an assessment of selected enivronmen-

tal modeling efforts supported by the National Science Foundation. They

said that many models had been developed with insufficient scientific

basis and large-scale models tended to lack conceptual generality.

Often large system models had been modified in favor of reduced process-

or component-models, and even management models were developed without

proper cognizance of model users. Mitchell et al. (1976) reported their

evaluation of three IBP modeling programs, and indicated a serious

shortfall in terms of model accuracy. They also concluded that several

modeling groups had opted for models of components rather than large


scale systems. Very few of the ecosystem models developed for manage-

ment problems are well validated, particularly the large scale models

(Mitchell et al., 1976). They are, nonetheless, tools of promising

potential for predicting effects of alternative management schemes.

A few regional-level models have been recently developed. Watt

and Wilson (1973) used a model with 14 subroutines to investigate var-

ious submodel processes involved in California planning policy decisions,

but initial plans to build an integrated regional model were modified in

favor of operative submodels (Mar and Newell, 1973). Craven et al.

(1973) developed a simulation model comprised of four submodels:

socio-economic; socio-political; ecological; and land-use. They tested

the effects of various land development patterns in the Knoxville,

Tennessee area. Antonini et al. (1974) coupled models of land-use and

water budget to predict the effects of different development policies

on reservoir sedimentation in a region of the Dominican Republic. This

model, though somewhat limited in scope, demonstrated the marked dif-

ference in sedimentation rates resulting from various watershed

practices. Koenig (1973) reports on five specific short-range resource

management studies using decomposed models with the intention of

reconstructing the system of study piecemeal. These studies range

from sewage recycling to power plant siting.

Environmental Analysis with Coupled Modeling and Evaluation Methods

As described above, Isard et al. (1972) combined: a "gravity

model" (in which the product of two populations is divided by a power

function of the distance between population centers) to estimate demand;


an economic and ecological input-output model to test the economic

effects of project options; and comparative costs methods to assess

alternative marine recreation-complex designs in Duxbury Bay, Massa-

chusetts. Russell and Spofford (1972) reported on an input-output

model cast in a linear optimization program to maximize economic effi-

ciency. The residuals of the input-output matrix were put into an

environmental model to simulate waste dispersion and ecological damage,

and the optimization model traded-off between environmental losses (as

effluent charges) and industrial production output. The concepts of

this analysis scheme were extended to a study of the Delaware River

estuary (Spofford, 1973), where a complex linear optimization program

linked economic costs to waste discharges predicted from an ecosystem

model (Kelley and Spofford, 1977).

Bishop et al. (1974) reviewed the work of Myers (1973) on the

Arizona Trade-Off Simulation Model which has been used by the state

planning office to investigate policies on growth, environmental impact

and land use. The model allows subjective trade-off between economic

values (measured as employment) and environmental values (measured in

the environmental quality units of Dee et al., 1970). Pavelis (1961)

and Castle (1961) have suggested combining linear programming and

simulation models with benefit-cost analysis for water resource planning.

They argued that prediction of future conditions under alternative

projects has been the weakest part of the benefit-cost analysis.

Hydrologic simulation models such as that of Beard (1968) are available

for predictive use in benefit-cost analysis but these do not consider

ecological values.

Another regional simulation model for the Vancouver area was



created by Goldberg et al. (1971) consisting of several submodels to

simulate the effects of various public policy decisions. The submodels

can be used to generate various indices as discussed by Holling and

Goldberg (1971), and policy decisions are built into the model when

indices exceed thresholds. Robinson (1973) attempted to combine stan-

dard air and water quality models with input-output analysis to

investigate the effects of waste abatement on the regional economy of

the lower Connecticut River basin.

Cooper (1969) suggested coupling of optimization and simulation

models. Swartzman and Van Tyne (1972) used a combination of a non-

linear simulation model (employing stochastic forcing functions) with

a linear optimization program to develop annual management schemes for

Australian arid grassland-shrub range. The two programs were coupled

by optimizing "management coefficients" in the simulation model year-

by-year. The system was designed to maximize long-term profit over

10 yrs with policy adjustments at annual intervals, and the year-by-

year management program produced 12% more profit than constant manage-

ment. The utility of this coupled model was further developed by

Jameson (1973). Considering the power plant question, Buchan (1972)

developed a statistical model of an aquatic ecosystem to simulate

effects of alternative waste heat discharge methods on species diversity,

and proposed that information from models be channeled directly into

the political-legal decision processes.

Recently, at the University of Florida several studies combining

regional and/or ecological simulation models with energy calculations

and cost-benefit analysis have been applied to environmental planning

problems. Mitsch (1975) modeled the effects of sewage recycling in


cypress domes and lake ecosystems in Florida and used energy cost-

benefit to show that this sewage treatment was more economic and

energetically adaptive than conventional tertiary treatment. Boynton

(1975) used an ecosystem model and a regional model to test the effects

of several planning policies on an oyster fishery and a county economy.

He also applied energy calculations to evaluate plans for an island

development and a dam project. In a large comprehensive study Odum and

Brown (1975) used these techniques to evaluate alternative land, fuel

and water use policies in South Florida in terms of a competitive

balance between the energies of nature and those of man.

Description of the Study Area

The theoretical questions raised in this study were considered for

the specific case of the Crystal River power plant on the northern Gulf

Coast of peninsular Florida.

The Powershed

The Crystal River plant is a major generating facility for the

Florida Power Corporation (FPC). The two units presently operating at

Crystal River comprise about 21% of the company's generating capacity,

and the third unit will increase this to 35%. The Crystal River

station is connected into the company's electric power grid which

serves a 32-county region in the northwestern part of Florida as shown

in Fig. 3. At its present capacity FPC produces about 26% of the

state's electric demand and the addition of Unit 3 will raise this to

about 32%. Once it enters into the grid system, electricity from

Figure 3. Map showing some geographic features of region
served by Florida Power Corporation.



Crystal River is indistinguishable from that generated at any other

plant, and it may be consumed at any point in this "powershed." Direct

economic and environmental effects of electricity generated at this

power plant are felt throughout the powershed.

The FPC powershed covers 25 whole counties and varying portions of

seven others. It is relatively rural part of Florida, including some

30% of the state's area but only 27% of its people (BEBR, 1975).

Agriculture is important with about $450 million worth of crops sold

in 1969, representing 40% of the state gross crop sales (BEBR, 1975).

Most of the agricultural production in the powershed is from mixed crop

truck-farms. Pine flatwoods were the dominant natural vegetation in

the region and much of this land has been converted to pine plantation.

The region includes the Suwannee River and the lower part of the

Apalachicola River, and numerous lakes, including Lake Apopka and

Orange Lake, are scattered throughout the area. There are various

moderate-sized cities in the powershed, and the largest of these are

Tallahassee, St. Petersburg and Orlando. Disneyworld is the central

tourist attraction in the region which hosted an estimated 39% of the

state's visitors in 1972 (Div. Tourism, 1972).

The region of study occupies about 496 km (308 mi) of the state's

total 2160 km (1350 mi) of smoothed length of coastline (BEBR, 1975),

and this coastal edge extends from Tampa to Apalachicola (see Fig. 3)

and includes the largest stretch of relatively undeveloped coast in

Florida. Commercial fishing is important in this area, but most of the

catch is dominated by lower market value species such as blue crabs and

mullet. However, valuable shrimping enterprise is important in the

region, and the Apalachicola Bay oyster industry is the second largest


in the country. The total marine area for the Crystal River power

plant region is designated as the Gulf Coast strip within the powershed

boundaries extending gulfward to where freshwater runoff is mixed to

95% seawater. This defines a coastal area 17 km (10 mi) wide and

496 km (308 mi) long.

The Power Plant and Estuary

The plant site shown in Fig. 4 is in Citrus County about 12 km

north of the town of Crystal River. During this study two oil-fired

generating units were in operation with a combined capacity of 897

megawatt (Mw) and a once-through cooling water flow of 2410 m3/min.

The maximum temperature rise across the condensers was designed at

6.10C (110F). Unit 1 began operation in July 1966, and Unit 2 in

November 1969. A third 855 Mw nuclear-powered unit is scheduled for

operation by the end of 1977. This unit will require an additional

2580 m3/min of cooling water and the combined system will have a net

temperature-rise of about 8.10C (14.50F).

The coastal shelf adjacent to the plant site has a shallow sloping

bottom (45 km to the 9 m contour) and extends relatively far (230 km to

the 100 m contour) into the Gulf of Mexico (Jones et al., 1973). This

area is part of what Tanner (1960) and Walton (1973) have classified as

the low wave-energy section of the Florida Gulf Coast. The topography

of this area is characterized by limestone karst, typical of this

portion of west-central Florida. The immediate coastal area contiguous

to the plant site is comprised of a series of shallow basins separated

by oyster reefs. Two major freshwater sources to the area are the

Crystal River 4.8 km to the south and the WithlacoocheeRiver 6.4 km to

Figure 4. Estuary adjacent to Crystal River power plant
showing intake and discharge canals, and locations
of field sampling stations.



,. CANAL-7,.


*, ,'. OYST


0 I 2


0 100



the north. The mean combined flow of these rivers was 3340 m3/min in

1974, which is about 1.4 times the present power plant circulating

water flow. The Withlacoochee River flows into the Gulf end of the

unfinished Cross-Florida Barge Canal (15.3 km long) at its eastern-most

extremity. Spoil islands from the Barge Canal continue about 6.5 km

into the Gulf, and these, as well as the cooling water canal dikes for

the power plant, influence local hydrographic circulation patterns.

The estuary adjacent to the power plant is characterized by five

ecological subsystems: 1) an inner bay; 2) an outer bay; 3) the salt

marsh; 4) the oyster reefs; and 5) the power plant intake and discharge

canals. After passing through the 4 km long discharge canal, the

heated plume flows over the shallow inner bay, which is about 1 m deep

and contains mixed benthic communities of sea grass, algae, oyster and

mud associations. Rising tides push the warmed water over the adjacent

tidal salt marsh, which is dominated by black rush, Juncus roemerianus.

Seaward of the inner bay are deeper outer basins (about 2 m mean depth)

in which plankton and oyster reef ecosystems become more important.

Oyster reefs, which comprise about 5% of the bay area are scattered

throughout the immediate offshore area.

The Cooling Water Canals

The intake and discharge canals have been cut through the salt

marsh and coastal bay systems west of the plant site, displacing

approximately 1.1 km2 of marsh and 1.9 km2 of bay (Fig. 4). The intake

channel extends from the plant about 12.5 km into the Gulf of Mexico,

and is laterally confined with double-bulk-heading for the first 5 km.


The mean depth of the intake canal is about 6.5 m compared to the 1-2 m

depth of the surrounding bays, and the width at mean low water (MLW)

varies from 90-110 m. The double-bulkhead portion of the discharge

canal extends approximately 2 km due west from the plant, and the total

length of the dredged channel is about 3.8 km. The discharge canal was

designed with a smaller cross-sectional area (4.5 m deep, 60 m wide)

so as to maintain a relatively high velocity, 20 cm/sec, and assure

adequate lateral flow entrainment and mixing upon discharge to the

shallow bay receiving waters. The intake canal is wider and deeper

than the discharge to accommodate the movement of fuel barges to and

from the plant, and its water velocity averages about 9 cm/sec.

The bottom material of both canal channels varies but is primarily

comprised of a clay-silt-sand matrix similar to the sediments of the

adjacent bays with organic content ranging from 3-6% dry weight

(Cottrell, 1974). The intake canal has wide, shoaled intertidal areas,

and its banks slope gradually until about 1-2 m mean depth, at which

point they become steeper (about 1:3) and continue to the channel

bottom. The substrate on the sides of both canals is dominated by

limestone talus material ranging from 0.1-0.5 m diameter, which com-

pletely buries the shelf in many areas. The sides of the discharge

canal are not shoaled and have uniform slope of about 1:1 to the base

of the channel (Carder et al., 1974b).

Approximately 47% of the water entering the canals is taken

directly from the deeper offshore systems, while 27% originates from

the area immediately south of the canal intake and the remaining 26%

is drawn from the nearshore shallow bay systems south of the canal

spoil bank. The warm, brackish nearshore water enters the canal in the


latter stages of an ebb tide, and this water precedes plantward in the

canal during low water, flood and high water tidal stages. During the

flood tide cooler, saline waters of Gulf origin enter the canal, forming

a pocket of less-dense water which moves down the canal and gradually

mixes with the underlying waters before being drawn into the plant

(Carder et al., 1974a). The canal waters, which have a combined resi-

dence time of about 24 hrs in the canal-power plant system, therefore

have characteristics of both nearshore and offshore ecosystems. The

intake canal water is generally clearer than the swifter discharge

canal water, but both canals regularly experience turbid waters re-

sulting from barge movement in the intake canal.

Previous Research at Crystal River

Prior to initial power plant construction at Crystal River very

few ecological investigations of this estuarine area had been reported.

Ingle and Dawson (1952), however, estimated oyster growth rates on

reefs near the present power plant site. Dawson (1955) later studied

the distribution of oysters at Crystal River in relationship to

hydrography. Phillips (1960) described the relative composition of

benthic macrophytes. During the early phase of power plant operation

(Units 1 and 2), the Florida Department of Natural Resources conducted

environmental studies in the estuary. Lyons et al. (1971) found benthic

invertebrates to be distributed near the power plant more in relation

to salinity than temperature gradients. Steidinger and Van Breedveld

(1971) studied the relative abundance and diversity of benthic algae

in the Crystal River area. They determined that control stations had


considerably greater species diversity than discharge stations, but

that the composition of the predominant algal community was about the

same in both areas. In a symposium on the effects of elevated tempera-

ture on oysters from Crystal River,Quick (1971) reported that prolonged

laboratory exposures of oysters to 350C resulted in decreases of

glycogen content and reduced gametogenesis (Burklew, 1971). However,

field measurements of temperatures of oyster tissue indicated that under

natural conditions temperatures approaching 500C were experienced by

oysters at low tide (Ingle et al., 1971). Nekton and other components

of the Crystal River estuarine ecosystems were studied by Grimes (1971),

Grimes and Mountain (1971), and Mountain (1972). They indicated that

growth and abundance of selected nekton species were not significantly

different between control and affected areas. In the shallow bays

species diversity of fish was higher in discharge areas during winter

but higher in the control areas during summer. As previously mentioned

Grimes (1971, 1975) also monitored fish impingement on the power plant

intake screens. Heavy metal concentrations were measured in oyster

tissues from intake and discharge canals, and there were significantly

higher concentrations of Zn and Cu in the discharge oysters.

With the planning of a third, nuclear unit at Crystal River, an

extensive ecological research program was initiated, and the present

study was a part of this effort. Standing stocks, distribution and

diversity of benthic macrophytes (Van Tine, 1974), benthic invertebrates

(Evink and Green, 1974), and nekton (Adams, 1974) were measured during

1973 and 1974. Migration of blue crabs was studied (Adams et al.,

1974; Oesterling, 1973, 1976), and the impingement of crabs and other

nekton, both juvenile and adult, on the power plant screens was measured


(Snedaker, 1974a,b). Food habits of adult and juvenile fish in the

bays were quantitatively investigated by Bolch et al. (1971), Adams

(1972) and Carr and Adams (1973). Sediment composition, distribution

and movement were examined by Griffin (1971) and Cottrell (1974), and

the estuarine hydrography was described in detail by Carder et al.

(1973, 1974 a, b), including the development of a computer model of the

thermal plume. Data on nutrients, organic matter, chlorophyll-a and

carbon-14 productivity have been provided by Gibson (1975) and McKellar

(1975). Zooplankton biomass, numbers and diversity were reported by

Maturo et al. (1974) in some detail, and zooplankton entrainment

mortalities were measured by Alden (1976) and Drew (1975), while

zooplankton respiration was reported by McKellar (1975). Total com-

munity metabolism was studied and ecological models were developed for

the bays (Smith et al., 1974b;McKellar, 1975; Smith 1976) and the salt

marshes (Young, 1974 a, b) near Crystal River. Lehman (1974) investi-

gated standing stocks, diversity and metabolism of oyster reef ecosystems

and used a simulation model to investigate relations between oyster

biomass, species diversity and oyster spat. Biomass, diversity and

trophic habits of fish inhabiting the tidal salt marsh creeks were

thoroughly studied by Homer (1974, 1976).


Three categories of methods were employed in this study:

(1) simulation models; (2) ecological field measurements; (3) and

calculations of energy cost.

Modeling Methods

Models were developed in this study to help determine: (1) what

field measurements were most important; (2) proper data organization

for overviews of systems; (3) energy relationships between system

components; (4) the consistency of theoretical concepts with empirical

facts as indicated through simulation; and (5) how estuarine systems

might respond to changes in power plant operation. Models were con-

ceptualized for systems at three scales, including the region, the

estuary and the power plant canals. Computer simulations were done for

the estuarine model.

Conceptualizing and Evaluating Models

Important storage components of the system being modelled were

identified and incorporated into the model. Diagrammatic models were

conceptualized using the energy circuit language symbols of H.T. Odum

(1971, 1972c). As suggested by Odum (1972b) and Wiegert (1975),

initial diagrams in this study included as much detailed understanding



of the system as possible, but in subsequent drawings, related com-

ponents and pathways were grouped and aggregated. Models were thus

condensed by lumping some system parameters. The influence of those

factors not explicitly included in the model were taken into account

implicitly in calculations of pathway coefficients. In some portions

of the model, where no direct measurements were available, values for

pathway flows and state variable storage were deduced by difference,

assuming that the rate-of-change of the variable was equal to zero.

For this reason model quantification and calculation of pathway coef-

ficients were done for mid-summer and mid-winter conditions when most

biological phenomena are at peak and trough, respectively. During these

maximum and minimum periods, the rate-of-change for system parameters

would be closest to zero.

Examining diagrammatic portrayals of models, with measured num-

erical values (representing the actual system) placed on the diagram's

pathways and storage, helped to give insight into the relative impor-

tance of various model parameters. Any flow into or out of a given

storage which was less than 0.1% of others was generally ignored from

further consideration. The average time constant or turnover time for

each state variable was calculated as the mean storage value divided by

the sum of the mean outflow rates. Any state variable whose turnover

time was four or more orders-of-magnitude less than those of the other

variables, was either omitted from the model or treated as an algebraic

constraint, rather than as a state variable (i.e., described with

algebraic rather than differential equations).


Simulation and Validation

An aggregated model of an estuarine ecosystem interacting with the

power plant at Crystal River was simulated on the University of Florida's

IBM 370/165 digital computer using DYNAMO programming language. The

behavior of alternative configurations for the primary producer com-

ponent of this model was investigated initially on a system of two slaved

Electronic Associates, Inc. Miniac analog computers. Here, model

response was observed on a Miniac Oscilloscope Repetitive-Operation

Display Unit (Mod. 34035) and recorded with a Bausch and Lomb, Houston

Instruments plotter (Mod. 2000).

Models were run initially with coefficients calculated and vali-

dated for conditions representing an estuarine study area which was

unaffected by the power plant (control area). The validity of the model

was determined by subsequent simulations with pathway coefficients

identical to those calculated for control conditions but forcing func-

tions modified to represent conditions in the discharge estuary. A

match of field data under both control and discharge conditions using

the same pathway coefficients was considered to be satisfactory vali-

dation. Once the model had been validated, simulation runs were done

with coefficients modified to reflect changes in external forcing

functions which represented changes in cooling water systems of the

power plant. Other simulations were done with changes in internal

coefficients to determine the sensitivity of model behavior to various



Ecological Field Measurements

Measurements of the estuary's ecological characteristics which

were made by other researchers, were assembled in this study according

to planning models (see number 2 under "Modeling Methods"). Other

field measurements were done as a part of this study to help character-

ize the structure and function of power plant canal ecosystems.

Total Community Metabolism

The metabolic activity of entire ecological communities in the

cooling water canals was determined using diurnal oxygen changes in the

free water with a modified version of the method developed by Odum

(1956) after Sargent and Austin (1949). The analysis of diurnal oxygen

curves is described by Odum and Hoskins (1958) and Odum and Wilson

(1962) and use of the two-station adaptation of this method for flowing

waters is demonstrated by Odum and Odum (1955) and Odum (1957). A

total of 43 diurnal metabolism studies were performed on 17 sampling

dates. More than half (9 of 17) of the metabolism experiments were

done during the summer. Between June and September, measurements were

spaced at about weekly or biweekly intervals, whereas fall, winter and

early spring measurements were done in 4-5 day clusters. Separate

analyses of surface and bottom water oxygen trends were made for the

intake canal ecosystem during periods of stratification.

During each diurnal oxygen study duplicate samples were taken

(approximately 5 min apart) at the surface and at about 1 m above the

bottom (5 m deep) in the intake canal, and at the surface only in the

discharge canal. Stations were sampled at about 3 hr intervals


throughout a 24 hr period. During the first few studies 3-4 replicate

samples were taken at each location and time; however, the small

variance (a = 3%) among replicates indicated that duplicate samples

were sufficient for this system. Concurrent with each oxygen sampling

temperature and salinity (T-S) profiles were measured for intake canal

stations at 1 or 2 m intervals using a Beckman Model RD5-3 salinometer.

Vertical T-S profiles (observed on July 10, and 11 and August 26, 1974)

indicated that water in the discharge canal was vertically homogeneous,

and therefore only surface temperature and salinity were routinely

measured. The bottom water of the intake canal was sampled with a

Wildco (Mod. 1120TT) 2.5 1, modified Van Dorn bottle. Dissolved oxygen

(DO) samples were taken at 1 m intervals throughout the water column on

several occasions (June 27, July 10 and August 26, 1974), and these

indicated that the mean DO of surface and 5 m depth measurements was

very close ( 2%) to the mean DO for the six 1 m interval samples.

Dissolved oxygen was determined by the Azide modification of the Winkler

technique (APHA, 1971) adapted for use with smaller collection bottles

as described by Smith et al. (1974b)and Smith (1976).

The rate of change of DO in aquatic systems is a function of the

two general physical processes -- advection and diffusion -- and the

two biological processes -- production and respiration (Odum, 1956).

Algebraically this can be expressed as,

= P R + Din + Ain (7)

where Q = the rate of change of oxygen in the water; P = gross primary

productivity; R = community respiration rate; D. = net rate of dif-
fusion into water (positive in, negative out); and Ain = net rate of



advection into study area. Diffusion of oxygen across the air-water

boundary was measured directly, and advection was accounted for by

measuring oxgyen trends in sequential stations in uni-directional flow-

ing waters (such as cooling water canals). Thus, after algebraically

subtracting the effects of these physical factors, the remaining oxygen

rate of change as described in equation (7) is the manifestation of P

and R only.

For flowing waters the rate of oxygen change in an ecosystem

between two sequential stations is calculated as the difference between

upstream oxygen concentration at time t and the downstream concentra-

tion at time t + T, divided by T, where T is the time it takes for a

parcel of water to flow from upstream station to downstream station.

In the power plant canals at Crystal River, the ebb and flood of tides

affect several parameters which are involved in the diurnal oxgyen

metabolism calculation. These include flow time between stations,

diffusion rate and water depth.

The time of flow between stations was estimated assuming that tidal

flows were constant during the ebb, flood and slack periods of a given

tidal cycle, but that cross-sectional areas changed at hour intervals.

In this way mean velocities were calculated for the mid-point of an

hourly interval, and distance traveled during each interval was esti-

mated until the total distance between stations was exceeded by the sum

of distances traveled in each hour. The flow time (in hours) was then

equal to the number of hours needed to just exceed the distance between

stations (tL) minus the quotient of the excess (beyond downstream

station) distance traveled (M) to the average velocity in the last hour.

An expression for estimating the flow time T, in the canals as a function


of tide is then

S (F ) + Ftplant

= = tt (8)
tide tL plant
S(F Atide)tL + Fplant
(A) tL


tL = number of hours until distance traveled just exceeds L (hr)

X = distance traveled between t = 0 and t = tL (m)

L (Ftide t Flant (hr)

t=0 (Axt

F = power plant pumping rate = 2410 m /min
F = tidal flow (m3/min) = + (h)(A )/T (m3/min)
tide (sign depends on direction of tide)

T = tidal period, excluding slack (min)

h = tidal range (m)

A = area of water surface from midpoint between stations to
s innermost end of canal (m2)

L = distance between stations (m)

A = mean cross-sectional area of canal between stations (m2)
= A + (Zt Z) W
xm t
A = cross-section area at mean low water (m2)
Zt = depth at time t (m)

Z = depth at mean low water (m)
W = mean width of canal between stations (m)

Locations for metabolism stations were selected so that flow times

would be long enough for significant oxygen changes to occur between


stations, but short enough so as not to involve too large a fraction of

the diel period. Generally, flow times in this study ranged from 1-4

hrs, which is consistent with those used by Odum (1957), Edwards and

Owens (1962) and Owens (1966). Some of the physical parameters in-

volved in computation of T are given in Fig. 5 and a representative

tabular calculation of flow times between two canal stations at 1 hr

intervals is given in Table 3.

The community metabolism for a given day can be calculated as the

integrated change in oxygen concentration for a water mass flowing

between stations, per time of travel between stations, times the mean

depth during that time, minus the diffusion rate, and this is given in

the following equations:

s AC
P n = f (- Z D) dt (9)
net t t
t t

r AC
Rite = (- Zt D) dt (10)
t t

D = k t (11)


Pne = net daytime productivity (g 02/m -day)

Rnte = night respiration (g 02/m -day)

AC = difference in oxygen concentration (g 02/m ) of upstream
station at time (t T) and of downstream station at time
(t + .)
k = diffusion rate coeffici which varies with ide (t 0/m-hr)
k = diffusion rate coefficient which varies with tide (t 02/m -hr)

Diagram of discharge canal illustrating the physical
parameters involved in calculating flow time, T,
between stations 5 and 6.

Figure 5.

E a:





* *
rr-1 if r-1

in %o Lf
'-4 H H

o .0
,- .J













0 M





u 0
0 *N



u u

0 p

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o -
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(U 0)



(U '4 d

O 0



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u II
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0 C -
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0 4-

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0 0

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0 (~44

m E-

























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r F




0 r


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0 c1 CJ -
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w 0
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U4 O



S = oxygen saturation concentration for given temperature and
salinity (g/m3)

Ct = mean concentration of dissolved oxygen (g/m )

t = time (hr); as a subscript it indicates time-dependence

t = time of sunrise; t = time of sunset
r s
Z, T = as previously defined

Typical diurnal variations in oxygen, water depth, temperature, and

salinity as measured for a metabolism analysis of the discharge canal

are given in Fig. 6. The rate-of-change curve is deduced with the aid

of hour-by-hour calculations as shown in sample calculation of Table 4

for the same data set. A continuous DO curve was assumed by plotting

the average value from measurements at the start and the finish of the

sampling. This, in effect, integrates the metabolism of the previous

day with that of the current day. Percent saturation was estimated from

the mean of temperature and salinity measurements made during the

sampling using the equation and tables of Green and Carritt (1967), and

this was used to calculate a diffusion correction for the rate-or-change


The water column of the deeper intake canal was often stratified

into two distinct layers as inferred from temperature, salinity and

oxygen profiles. Therefore, water samples for oxygen analysis were

drawn from both epilimnic and hypolimnic strata, and separate metabolism

calculations were done for each. The main assumption involved in

separating diurnal oxygen analyses into upper and lower subsystems is

that the two layers move along the canal at about the same rate. Cur-

rent meter surveys in the intake canal for a full tidal

cycle (Carder et al., 1974) have indicated that this may be a

Figure 6. Typical diurnal variations in measured parameters for
stations 5 and 6 on 1-2 July 1974.




6.2 I
0 6 12 18 24
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6 12 18 24


6.4 -------
0 6 12 18 24
36 .
0 6 12 18 24
0 6 12 18 24




w 10


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ale 41


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reasonable assumption. Figure 7 illustrates all pertinent processes

affecting oxygen content of the two layers.

In the analysis of surface and bottom diurnal oxygen curves,

advective, and diffusive oxygen exchange between layers upward (Vu) and

downward (Vd) were taken into account indirectly. When the intake

canal water column is stratified, these vertical exchanges are rela-
tively small (0.1 0.5 g 02/m2 day, using vertical diffusivity coef-

ficients of Jassby and Powel, 1975 and Steinberg, 1975); therefore,

epilimnion and hypolimnion can be treated as separate water bodies.

Under this condition the total community metabolism is simply the sum

of the metabolism calculated for the two vertical halves. However, the

stratification sometimes breaks down during a diurnal sampling (see

description of canal hydrography in "Introduction"). Thus, two new

processes, Vd and Vu, enter into the oxygen balance for the upper and

lower subsystems. In the surface oxygen compartment of Fig. 7, Vd

would appear as additional respiration and V as additional photo-

synthesis, introducing an error. However, an equal but opposite (and

therefore compensating) error occurs in the bottom oxygen compartment,

where Vd appears as photosynthesis and Vu as added respiration. There-

fore, the summation of both surface and bottom metabolism calculations

to get total community metabolism is again justified. During the

night, the advective exchange of higher oxygen surface water for bottom

water with lower oxygen concentrations, if great enough, could appear

as spurious photosynthesis in the bottom subsystem and inflated respira-

tion in the upper subsystem. Thus, any positive oxygen changes at

night in one layer should be subtracted algebraicallyy added) from the

respiration in the other layer.

Diagram illustrating pertinent processes affecting
oxygen concentration in two layers of the intake canal.
P is gross photosynthesis; R is total respiration; D
is diffusion across the air-water interface; V is ver-
tical eddy diffusion between layers; and A is advection
of oxygen as water traverses the canal. Subscripts u
and d represent upstream and downstream for advection,
and upwards and downwards for vertical eddy diffusion,
while s and b designate surface and bottom layers.

Figure 7.



Oxygen Diffusion

The process of oxygen diffusing across an air-water interface is

driven by the difference in partial pressures exerted by concentra-

tions of oxygen in the water and in the atmosphere. This relationship

is given by eq. (11). The diffusion rate coefficient, k, is a function

of: temperature; water and air turbulence; and water depth.

Diffusion rate coefficients were measured under several different

hydrographic and meteorological conditions using the experimental method

of Copeland and Duffer (1964) as modified by Hall (1971) and Day (1971).

The method involved measurements of time-changes in oxygen concentra-

tion under a plastic dome which floated on the water surface, and which

was initially purged of its oxygen content with nitrogen gas. Oxygen

concentrations were measured with a Yellow Springs Instrument Model

51-A oxygen probe mounted under the dome and above the water at 10-15

minute intervals for a 1-2 hour duration. The rate of oxygen return

at high saturation deficit appeared to be linear as shown by the results

from six diffusion experiments in Fig. 8. Diffusion rate coefficients

were calculated from this data by the following expression,

k P)(12)
(A)(t)(mean % sat. def.) (

where k = diffusion rate coefficient in g 02/m /hr at 100% saturation

deficit; V = volume of oxygen diffused into the dome; p = density of

oxygen; A = area of water surface covered by dome; t = duration of

experiment; and (mean % sat. def.) = mean percent saturation deficit

between water and atmosphere under the dome during the experiment.

Diffusion rates observed for the cooling water canals at Crystal

Figure 8.

Oxygen return to a nitrogen-filled plastic dome in
experiments to measure oxygen diffusion coefficients
(k, g 02/m /hr at 100% saturation deficit). Straight
lines, which were fit by inspection, apply only at
these high saturation deficits. Data for each experi-
ment given below:

Intake, Wind
I or Speed &
Discharge, Direction Current,
Key D Date kt Tide fps k

A I 8 Sept 73 5S High Slack 0.3 0.42

B I 19 Nov 75 1OE High Slack 0.5 0.44

C D 8 Sept 73 5SE Max Ebb 0.65 2.04

D D 2 Aug 74 20W High Slack 0.45 0.74

E D 2 Aug 74 15S High Slack 0.6 1.02

F D 19 Nov 75 ION Max Flood 1.0 1.72


30 60 90






River appeared to be a function of current velocities as indicated by

others (O'Connor and Dobbins, 1956; Churchill et al., 1962; Edwards

and Owens, 1965; McKellar, 1975). However, direct diffusion measure-

ments made in this study were substantially higher than those predicted

by the empirical expressions of these authors. Measurements in the

swifter flowing discharge canal were often two or more times as great

as in the intake canal. Velocities in the canals vary with tidal phase

(see Table 3), being greater in the discharge canal on an ebb tide and

in the intake canal on a flood tide. Spoil banks generally shield the

waters in both canals from wind effects. However, direct easterly or

westerly winds can significantly add to turbulent diffusion, since under

these conditions the canal length provides adequate fetch for wind

shear. In this study different diffusion rate coefficients were

applied for intake and discharge canal systems during tidal ebbs and

during tidal floods. Based on data shown in Fig. 8: diffusion coef-

ficients of k = 0.25 g 02/m2/hr and k = 0.75 were used to correct

diurnal oxygen curves during ebb and flood tides, respectively, for the

intake canal; and diffusion coefficients of k = 0.9 and 1.9 were used

for the discharge canal under flood and ebb tides, respectively. These

coefficients led to diffusion corrections which were generally less

than 10% of observed oxygen changes for the intake canal and less than

25% for the discharge canal.

Plankton Metabolism

Net primary production and total respiration of the plankton

community were estimated by oxygen changes in light and dark bottles

according to the method first described by Gaarder and Gran (1927) and


widely used by Riley (1946), Ryther (1956) and others. Standard 300 ml

BOD bottles were used with dark bottles painted black and wrapped with

grey duct tape. Dark bottle tops were sealed with 2 layers of heavy

aluminum foil during experiments. Three sets of three-replicate light

bottles and duplicate dark bottles, as well as a pair of initial

bottles (to give DO at start of experiment) were filled from a single

bucket surface sample with a rubber siphon. Initial bottles were "fixed"

in the field and returned to the laboratory for titration. The three

sets of light and dark bottles were suspended on chains from floating

racks at depths of 0.3 m, 1.5 m, 3.0 m for 24 hrs. It was suggested by

Ryther (1956) and Hall and Moll (1975) that 12-15 hr incubation periods

be used, primarily to avoid slime growths on internal walls of bottles.

However, in marine waters with lower bacterial concentration, this

seems less likely a problem than in fresh waters. Numerous researchers,

including Odum and Hoskins (1958), Edwards and Owens (1965), Patten

and Van Dyne (1968) and Mann et al. (1972) have used diurnal incuba-

tions with reasonable success. Metabolism in grams oxygen per m per

day was calculated by integrating rates-of-change of oxygen per m over

profile to the depth of the euphotic zone which was estimated during

dyalight hour of diurnal samples by Secchi disk and submarine photometer.

Sunlight Measurements

Solar insolation was recorded using a Weather Measure Corp. Solar

Radiation Recorder Mod. R 401 during the winter and spring of 1974-75.

Data was provided by Florida Power Corporation for other dates.

Penetration of sunlight through the water column was determined

using Secchi disc readings and a submarine photometer (InterOceans, T.S.


Submarine Illuminance Meter S/N 88/30). Light intensity illuminancee)

was measured in the water column and just above the water surface with

Nikkon 50 mm filtered lenses at about 0.2 m intervals of water depth

from surface to bottom. Two cells were calibrated together on deck and

then the underwater cell was lowered into the water to measure percent

surface light at various depths. This data plotted on semi-log paper

yielded relatively straight lines as shown in Fig. 9, and the light

intensity usually decreased exponentially with depth according to the


1 = e-K(z2 z1) (13)

so that,

In (11/12)
K = (14)
z2 z

where 12 is the light intensity at a lower depth, z2; I1 is the light

intensity at an upper depth, zl; and K is extinction coefficient.

Benthic Community Structure

Littoral and shallow subtidal benthic animal community structure

in the canals was studied by measuring abundance, biomass and species

diversity. Relatively homogeneous sampling areas were established for

both canal ecosystems (Fig. 4) and were marked-off with stakes at 5 m

intervals for 50-60 m along the mean-low-water (MLW) mark. Each square-

meter quadrat was assigned a number, and the quadrat to be sampled on a
given date was selected randomly. Within the designated 1 m quadrat,

a 0.25 m2 frame was placed so as to obtain a representative sample of

that quadrat.

Figure 9. Example of light penetration data measured with submarine
photometer on 19 Nov. 1975 at Sta. 6 in the vertically
well-mixed discharge canal.


;u 30 40 50

0 0,


p -'

3- ,-

4 -0 EI

5-- '_______



All substrate and organisms inside the frame were collected to a

depth of about 15 cm below the sediment surface or to the zone of black

anaerobic mud, and were returned to the laboratory for sorting. Samples

were washed onto a 2 mm mesh screen to retain those animals defined as

the macrofauna, which typically comprise greater than 90% of the total

benthic faunal biomass (Thorson, 1966). The occurrence and abundance

of all animals was recorded, and organisms were blotted, weighed and

then dried to constant weight at 320C (900F) (Lehman, 1975). Blotted

wet and dry weights were recorded along with the total number of macro-
faunal species encountered in the 0.25 m sample. To make samples with

different total numbers of individuals comparable, the number of species

which would have been found if just 1000 individuals had been counted

in each sample was calculated. This was done assuming that S = c log N,

where S is the number of species in the sample, N is the total number

of individuals sampled and c (slope of logarithmic plot of S vs. N) is

a coefficient of diversity (Odum et al., 1960).

Early in the study, several bottom samples (obtained with Peterson

and Ekman dredges), as well as SCUBA observations and hand-cores, in-

dicated that the animal community in the mud at the bottom of canal

channels was very sparse (each of 24 samples gave biomass < 1 g organic


Nekton Sampling

The actively swimming pelagic nekton, as well as some demersal

fish were sampled on two occasions (19-20 March and 24-25 June, 1975)

by overnight gill-netting. Designated areas (about 5500 m2) in each

canal were enclosed by combinations of 5.1 and 10.2 cm (2 and 4 in)