United States
                Environmental Protection
                Agency
                National Training
                and Operational
                Technology Center
                Cincinnati OH 45268
                Water
I
I
Benthic  Analysis

Training  Manual
EPA-430/1-79-001
March 1979
                                                  EPA REGION VII IRC
                                                   160874

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                                                        EPA-430/1-79-001
                                                        March 1979
                     BENTHIC  ANALYSES
This course is for technicians and biologists who have responsibility
for collection, identification and interpretation of findings of benthic
communities in surveillance of the aquatic environment.  This is an
introductory course in benthic community analysis.

After successfully completing the course, the student will be able
to plan, conduct and evaluate benthic monitoring programs.

The training consists of classroom instruction and activities,
laboratory studies and field experience.

Course coverage emphasizes benthic macroinvertebrate communities
in freshwater, including sampling considerations,  taxonomic analysis,
sorting techniques, sampling handling, and data presentation  and
interpretation.
          U. S.  ENVIRONMENTAL PROTECTION AGENCY
                 Office of Water Program Operations
        National Training and Operational Technology Center

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                    DISCLAIMER

Reference to commercial products, trade names or
manufacturers is for purposes of example and
illustration.  Such references do not constitute
endorsement by the Office of Water Program Operations,
U. S. Environmental Protection Agency.

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                                        CONTENTS











Title or Description                                                       Outline Number






Benthic Communities (Marine)                                                    1




Using Benthic Biota in Water Quality Evaluation                                   2




Statistics As An Ecological Tool                                                  3




The Interpretation of Biological Data With Reference To Water Quality              4




Application of Biological Data                                                    5




Optics And the Microscope                                                       6




Artificial Substrates                                                              7




Benthic Integrity and  Macro Invertebrate Drift                                     8




Effects of Thermal Pollution On the Benthos                                       9

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                                  BENTHIC COMMUNITIES (MARINE)
I  INTRODUCTION

A  The term community in the ecological sense
   includes all of the populations of animals
   and plants occupying a given area.   The
   community and the nonliving environment
   function together as an ecological system or
   ecosystem.

B  The community  cannot exist without the
   cycling of materials and the flow of energy
   in the ecosystem.

C  The community  concept is important in
   ecological theory because  it emphasizes
   the fact that diverse organisms usually
   live together  in an orderly manner.

D  Since organisms in salt water (or in any
   other natural habitat) are not arranged in
   taxonomic or systematic orders, classi-
   fication on an  ecological basis  as one of the
   following is  useful:

   1  On major niches or position in energy
      or food chain

      a  Producers

      b  Consumers

      c   Decomposers

   2 On their mode of life

     a   Benthos

     b   Periphyton

      c   Plankton

     d   Nekton

     e   Neuston

   3 On region or  subhabitat (see Figure 1)

     a   Intertidal
       b  Subtidal

       c  Lower Neritic

       d  Bathyal

       e  Abyssal

       f  Hadal

 E  Among benthic organisms the biotic factors
    of the environment are manifested in pre-
    dacity,  competition for food and space, and
    materialisms.

 F  The zonation  of varied and important groups
    of plant-like sessile animals on the  sea
    bottom is often as striking as the zonation
    of trees on a  mountain and similarly pro-
    vides shelter for small organisms.

 G  Because of their stability benthic organisms
    provide a basis for  the classification of
    zones.
II   THE BENTHIC HABITAT

 A  Distinct faunas in marine environments
    depend on the physical characteristics of
    the environments,  the ecological activities
    of the  organisms, the geological history of
    the region and the biology of the species.
    On this basis the following types of assem-
    blages and environments can be generalized:

    1  Intertidal and rocky shores.

    2  Intertidal sand beaches and flates to
       10  m.

    3  Low salinity lagoons and mangroves.

    4  Nearshore, sand and sand-mud, 10-30 m.

    5  Intermediate shelf to 65 m.

    6  Outer  shelf to 130 m.
BI. MAR. eco. 3. 2. 79
                                                                                       1-1

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Benthic Communities
                           THE    MARINE    ENVIRONMENT
           X
           en
           o
           o
           c
           6
           c.
           0>
          h-
           W
           o
           03
          U.
               erres
         trial
                                                                    lanne
                                    Neritic   zone
                                          Bathyal zon
                        Pelagie-neriticl
                        Infra-littoral Jrr
                                            Abyssal   zone
                           Pelagic-oceanic (Nekton  «• Plankton) 1
                       Hemipelagic   Ln         Pelagic
                  Light
Temperature,
 Salinity
                Movement
  '   Algae,
(green, red, brown).
  a o  herbivora.
   Variable.
 Eurythermal  fauna.
                    Waves »fast  currents
                                (tidal etc.).
                     Thick shells, of ten broken
                      Boring and fixed
                                  animals .
                     Accumulation swift
                     with diastems, variable.
                        Ripple  marks
                      Cross-tam i nation
                                             Surface , a o.  herbivora.
                                           Jeeper, no herbivora (carnivora ,mud eaters)-
                                           Blind or large eyes, light-organs.
                                                                   Variable at the  surface.
                                                         Deeper, constant, low.  Stenothermal  fauna
                                                                                               In  the abyss 1O*
                                                                  Oceanic
                             Convect
>ic )
   \
ion )
                                                                           currents,  slow
                                                                      Accumulation
                                                                    Slow to extremely  slow, uninterrupted.
                                                                     Extensive,  uniform  deposits
                                                      Phytoplankton-
                  Flora
                     Calcareous algae,
                    (Lithothamnium  reefs).
                          Bacteria
                       precipitating  lime.
                                                                       I
                                                              Coccolithophora
                                                                              „ Diatoms
                   Fauna
                                        Nekton            I
                              (C«phalopods, Crusttceans, Vertebrates, etc.).
                                   Zooplankton            |
                                               ^roraminifera (Clobigerina )
                                   Coral-, Bryozoan reefs.
                                   . Shells  of benthos.
                                                  CaCO,
                                                                          Radiolarians
           (f)
                Llthosphere
                     Terrigenous.-(abrasion, rivers, glaciers,  wind )  and  Volcanic matter.
                    j        (Transport aqgeous  and eolian).
                    -Coarse	>-        I               |
                     -*	Tine 	'	>-
                                                                 • Colloidal •
                Evaporation
                       Limestone, gypsum,
                            sails
                Precipitation,
               jartly organic
                        Limestone,  chert,
                      phosphate, glauconite,
                        pynte, limonite,
                            etc.
                                                                                        Manganese  nodules.
           -a
            0)
                                    Shallow water dep
                                           Terrigenous
                                      - Clay -
                  (    Limestone, dolomite.
                  <	Reef rock
                  «—Ooii.es.
                   °|   Black (organic) mud I
                                          Pelagic  deposits
                                                                         Pteropod
                                                                                   igenna t
                                                                 Clobigerina 1
                                                         Diatom
                                                                                    Red clay
                                                                                                Radiolarian)
              Figure 1.   THE ENVIRONMENTS OF SEDIMENTATION IN  THE OCEAN
 1-2

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                                                                    Benthic Communities
            Table 1.  SIZE CLASSIFICATION OF SEDIMENTARY PARTICLES

            As frequent reference will be made to materials of various grain
            sizes, the following table shows the most used size classifications
                                      (grade scales)
                                   Diameters in millimeters
Wentworth
Boulder
Coblilc

Pebble
Granule
Very coarse sand
Coarse sand
Medium sand
Fine sand
Very fine sand
Silt
Oay
Above 256
256-64

64-4
4-2
2-1
1-M
M-W
K-K
>»-«s
M«-hs«
Below M«.
2-1
1-0.5
O.S-0.25
0.25-0. 125
0.125-0.0625
0.0625 0.004
Below 0.004-
Attcrberg
Block
Cobble

Pebble

Coarse sand
Fine sand

Silt
Clay
2000-200
200-20

20-2

2-0.2
0.2-0.02

0.02 0.002
Below 0.002


1 „ ...
Gravel PscPhltl:



Psammitc
(arenaceous)

Petite or lutite
            The finest fractions of sediments are frequently called "clay. " But
            as this word has a definite mineralogical implication the terms "pelite"
            or "lutite" or "lutum" are used by some authors to denote all particles
            smaller than the sand fraction, whether consisting of clay minerals,
            calcite,  or any other mineral.  The word "ooze" signifies a fine de-
            posit composed principally of the shells and debris of pelagic organisms.
            By "mud" the marine geologist means all fine-grained deposits of a
            more or less plastic nature  in moist condition.

            For a more extensive  review of this and other problems of sedimen-
            tary petrography the reader may  consult Krumbein and Pettijohn
            (1938), Pettijohn (1949),  or  other manuals of  petrography and also
            Twenhofel's books.

            FromKuenen,  P. H.  Marine Geology.  1950.
    a  clay  bottom or

    b  sand bottom (depth figures are
       approximation)

 7  Basins and troughs to 1500 m.

 8  Upper (inner) Continental Slope.

 9  Middle Continental Slope.

10  Lower (outer) Continental Slope.
  11  Abyssal basins to 10, 000 m.

  12  Hadal basins to 13, 000 m.

B  Investigations of marine bottom com-
   munities, with relatively few exceptions
   have been concerned with describing the
   aggregations of species of infaunal in-
   vertebrates along the broad areas of
   differing sedimentary factors.
                                                                                       1-3

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Benthic Communities
C   An investigation of the temporal sequences
    and biotic successions in the fouling of
    artifacts may be a prime feature in the
    detection of pollution.

D   In shore the relationship between popu-
    lation density and substratum type  is
    quite striking. This is brought about by
    rain wash, stream erosion, aeolian
    deposits and glacial action.

E   Marine sediments on and in which the
    benthos lives  are  derived from a great
    number of different sources

    1  Sources

       a  Skeletons and tests of organisms

       b  Decomposable organic matter
          (1  kg/m^/yr.  in coastal  waters)

       c  Precipitates:  lime, iron, Mn. , etc.

       d  Coastal and bottom erosion:  waves,
          currents, etc.
                               3
       e  Rivers  (Miss. R.  1 km   sand and
          silt/yr)

       f  Glaciers and ice

       g  Weathering  on the  sea floor

    2  Media of transport

       a  The atmosphere

          1)  Meteoric dust (10 to 20 million
             particles/day)

          2)  Volcanos:  pumice,  ash, etc.

          3)  Offshore winds; dust,  sand

       b  Sediment slumping and currents
          (settling rates)

       c  Horizontal currents

       d  Currents and wave turbulence

       e  Rhythmic accumulations
F  The macroscopic fauna of sandy beaches
   is composed mostly of burrowers.

G  The microscopic fauna of sandy beaches
   is highly specialized and depends largely
   on the composition of the substratum and
   the percent composition of sand grain size.

H  In the neritic zone the benthos are con-
   sumers and exhibit marked zonation be-
   cause of the large number  of distinct
   sessile  forms.   They are distinct for each
   of the neritic zones.

I  The unequal distribution of animal mass
   in shallow waters is the result of inter-
   twined biological and physical factors in
   the bottom, some of which involve aerobic
   and anaerobic exchanges with the environ-
   ment, but many of which are not understood.

J  The  burrowing habit is more common in
   muddy sand than in sand or solid rock.

K  The variety of  organisms on the bottom  is
   greatest where measurable light can reach
   to the bottom and where plankton production
   is high.

L  The eulittoral zone gives rise to many
   communities  because it is  greatly varied
   with regard to  type of substratum and
   also to character of shoreline and degree
   of  exposure.

M In deeper water, 2000 m or more,  gravels,
   sands and silts from the land  are replaced
   by pelagic oozes or red clay.  The former
   are important as a substratum and because
   of their organic matter content.

N  On the level bottoms of the sea live 2 eco-
   logically distinct groups: the  eipfauna com-
   prising 3% of all species of animals (more
   than 4/5 of all  bottom dwellers) and the
   infauna  making up 11% of known species.
   (less than 1/5 of all bottom dwellers).

O  Rocky shores from outcrops,  boulders,
   etc.  present  characteristic faunas on
   their slopes,  in crevices and in pools,
   communities whose composition is also
   dependent on vagueries of the tides.
 1-4

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                                                                     Benthic Communities
P  Benthic communities are irregularly
   spaced: the same type of level bottom
   substrata at similar depths in widely
   spread regions support paralleled groups
   of invertebrates.

Q  The bottom fishes as soles, plaice, halibut,
   founders,  rays, sculpin, etc. , depend to
   a great extent on consistent productivity
   of the bottom on which they live for food,
   shelter and reproduction.

R  Deep sea benthic animals  are mainly mud-
   dwelling forms variously adapted to this
   mode of life.   The deepest fauna in the
   most widely distributed; the poverty of
   individuals being apparently related to
   distance from the shore.

S  Much of the animal life on  the deep sea is
   endemic not merely an extension of eury-
   bathic forms.   This fauna has a relatively
   small number of species in proportion to
   the number of genera.

T  The abyssal and hadal zones are regions
   of relatively uniform conditions in terms
   of pressure,  temperature and light.   The
   communities  in these areas are correspond-
   ingly similar while in many respects and
   depend on the productivity  of the euphotic
   zone.
 3  Holme,  N. A.  Methods of Sampling the
       Benthos.  Adv. Mar.  Biol. 2:171-260.
       1964.

 4  Jones, N. S.  Marine Bottom Communities.
       Biol.  Rev. 25:283-313.   1950.

 5  Kanwisher,  John .  Gas Exchange of
       Shallow Marine Sediments.  Symposium
       on the Environmental Chemistry of
       Marine Sediments; Occasional Publ.
       1:13-19.   1962.

 6  Kuenen,  P. H.  Marine Geology.  New York
       City,  John Wiley  & Sons.,  Inc.  1952.

 7  Marshall, N. 3rd.  The Environmental
       Chemistry of Marine Sediments.  URI
      Grad. School of Oceanog. Occ.  Publ.  1.
       1962.

 8  Odum, E. P. , and Odum, H. T.  Funda-
      mentals of Ecology.   Philadelphia,
       W. B. Saunders Co.  1959.

 9  Southward, A. J.  Life on the Sea Shore.
       Cambridge,  Mass. Harvard University
      Press.  1965.

10  Thorson, G.  Bottom Communities. Geol.
       Soc.  Am.  Mem. 67(1): 461-534.  1957.
 REFERENCES
 1  Elton, C.  Ecological Communities.  J.
      Animal Ecology.  5:1-56.  1946.

 2  Gorsline, D. S. Ed.   Proceedings of the
      First National Coastal and Shallow
      Water Conference. NSF and ONR,
      Tallahassee, Fla.  1962.
 This outline was prepared by D.  J.  Zinn,
 Professor of Zoology, Graduate School of
 Oceanography,  University of Rhode  Island,
 Kingston,  Rhode Island.
                                                   Descriptors:  Aquatic Life,  Benthos,
                                                   Benthic fauna, Benthic flora, Biological
                                                   communities, Ecological distribution,
                                                   Marine biology, and Oceans.
                                                                                        1-5

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             USING BENTHIC BIOTA IN WATER QUALITY EVALUATION
 I   BENTHOS ARE ORGANISMS GROWING
    ON OR ASSOCIATED PRINCIPALLY
    WITH THE BOTTOM OF WATERWAYS

    Benthos is the noun.

    Benthonic, benthal and benthic are
    adjectives.

 II  THE BENTHIC COMMUNITY

 A  Composed of a wide variety of life
    forms that are related because they
    occupy "common ground"--substrates
    of oceans, lakes,  streams, etc.
    Usually they are attached or have
    relatively weak powers of locomotion.
    These life forms are:

     1  Bacteria

       A wide variety  of decomposers work
       on organic materials, breaking them
       down to elemental or simple com-
       pounds.

     2  Algae

       photosynthetic plants having no true
       roots,  stems,  and leaves.  The basic
       producers of food that nurtures the
       animal components of the  community.

     3  Flowering Aquatic Plants (Pondweeds)

       The largest flora, composed of
       complex and differentiated tissues.
       May be emersed, floating, sub-
       mersed according to habit.
     4  Microfauna

       Animals that pass through a U. S.
       Standard Series No. 30 sieve, but
       are retained on a No. 100 sieve.
       Examples are rotifers and micro-
       crustaceans.  Some forms have
       organs for attachment to substrates,
       while others burrow into soft materi"!"
       or occupy the interstices between rocks,
       floral or faunal materials.
   5  Meiofauna

      Meiofauna occupy the interstitial zone
      (like between sand grains) in benthic
      and hyporheic habitats.  They  are inter-
      mediate in size between the microfauna
      (protozoa and rotifers) and the macro-
      fauna (insects, etc.).  They pass a No. 30
      sieve (0. 5 mm approximately).  In fresh-
      water they include nematodes,  copepods,
      tardigrades,  naiad worms,  and some flat
      worms.  They are usually ignored in fresh-
      water studies, since they pass the standard
      sieve and/or sampling devices.

   6  Macrofauna (macroinvertebrates)

      Animals that are retained on a No. 30 mesh
      sieve (0. 5 mm approximately).  This group
      includes the insects, worms,  molluscs,  and
      occasionally fish.  Fish are not normally
      considered as benthos, though there are bottom
      dwellers such as sculpins and  darters.

B  It is a  self-contained community, though there
   is  interchange with other communities.  For
   example:  Plankton settles to it,  fish prey on
   it and lay  their eggs  there, terrestrial  detritus
   leaves are added to it, and many  aquatic insects
   migrate from it to the terrestrial environment
   for their mating cycles.

C  it is stationary water quality monitor.   The
   low mobility of the biotic components  requires
   that they "live with"  the quality changes of the
   over-passing waters.  Changes imposed in the
   long-lived components remain  visible for
   extended periods,  even after the  cause  has
   been eliminated.  Only time will  allow a cure
   for the community by drift, reproduction,  and re-
   cruitment from the hyporheic  zone.

D  Between the benthic zone (substrate/water
   interface) and the underground water table
   is  the hyporheic zone.   There is  considerable
   interchange from one zone to another.

Ill  HISTORY OF BENTHIC OBSERVATIONS

A  Ancient literature  records the  vermin associ-
   ated with fouled waters.
BI. MET. fm. 8i. 8. 78
                                       2-1

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   Using Benthic Biota In Water Quality Evaluation
B   500 -year- old fishing literature refers
    to animal forms that are fish food and
    used as bait.

C   The scientific literature associating
    biota to water pollution problems is
    over 100 years old (Mackenthun and
    Ingram, 1964).

D   Early this century,  applied biological
    investigations were initiated.

    1  The  entrance of state boards of health
      into  water pollution control activities.

    2  Creation of state conservation agencies.

    3  Industrialization and urbanization.

    4  Growth of limnological programs
      at universities.

E   A decided increase in benthic  studies
    occurred in the 1950's and much of
    today's activities are strongly influenced
    by developmental work conducted during
    this period.  Some of the reasons for this
    are:

    1  Movement of the universities from
      "academic biology" to applied
      pollution programs.

    2  Entrance of the federal government
      into  enforcement aspects of water
      pollution  control.

    3  A  rising economy and the development
      of federal grant systems.

    4  Environmental Protection Programs
      are a current stimulus.

IV  WHY THE BENTHOS?

A   It is  a natural monitor

B   The community contains all of the
    components of an ecosystem.

    1  Reducers
      a  bacteria
      b  fungi
    2  Producers  (plants)
   3  Consumers

      a  Detritivores and bacterial feeders

      b  Herbivores

      c  Predators

C  Economy of Survey

    1 Manpower

    2 Time

    3 Equipment

D  Extensive Supporting Literature

E  Advantages of the Macrobenthos

    1 Relatively sessile

    2 Life history length

    3 Fish food organisms

    4 Reliability of Sampling

    5 Dollars/information

    6 Predictability

    7 Universality

F  "For subtle chemical changes,
   unequivocal data, and observations
   suited to some  statistical evaluation will
   be needed.  This  requirement favors the
   macrofauna as  a parameter.  Macro-
   invertebrates are easier to sample
   reproductively  than other organisms,
   numerical estimates are possible and
   taxonomy needed  for synoptic investi-
   gations is within the reach of a non-
   specialist.''  (Wuhrmann)
G  "It is self-evident that for a multitude of
   non-identifiable though biologically active
   changes of chemical conditions in rivers,
   small organisms with high physiological
   differentiation are most  responsive.
   Thus the small macroinvertebrates
   (e. g.  insects) are doubtlessly the most
   sensitive organisms for  demonstrating
   2-2

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                                          Using Benthic Biota In Water Quality Evaluation
V
   unspecified changes of water
   chemistry called 'pollution' .
   Progress in knowledge on useful
   autecological properties of
   organisms or of transfer of such
   knowledge into bioassay  practice
   has been very small in the past.
   Thus, the bioassay concept
   (relation of organisms in a
   stream to water quality) in
   water chemistry has brought not
   much more than visual demon-
   stration of a few overall chemical
   effects.  Our capability to derive
   chemical conditions from biological
   observations is, therefore,  almost
   on the same level as fifty years ago.
   In the author's opinion it is  idle to
   expect much more in the future because
   of the limitations inherent to natural bio-
   assay systems (relation  of organisms
   in a stream to water quality). "  (Wuhrmann)
REACTIONS OF THE BENTHIC MACRO-
INVERTEBRATE COMMUNITY TO
PERTURBATION
A  Destruction of Organism Types

   1  Beginning with the most sensitive
      forms, pollutants kill in order of
      sensitivity until the most tolerant form
      is the last survivor.  This results in a
      reduction of variety or diversity of
      organisms.

   2  The generalized order of macro-
      invertebrate disappearance on a
      sensitivity scale below pollution
      sources is shown in Figure 2.
Water
Quality
Deteriorating
            Stoneflies
            Mayflies
            Caddisflies
            Amphipods
             Isopods
             Midges
             Oligochaetes
Water
Quality
improving
      As water quality improves, these
      tend to reappear in the same order.

B  The Number of Survivors Increase

    1 Competition and predation are reduced
      between different species.

    2 When the pollutant is a food (plants,
      fertilizers,  animals, organic materials).

C  The Number of Survivors Decrease

    1 The material added is toxic or has no
      food value.

    2 The material added produces toxic
      conditions as a byproduct of decom-
      position  (e.g., large organic loadings
      produce  an anaerobic environment
      resulting in the  production of toxic
      sulfides,  methanes,  etc. )

D  The Effects May be Manifest in Com-
    binations

    1 Of pollutants and their effects.

    2 Vary with longitudinal distribution
      in a stream. (Figure 1)

E  Tolerance to Enrichment Grouping
    (Figure 2)

    Flexibility  must be maintained in the
    establishment  of tolerance lists based
    on the response of organisms to the
    environment because of complex relation-
    ships among varying environmental
    conditions.   Some  general tolerance
    patterns can be established.  Stonefly
    and mayfly  nymphs, hellgrammites,
    and caddisfly larvae represent a grouping
    (sensitive or intolerant) that is generally
    quite sensitive to environmental
    changes.  Blackfly larvae, scuds,  sow-
    bugs,  snails, fingernail clams, dragon-
   fly and damselfly naiads, and most
    kinds of midge larvae are facultative
   (or intermediate)  in tolerance.
    Sludge-worms, some kinds of midge
   larvae (bloodworms), and some leeches
                                                                                   2-3

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 Using Benthic Biota In Water Quality Evaluation
  cc
  u
  m
  2
  LJ
  >
  Ul
  
          &'    \
          i     \
      B.
                           C.
CO
in
                            D.
                  TIME  OR DISTANCE

          ..NUMBER  OF  KINDS
          ..NUMBER  OF  ORGANISMS
           .SLUDGE  DEPOSITS
      Four basic responses of bottom animals to pollution.
A. Organic wastes eliminate  the sensitive bottom animals
and provide food in the form of sludges for the surviving toler-
ant forms. B. Large quantities of decomposing organic wastes
eliminate sensitive bottom animals and the excessive quanti-
ties of byproducts of organic decomposition inhibit the tolerant
forms; in time, with natural stream purification, water quality
improves so that the tolerant forms can flourish, utilizing the
sludges  as  food. C.  Toxic materials  eliminate the sensitive
bottom animals; sludge is absent and food is restricted to thai
naturally occurring in the stream, which limits the number ol
tolerant  surviving forms. Very  toxic materials may eliminate
all organisms below a waste source. D. Organic sludges with
toxic materials reduce the number of kinds by eliminating
sensitive forms. Tolerant survivors do not utilize the organic
sludges  because the  toxicity restricts their growth.
                      Figure 1
   are tolerant to comparatively heavy loads
   of organic pollutants.  Sewage mosquitoes
   and rat-tailed maggots are tolerant of
   anaerobic environments  for they are
   essentially air-breathers.


F   Structural Limitations

    1 The morphological structure of a
      species limits the type of environment
      it may occupy.

      a  Species with complex appendages
         and exposed  complicated respiratory
         structures, such as stonefly
         nymphs, mayfly nymphs, and
         caddisfly larvae, that are subjected
         to a constant deluge of  setteable
         particulate matter soon abandon
         the polluted area because of the
         constant preening required to main-
         tain mobility or respiratory func-
         tions; otherwise, they are soon
         smothered.

      b  Benthic animals in depositing zones
         may also be burdened by "sewage
         fungus" growths including stalked
         protozoans.  Many of these stalked
         protozoans are host specific.

    2 Species without complicated external
      structures, such as bloodworms and
      sludgeworms, are not so limited in
      adaptability.

      a  A sludgeworm,  for example, can
         burrow in a deluge of particulate
         organic matter and flourish on the
         abundance of "manna. "

      b  Morphology also determines the
         species that are found in riffles,  on
         vegetation, on the bottom of pools,
         or in  bottom  deposits.
2-4

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                                            Using Benthic Biota In Water Quality Evaluation
VI  SAMPLING PROCEDURES

A   Fauna

    1  Qualitative sampling determines the
       variety of species occupying an area.
       Samples may be taken by any method
       that will capture representatives of the
       species present.  Collections from
       such samplings indicate changes in the
       environment, but generally do not
       accurately reflect the degree of change.
       Mayflies, for example, may be re-
       duced from 100 to 1 per square meter.
       Qualitative data would indicate the
       presence of both species, but might not
       necessarily delineate the change in pre-
       dominance from mayflies to sludge-
       worms.  The stop net or kick sampling
       technique is  often used.

    2  Quantitative  sampling is performed to
       observe  changes in predominance.
       The most common quantitative sampling
       tools are the Petersen, Ekman,  and Ponak
       grabs and the Surber stream bottom or
       square-foot  sampler.  Of these, the
       Petersen grab  samples the widest  variety
       of substrates.  The Ekman grab is limited
       to fine-textured and soft substrates, such
       as  silt and sludge, unless hydraulically
       operated.
The Surber sampler is designed for
sampling riffle areas; it requires
moving water to transport dislodged
organisms into its net and is limited
to depths of two feet or less.

Kick samples of one minute duration will
usually yield around 1, 000  macroinvert-
ebrates per square meter (10. 5 X a one
minute kick= organisms/m^).

Manipulated substrates (often referred to
as "artificial substrates") are
placed in a stream and left for a specific
time period.  Benthic  macroinvertebrates
readily colonize these forming a manipu-
lated community.  Substrates may be con-
structed of natural materials or synthetic;
may be placed in a natural  situation or
unnatural; and may or may not resemble
the normal stream community.   The
point being that a great number of envi-
ronmental variables are standardized and
thus upstream and downstream  stations
may be legitimately compared in terms of
water quality of the moving water column.
They naturally do not evaluate what may
or may not be happening to the substrate
beneath said monitor.   The latter could
easily  be the more important.
REPRESENTATIVE BOTTOM-DWELLING MACROANIMALS
Drawings from Geckler, j., K. M. Mackenthun and W. M. Ingram, 1963.
Glossary of Commonly Used Biological and Related Terms in Water and
Waste Water Control, DHEW, PHS, Cincinnati, Ohio, Pub. No. 999-WP-2.
A
B
C

D
E
F
G
H

Stonefly nymph
Mayfly nymph
Hellgrammite or
Dobsonfly larvae
Caddisfly larvae
Black fly larvae
Scud
Aquatic sowbug
Snail

(Plecoptera)
(Ephemeroptera)

(Megaloptera)
(Trichoptera)
(Simuliidae)
(Amphipoda)
(Isopoda)
(Gastropoda)
KEY TO
I Fingernail clam
J Damselfly naiad
K Dragonfly naiad
(Sphaeriidae)
(Zygoptera)
(Anisoptera)
L Bloodworm or midge
fly larvae
M Leech
N Sludgeworm
O Sewage fly larvae
P Rat -tailed maggot
FIGURE 2
( Chironumidae)
(Hirudinea)
(Tubificidae)
(Psychodidae)
(Tubifera-Eristalis)

                                                                                     2-5

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                         Using Benthic Biota in Water Quality Evaluations
                    B       X^  C

                    SENSITIVE
f—
                F              G
                 INTERMEDIATE
  M
                    TOLERANT

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                                      Using Benthic Biota In Water Quality Evaluation
 Invertebrates which are part of the           B  Flora
 benthos, but under certain conditions
 become carried downstream in
 appreciable numbers,  are known as
 Drift.

 Groups which have members forming
 a conspicuous part of the drift
 include the insect orders Ephemeroptera,
 Trichoptera, Plecoptera and the
 crustacean order Amphipoda.

 Drift net studies are widely used and
 have a proven validity in stream
 water quality studies.

 The collected sample is screened with
 a standard sieve to concentrate the
 organisms; these are sorted from
 the retained material, and the number
 of each kind determined. Data are then
 adjusted to number per unit area,
 usually to number of bottom organisms
 per square meter.

 Independently, neither qualitative not
 quantitative data suffice for thorough
 analyses of environmental conditions.
 A cursory examination to detect damage
 may be made with either method, but
 a combination of the two gives  a more
 precise determination.   If a choice must
 be made, quantitative sampling would
 be best, because it incorporates a
 partial qualitative sample.

 Studies have shown that a significant
 number and variety of macroinverte-
brates inhabit the hyporheic zone in streams.
 As much as 80%  of the  macroinverte-
 brates may be below 5  cm  in this
hyporheic zone.   Most samples and
 sampling techniques do not penetrate
 the substrate below the 5 cm  depth.
 All quantitative studies must take this
 and other substrate factors into account
 when absolute figures are presented on
 standing crop and numbers per square
 meter,  etc.
      Direct quantitative sampling of natu-
       rally growing bottom algae is difficult.
       It is basically one of collecting algae
       from a standard or uniform area of the
       bottom substrates without disturbing
       the delicate growths and thereby dis-
       tort the sample.  Indirect quantitative
       sampling is the best available method.

       Manipulated substrates,  such as wood
       blocks,  glass or plexiglass slides,
       bricks,  etc., are placed in a stream.
       Bottom-attached algae will grow on
       these artificial substrates.  After two
       or more weeks,  the artificial sub-
       strates  are removed for analysis.
       Algal growths are scraped from the
       substrates and the quantity measured.
       Since the exposed substrate area and
       exposure periods are equal at all of
       the sampling sites, differences in the
       quantity of algae can be related to
       changes in the quality of water flowing
       over the substrates.
VII ANALYSES OF MICROFLORA

    A  Enumeration

       1  The quantity of algae on manipulated
          substrates can be measured in several
          ways.  Microscopic counts of algal
          cells and dry weight of  a algal mater-
          ial are long established methods.

       2  Microscopic counts involve thorough
          scraping,  mixing and suspension of
          the algal cells.  From this mixture
          an aliquot of cells is withdrawn  for
          enumeration under a microscope.
          Dry weight is determined by drying
          and weighing the algal sample, then
          igniting the sample to burn off the
          algal materials, leaving inert inorganic
          materials that are again weighed.
          The difference between  initial dry weight
          and weight after ignition is attributed to
          algae.

       3  Any organic sediments, however,
          that settle on the  substrate along
          with the algae are processed also.
                                                                              2-7

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Using Benthic Biota In Water Quality Evaluation
      Thus, if organic wastes are present
      appreciable errors may enter into
      this method.
     Autotrophic Index
Ash-free Wgt (mg/m )
Chlorophyll a (mg/m^)
 B   Chlorophyll Analysis

      1   During the past decade, chlorophyll
         analysis has become a popular method
         for estimating algal growth.  Chloro-
         phyll is extracted from the algae and
         is used as an index of the quantity of
         algae present.  The advantages of
         chlorophyll analysis are  rapidity,
         simplicity, and-vivid pictorial results.

      2   The algae are scrubbed from the
         artificial substrate samples, ground,
         then each sample is steeped in equal
         volumes, 90% aqueous acetone, which
         extracts the chlorophyll from the algal
         cells.  The chlorophyll extracts  may
         be compared visually.

      3  Because the cholorophyll  extracts fade
         with time,  colorimetry should be used
         for permanent records.   For routine
         records, simple colorimeters will
         suffice.  At very high cholorophyll
         densities,  interference with colori-
         metry occurs, which must be corrected
         through serial dilution of the sample
         or with a nomograph.
  C   Autotrophic Index

      The  chlorophyll content of the periphyton
      is used to estimate the algal biomass and
      as an indicator of the nutrient content
      (or trophic Status) or toxicity of the water
      and the taxonomic composition of the
      community.  Periphyton growing in sur-
      face water relatively free of organic
      pollution consists largely of algae,
      which contain approximately 1 to 2  percent
      chlorophyll a by dry weight.  If dissolved
      or particulate organic matter is present
      in high concentrations, large populations
      of filamentous bacteria,  stalked protozoa,
      and  other nonchlorophyll bearing micro-
      organisms develop and the  percentage
      of chlorophyll is then reduced.   If the
      biomass-chlorophyll a relationship
      is expressed as  a ration  (the autotro-
      phic index),  values greater than 100
      may result from organic pollution
      (Weber and McFarland,  1969; Weber,
       1973).
VIII  MACROINVERTEBRATE ANALYSES

  A Taxonomic

     The taxonomic level to which animals are
     identified depends on the needs,  experience,
     and available resources.  However,  the
     taxonomic level to which identifications are
     carried in each major group should be
     constant throughout a given study.

  B Biomass

     Macroinvertebrate biomass (weight of
     organisms per unit area) is a useful
     quantitative estimation of standing crop.

  C  Reporting Units

     Data from quantitative  samples may be used
     to obtain:

     1  Total standing crop  of individuals, or
        biomass,  or both per unit area or unit
        volume or sample unit, and

     2  Numbers  of biomass,  or both, of individual
        taxa per unit area or unit volume or sample
        unit.

     3  Data from devices sampling a unit area
        of bottom  will be  reported in grams dry
        weight or  ash-free dry weight per square
        meter  (gm/m ), or numbers of indi-
        viduals per square meter,  or both.

     4  Data from multiplate samplers will be
        reported in terms of the total surface
        area of the plates in grams dry weight
        or ash-free dry weight or numbers  of
        individuals per square  meter, or both.

     5  Data from rock-filled basket  samplers
        will be reported as grams dry weight
        or numbers of individuals per sampler,
        or both.
     2-8

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                                             Using Benthic Biota In Water Quality Evaluation
IX  FACTORS INVOLVED IN DATA INTER-
    PRETATION

 Two very important factors in data evalua-
 tion are a thorough knowledge of conditions
 under which the data were collected and a
 critical assessment of the reliability of the
 data's representation of the situation.

 A  Maximum-Minimum Values

    The evaluation of physical and chemical
    data to determine their effects on aquatic
    organisms is primarily dependent on
    maximum and minimum observed values.
    The mean is useful only when the  data are
    relatively uniform.  The minimum or
    maximum values usually create acute
    conditions  in the environment.

 B  Identification

    Precise identification of organisms to
    species requires a specialist in limited
    taxonomic  groups. Many immature
    aquatic forms have not been  associated
    with the adult species.  Therefore,  one
    who is certain of the genus but not the
    species should utilize the generic name,
    not a potentially incorrect species name.
    The method of interpreting biological
    data on the basis of numbers of kinds
    and numbers of organisms will typically
    suffice.

 C  Lake and Stream Influence

    Physical characteristics of a body of
    water also affect animal populations.
    Lakes or impounded bodies of  water
    support different faunal associations
    from rivers.  The number of kinds
    present in a lake may be less than that
    found in a  stream because of a more
    uniform habitat.   A lake is all pool,
    but a river is composed of both pools
    and riffles.  The nonflowing water of
    lake exhibits a more complete set-
    tling of particulate organic matter that
    naturally supports a higher population
    of detritus consumers.   For these
   reasons, the bottom fauna of a lake or
   impoundment, or stream pool cannot be
   directly compared with that of a flowing
   stream riffle.

D  Extrapolation

   How can bottom-dwelling macrofauna  data
   be extrapolated to other environmental
   components?  It must be borne in mind
   that a component of the total environment
   is being sampled.  If the sampled com-
   ponent exhibits changes, then so must the
   other interdependent components of the
   environment.  For example, a clean stream
   with a wide variety of desirable bottom
   organisms would be expected to have a
   wide variety of desirable bottom fishes;
   when pollution reduces  the number of bottom
   organisms,  a comparable reduction would
   be expected in the number of fishes.   More-
   over, it would be logical to conclude that
   any factor that eliminates all bottom organ-
   isms would eliminate most other aquatic
   forms of life. A clean  stream with a  wide
   variety of desirable bottom organisms
   would be expected to permit a variety of
   recreational,  municipal and industrial uses.

E  Expression of Data

   1  Standing crop and taxonomic composition

      Standing crop and numbers of taxa  (types
      or kinds) in a community are highly
      sensitive to environmental perturbations
      resulting from the introduction  of contam-
      inants.  These parameters, particularly
      standing crop,  may  vary considerably in
      unpolluted habitats,  where they may range
      from the typically high standing crop of
      littoral zones of glacial lakes to the
      sparse fauna of torrential soft-water
      streams.   Thus,  it is important that
      comparisons are made only between truly
      comparable environments.
                                                                                   2-9

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Using Benthic Biota In Water Quality Evaluation
2  Diversity

   Diversity indices are an additional tool
   for measuring the quality of the environ-
   ment and the effect of induced stress on
   the structure  of a community of macro-
   invertebrates.  Their use is based on
   the generally  observed phenomenon that
   relatively undisturbed environments
   support communities having large
   numbers of species with no individual
   species present in overwhelming
   abundance.  If the species in such a
   community are ranked on the basis  of
   their numerical abundance,  there will
   be relatively few species with large
   numbers of individuals and large
   numbers of species represented by  only
   a few individuals.  Many forms of stress
   tend to reduce diversity by making the
   environment unsuitable for some species
   or by giving other species a competitive
   advantage.

3  Indicator-organism scheme (rat-tailed
   maggot studies)

      a  For this technique, the individual
         taxa are classified on the basis of
         their tolerance or intolerance to
         various levels of putrescible wastes.
         Taxa are classified according to
         their presence  or absence of
         different environments as deter-
         mined by field studies. Some
         reduce  data based on the presence
         or absence of indicator organisms
         to a simple numerical form for ease
         in presentation.
        t;
      b  Biologists are engaging in fruit-
         less exercise if they  intend to make
         any decisions about indicator
         organisms by operating at the
         generic level of macroinvertebrate
         identifications."  (Resh and Unzicker)

 4 Reference station methods

   Comparative  or control station methods
   compare the qualitative characteristics
   of the fauna in clean water  habitats  with
   those of fauna in habitats subject to stress.
   Stations are compared on the basis  of
   richness of species.
    If adequate background data are avail-
    able to an experienced investigator,
    these  techniques can prove quite useful—
    particularly for the purpose of demon-
    strating the effects of gross to moderate
    organic contamination on the macro-
    invertebrate community.  To detect
    more subtle changes in the macroinver-
    tebrate community,  collect quantitative
    data on numbers or biomass of organisms.
    Data on the presence of tolerant and
    intolerant taxa and richness  of  species
    may be effectively summarized for evalu-
    ation  and presentation by means of line
    graphs,  bar graphs, pie diagrams,
    histograms, or pictoral diagrams.

X  IMPORTANT ASSOCIATED ANALYSES

A  The Chemical Environment

    1  Dissolved oxygen

    2  Nutrients

    3  Toxic materials

    4  Acidity and alkalinity

    5  Etc.

 B  The Physical Environment

    1  Suspended solids

    2  Temperature

    3  Light penetration

    4  Sediment composition

    5  Etc.

XI  AREAS IN WHICH  BENTHIC STUDIES
    CAN BEST BE APPLIED

 A  Damage Assessment or Stream  Health

    If a stream is suffering from abuse the
    biota will so indicate.  A biologist  can
    determine damages by looking at the
    "critter" assemblage in a matter of
    minutes. Usually, if damages  are  not
    found,  it will not be necessary to alert
    the remainder of the agency's staff,
     2-10

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                                              Using Benthic Biota In Water Quality Evaluation
   pack all the equipment,  pay travel and per
   diem, and then wait five days before
   enough data can be assembled to begin
   evaluation.

B  By determining what damages have been
   done, the potential cause "list" can be
   reduced to  a few items for emphasis and
   the entire "wonderful worlds" of science
   and engineering need not be practiced with
   the result that much data are discarded
   later because they were not applicable to
   the problem being investigated.

C  Good benthic data associated with chemi-
   cal,  physical,  and engineering data can
   be used to predict the direction of future
   changes and to estimate the amount of
   pollutants that need to be removed from
   the waterways to make them productive
   and useful once more.

D  The benthic macroinvertebrates are an
   easily used index to stream health that
   citizens may use in stream improve-
   ment programs.  "Adopt-a-stream"
   efforts have successfully used simple
   macroinvertebrate indices.

E  The potential for restoring biological
   integrity in our flowing streams using
   macroinvertebrates has barely been
   touched.

REFERENCES

 1  Hynes,  H.  B. N.  The Ecology of Running
    Waters.  Univ. Toronto Press.   1970

 2  Keup,  L. E., Ingram, W. M. and
    Mackenthun, K. M.   The Role of
    Bottom Dwelling Macrofauna in
    Water Pollution Investigations.  USPHS
    Environmental Health Series Publ. No.
    999-WP-38, 23pp.  1966.

 3   Keup, L. E.,  Ingram,  W. M.  and
     Mackenthun, K. M.  Biology of Water
     Populations: A Collection of Selected
     Papers on Stream Pollution, Waste
     Water, and Water Treatment.
     Federal Water Pollution Control
     Administration Pub. No. CWA-3,
     290 pp.  1967.
4 Mackenthun, K.M.  The Practice of
    Water Pollution Biology.  FWQA.
    281pp.  1969.

5 Stewart, R.K., Ingram,  W.M. and
    Mackenthun, K. M.  Water Pollution
    Control, Waste Treatment and Water
    Treatment:  Selected Biological  Ref-
    erences on Fresh and Marine Waters.
    FWPCA Pub. No. WP-23, 126pp. 1966.

6 Weber,  Cornelius  I.,  Biological Field
    and Laboratory Methods for Measuring
    the Quality of Surface Waters and
    Effluents.  U.S. Environmental Pro-
    tection Agency, NERC,  Cincinnati,
    OH .   Environmental Monitoring Series
    670/4.73.001 July 1973

7 Keup, L. E.  and Stewart, R.  K.  Effects
    of  Pollution on Biota of  the Pigeon River,
    North Carolina and Tennessee.   U.  S.  EPA,
    National Field Investigations Center.   35 pp.
    1966.  (Reprinted 1973, National Training
    Center)

8 Wuhrmann,  K.,  Some Problems and
    Perspectives in Applied Limnology
    Mitt.  Internat.  Verein  Limol. 20:324-402.
    1974.

9  Armitag,  P. D., Machale, Angelu M.,  and
   Crisp, Diane C. A Survey of Stream
   Invertebrates in the Cow Green Basin
   (Upper Teesdale) Before Inundation.
   Freshwater  Biol.  4:369-398.  1974.

10 Resh,  Vincent H.  andUnzicker,  John D.
   Water Quality Monitoring and Aquatic
   Organisms: the  JWPCF 47:9-19.  1975.

11 Macan, T. T.   Running Water.  Mitt.
   Internat. Limnol.  20:301-321.  1974.

This outline was prepared by Lowell E.
Keup,  Chief,  Technical Studies Branch,
Div. of Technical Support,  EPA, Wash-
ington, D.C.  20460, and revised by
R. M.  Sinclair,  National Training Center,
MOTD, OWPO, USEPA, Cincinnati,  Ohio
45268.

Descriptors:  Aquatic Life, Benthos, Water
Quality,  Degradation, Environmental Effects,
Trophic  Level,  Biological Communities,
Ecological Distributions
                                                                                 2-11

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                           STATISTICS AS AN ECOLOGICAL TOOL
I  SAMPLING

A  Introduction

   The sampling problem is seldom fully
   appreciated in spite of the fact that the
   ecologist relies heavily on sampling ex-
   periments  as  a source of information for
   decisions.

   1  Conditions necessary

      Two main considerations  should be
      satisfied:

      a  Avoid bias

         Bias often arises from particular
         experimental conditions which al-
         most never represent  the exact
         model of the situation  about which
         inferences are desired.

      b  The sample should yield information
         on its own accuracy.

         To obtain  a valid estimate of sam-
         pling error, each batch of material
         must be so sampled that two or more
         sampling units are obtained from it.

   2  Advantages over  complete enumeration.

      These include:  reduced cost,  greater
      speed,  greater scope,  greater accuracy.

B  Definitions

   We refer to sampling from finite populations.
   These are populations from which the ex-
   perimental units can be enumerated,  and
   consequently,  randomly sampled.  In sam-
   pling  finite populations, there are several
   ways  in which a selection may be made.
   These include:
   1  Simple random sampling

      The population is listed and the plan
      and sample size fixed.  The important
      criterion is that each possible sample
      has the same probability of being
      selected.  In the actual process random
      number tables are used, and the sam-
      pling units are drawn independently.

   2  Systematic sampling

      In systematic sampling the  samples
      are equally spaced throughout the area
      or population to be sampled.   There
      are analytic   difficulties connected
      with this procedure.

   3  Stratified  random sampling

      The material or area is divided into
      uniform groups or strata and  a number
      of observations are taken from each
      stratum.

   Figure 1 illustrates random, systematic
   and stratified random sampling  along a
   line.

C  Simple Random Sampling - Notation

   Generally, guides for using simple random
   sampling are: a) when the population is
   not highly variable, b) when sampling for
   proportions,  use simple random sampling
   when the true value lies between 20 and 80%.

   1  Let YI be the i th observation in the
      population.

      Population size: N
      Sample size:     n
      Population mean:
      Y  =
                                                               N
=  -JTJ.,  for a continuous
         variable
                                                        P  =   ~:T , for a proportion
BI. MET. stat.1.2.79
                                                                                         3-1

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Statistics as an Ecological Tool
For a proportion,  Y. = 0 or 1.  Replace
S.Y. by A.

Sample mean:

   A         S  Y
   —          i  i    v
   Y = v =	=  — .  for a continuous
               n      n       . , ,
                           variable
      P  = P  = —,  for a proportion

      For a proportion, replace SY. by a.

Population variance:
                    N- 1

Population variance for a mean:

                 2
         s.2
          y
              o     , N - n
              IT   l~N~'
   Sample variance:
            (Y - y)
                —;—  an unbiased estimate
             n - 1
                       or S
   For computational purposes:

    „     SY2 - (SY.)2/ n
              n - 1

Sample variance of a mean:
       g2  ,   .L  .„...
        y       n
                         N
           n - 1
               N - n
                 N
                         when q = 1 - p
   (N - n) /N is the finite population correlation
   factor or Fpc.  It is also written as 1 - n/N
   and n/N is the sampling fraction.  If it is
   small,  say 5%, it is usually neglected.
   The confidence interval for a mean:
                                                           CI = y+ t
                                                An approximation to the confidence interval
                                                 for a proportion:
                                                           CI = p +
                                                                     /pq    N - n
                                                                    /  n    N  -  1
Note:  In the formula above,  estimated stan-
dard deviation is comparible to population
quantity, not sample  quantity.  Above more
commonly  used.

Example:  Attribute sampling. Of 1000
lobsters, 400 are sampled and 120 harbor a
certain parasite.  The estimated proportion
with the parasite is a/n = 120/400 = 0. 30.
The 95% confidence interval is . 30 + . 048
using the formula for CI above with
                                                 t
                                                  .05,
                                                     = 1.96.
                                                                                  .05, 10
Example: Continuous variable.  The follow-
ing 11 measurements represent a random
sample from a set of 50 objects.  Their
measurements are: 3, 6, 6/ 12,  9,  12,  10,
9, 16, 14, 17. The mean is 10 and the stan-
dard deviation is 4.  The 95% confidence in-
terval for the mean is 10 +_ 2. 34, t
is 2.228.

D  Stratified Sampling.   Notation.

   To increase precision we may increase n
   or reduce population variance.  A good way
   to decrease population variance is to con-
   struct relatively homogeneous strata from
   the sampling units.  Variations in strata
   means in the population do not contribute to
   the sampling error of the estimate of the
   population mean.

   Let Y, . be the ith observation in the kth
         lei
   stratum,  k =  1, ...  , s.  Strata sizes,
   means and variances are described by
                                                    N
                                                     . ,
                                                          or P^,  and S   with corresponding
                                                 sample values of n, , y  or p,  and s, .
                                                                   rC  it     K.      K
 3-2

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       Statistics as an Ecological Tool
Stratum mean and variance:
Nk
S Y. . v
| _ i = 1 kl _ Yk
k Nk Nk
r - Ak
k Nk
Nk
K -2
S (Yki-Yk>
.2 _ i = 1 kl k
Nk - 1
Sample mean and variance for k stratum:
\
2 Y, .
£ . i-1 kl \
k ^ nk \
£ - o - &k
Pk - Pk - nk
"k
2 .S, (Yki-^2
k nk- 1
Let N = 1 Nk and n = \ "k and Nk/N = Wk
k K
where W stands for weight.
Population mean (st mean stratified):
f N Y 2 w. Y
- _ k k k _ kk
st " N k
N P -
_ 2 iNk *k _ 2 W P
st " k N k k k
Estimate of population mean:
£ . L Nk^k S W, y,
"st ^st ~ k N k k k
S
ft k k Pk 2 W, p,
st st N k
(sample means are y = 2n y /n and
k k
P = 2 nkpk/n.)
Variance of estimate of population mean:
„ „ N, S.2 N - n,
2 . _ . 2 k k w k
" (yst' ~ k N n, N,
k k
- ^ 1ST ^ 1ST nN
" KT2 " Nk ( Nk nk} " n,
N k
2 , . 2 Nw2 Pk^k Nk - "k
* ( Pst' k 2 n, N. - 2
N k k
Sample variance of the estimate of the
population mean;
2
9 1 St
c^/-\_ -1 S ivr /TVT ,,\ K
S \y i' 0 k ^1^1 ni '
J st !VT2 k k k n.
N k
2
_ 2 2 Sk 1S W s 2
' k Wk n, N k k k
k
In formulas where pfc occurs it is ignore
if small when computing confidence inter
Note:  Stratified sampling may be used with
proportional allocation or with a variable
sampling fraction.

-------
 Statistics as an Ecological Tool
II   EXPERIMENTATION

 A  Planning Steps

    1   Decide and define what the experiment
       is intended to do.  Specify population
       to which results are intended to apply.

    2   Gauge the probable accuracy of the
       results likely to be obtained.

       This is usually done by:

       a Estimating the coefficient of variation,
         the precentage variation in the ob-
         servations that cannot be accounted
         for by experimental factors.

       b Specifying a value for the accuracy
         desired in the treatment effect, ex-
         pressed as a percentage of the over-
         all mean.

       c Specifying the probability for the
         true value of the difference  to fall
         within assigned limits.

 B  Experimental Design

    Definition includes:

    1   the  set of treatments selected for com-
       parison,

    2   the  specification of the units (animals,
       plants, plots,  samples) to which the
       treatments are to be applied,

    3   the  rules by which the treatments are
       allocated to experimental units,

    4   specification of measurements or other
       records to be made on each unit.
 C  Choosing the design includes deciding:

    1  whether the design is unifactor or
       factorial - unifactor implies one
       treatment (factor) to be tested holding
       others constant.  Factorial implies all
       combinations of the different treatments
       or factors.
    2  whether  to group observations

    3  whether the number of treatments or
       conclusipns is too large to allow full
       replication - i. e.   <•>•"•*—'
       incomplete bl

 D Classification of
    signs are shown :
III  DATA INTERPRE

 A Associated Measuicmems

    Ecologists frequently obtain data which
    may look something like that shown be-
    low, and wish to perform statistical tests
    with these data.
                   x
                X   X
  B Procedure

    1  Guess the nature of the relationships
       from the graph.  That is:  we may
       have

                 y  = bx

                 y  = a  +  bx
                        b
                 y  = ax   etc.

    2  Test  the guess by  graphical inspection.

    3  Perform the appropriate computations
       on the transformed data, and  make the
       appropriate statistical tests.  Any
       equation which can be converted to the
       form:

                 y  = a  +  bx

       can be handled by ordinary regression
       computing techniques,  described in any
       standard statistical text.
  3-4

-------
                                                           Statistics as an Ecological Tool
C Examples of  Linear Relationships
         1.
At x • 0, y = 0.
Thus, there is no
intercept, and
y = bx
                                                    3.
                                                       -a
           At x = 0, y = -a.
           Thus
           y •= -a+bx
         2.
           a-
At x = 0, y - a.
There is an inter-
cept.
y = a + bx
           Negative slope,
           thus
           y = a - bx
D  Other graphs,  postulated relations, and
   graphical tests include the following:
             Raw Data
         1.
                 x
                  X
                      xxxx
         3.
                       X

                       X

                       X
                  XX*
                 XXXXXXXx
                                       Possible Equation
                                       y = ac
                -bx
                                      y = ax
Test giving linearity if
equation describes data

  log y = log  a-bx
  plot y against  x on
  semi log paper
                                   log y • log a + b log  x
                                   Plot y against x on log-log
                                   paper
                                                                Plot y against  _
                                                                                x
                                                                                            3-5

-------
Statistics as an Ecological Tool
                              Figure 1.  METHODS OF SAMPLING
                                                -x
                   -X

                   -X

                   -X
                   -X
                   -X
                                                                            -X
                                                                            -X
                                                                            -X

                                                                            -X
                random
                        systematic
                              stratified  random
    COMPLETE,
     BLOCK
                   one grouping
                   two groupings
                                            Figure  2
                                        UNIFACTOR
                                                          FACTORIAL
                                                      random blocks
                                                      Latin squares
    INCOMPLETE
     BLOCK
one grouping


two groupings
Balanced incomplete
   blocks
Lattice designs

Lattice squares
Youden squares
Confounded designs
Fractional replications
Split-plots

Quasi-latin squares
 3-6

-------
                                                          Statistics as an Ecological Tool
E  Calculations in Regression and Correlation

   1  The basic observations are in pairs of
      associated observations represented by
      (x, y).  We assume x and y follow,  at
      least approximately, a bivariate normal
      distribution.

   2  A convenient desk calculator procedure
      is to find the sums, and sums of squares
      of products as follows:
(1)
 n
Z X

zx2
                 Z Y
                Z Y
                            ZXY
      Next,  calculate the three quantities in
      the line below:
(2)   --   ( Z X)
                —  (Z Y)2, — (ZX) (ZY)
                n           n
                                                       The variance of the deviations of y from
                                                       the regression line is estimated by:
                                                                n - 2
                                                                           Sx
                                                       The correlation coefficient r is cal-
                                                       culated as:
                                                        r  =
                                                                   Zxy
(Zx)(Zy
                                                 REFERENCES

                                                 Elementary
                                                    Snedecor,  G. W.  Statistical Methods.
                                                       Fifth edition. Iowa State College Press,
                                                       1956.
      Subtract each of these from the last
      line of set (1) to give the corrected sums
      of squares and cross-products.
                                             Sampling

                                                Cochran,  W. G.  Sampling Techniques.
                                                   New York: John Wiley &  Sons,  1953.
(3)  Zx2 = ZX2 - -  (ZX)2,  Zy2 = ZY2 - - (ZY)2,
                n                     n
           Zxy = ZXY -    (ZX) (ZY)
                                             Experimental Design

                                                Cochran,  W. G. ,  and Cox,  G. M.   Experi-
                                                   mental Designs.  Second edition.  New
                                                   York: John Wiley & Sons, 1957.
      The estimate of the true regression co-
      efficient is given by:
(4)  b  =
       Zxy
         2~
        x

    and the  constant a is given by

    a = y - bx.
                                                 Bioassay

                                                    Finney, N. J.  Statistical Method in Bio-
                                                       logical Assay.  London: Charles Griffin
                                                       and Company, 1952.

                                                 This outline was prepared by S. B. Saila,
                                                 Associate Professor of Oceanography,
                                                 Graduate School of Oceanography, University
                                                 of Rhode Island, Kingston, Rhode Island.

                                                 Descriptors:  Statistics, Statistical Methods,
                                                 Data Processing and Ecology
                                                                                       3-7

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                    THE INTERPRETATION OF BIOLOGICAL DATA
                        WITH REFERENCE TO WATER QUALITY
 I  INTRODUCTION

 Sanitary engineers like to have data
 presented to them in a readily assimilable
 form and some of them seem a little
 impatient with biologists who appear unable
 to provide definite quantitative criteria
 applicable to all kinds of water conditions.
 I think the feeling tends to be that this is
 the fault of biologists, and if they would
 only pull themselves out of the scientific
 stone-age all would be well.  I will try to
 explain here why I believe that biological
 data  can never be absolute nor interpret -
 able without a certain amount of expertise.
 In this respect biologists resemble medical
 men who make their diagnoses against a
 complex background of detailed knowledge.
 Anyone can diagnose an open wound but it
 takes a doctor to identify an obscure
 disease; and although he can explain how
 he does it he cannot pass on his knowledge
 in that one explanation.  Similarly, one
 does not need an  expert to recognize gross
 organic pollution, but only a biologist can
 interpret more subtle biological conditions
 in a water body; and here again he can
 explain how  he does it,  but that does not
 make his hearer a biologist.  Beck (1957)
 said  something similar at a previous
 symposium in Cincinnati in 1956.
II   THE COMPLEXITY OF BIOLOGICAL
    REACTIONS TO WATER CONDITIONS

 A  Complexity of the Aquatic Habitat

    The aquatic habitat is complex and
    consists not only of water but of the
    substrata beneath it,  which may be
    only indirectly influenced by  the quality
    of the water.  Moreover,  in biological
    terms, water quality includes such
    features as rate of flow and tempera-
    ture regime,  which are not considered
    of direct importance by the chemist.
To many animals and plants,  maximum
summer temperature or maximum
rate of flow is just as important as
minimum oxygen tension.  The result
is that inland waters provide  an
enormous array of different com-
binations of conditions, each  of which
has its own community of plants and
animals; and the variety of species
involved is very great.  Thus, for
example,  Germany has about  6000
species of aquatic animals (lilies 196 la)
and probably at least as many species
of plants.  Yet Europe has a rather
restricted fauna because of the
Pleistocene ice age; in most other
parts of the world the flora and fauna
are even richer.

Distribution of Species and Environ-
mental Factors

We know something about the  way in
which species are distributed in the
various habitats, especially in the
relatively much studied continent of
Europe, but we have, as yet,  little
idea as to what factors or combination
of factors actually control the individual
species.

1   Important ecological factors

    Thus, it is possible to list the
    groups of organisms that occur in
    swift  stony upland rivers
    (rhithron in the  sense of lilies,
    1961b) and to contrast them with
    those of the lower sluggish reaches
    (potamon).  Similarly we know,
    more or less, the different floras
    and faunas we can expect in
    infertile (oligotrophic) and fertile
    (eutrophic) lakes.  We are,  however,
    much less informed as to just what
    ecological factors cause these
    differences. We know they include
    temperature and its yearly
BI.EN. Id. 10.75
                                                                                    4-1

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The Interpretation of Biological Data with Reference to Water Quality
        amplitude; oxygen, particularly at
        minimal levels; plant nutrients,
        such as nitrate, phosphate, silica,
        and bicarbonate; other ions in
        solution,  including calcium, chloride,
        and possibly hydrogen;  dissolved
        organic matter, which is necessary
        for some bacteria and fungi and
        probably for some algae; the nature
        of the substratum; and current.

    2   Complexity of interacting factors

        We also know these factors can
        interact in a complex manner and
        that their action on any particular
        organism can be indirect through
        other members of the biota.

        a    Induced periphyton growths

             Heavy growths of encrusting
             algae induced by large amounts
             of plant nutrients,  or of
             bacteria induced by ample
             supplies of organic matter,
             can eliminate or decimate
             populations of lithophile insects
             by  simple mechanical inter-
             ference.  But the change does
             not stop there: the growths
             themselves provide habitats
             for the animals,  such as
             Chironomidae and Naidid worms,
             which could not otherwise  live
             on the stones.

        b    Oxygen levels and depositing
             substrates

             If oxygen conditions over a
             muddy bottom reach levels
             just low enough to be intolerable
             to leeches, tubificid worms,
             which the leeches normally
             hold in check,  are  able to  build
             up to enormous numbers
             especially as some of their
             competitors (e. g. Chironomus)
             are also eliminated.
c   Oxygen levels and non muddy
    substrates

    One then finds the typical
    outburst of sludge worms, so
    often cited as indicators of
    pollution.  This does not
    happen if the same oxygen
    tension occurs  over sand or
    rock,  however,  as these are
    not suitable substrata for the
    worms. Many such examples
    could be given,  but they would
    only be ones we understand;
    there must be a far greater
    number about which we know
    nothing.

d   One must conclude, therefore,
    that quite simple chemical
    changes can produce far-
    reaching biological effects;
    that we only understand a
    small proportion of them; and
    that they are not always the
    same.

Classic examples

This seems like a note of despair,
however,  if water quality deviates
too far from normal, the effects
are immediately apparent.  Thus,
poisonous  substances eliminate
many species and may leave no
animals (Hynes  1960); excessive
quantities  of salt remove all
leeches, amphipods, and most
insects and leave a fauna con-
sisting  largely of Chironomidae,
caddis worms,  and oligochaetes
(Albrecht 1954) and  excessive
amounts of dissolved organic
matter  give rise to carpets of
sewage fungus, which never occur
naturally.   Here no  great biologi-
cal expertise is needed, and there
is little difficulty in the
communication of results.  It is
when  effects are slighter and  more
subtle that biological findings
 4-2

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                        The Interpretation of Biological Data with Reference to Water Quality
III
        become difficult to transmit
        intelligibly to other disciplines.
THE PROBLEMS IN PRESENTATION
OF BIOLOGICAL RESULTS
 Because of these difficulties various
 attempts have been made to simplify the
 presentation of biological findings, but to
 my mind none of them is very successful
 because of the complexity of the subject.
 Early attempts at systematization developed
 almost  independently on the two sides of
 the Atlantic, although they had some
 similarities.

 A  Early Studies in the  United States
    (Richardson and the  Illinois River)

    In America, there was a simple division
    into  zones of pollution,  e. g. degradation,
    septic,  and recovery,  which were
    characterized in broad general terms.
    This simple,  textbook approach is
    summarized by Whipple et al.  (1947),
    and serves fairly well for categorizing
    gross organic pollution such as has been
    mentioned above.  It was,  however,
    soon found by Richardson (1929) during
    his classical studies on the Illinois
    River that typical  "indicators" of foul
    conditions, such as  Tubificidae and
    Chironomus,  were not always present
    where they would be expected to occur.
    This was an early indication that it is
    not the water quality itself that provides
    suitable conditions for "pollution faunas, "
    but other, usually associated,  conditions -
    in this instance deposits of rich organic
    mud.  Such conditions may, in fact, be
    present in places where water  quality
    in no way resembles pollution, e. g.,
    upstream of weirs in trout streams
    where autumn leaves accumulate and
    decay and cause the  development of
    biota typical of organically polluted
    water.   Samples must therefore be
    judged against a background of biological
    knowledge. Richardson was fully aware
    of this and was in no doubt about the
    condition of the Illinois River even in
    places where his samples showed few
    or no pollution indicators.
B   The European Saprobic System

    In Europe, the initial stress was
    primarily on microorganisms and
    results were first codified in the
    early years of the century by
    Kolkwitz and Marsson.  In this
    "Saprobiensystem, " zones of organic
    pollution similar to those described
    by the American workers were defined
    and organisms were listed as charac-
    teristic of one or more zones;
                                                               TABLE 1
                                              SAPROBIENSYSTEM - A European system
                                              of classifying organisms according to their
                                              response to the organic pollution in slow
                                              moving streams.   (22)

                                                  Alpha-Mesosaprobic Zone  - Area of
                                                  active decomposition, partly aerobic,
                                                  partly anaerobic, in a stream heavily
                                                  polluted with organic wastes.

                                                  Beta-Mesosaprobic Zone - That reach
                                                  of stream that is moderately polluted
                                                  with organic wastes.

                                                  Oligosaprobic Zone - That reach of a
                                                  stream that is slightly polluted with
                                                  organic wastes and contains the
                                                  mineralized products of self-
                                                  purification from organic pollution,
                                                  but with none of the organic pollutants
                                                  remaining.

                                                  Poly saprobic Zone  - That area of a
                                                  grossly polluted stream which contains
                                                  the complex organic wastes that are
                                                  decomposing primarily by anaerobic
                                                  processes.
                                                 A recent exposition of this list is
                                                 given by Kolkwitz (1950).  It was then
                                                 claimed that with a list of the  species
                                                 occurring at a particular point it was
                                                 possible to allocate it to a saprobic
                                                 zone.  This system early  met with
                                                 criticism for several reasons.  First,
                                                                                    4-3

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 The Interpretation of Biological Data with Reference to Water Quality
                                        TABLE 2

                  SAPROBICITY LEVELS ACCORDING TO THE TROPHIC
                   STRUCTURE OF THE COMMUNITIES OF ORGANISMS
         Saprobicity Level
       Structure of the Communities of Organisms
       I  /3-oligosaprobic
Balanced relationship between producers,  consumers
and destroyers; the communities of organisms are
poor in individuals but there is a moderate variety of
species,  small biomass and low bioactivity.
      II  a-oligosaprobic
Balanced relationship between producers,  consumers
and destroyers; communities of organisms are rich in
individuals and species with a large biomass and high
bioactivity.
     Ill  /3-mesosaprobic
Substantially balanced relationship between producers,
consumers and destroyers; a relative increase in the
abundance of destroyers and, accordingly,  of the con-
sumers living off them; communities of organisms are
rich in individuals and species with a large biomass and
high bioactivity.
     IV  a-mesosaprobic
      V  /3-polysaprobic
Producers decline as compared with an increase in
consumers and destroyers; mixotrophic and amphitrophic
forms predominate among the producers; communities of
organisms rich in individuals but poor in species with a
large biomass and extremely high bioactivity; still only
few species of macro-organisms; mass development of
bacteria and bacteria-eating ciliates.

Producers drastically decline; communities of organisms
are extremely rich in individuals but poor in species with
a large  biomass and high bioactivity; macrofauna represented
only by  a few species of tubificids and chironomids; as in
IV these are in great abundance; mass development of
bacteria and bacteria-eating ciliates.
     VI  a -polysaprobic
Producers are absent; the total biomass is formed
practically solely by anaerobic bacteria and fungi;
macro-organisms are absent;  flagellates outnumber
ciliates amongst the protozoa.
      Saprobicity - "Within the bioactivity of a body of water,  Saprobicity is the sum
                   total of all those metabolic processes which are the antithesis of
                   primary production.  It is therefore the sum total of all those
                   processes which are accompanied by a  loss of potential energy. "
                   Part I, Prague Convention.
4-4

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                     The Interpretation of Biological Data with Reference to Water Quality
   all the organisms listed occurred in
   natural habitats--they were not evolved
   in polluted water--and there was much
   doubt as to the placing of many of the
   species in the lists.   The system, how-
   ever, did serve to codify ecological
   knowledge about a long list of species
   along an extended trophic scale.  Its
   weaknesses appeared to be merely due
   to lack of knowledge; such a rigid
   system took far too little account of the
   complexity of the reaction of organisms
   to their habitats.  For instance, many
   organisms  can be found, albeit rarely,
   in a wide range of conditions and others
   may occur  in restricted zones for
   reasons that have nothing to do with
   water quality.  We often do not know if
   organisms  confined to clean headwaters
   are kept there by high oxygen content,
   low summer temperatures,  or inability
   to compete with other species under
   other conditions. In the swift waters of
   Switzerland the system broke down in
   that some organisms appeared in more
   polluted zones than their position in the
   lists would indicate.   Presumably here
   the controlling factor was oxygen, which
   was relatively plentiful  in turbulent cold
   water. In a recent series of experiments,
   Zimmerman (1962) has proven that
   current alone has a great influence on
   the biota, and identically polluted water
   flowing at different speeds produces
   biotic communities characteristic of
   different saprobic levels.  He finds this
   surprising,  but to me it seems an
   expected result, for  the reasons given
   above.

C  Recent Advances in the Saprobic System

   1    Perhaps Zimmerman's  surprise
       reflects the deeply rooted entrench-
       ment of the Saprobiensystem in
       Central Europe.  Despite its obvious
       shortcomings it  has been  revised
       and extended.  Liebmann  (1951)
       introduced the concept of  consider-
       ing number as well as occurrence
       and very rightly pointed out that the
       community of organisms is what
       matters rather than mere species
       lists.   But he did not stress the
importance of extrinsic factors,
such as current, nor that the
system can only apply to organic
pollution and that different types
of organic pollution differ in their
effects; e.g., carbohydrate solu-
tions from paper works produce
different results from those of
sewage,  as they contain little
nitrogen and very different  sus -
pended solids.   Other workers
(Sladecek 1961 and references
therein) have subdivided the more
polluted zones,  which now,  instead
of being merely descriptive, are
considered to represent definite
ranges of oxygen content, BOD,
sulfide, and even E.  coli populations.
Every  water chemist knows that
BOD and oxygen content are not
directly related and to assume that
either  should be more than  vaguely
related to the complexities  of
biological  reactions seems to me
to indicate a fundamental lack of
ecological understanding.  I also
think it is  damaging to the hope of
mutual understanding between the
various disciplines concerned with
water  quality to give the impression
that one can expect to find a close
and rigid relationship between
water  quality measurements as
assessed by different sets of
parameters.  Inevitably these
relationships vary with local con-
ditions; what applies in a sluggish
river in summer will certainly  not
apply to a mountain stream or even
to the  same river in the winter.
Correlation of  data, even within
one discipline, needs understanding,
knowledge,  and judgment.

Gaspers and Schulz (1960) showed
that the failure of the system to
distinguish between waters that are
naturally productive and those
artifically  enriched can lead to
absurd results. They studied a
canal in Hamburg,  which because
of its urban situation can only be
regarded as grossly polluted.
Yet it  develops a rich plankton.
                                                                                    4-5

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 The Interpretation of Biological Data with Reference to Water Quality
         the composition of which, according
         to the system,  shows it to be
         virtually clean.

  D Numerical Application of the Saprobic
    System

    Once the  Saprobiensystem was accepted
    it was logical to attempt to reduce its
    findings to simple figures or graphs for
    presentation of results.  Several such
    methods were  developed, which are
    described by Tumpling (1960), who also
    gives the original references.  In all
    these methods, the  abundance of each
    species is recorded on some sort of
    logarithmic scale (e.g.  1 for present,
    3 for frequent,  5 for common, etc.).
    The sums of these abundances in each
    saprobic  level are plotted on graphs,
    the two most polluted zones showing as
    negative and others  as positive.   Or, the
    various saprobic levels are given
    numerical values [1 for oligosaprobic
    (clean),  2 for j3-mesosaprobic,  etc.]
    and the rating  for each species is
    multiplied by its abundance number.
    The sum  of all these products divided
    by the sum of all the frequencies gives
    a  "saprobic index" for the locality.
    Clearly the higher this number,  the
    worse the water quality in terms of
    organic pollution.  In a  similar  way the
    so-called "relative  Belastung" (relative
    load) is calculated by expressing the
    sums of all the abundances of organisms
    characteristic of the two most-polluted
    zones as  a percentage of the  sum of all
    abundances.  Then 100 percent is
    completely polluted water,  and clean
    localities will give a low number.

  E Weaknesses of the Saprobic System

    There are various elaborations  of these .
    methods, such as sharing of species
    between zones and taking account of
    changes in base-line as one passes
    downstream.   None of them,  however,
    eliminates the basic weaknesses of the
    system nor the fact that, as Caspers
    and Schulz (1960) point out,  there is
    little agreement between the  various
         authors in the assignment of species to
         the different levels.  Therefore, one
         gains a number or a figure that looks
         precise and is  easily understood, but
         it is based on very dubious foundations.

     F   Comparative North American Systems

         Similar systems are indigenous to
         North America, but were independently
         evolved.

         1    Wurtz (1955) and Wurtz and Dolan
              (1960) describe a system whereby
              animals are divided  into sensitive-
              to-pollution and non-sensitive
              (others are ignored), and also into
              burrowing, sessile,  and foraging
              species  (six classes).
     BSFP BSFP BSFP  BSFP  BSFP  BSFP BSFP BSFP BSFP
                                              13
          M-6
     M-5
M-4   8/ZTA6
8/2648 RECOVERY
  EPTC
                                             14
                                             M-8
                                             8/28/48
                                       RECOVRY DEGRAD.
   \OOJ-
Figure 1. Histograms, based on selected organisms, illustrating stream
  reaches of clean, degradation, septic, and recovery conditions [after
  Wurtz]  1(22)
             Numbers of these species rep-
             resented are plotted for each station
             as six histograms on the basis of
             percentage of total number of
             species.  If the constitution of the
             fauna from control stations or from
             similar localities is known,  it is
             possible to express numerically
             "biological depression" (i.e.,
             percentage reduction in total
4-6

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               The Interpretation of Biological Data with Reference to Water Quality
number of species), "biological
distortion" (changes in pro-
portions of tolerant and non-tolerant
species), and "biological skewness"
(changes in the ratios of the three
habitat classes).  Such results must,
of course, be evaluated,  and the
definition of tolerance is quite
subjective; but the method has the
advantages of simplicity and depend-
ence on control  data.  Like  the
Saprobiensystem, however,  it can
have no universal validity.   It also
suffers from the fact that it takes
no account of numbers; a single
specimen, which may be there by
accident, carries as  much weight
as a dense population.

Patrick (1949) developed a  similar
system in which several clean
stations  on the water body being
investigated are chosen,  and the
average  number of species is deter-
mined occurring in each of seven
groups of taxa chosen because of
their supposed reaction to pollution.
These are then plotted as seven
columns of equal height,  and data
from other stations are plotted on
the same scale;  it is  assumed that
stations  differing markedly  from the
controls will show biological
imbalance in that  the columns will be
of very unequal heights.  Number is
indicated by double width in any
column containing species with an
unusual number  of individuals.
I have already questioned the use-
fulness of this method of presentation
(Hynes 1960), and doubt whether it
gives any more readily assimilable
data than simple tabulation;  it does
however, introduce the concept of
ecological imbalance.
200


150
                        250

                        200
                              £
                               SEMI-HEALTHY
    III..
_n
         3
                               VERY POLLUTED
Figure 2. Histograms, based on selected organisms, illustrating healthy,
  semi-healthy, polluted, and  very polluted stations in Conestoga
  Basin, Pa. [ after Patrick ]  (22)
        TABLE 3 —Classification of Groups
            of Organisms Shown in Figure2
 I     Blue-green algae; green algae of the genera Stigeoc/onium, Spi-
       rogyra, and TVibonema; the bdelloid rotifers plus Cepha/odelfa
       mega/ocephala and Proales dec/piens
 II     Oligochaetes, leeches, and pulmonate snails
 III     Protozoa
 IV     Diatoms, red algae, and "most of the green algae"
 V     All rotifers not included in Group I, clams, gill-breathing snails,
       and tricladid ftatworms
 VI     All insects and Crustacea
VII     All fish
         Beak  (1964),  another author,
         recognized the need for a concise
         expression of pollution based on
         biological information. Toward
         this end, he developed a method of
         biological scoring which is based on
         the frequency of occurrence  of
         certain macroscopic invertebrates
         obtained from 6 years of study on
         one river.  It will be  noted that the
         Biological Score is a  modification
         and expansion of Beck's Biotic
         Index.

-------
   The Interpretation of Biological Data with Reference to Water Quality
            The indicator organisms are
            divided into three categories:
            Group  I contains the pollution -
            tolerant species; Group II comprises
            those species which are facultative
            with respect to pollution; and
            Group  III contains the pollution-
            intolerant forms.  Each group is
            assigned a weighted score that can
            be allotted to field samples  on the
            following basis:

            a   Normal complement of  Group III
                scores 3 points.

            b   Normal complement of  Group II
                scores 2 points.

            c   Normal complement of  Group I
                scores 1 point.

            The scores are additive; thus an
            unpolluted  stream will have a
            Biological  Score of 6.  If only
            pollution-tolerant forms are found,
            the score will be 1.  If no organisms
            are found,  the score will be zero.
            Furthermore,  a score of, 1 or 2
            points  could be allotted to Group III
            when less than the normal com-
            plement is present.  Group  II could
            be treated  in a similar manner.
            This scoring device correlated well
            with the biological oxygen demand,
            dissolved oxygen, and solids content
            of the  receiving water. Beak also
            related his scoring device to the
            fisheries potential. This relation-
            ship is shown in Table 4]


                     TABLE 4
TENTATIVE RELATIONSHIP OF THE BIOLOGICAL SCORE TO THE FISHERIES
            POTENTIAL (after Beak, 196-1) (30)
                                          It has long been known that
                                          ecologically severe habitats con-
                                          tain fewer species than normal
                                          habitats and that the few species
                                          that can survive the  severe con-
                                          ditions are often very abundant as
                                          they lack  competitors.  Examples
                                          of this are the countless millions
                                          of Artemia and Ephydra in saline
                                          lakes and the  Tubifex tubifex in
                                          foul mud.   This idea has often been
                                          expressed in terms of diversity,
                                          which is some measure of numbers
                                          of species divided by number of
                                          specimens collected.  Clearly,
                                          such a parameter is larger the
                                          greater the diversity,  and hence
                                          the normality of the  habitat.
                                          Unfortunately, though as the
                                          number of species in any habitat
                                          is fixed, it also decreases as
                                          sample size increases so no index
                                          of diversity has any  absolute value
                                          (Hairston 1959).   If a definite
                                          sample size is fixed, however, in
                                          respect to numbers of organisms
                                          identified, it is possible to  arrive
                                          at a constant index.
                                     20
                                   f
                                     10
Pollution status
Biotic index
Fisheries potential
       o          10          ?o
                Miles from source
Figure 3.  Zooplankton species diversity
per thousand individuals encountered in
marine systems affected by waste waters
from petrochemical industrial wastes.
The  vertical lines indicate seasonal
variations. (30)
Unpolluted

Slight to moderate pollution

Moderate pollution
Moderate to heavy pollution

Heavy pollution
Severe pollution, usually toxic
    6     All normal fisheries for type of
          water well developed
  5 or 4   Most sensitive fish species re-
          duced in numbers or missing
    3     Only coarse fisheries maintained
    2     If fish present, only those with
           high toleration of pollution
    1     Yen- little, if any, fishery
    0     No fish
   4-8

-------
                           The Interpretation of Biological Data with Reference to Water Quality
           Patrick et al. (1954) in effect used
           this concept in a study of diatom
           species growing on slides suspended
           in water for fixed periods. They
           identified 8000 specimens per
           sample and plotted the results as
           number of species per interval
           against number of specimens per
           species on a logarithmic scale.
           This method of plotting gives a
           truncated normal curve  for a wide
           variety of biotic communities.
           In an ordinarily diverse habitat the
           mode is high and the curve short;
           i.e., many species occur in small
           numbers and none is very abundant.
           In a severe habitat the mode is low
           and the curve long; i. e., there  are
           few rare species and a few with
           large numbers.  This, again,  seems
           to me to be an elaborate way of
           presenting data and to involve  a lot
           of unnecessary arithmetic.
30 -
                                          __
15
   1-2  2-4  4f  3-lf,  16-32 ~32-~5 C-1-12S 1?8- •<•:,
                          ?55 512  !
              Number of ! vjvijvj •':, ;,rr $j:2(:;?~
    Figure 4.  A graphic comparison of diatom
    communities from two different environ-
    ments.  (After Patrick et al.,  1954)  (30)


       6   Diversity indices vs tabulated data

           Allanson (1961) has applied this
           method to the invertebrate faunas
           of streams in South Africa and has
           shown,  as has Patrick for diatoms,
           that the log normal curve  is flatter
           and longer for polluted stations;
           the difference, however,  is not so
           apparent that it does  not need
exposition.  Here,  again,  I would
suggest that tabulated data are just
as informative.  Indeed I would go
further and say that tabulated data
are essential in the present state
of our knowledge.  We are learning
as we go along and if the  details of
the basic findings are concealed by
some sort  of arithmetical manip-
ulation they cannot be re-interpreted
in the light of later knowledge,  nor
are they preserved in the  store of
human knowledge.  This point
becomes particularly clear when
one examines some of the early
studies that include tables.
Butcher (1946) requotes a con-
siderable amount of data  he
collected from studies of various
English rivers during the  thirties;
they are not only clear and easy to
follow, but they are also  informative
about the generalities of pollution
in a way that data quoted  only
within the confines of some
particular  system are not.

Examples of tabulated data(Table  5)

Simple tabulation of biological data
in relation to water quality,  either
in terms of number of organisms,
percentage composition of the biota,
some arbitrary abundance scale,
or as histograms, has been
effectively practiced in many parts
of the world:  in America  (Gaufin
and Tarzwell  1952,  Gaufin 1958),
Africa (Harrison 1958 and 1960,
Hynes and  Williams 1962), Europe
(Albrecht 1954, Kaiser 1951,
Hynes 1961, Hynes and Roberts
1962), and New Zealand (Hirsch
1958) to cite a few.  These tabu-
lated  data are easy to follow, are
informative to the expert reader,
and conceal no facts.  Although the
non-biologist may find them tedious,
he need only read the explanatory
paragraphs.  It is a delusion to
think  that it is possible to reduce
biological data to simple  numerical
levels. At best, these can only be
produced for limited situations and
                                                                                         4-9

-------
The Interpretation of Biological Data with Reference to Water Quality
                  TABLE 5
ORGAH1SM3
DeodroBoma
Spongllla fragills
Trochoapongilla leidyi
Unidentified Sponge
Cordylopbora lacustrls
Dugeala tigrina
Urnatella gracllis
Psludlcella articulata
Fredericella sultana
Prlstina
Hals coanunls
ParanaiB
Unidentified leech
Unidentified Beetle
Chaoborus punctipennls
HydrobaenuB sp. A
Cricotopiia bicinctuo
Unidentified Tendlpedlnl
Harnischia ep. A
Tendlpes oervoaua
Tendlpea, uodestus
Polypedllun sp. B
Calopsectra exigua
Trycorythodes
Stenoneaa
Agraylea
Athripsodes
Pataayia flava
Bydropsyche orrlfl
Cheumatopsyche
Paychonyildae Genua A
Lithasia verrucoBa
Ferrisala shlmekll
QuadrulA sp.
Quadrula tuberculata
Corbicula fluminea
TOTAL

left
F
C
C

5
C
C



31
59
1
51

152

mid


F





5
Ik

1
22
1
90
298
right



2



1
5
2
16
2

2
21
5
56

left

C
p
k
F
1


9
7
5
1
1
2
1(1
141
1 It
30
i*
11
261

aid

F
A
k
F



1
117
29
k
12
3

5

229
671
right '


A
6
F
1


68
1
2
15
7
1)8

17
92
33
1
2
1
381

left



14
F
y
i


i
i
i
3
1
1
19
2
11
7
1
77
11*1
1
mid

A
A



7


26
1
8
2
169

in
.LJA
30
193
5
575
,153
right
F


19
F
F

1

1
3
1
101
1
23^
11
21
1
19
7
M7

  F - rev C -
             A - abundant
  Benthos from Pickwick Tailwater  (35)
         even then they need verbal exposition;
         at worst, they give a spurious im-
         pression of having absolute validity.

    8    Comparison of stations

         My final point in this section con-
         cerns comparisons.   It is claimed
         that the German system, in effect,
         measures  an absolute state,  a
         definite level of water quality. We
         have seen that this is not a tenable
         claim.  In the other  systems, by
         and large, the need to establish
         local control stations at which to
         measure the normal or "natural"
         biotic conditions is accepted, and
         then other areas are compared with
         this supposed norm.  This is, of
         course not always possible as there
         may remain no unaffected area, or
         no unaffected area that is,  with
         respect to such factors as current,
nature of substratum, etc.,
sufficiently similar to act as a
base-line for data.  Nevertheless,
basically,  these systems can be
used to compare stations and thus
to assess changes in water quality.
In doing this, they can all be used
more or less successfully, but I
maintain that a table is just as use-
ful as an elaborate analysis, and
I believe that the table should be
included witn whatever is done.
For a particular situation,  however,
it is often possible to distill the data
into a single figure as a measure of
similarity between stations.

Coefficients of similarity

Burlington (1962) and Dean and Bur-
lington (1963) have recently proposed
an entirely objective means of doing
this,  which involves simple arith-
metical manipulation.  In his system,
a "prominence value" is calculated
for each species at each station.
This is a product of  its  density and
some function of its frequency in
samples, but the details of this
calculation can be altered to suit
any particular situation.  Then a
coefficient of similarity between
each pair of stations can be calcu-
lated by dividing twice the  sum of
the lower prominence values of taxa
that the two stations have in common
by the sum of all the prominence
values of both stations.  Identical
 stations will then have a coefficient
 of similarity of 1:00; this coefficient
 will be lower the more  the stations
 differ from one another.  This is an
 easy way to compare stations in an
 entirely unbiased way and as such
 may satisfy the need for numerical
 exposition; however, it tells one
 nothing about why the localities are
 different and like all the other more
 or less numerical methods of pre-
 senting data has no absolute value.
 Moreover, it still leaves unanswered
 the fundamental question of how
 different is "different?"
    10

-------
                       The Interpretation of Biological Data with Reference to Water Quality
                                          TABLE 6
•^ Clean
TY (high multiple use indicated^
Order of Tendency to Disappear as |N
gree of Pollution Increases '
DB
CO
OT-(
ci
cO
00
a o
1
•{^Polluted
Types of
Organisms
Present
Plecoptera
nymph
present
Ephemeroptera
nymph
present
Trichoptera
larvae
present
Gammaridae
present
Asellus and/or
Lirceus
present
Tubificid worms,
Tendipes , and
Cricotopus
bicinctus
(one or more of
these groups)
All above types
absent
BIOTIC INDEX
Variety Present
More than one species
One species only
\>
More than one species
JL>
One species only
More than one species
One species only *
All above species absent
All above species absent
All above species absent
Some organisms such as
Eristalis tenax not requiring
dissolved oxygen may be present
•\/ Total Number of Groups
Present
0-1
~
—
—
--
--
4
3
2
1
0
2-5
Bio
7
6
6
5
5
4
4
3
2
1
6-10
Inde
8
7
7
6
6
5
5
4
3
2
11-15
9
8
8
7
7
6
6
5
4
~
16+
10
9
9*
8
8
7
7
6

—
 *Stenonema nepotellum excluded          10^. main stream reservoirs and west Tennessee streams
 * Stenonema nepotellum (Ephem.) is counted in this section for the purpose of classification.

       V QKE FOR EACH KNOWN SPECIES IN THESE GROUPS:

               Platyhelminthes
               Hirudinea
               Mollusca
               Crustacea
               Plecoptera
               Diptera (excluding specific ones  listed below)
               Coleoptera
               Neuroptera
       V ONE FOR EACH GROUP.  REGARDLESS  OF NUMBER OF SPECIES, ETC.:
               Annelida excluding  Naididae
               Naididae
               Each Mayfly genera  (excluding  Stenonema nepotellum)
               Stenonema nepotellum
               Each Trichoptera family
               Chironomidae (excluding  specific ones listed below)
               Chironomus  riparius  and  plumosus and Cricotopus bicinctus.
               Family Simuliidae
adapted from Trent  River Board  -  Tennessee Stream Pollution Control Board 8/66 RMS
                                                                                               11

-------
 The Interpretation of Biological  Data With Reference to Water  Quality
IV   THE  PROBLEMS OF SAMPLING

  The systems outlined above are all based on
  the assumption that it is possible to sample
  an aquatic habitat with some degree  of
  accuracy; this  is  a  dubious assumption,
  however,  when applied to biological data.
  From what has been said about the com-
  plexity of biological  reactions to the various
  factors in the environment, and from the
  obvious fact that rivers especially are a
  mosaic of microhabitats,  it is clear that to
  achieve numerical accuracy or even  some
  limits  of confidence  considerable  numbers
  of samples need  to  be taken.   Indeed,  even
  in so  apparently  unvaried a habitat as  a
  single  riffle, Needham and Usinger (1956)
  showed that a very  large  number  of  samples
  would be necessary to give significant
  numerical data.

  A   Representative  Sampling
      There is a limit to the number  of  sam-
      ples that can reasonably be  taken and,
      anyway,  it is desirable to sample many
      different types  of habitat  so as to get
      as  broad as possible an estimate of the
      biota.    This is  the more recent  approach
      of most  of the  workers in Central  Europe,
      who have been  content to cite abundances
      on  a  simple relative  but arbitrary  scale
      and to convert  this to figures on some      C
      sort of  logarithmic scale for use in
      calculations.   An alternative is  to  ex-
      press  the  catch in terms of percentage
      composition,  but this had the  disadvantage
      that micro- and macro-organisms cannot
      be  expressed on the  same scale  as they
      are obtained by different  collecting tech-
      niques.  Also,  of course,  implicit in
      this approach is the  assumption that
      the sampling is reasonably representa-
      tive.   Here again we run into the need for
      knowledge  and  expertise.   In collection as
      well as  in  interpretation, the  expert is
      essential.   Biological sampling,   unlike
      the simple,  or fairly simple,  filling of
      bottles for chemical  analysis or the
      monitoring of measuring equipment, is
      a highly skilled job and not  one  to be
      handed over to a couple of vacationing
      undergraduates who are sent out with
      a Surber sampler and told to  get on
    with it.   This point has also been made
    by other biologists,  e.g.,  Patrick (1961)
    who stresses the need  for  skilled and
    thorough collecting even for the deter-
    mination of a  species list.

B   Non-Taxonomic  Techniques
     Alternatively we  can use the less
     expert  man  when concentrating on  only
     part  of the  habitat,  using,  say, micro-
     scopical  slides suspended in the  water
     to  study  algal growth.   This method
     was  extensively used by  Butcher (1946),
     and Patrick et al.  (1954) who studied
     diatoms in this way.   This gives only
     a partial biological  picture,  but is
     useful as a  means  of monitoring a
     stretch of water  where it is possible
     that  changes might  occur.   It is a
     useful short-hand method, and as  such
     is  perhaps comparable to studying the
     oxygen absorbed  from  potassium
     permanganate instead of  carrying out
     all the usual chemical analyses on  water.
     A short method of this kind may  serve
     very well most  of the  time, but,  for
     instance,  would not be likely to  detect an
     insecticide in concentrations that  could
     entirely  eliminate arthropods and hence
     fishes by starvation.

     Monitoring

     It is possible to  work  out  biological
     monitoring  systems for any specific
     purpose.  The simplest  of  these is the
     cage of fish,  which, like a single type
     of chemical analysis,  can  be expected
     to monitor  only one thing  — the ability
     of fish to live in the water —  with no
     information on whether they can  breed
     or whether  there is anything for them
     to eat.   Beak et al. (1959) describes  a
     neat way in which  the  common  con-
     stituents of the bottom fauna of  Lake
     Ontario can be used to monitor the
     effluents from an industrial site.
     Obviously there  is  much room for such
     ingenuity in devising biological systems
     for particular conditions, but this  is
     perhaps  outside the  scope of this meeting.
    4-12

-------
                         The Interpretation of Biological Data with Reference to Water Quality
V
CONCLUSIONS
 It may appear from the previous  sections
 that my attitude to this problem is entirely
 obstructionist. This is far from being so.
 Water quality is as much biological phenom-
 enon as it is a chemical  or physical one;
 often what we want to know about water is
 almost exclusively biological - - will it smell
 nasty,  is it fit to  drink,  can one bathe in it,
 etc? I suggest, therefore, that it is desirable
 to organize water monitoring programs that
 will tell one what one wants to  know.  There
 is no point in measuring everything biolog-
 ical, just as there is no  point in performing
 every possible chemical analysis; what is
 measured should  be related to  local conditions.
 It would be a waste of time to measure
 oxygen content in a clean mountain stream;
 we know it to be high, and it becomes  worth
 measuring only if we suspect that it may
 have been lowered by pollution.  Similarly,
 there is little point in studying  the plankton
 in such a stream; we know it only reflects
 the benthic flora.   In a lake or  in a slow
 river,  on the other hand, if our interest in
 the water lies in its potability,  records of
 the plankton are of considerable importance
 as changes in plankton are, in  fact,  changes
 in the usability of the water.

 A   Periphyton and Benthos Studies

     For long-term studies, especially for
     the recording of trends or  changes
     induced by pollution, altered drainage,
     agricultural poisons, and other  havoc
     wrought by man,  one can expect in-
     formative results from two principal
     techniques: First,  we can study
     microscopic plant and animal growth
     with glass slides placed in the water for
     fixed periods; second,  we  can obtain
     random samples of the benthic fauna.
     The algae and associated microfauna
     tell one a good deal about the nutrient
     condition of the water and the changes
     that occur in  it, and the larger benthic
     fauna reveal  changes in the trophic
     status, siltation due to soil erosion,
     effects of insecticides and other poisons,
     etc.
B   Varying Levels of Complexity

    The study of growths on glass slides is
    reasonably skilled work, but can easily
    be taught to technicians; like chemical
    monitoring,  such study needs to be
    done fairly often. Sampling the benthos
    is more difficult and,  as explained
    above,  needs expert handling; unlike
    most other monitoring programs,
    however, it need be done only in-
    frequently,  say, once or twice a year.
    Inevitably sampling methods will vary
    with type of habitat; in each case,  the
    question will arise as to whether it is
    worth looking at the fish also.  It is
    here that the biologist must exercise
    judgment in  devising and carrying out
    the sampling program.

C   Data Interpretation

    Judgment is  also needed in the inter-
    pretation of the data.  It is for this
    reason  I maintain that it should all be
    tabulated so  that it remains available
    for reassessment or comparison with
    later surveys.  If need be,  some sort
    of numerical format can be prepared
    from the data for ad hoc uses, but it
    should never become a substitute for
    tabulations.  Only in this way can we
    go on building up our knowledge.
    Perhaps some day we shall be able to
    pass all this information into a com-
    puter, which will then be able to
    e^rcise better judgment than the
    biologist.  I  hope this will happen,  as
    computers are better able to remember
    and to cope with complexity than men.
    It will not, however,  pension off the
    biologist.  He will still be needed to
    collect  and identify the samples.
    I cannot imagine any computer wading
    about on rocky riffles nor persuading
    outboard motors and mechanical grabs
    to operate from the unstable  confines
    of small boats.   We shall still need
    flesh and blood  biologists long after the
    advent of the hardware water chemist,
    even though, with reference to my
    earlier analogy, a Tokyo University
                                                                                      4-13

-------
 The Interpretation of Biological Data with Reference to Water Quality
   computer recently outpointed 10 veteran
   medicals in diagnosing brain tumors and
   heart disease.  It should be pointed out,
   however, that the computer still had to be
   fed with information, so we are still
   a long way from the hardware general
   practitioner.  I believe though that he is
   likely to evolve before the hardware
   biologist; after  all,  he studies only one
   animal.
 REFERENCES
   Albrecht, M. L.  Die Wirkung der
      Kaliabwasser auf die Fauna der
      Werra and Wipper.  Z. Fisch. N.
      3:401-26.  1954.
F.
 2  Allanson, B.  R.  Investigations into the
      ecology of polluted inland waters in
      the Transvaal.  Part I.  Hydrobiologia
      18:1-94.  1961.

 3  Bartsch,  A.  F. and Ingram, W.  M.
      Biological Analysis of Water Pollution
      in North America.  Verh.  Internat.
      Verein.  Limnol.   16:788-800.  1968.

 4  Beak, T. W., de Courval,  C.  and
      Cooke, N. E.  Pollution monitoring
      and prevention by use of bivariate
      control charts.  Sew.  Industr.
      Wastes 31:1383-94.  1959.

 5  Beck, W. M. , Jr.  The Use and Abuse of
      Indicator  Organisms.  Transactions
      of a Seminar on Biological Problems
      in Water Pollution.  Cincinnati.  1957.

 6  Burlington, R. F.  Quantitative Biological
      Assessment of Pollution.  J. Wat.
      Poll. Contr. Fed.  34:179-83.  1962.

 7  Butcher,  R.  W.  The Biological Detection
      of Pollution.  J. Inst. Sew. Purif.
      2:92-7.  1946.

 8  Cairns,  John, Jr.  et al.  A Preliminary
      Report on Rapid Biological Information
      Systems for Water Pollution Control.
      JWPCF.  42(5):685-703.  1970.

 9  Caspers, H.  and Schulz, H.  Studien
      zur Wertung der Saprobiensysteme.
      Int.  Rev.  ges. Hydrobiol.  45:535-65.
      1960.

10  Dean. J.  M.  and Burlington,  R.  F.
      A Quantitative Evaluation of Pollution
      Effects on Stream Communities.
      Hydrobiologia 21:193-9.  1963.
11  Ferdjingstad, E.  Taxonomy and
       Saprobic Valency of Benthic Phyto-
       microorganisms.  Inter. Revue der
       Ges. Hydrobiol.  50(4):475-604.  1965.

12  Ferdjingstad, E.  Pollution of Streams
       Estimated by Benthal Phytomicro-
       organisms.  I.  A  System Based on
       Communities of Organisms and
       Ecological Factors.  Int.  Revue  ges.
       Hydrobiol. 49:63-131.

13  Gaufin, A.  R.   The Effects of Pollution
       on a Midwestern Stream.  Ohio J.
       Sci.  58:197-208.  1958.

14  Gaufin, A.  R.  and Tarzwell, C. M.
       Aquatic Invertebrates as Indicators
       of Stream Pollution.  Pub. Hlth.
       Rep. 67:57-64.   1952.

15  Hairston,  N. G.  Species  Abundance and
       Community Organization. Ecology
       40:404-15.   1959.

16  Harrison, A. D.  The Effects of Sulphuric
       Acid Pollution on the Biology of
       Streams in the Transvaal, South
       Africa,  Verh. Int. Ver.  Limnol.
       13:603-10.   1958.

17  Harrison, A. D.  The role of River Fauna
       in the Assessment of Pollution.
       Cons. Sci. Afr.  Sud Sahara Pub.
       64:199-212.  1960.

18  Hirsch, A.  Biological  Evaluation of
       Organic Pollution of New Zealand
       Streams.  N.Z.  J. Sci.  1:500-53.
       1958.

19  Hynes,  H. B. N.  The Biology of
       Polluted Waters.  Liverpool.  1960.

20  Hynes,  H. B. N.  The Effect of  Sheep-
       dtp  Containing the Insecticide BHC
       on the Fauna of a Small Stream.
       Ann. Trop.  Med. Parasit.
       55:192-6.  1961.

21  Hynes,  H. B. N. and Roberts, F.W.
       The Biological Effects of Detergents
       in the River Lee, Hertfordshire.
       Ann. Appl. Biol. 50:779-90. 1962.

22  Hynes,  H. B. N. and Williams,  T.  R.
       The Effect of DDT on the Fauna of
       a Central African Stream.  Ann. Trop.
       Med. Parasit.  56:78-91.  1962.

23  lilies,  J.  Die Lebensgemeinschaft des
       Bergbaches.  Wittenberg-Luther stadt.
       1961a.
   4-14

-------
                           The Interpretation of Biological Data with Reference to Water Quality
24  lilies,  J.  Versuch einer allgemeiner
       biozonotischen Gliederung der
       Fliessgewasser.  Int. Rev. ges
       Hydrobiol.  46:205-13.  1961b.

25  Ingram, W.  M., Mackenthun, K. M.,  and
       Bartsch,  A. F.  Biological Field
       Investigative Data for Water Pollution
       Surveys.   USDI, FWPCA Pub. WP-13,
       139 pages.   1966.

26  Kaiser, E. W.  Biolgiske, biokemiske,
       bacteriologiske samt hydrometriske
       undersogelser af Poleaen 1946 og
       1947.  Dansk.  Ingenforen.  Skr.
       3:15-33.  1951.

27  Keup, Lowell E.,  Ingram, W. M. ,  and
       Mackenthun, K. M.  Biology  of Water
       Pollution.  USDI.   FWPCA CWA-3,
       290 pages.   1967.

28  Kolkwitz,  R.  Oekologie der Saprobien.
       Uber die  Beziehungen der Wasser-
       organismen zur Ummelt.  Schr.
       Reihe ver Wasserhyg.  4:64 pp.  1950.

29  Liebmann, H.  Handbuch der Frischwasser
       und Abwasserbiologie.  Munich.   1951.

30  Maciel, Norma C.  Levantamento
       hipotetico de um rio com rede
       Surber.   Inst.  de  Engenharia Sanitaria,
       Rio de Janeiro, Brazil. Pub. No. 58,
       96 pages.  1969.  (Zones of pollution
       in a Brazilian river.)

31  Mackenthun, K.  M.  The Practice of
       Water Pollution Biology.  USDI.
       FWPCA.   281 pp.  1969.

32  Needham,  P. R. and Usinger, R. L.
       Variability in the  Macrofauna of a
       Single Riffle in Prosser Creek,
       California, as indicated by the Surber
       Sampler.   Hilgardia 24:383-409.  1956.

33  Olson, Theodore A.,  and Burgess,  F. J.
       Pollution and Marine Ecology.  Inter-
       science Publishers.  364 pages.   1967.

34  Patrick, R.  A Proposed Biological
       Measure  of Stream  Conditions, based
       on a Survey of the Conestoga  Basin,
       Lancaster County, Pennsylvania.
       Proc. Acad. Nat. Sci. Phila.
       101:277-341.  1949.

35  Patrick, R.  A Study of the Numbers and
       Kinds of Species found in Rivers in
       Eastern United  States.  Proc. Acad.
       Nat.  Sci.  Phila. 113:215-58.   1951.
36  Patrick,  R.,  Hohn, M.  H. and Wallace,
       J. H.  A New Method for Determining
       the Pattern of the Diatom Flora.
       Not. Nat.  Phila. Acad.  Sci.  259.
       12 pp.  1954.

37  Patrick,  Ruth.  Benthic Stream Com-
       munities.  Amer. Sci.  58:546-549.
       1970.

38  Richardson, R. E.  The Bottom Fauna of
       the Middle Illinois River,  1913-1925;
       Its Distribution, Abundance,  Valuation
       and Index Value in the Study of Stream
       Pollution.  BuH. 111. Nat.  Hist.  Surv.
       17:387-475.   1929.

39  Sinclair,  Ralph M.,  and Ingram,
       William M.  A New Record for the
       Asiatic Clam in the United States--
       The Tennessee River.  Nautilus
       74(3):114-118.  1961.  (A typical
       benthos faunal list for a large inland
       unpolluted river,  with an eroding
       substrate.)

40  Sladecek, Vladimir. Water Quality
       System. Verh.  Internat. Verein.
       Limnol.  16:809-816.  1966.

41  Sladecek, V.  Zur biologischen
       Gliederung der hoheren Saprobi-
       tatsstufen.  Arch.  Hydrobiol.
       58:103-21.  1961.

42  Sladecek, Vladimir.  The Ecological and
       Physiological Trends in the  Sapro-
       biology. Hydrobiol.  30:513-526.
       1967.

43  Tumpling, W. V.  Probleme,  Methoden
       und Ergenbnisse biologischer
       Guteuntersuchungen an Vorflutern,
       dargestellt am Beispiel der Werra.
       45:513-34.  1960.

44  Whipple,  G. C. , Fair, G.  M. and
       Whipple, M. C.  The Microscopy of
       Drinking Water.   New York.  1947.

45  Woodiwiss, F.  S.  The Biological System
       of Stream  Classification used by the
       Trent  River  Board.  Chem.  and  Ind. ,
       pp. 443-447.  March 1964.

46  Wurtz, C. B. and Dolan,  T.  A Biological
       Method Used in the Evaluation of Effects
       of Thermal Discharge in the Schuylkill
       River. Proc. Ind. Waste Conf.  Purdue.
       461-72.  1960.
                                                                                         4-15

-------
 The Interpretation of Biological Data with Reference to Water Quality
47  Zimmerman, P.  Der Einfluss auf die
      Zusammensetzung der Lebensgemein-
      schaften in Experiment.   Schweiz. Z.
      Hydrol.  24:408-11.  1962.

48  Hynes, H. B. N.  The Ecology of Flowing
      Waters in Relation to Management.
      JWPCF.  42(3):418-424. 1970.

49  Hynes, H. B. N.  The Ecology of Running
      Waters.   Univ.  of Toronto Press. 555 pp.
      1970.

50  Scott, Ralph D.  The Macro-invertebrate
      Biotic Index - A Water Quality Measure-
      ment and Natural Continuous Stream
      Monitor for the Miami River Basin.
      17 pp.  The Miami Conservancy District,
      Dayton,  OH 45402.  1969.

 51 Cooke, Norman E. Stream Surveys
      Pinpoint Pollution.  Industrial Water
      Engineering, p. 31-33. Sept.  1970.
This outline was prepared by Dr. H.B.N.
Hynes,  Chairman, Department of Biology,
University of Waterloo, Ontario, Canada.


Reprinted from:  Symposium Environmental
Measurements Valid Data and Logical
Interpretation, July 1964, PHS Publication
No. 999-AP-15, pp. 289-298.


Figures, tables,  additional references, and
headings are editorial changes by R.  M.
Sinclair, Aquatic Biologist, National Training
Center, MPOD, OWPO,  USEPA., Cincinnati,
Ohio 45268.

Descriptors:  Aquatic  Life, Benthos, Water
Quality, Environmental Effects, Biological
Indices
    4-16

-------
                               APPLICATION OF BIOLOGICAL DATA
 I   ECOLOGICAL DATA HAS TRADITIONALLY
    BEEN DIVIDED INTO TWO GENERAL
    CLASSES:

 A  Qualitative - dealing with the taxonomic
    composition of communities

 B  Quantitative - dealing with the population
    density or rates of processes occurring
    in the communities

    Each kind of data has been useful in its own
    way.
II   QUALITATIVE DATA

 A  Certain species have been identified as:

    1  Clean water (sensitive) or oligotrophic

    2  Facultative,  or tolerant

    3  Preferring polluted regions
      (see:  Fjerdinstad 1964, 1965; Gaufin
      & Tarzwell 1956; Palmer 1963, 1969;
      Rawson 1956; Teiling 1955)

 B  Using our knowledge  about ecological
    requirements the biologist may compare
    the species present

    1  At different stations in  the same river
      (Gaufin 1958) or lake (Holland 1968)

    2  In different rivers or lakes (Robertson
      and Powers 1967)

    or changes in the species in a river or/lake
    over a period of several years.  (Carr
    & Hiltunen 1965; Edmondson & Anderson
    1956; Fruh, Stewart,  Lee  & Rohlich 1966;
    Hasler 1947).

 C  Until comparatively recent times taxonomic
    data were not subject to statistical treat-
    ment.
Ill  QUANTITATIVE DATA; Typical
    Parameters of this type include:
                                 2
 A Counts  - algae/ml; benthos/m ;
    fish/net/day
                 3
 B Volume - mm  algae/liter

 C Weight  - dry wgt; ash-free wgt.

 D Chemical content - chlorophyll;
    carbohydrate; ATP; DNA; etc.

 E Calories (or caloric equivalents)

 F Processes -  productivity; respiration
IV  Historically, the chief use of statistics
 in treating biological data has been in the
 collection and analysis of samples for these
 parameters.  Recently, many methods have
 been devised to convert taxonomic data into
 numerical form to permit:

 A Better communication between the
    biologists and other scientific disciplines

 B Statistical treatment of taxonomic data

 C In the field of pollution biology these
    methods include:

    1  Numerical ratings of organisms on the
       basis of their pollution tolerance

       (saprobic valency:  Zelinka & Sladecek
       1964)

       (pollution index:  Palmer  1969)

    2  Use of quotients or ratios of species in
       different taxonomic groups (Nygaard
       1949)
  BI.EN. 3a. 6.76
                                                                                      5-1

-------
Application of Biological Data
3  Simple indices of community diversity:

   a  Organisms are placed in taxonomic
      groups which behave similarly under
      the same ecological conditions.  The
      number of species in these groups
      found at "healthy"  stations is com-
      pared to that  found at "experimental"
      stations.   (Patrick 1950)

   b  A truncated log normal  curve is
      plotted on the basis of the number
      of individuals per diatom species.
      (Patrick, Hohn,  & Wallace 1954)

   c  Sequential comparison index.
      (Cairns,  Albough,  Busey & Chanay
      1968).  In this technique,  similar
      organisms encountered  sequentially
      are grouped into "runs".
      SCI  =
                       runs
             total organisms examined
      d  Ratio of carotenoids to chlorophyll
         in phytoplankton populations:


         °D430/°D665(Margalef 1968)
                OD670(Tanaka, et al 1961)
   e  The number of  diatom species present
      at a station is considered indicative
      of water quality or pollution level.
      (Williams 1964)

      number of species (S)
      number of individuals (N)

      	number of  species (S)	
      square root of number of individuals (>J N)

   "  r~
      log^
                                                       j  Information theory:

                                                          The basic equation used for
                                                          information theory applications was
                                                          developed by Margalef (1957).
                                                                             N!
                                                                       N  ! N,  !. . . N  !
                                                          where I - information/in dividual;
                                                          N , N . . . N  are the number of
                                                          individuals in species a, b,  ...
                                                          s, and N is their sum.
         This equation has also been used
         with:

         1) The fatty acid content of algae
           (Mclntire, Tinsley, and Lowry
           1969)

         2) Algal productivity (Dickman 1968)

         3) Benthic bio mass (Wilhm 1968)
             N
                 (Menhinick 1964)
         d =
             En. (n. - 1) (Simpson 1949)
         where n. = number of individuals
                   belonging to the i-th species,
                   and
               N = total number of individuals
REFERENCES

1  Cairns, J., Jr.,  Albough, D.W.,
      Busey, F, and Chaney,  M.D.
      The sequential comparison index -
      a simplified method for non-biologists
      to estimate relative differences in
      biological diversity in stream pollution
      studies.   J. Water Poll.  Contr.  Fed.
      40(9):1607-1613.   1968.

2  Carr, J.F.  and Hiltunen,  J.K.   Changes
      in the bottom fauna of Western Lake
      Erie from 1930 to 1961.   Limnol.
      Oceanogr. 10(4):551-569.  1965.

3  Dickman, M.  Some indices  of diversity.
      Ecology 49(6):1191-1193.   1968.
   5-2

-------
                                                             Application of Biological Data
 4  Edmondson, W.T. and Anderson,  G. C.
       Artificial Eutrophication of Lake
       Washington.   Lininol. Oceanogr.
       l(l):47-53.   1956.

 5  Fjerdingstad,  E. Pollution of Streams
       estimated by benthal phytomicro-
       organisms.   I.  A saprobic system
       based on communities of organisms
       and ecological factors.   Internat'l
       Rev. Ges. Hydrobiol. 49(1):63-131.1964.

 6  Fjerdingstad,  E.  Taxonomy and saprobic
       valency of benthic phytomicro-
       organisms.   Hydrobiol.  50 (4):475-604.
       1965.

 7  Fruh, E.G.,  Stewart,  K.M.,  Lee, G.F.
       and Rohlich, G.A.   Measurements of
       eutrophication and trends.   J.  Water
       Poll. Contr. Fed. 38(8):1237-1258.
       1966.

 8  Gaufin, A.R.  Effects of Pollution on a
       midwestern stream.   Ohio J.  Sci.
       58(4):197-208.   1958.

 9  Gaufin, A.R. and Tarzwell, C.M.  Aquatic
       macroinvertebrate communities as
       indicators of organic pollution in Lytle
       Creek.  Sew.  Ind. Wastes.  28(7):906-
       924.  1956.

10  Hasler, A.D.   Eutrophication of lakes by
       domestic drainage.   Ecology 28(4):383-
       395. 1947.

11  Holland,  R.E.  Correlation of Melosira
       species with trophic conditions  in Lake
       Michigan.   Limnol.   Oceanogr.
       13(3):555-557.   1968.

12  Margalef, R.   Information theory in
       ecology.   Gen. Syst.   3:36-71.  1957.  .

13  Margalef, R.   Perspectives in ecological
       theory.  Univ.  Chicago Press.   1968.

14  Mclntire,  C.D., Tinsley, I.J. and
       Lowry,  R.R.   Fatty acids in lotic
       periphyton: another measure of
       community  structure.  J. Phycol.
       5:26-32.   1969.
15  Menhinick, E.F.  A comparison of some
       species - individuals diversity indices
       applied to samples of field insects.
       Ecology 45:859.  1964.
16  Nygaard, G.   Hydrobiological studies in
       some ponds and lakes.  II.  The
       quotient hypothesis and some new or
       little-known phytoplankton organisms.
       Klg. Danske Vidensk.  Selsk.  Biol.
       Skrifter 7:1-293.  1949.

17  Patten, B.C.  Species diversity in net
       plankton of Raritan Bay.   J.  Mar.
       Res. 20:57-75.  1962.

18  Palmer,  C.M.  The effect of pollution on
       river algae.  Ann. New York Acad.
       Sci.   108:389-395.    1963.

19  Palmer,  C.M.   A composite  rating of
       algae tolerating organic pollution.
       J.  Phycol.  5(l):78-82.  1969.

20  Patrick,  R.,  Hohn, M.H. and Wallace,
       J.H.  A new method for determining
       the pattern of the diatom flora.  Not.
       Natl. Acad. Sci., No. 259.
       Philadelphia.   1954.

21  Rawson,  D.S.  Algal indicators of trophic
       lake types.  Limnol.  Oceanogr.
       1:18-25.   1956.

22  Robertson, S. and Powers, C.F.
       Comparison of the distribution of
       organic matter in the  five  Great Lakes.
       in:  J. C. Ayers and D. C.  Chandler,
       eds.   Studies on the environment and
       eutrophication of Lake Michigan.
       Spec.  Rpt. No. 30,  Great  Lakes Res.
       Div.,Inst.  Sci. &Techn.,  Univ.
       Michigan,  Ann Arbor.  1967.

23  Simpson, E.H.   Measurement of diversity.
       Nature (London) 163:688.   1949.

24  Tanaka, O. H., Irie, S. Izuka, and Koga, F
       The fundamental investigation on the
       biological productivity in the Northwest
       of  Kyushu.  I.  The  investigation of
       plankton.  Rec. Oceanogr.  W. Japan,
       Spec.  Rpt. No. 5, 1-57.   1961.
                                                                                       5-3

-------
 Application of Biological Data
25  Teiling, E.   Some mesotrophic phyto-
      plankton indicators.  Proc. Intern.
      Assoc.  Limnol.   12:212-215.   1955.

26  Wilhm,  J. L.   Comparison of some
      diversity indices applied to populations
      of benthic  macroinvertebrates in a
      stream receiving organic wastes.  J.
      Water Poll. Contr.  Fed.   39(10):1673-1683.
      1967.

27  Wilhm,  J. L.   Use of biomass units in
      Shannon's  formula.  Ecology 49:153-156.
      1968.
28  Williams, L.G.   Possible relationships
       between diatom numbers and water
       quality.  Ecology 45(4):810-823.   1964.
29  Zelinka,  M. and Sladecek, V.   Hydro-
       biology for water management.
       State Publ. House for Technical
       Literature, Prague.    122 p.   1964.
 This outline was prepared by C.I. Weber,
 Chief,  Biological Methods Section, Analytical
 Quality Control Laboratory,  NERC, EPA,
 Cincinnati, Ohio,  45268
                                                  Descriptors:  Analytical Techniques,  Indicators
   5-4

-------
                              OPTICS AND THE MICROSCOPE
I  OPTICS

An understanding of elementary optics is
essential to the proper use of the microscope.
The  microscopist will find that unusual pro-
blems in illumination and  photomicrography
can be handled much more effectively once
the underlying ideas in physical optics are
understood.

A Reflection

   A good place to begin is with reflection at
   a surface or interface.   Specular (or
   regular) reflection results  when a beam
   of light leaves a surface at  the same angle
   at which it reached it.  This type of
   reflection occurs with highly polished
   smooth surfaces.  It is stated more pre-
   cisely as Snell's Law,  i. e., the angle of
   incidence,  i,  is equal to the angle of
   reflection, r (Figure l) • Diffuse (or
   scattered)  reflection results when a beam
   of light strikes a rough or irregular sur-
   face and different portions of the incident
   light are reflected from the surface at
   different angles.  The light reflected from
   a piece of white paper or a  ground glass is
   an example of diffuse reflection.
                 Figure 1
SPECULAR REFLECTION - SNELL'S
LAW
BI. MIC. 18.2.79
   Strictly speaking,  of course, all reflected
   light, even diffuse, obeys Snell's Law.
   Diffuse  reflected light is made up of many
   specularly reflected rays,  each from a
   a tiny element of surface, and appears
   diffuse when the reflecting elements are
   very numerous and very small.   The terms
   diffuse and .specular,  referring  to reflection,
   describe not so much a difference in the
   nature of the reflection but rather a differ-
   ence in  the type of surface.   A polished sur-
   face gives specular reflection; a rough
   surface gives diffuse  reflection.

   It is also important to note and remember
   that specularly reflected light tends to be
   strongly polarized in  the plane of the reflect-
   ing surface.  This is  due to the  fact that
   those rays  whose vibration directions  lie
   closest  to the plane of the reflection surface
   are most strongly  reflected.  This effect is
   strongest when the angle of incidence is
   such that the tangent of the angle is equal
   to the refractive index of the reflecting sur-
   face.  This particular angle of incidence is
   called the Brewster angle.

B  Image Formation on Reflection

   Considering reflection by mirrors,  we find
   (Figure 2) that a plane mirror forms a
   virtual image behind the mirror, reversed
   right to left but of the same size as the
   object.  The word  virtual means that the
   image appears to be in a given plane but
   that a ground glass screen or a  photographic
   film placed in that plane would show no
   image.  The converse of a virtual image is
   a real image.

   Spherical mirrors are either convex or con-
   cave with the surface of the mirror repre-
   senting  a portion of the surface  of a sphere.
   The center of curvature is the center of the
   sphere, part of whose surface forms the
   mirror.  The focus lies halfway between the
   center of curvature and the  mirror surface.
                                                                                     6-1

-------
Optics and the Microscope
   Object
Virtuol
Image
                  Mirror
                 Figure 2

 IMAGE FORMATION BY PLANE MIRROR
   Construction of an image by a concave
   mirror follows from the two premises
   given below (Figure 3):
                  Figure 3
 IMAGE FORMATION BY CONCAVE MIRROR

   1  A ray of light parallel to the axis of
      the mirror must pass through the
      focus after reflection.

   2  A ray of light which passes through the
      center of curvature must return along
      the same path.

 A corollary of  the first premise  is:
                                                  3  A ray of light which passes through the
                                                     focus  is reflected parallel to the axis
                                                     of the mirror.

                                                  The  image from an object can be located
                                                  using the familiar lens formula:
                                                          JL
                                                          P
                                1
                                q
                   where p = distance from the object to
                            the mirror
                         q = distance from the image to
                            the mirror
                         f  = focal length

             C  Spherical Aberration

                No spherical surface can be perfect in its
                image-forming ability.  The most serious
                of the imperfections, spherical aberration,
                occurs in spherical mirrors of large
                aperture (Figure 4). The rays of light
                making up an image point from the outer
                zone of a spherical  mirror do not pass
                through the same point as the more central
                rays. This type of aberration is  reduced by
                blocking  the outer zone rays from the image
                area or by using aspheric surfaces.
                               Figure 4

                     SPHERICAL ABERRATION BY
                         SPHERICAL MIRROR
 6-2

-------
                                                                     Optics and the Microscope
 D Refraction of Light

    Turning now to louses rather than mirrors
    we find that the  most important character-
    istic is refraction.  Refraction refers to
    the  change of direction and/or velocity of
    light as it passes  from one m.-dium to
    another.  The ratio of the velocity in air
    (or  more correctly  in a vacuum) to UK-
    velocity in the medium is called tin-
    refractive  index.  Some- typical values of
    refractive  index measured with mono-
    chromatic  light  (sodium D line) are listed
    in Table 1.

    Refraction causes an object  immi-rsed in
    a medium of higher refractive index than
    air  to appear closer to the surface than it
    actually is (Figure 5).  This effect may
                                           into focus and the new micrometer reading
                                           is taken.  Finally, the microscope is re-
                                           focused until the surface of the liquid appears
                                           in sharp focus.  The micrometer reading
                                           is taken again and, with this information,
                                           tho refractive index rmy be calculated from
                                           the simplified equation:
                                                 refractive index =
                         actual depth
                        apparent depth
                                        Table 1.   KKFRACTIVK  INDICES OF COMMON
                                        MATERIALS MKASURED  WITH SODIUM LIGHT
Vacuum
Air
CO,
Water
1. 0000000
1. 0002918
1. 0004498
i. :mo
Crown glass
Rock salt
Diamond
Lead sulfide
1.48 to
1. 5443
2.417
3.912
1. 61



Actual
depth
Apparent
  depth
                                      Air
                                      Medium
                     Image

                     Object
When the situation is reversed,  and a ray
of light from a medium of high refractive
index passes through the interface  of a
medium of lower index,  the ray  is refracted
until a critical angle is reached  beyond which
all of the light is reflected from the interface
(Figure 6).  This  critical angle, C,  has the
following relationship to the refractive  indices
of the two media:                       {


      sin C =  —2 , where no 
-------
 Optics and the  Microscope
 £  Dispersion

    Dispersion is another important property
    of transparent materials.  This is the
    variation of refractive index with color
    (or wavelength) of light.  When white light
    passes through a  glass prism,  the light
    rays are refracted by different amounts
    and separated into the colors of the
    spectrum.  This spreading of light into
    its component colors is due to dispersion
    which, in turn, is due to the fact that the
    refractive index of transparent substances,
    liquids and solids, is lower for long wave-
    lengths than for short wavelengths.

    Because of dispersion, determination of
    the refractive index of a  substance re-
    quires designation of the particular wave-
    length used.  Light from a sodium lamp
    has a strong,  closely spaced doublet with
    an average wavelength of 5893A,  called
    the D line,  which  is commonly used as a
    reference wavelength.  Table 2 illustrates
    the change of refractive index with wave-
    length for a few common substances.
 F Lenses

   There are two classes of lenses, con-
   verging and diverging,  called also convex
   and concave,  respectively.   The focal
   point of a converging lens is defined as
   the point at which a bundle of light rays
   parallel to the axis of the lens appears to
   converge  after passing  through the lens.
   The focal length of the  lens is the distance
   from the lens to the focal point (Figure 7).
 Table 2.  DISPERSION OF REFRACTIVE
INDICES OF SEVERAL COMMON MATERIALS

                       Refractive index
                    F line   D line    C line
                    blue    (yellow)   (red)
                    4861A   5893A    6563A
Carbon disulfide
Crown glass
Flint glass
Water
1.
1.
1.
• 1.
6523
5240
6391
3372
1.
1.
1.
1.
6276
5172
6270
3330
1.
1.
1.
1.
6182
5145
6221
3312
    The dispersion of a material can be defined
    quantitatively as:
                    n (yellow) - 1
    v = dispersion  =  n (£lue) . n (red)

        n (593mn)  - 1
        n (486mji) - n(656mjx)

    where n is the refractive index of the
    material at the particular wavelength
    noted in the parentheses.
                   Figure 7

CONVERGENCE OF LIGHT AT FOCAL POINT
G  Image Formation by Refraction

   Image formation by lenses (Figure  8)
   follows rules analogous to those already
   given above for mirrors:

   1  Light traveling parallel to the axis of
      the lens will be refracted so as to pass
      through the focus of the lens.

   2  Light traveling through the geometrical
      center  of the lens will be unrefracted.

   The position of the image can be determined
   by remembering that a light ray passing
   through the focus, F, will be parallel to
   the axis of the lens on the Opposite  side of
   the lens and that a ray passing through the
   geometrical center of the lens will  be
   unrefracted.
 6-4

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                                                                   Optics and the Microscope
                 Figure.' 8

 IMAGE FORMATION BY A CONVEX l.ENS

   The magnification,  M, of an image of an
   object produced by  a lens is given by the
   relationship:

           image size _  image distance _ q
           object size    object distance   p

   where q = distance  from image to lens
     and p = distance  from object to lens.

H  Aberrations of  Lenses

   Lenses have aberrations of several types
   which, unless corrected,  cause loss  of
   detail in the image.  Spherical aberration
   appears in lenses with spherical surfaces.
   Reduction of spherical aberration can be
   accomplished by diaphragming the outer
   zones of the lens or by designing special
   aspherical surfaces in the lens system.

   Chromatic aberration  is a phenomenon
   caused by the variation of refractive  index
   with wavelength (dispersion).  Thus a lens
   receiving  white light from an object will
   form a violet image closer to the lens and
   a red  one  farther away.  Achromatic
   lenses are employed to minimize this
   effect. The lenses  are combinations  of
   two or more lens elements made up of
   materials having different dispersive
   powers.  The use of monochromatic light
   is another obvious way of eliminating
   chromatic aberration.

   Astigmatism is a third aberration of
   spherical  lens systems  It occurs when
   object points are not located on the optical
   axis of the lens and results in the formation
   of an indistinct image.  The simplest
   remedy for astigmatism is  to place the
   object close to the axis of the lens system.

I  Interference Phenomena

   Interference and diffraction are two phe-
   nomena which are due  to the wave character-
   istics of light.  The superposition of  two
   light rays arriving simultaneously at a given
   point will  give rise to interference effects,
   whereby the intensity at that point will vary
   from dark to bright depending on the  phase
   differences between the two light rays.

   The first requirement  for interference  is
   that the light must come from a single
   source. The light may be split into any
   number of paths but must originate from
   the  same point (or coherent source).  Two
   light waves from a coherent source arriv-
   ing at a point in phase  agreement will
   reinforce each other (Figure 9a).  Two
   light waves from a coherent source arriv-
   ing at a point in opposite phase will cancel
   each other (Figure 9b).
   Figure 9a.
Two light rays,  1 and  2, of
the same frequency but dif-
ferent amplitudes, are in phase
in the upper diagram.   In the
lower diagram,  rays 1 and 2
interfere constructively to give
a single wave of the  same  fre-
quency and with an amplitude
equal to the summation of  the
two former waves.
                                                                                     6-5

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Optics and the Microscope
                                   o+b
  Figure 9b. Rays 1 and 2 are no.v 180°
             out of phase and interfere
             destructively.  The resultant,
             in the bottom diagram,  is of
             the same frequency but is of
             reduced  amplitude  (a is
             negative and is subtracted
             from b).
The reflection of a monochromatic light
beam by a thin film results in two beams,
one reflected from the top surface and one
from  the bottom surface.  The distance
traveled by  the latter beam in excess  of
the first is twice the thickness of the film
and its equivalent air path is:

              2 nt

   where n is the  refractive index and
   t is the thickness of the film.

The second  beam,  however, upon reflection
at the bottom surface, undergoes a half
wavelength shift and now the total retard-
ation of the  second beam with respect to
the first is given as:

      retardation  = 2 nt  + -^-
      where X is the wavelength of the light
      beam.

   When retardation is exactly an odd number
   of half wavelengths,  destructive interfer-
   ence takes place resulting in darkness.
   When it is zero or an even number of half
   wavelengths, constructive interference
   results in brightness  (Figure  10).
 6-6
               Figure 10

    INTERFERENCE IN A THIN FILM

A simple interferometer can be made by
partially silvering a microscope slide and
cover slip.  A preparation between the two
partially silvered surfaces will show  Inter-
ference fringes when viewed with mono-
chromatic light,  either transmitted or by
vertical illuminator.   The fringes will be
close together with a wedge-shaped prep-
aration and  will reflect refractive index
differences  due to temperature variations,
concentration differences, different solid
phases, etc.  The method has  been used  to
measure quantitatively the concentration of
solute around a growing crystal^MFigure 11).
                                                                     Mirror/^
                                                                 -Cover slip-
                                                                   Spccimen
\
- * ..





•i
\ /\ / x"IOO%
V X?-1 /Mirror
f *
               Figure 11
MICROSCOPICAL METHOD OF VIEWING
          INTERFERENCE IMAGES
 a  Examination is by transmitted light.
      Light  ray undergoes  multiple
      reflections and produces dark and
      light fringes  in the field.  A speci-
      men introduces a phase shift and
      changes the fringe  pattern.
 b  Illumination is from the top.  The
      principle is the  same but fringes
      show greater contrast.

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                                                                     Optics and the Microscope
   Each dark band represents an equivalent
   air thickness of an odd number of half
   wavelengths.  Conversely, each bright
   band is the result of an even number of
   half wavelengths.

   With interference illumination,  the effect
   of a transparent  object of different re-
   fractive index than the medium  in the
   microscope field is:

   1  a change of light intensity  of  the object
      if the background  is uniformly illumi-
      nated (parallel cover slip), or

   2  a shift of the interference bands within
      the  object  if the background consists
      of bands (tilted cover slip) .

   The relationship of refractive indices  of
   the surrounding  medium and the object is
   as  follows:
          d =
             nm(l
                      ex
2.44 fx
  D
       where f is the focal length of the lens,
       X the  wavelength, and D the diameter
       of the lens.

    It is seen that in order to maintain a
    small diffraction disc at a given wave-
    length, the diameter of  the lens should
    be as large as possible with respect to
    the focal length.  It should be noted,
    also, that a shorter wavelength produces
    a  smaller  disc.

    If two pin points of light are to be distin-
    guished in an image, their diffraction discs
    must not overlap more than one half their
    diameters.  The ability to distinguish such
    image  points is  called resolving power and
    is  expressed as  one half of the preceding
    expression:
                                                          resolving power =
                      360t
                             1. 22 f X
                               D
      where ns =  refractive index of the
                  specimen
            n   -  refractive index of the
                  surrounding medium
            6  =  phase shift of the  two
                  beams, degrees
            X  =  wavelength of the  light
            t  =  thickness of the specimen.
J Diffraction
  In geometrical  optics, it is assumed that
  light travels in straight lines.  This is not
  always true.   We note that a beam passing
  through a slit toward a screen  creates a
  bright band wider than the slit with alter-
  nate  bright and dark bands appearing on
  either side of the central bright band,
  decreasing in intensity as a function of
  the distance from the center.  Diffraction
  describes this phenomenon and,  as one of
  its practical consequences, limits the
  lens  in itF ability to reproduce an image.
  For example, the image of  a pin  point of
  light  produced by a lens is  not a  pin point
  but is revealed to be  a somewhat larger
  patch of light surrounded  by dark and
  bright rings.  The diameter, d,  of this
  diffraction disc (to  the first dark ring)
  is given as:
II   THE COMPOUND MICROSCOPE

 The compound microscope is an extension in
 principle of the simple magnifying glass;
 hence it is essential to understand  fully the
 properties of this simple lens system.

 A  Image Formation by the Simple  Magnifier

    The apparent size of an object is determined
    by the angle that is  formed at the eye by the
    extreme rays of the object.  By  bringing the
    object closer to the  eye, that angle (called
    the visual angle) is  increased.   This also
    increases the apparent size.  However a
    limit of accommodation of the eye is reached,
    at which distance the eye can no longer focus.
    This limiting  distance is about 10 inches or 25
    centimeters.  It is at this distance that the
    magnification of an object observed by the
    unaided eye is  said  to be unity.   The eye can,
    of course, be focused at shorter distances but
    not usually in a  relaxed condition.

    A positive,  or converging,  lens  can be used
    to permit placing an object closer than 10
    inches to  the eye (Figure 12).  By this  means
   the visual angle of the object is increased
    (as is its  apparent size) while the image of
                                                                                      6-7

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Optics and the Microscope^
                                                                          Ey«
    VIRTUAL IMAGE FORMATION BY
             CONVEX LENS

   the object appears  to be 10 inches from
   the eye,  where it is best accommodated.

B Magnification by a Single  Lens System

   The magnification, M,  of a simple magni-
   fying glass is given by:

         M-  f +1

      where f = focal length of the lens in
                centimeters.

   Theoretically the magnification can be
   increased with shorter focal length lenses.
   However such lenses require placing the
   eye  very close to the lens surface and
   have much image distortion and other
   optical aberrations.  The practical limit
   for a simple magnifying glass is about
   2 OX.

   In order to go to magnifications higher
   than 20X, the compound microscope is
   required.  Two lens systems are used
   to form  an enlarged image of an object
   ^Figure  13).  This is accomplished in
   two steps, the first by  a lens called the
   objective and the second by a lens known
   as the eyepiece (or ocular).

 C The Objective

   The objective is the lens (or lens system)
   closest to the object.  Its  function is to
   reproduce an enlarged  image of the object
   in the body tube of the microscope.
   Objectives are available in various focal
         Ob)*cttv*
         V Mud
                Figure  13
         IMAGE FORMATION IN
       COMPOUND MICROSCOPE

lengths to give different magnifications
(Table 3).  The magnification is  calculated
from the focal length by dividing the latter
into  the tube length, usually 160  mm.

The  numerical aperture (N. A.) is a measure
of the ability of an objective to resolve detail.
This is more fully discussed in the next
section.  The  working distance is in the free
space between the objective and the cover
slip  and varies slightly for objectives of the
same focal length depending upon the degree
of correction and the manufacturer.

There are three basic classifications  of
objectives:  achromats, fluorites and
apochromats,  listed in the order of their
complexity.  The achromats are good for
routine work while the  fluorites and apo-
chromats offer additional optical corrections
to compensate for spherical, chromatic and
other aberrations.
   6-8

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                                                                 Optics and the Microscopy
Table 3. NOMINAL CHARACTERISTICS OF USUAL
Nominal
focal length
mm
56
32
16
8
4
4
1.8
Nominal
magnif.
2. 5X
5
10
20
43
45
90
N. A.
0. 08
0. 10
0. 25
0.50
0. 66
0. 85
1. 30
Working
distance
mm
40
25
7
1. 3
0. 7
0.5
0.2
Depth
focus
^
50
16
8
2
1
1
0.4
Diam. of
field
mm.
8. 5
5
2
1
0.5
0.4
0.2
MICROSCOPE OBJECTIVES
Resolving
power, white
light, JJL
4.4
3.9
1.4
0. 7
0.4
0.35
0.21
Maximum
useful
magnif.
SOX
90X
250X
500X
660X
850X
1250X
Eyepiece
for max.
useful magnif,
SOX
2 OX
25X
25X
15X
20X
12X
Another system of objectives employs  •
reflecting surfaces in the shape of concave
and convex mirrors.  Reflection optics,
because they have no refracting elements,
do not suffer from chromatic aberrations
as ordinary refraction objectives do.  Based
entirely on reflection, reflecting objectives
are extremely useful in the infrared and
ultraviolet regions of the  spectrum.  They
also have a much longer working distance
than the refracting objectives.

The body tube of the microscope supports
the objective at  the bottom (over the object)
and the eyepiece at the top.  The tube
length is maintained at 160 mm except for
Leitz instruments, which have a 170-mm
tube length.

The objective support may be of two kinds,
an objective clutch changer or a rotating
nosepiece:

1  The objective clutch changer ("quick-
   change" holder) permits the  mounting  ,
   of only one objective at a  time on the
   microscope.  It has a centering arrange-
   ment, so that each objective need be
   centered only once with respect to the
   stage  rotation.  The  changing of objec-
   tives with this system is somewhat
   awkward compared with the rotating
   nosepiece.

2  The revolving nosepiece allows mounting
   three  or four objectives on the microscope
      at one time (there are  some nosepieces
      that accept five and even six objectives).
      In this system, the objectives are
      usually noncenterable and the  stage is
      centerable.  Several manufacturers pro-
      vide centerable objective mounts so that
      each objectiva on the nosepiece need  be
      centered only once to the fixed rotating
      stage.  The insides of  objectives are
      better protected from dust by  the rotating
      nosepiece.  This,  as well as the  incon-
      venience of the so-called "quick-change"
      objective holder, makes it worthwhile
      to have one's microscope  fitted with
      rotating nosepiece.

D  The Ocular

   The eyepiece, or ocular,  is necessary in
   the second step of the magnification process.
   The eyepiece functions as a simple magni-
   fier viewing the image formed by the
   objective.

   There are three classes of eyepieces in
   common use:  huyghenian, compensating
   and flat-field. The huyghenian (or huyghens)
   eyepiece is designed  to be used with
   achromats while the compensating type is
   used with fluorite and apochromatic
   objectives.  Flat-field eyepieces, as the
   name implies, are  employed in photo-
   micrography or projection and can be  used
   with most  objectives.  It is best to follow
   the recommendations of the manufacturer
   as to the proper combination of objective
   and eyepiece.
                                                                                 6-9

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Optics and the Microscope
   The usual magnifications available in
   oculars run from about 6X up to 25 or
   SOX.  The 6X is generally too low to be of
   any real value while the 25 and  30X oculars
   have slightly poorer imagery than medium
   powers and have a very low eyepoint.  The
   most useful eyepieces lie in the 10 to 20X
   magnification range.

E  Magnification of the Microscope

   The total magnification of the objective-
   eyepiece  combination is simply the product
   of the two individual magnifications.  A
   convenient working rule to assist in the
   proper choice of eyepieces states that  the
   maximum useful magnification  (MUM)  for
   the  microscope is 1, 000 times  the numeri-
   cal  aperture (N. A.) of the objective.
   The MUM is related to resolving power
   in that magnification in excess  of MUM
   gives little or no additional resolving
   power and results in what is termed empty
   magnification.  Table 4 shows the results
   of such combinations and a comparison
   with the 1000XN.A.  rule.  The under-
   lined figure shows the magnification near-
   est to the MUM and the eyepiece required
   with each objective to achieve the MUM.
   From this table it is apparent that only
   higher power eyepieces can give full use
   of the resolving power of the objectives.
   It is obvious that a 10X, or even a 15X,
   eyepiece gives insufficient magnification
   for the eye to see detail actually resolved
   by the objective.

F  Focusing the  Microscope

   The coarse adjustment is used to roughly
   position the body tube (in some newer
   microscopes, the stage) to bring the image
   into focus.  The fine adjustment is used
   after the coarse adjustment to bring the
   image into perfect focus and to maintain
   the focus as the  slide is moved across the
   stage.  Most  microscope objectives are
   parfocal so that once they are focused any
   other objective can be swung into position
   without the  necessity of refocusing except
   with the fine adjustment.

   The student of the microscope should first
   learn to focus in the  following fashion, to
   prevent damage to a  specimen or objective:

   1  Raise the body tube and place the speci-
      men on the stage.

   2  Never focus the body tube down (or the
      stage up) while observing the field
      through  the eyepiece.

   3  Lower the body tube (or raise the stage)
      with the coarse adjustment while care-
      fully observing the space between the
                   Table 4.  MICROSCOPE MAGNIFICATION CALCULATED
                    FOR VARIOUS OBJECTIVE-EYEJflECE COMBINATIONS
Objective
Focal Magni-
length
56mm
32
16
8
4
1.8
fication
3X
5
10
20
40
90
5X
15X
25X
SOX
100X
200X
450X
10X
30X
SOX
100X
200X
400X
900X
Eyepiece
15X
45X
75X
150X
300X
600X
135 OX

20X
60X
100X
200X
40 OX
800X
1800X

25X
75X
125X
25 OX
500X
1000X
2250X
MUMa
(1000 NA)
SOX
100X
250X
500X
660X
1250X
            aMUM =  maximum useful magnification
       6-10

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                                                                    Optics and the Microscope
      objective and slide and permitting the
      two to come close together without
      touching.

   4  Looking through the microscope and
      turning the fine adjustment in such a
      way as to move the  objective away from
      the specimen, bring the image into
      sharp focus.

   The fine adjustment is usually calibrated
   in one-  or two-micron steps to indicate
   the vertical movement of the body tube.
   This feature  is useful in making depth
   measurements but should not be relied
   upon for accuracy.

G  The Substage Condenser

   The substage holds the condenser and
   polarizer.  It can usually be focused in a
   vertical direction so that the condenser  can
   be brought into the correct position  with
   respect to the specimen  for proper
   illumination.  In some models, the conden-
   ser is centerable so that it may be set
   exactly  in the axis of rotation of the  stage;
   otherwise it will have been precentered  at
   the factory and should be permanent.

H  The Microscope Stage

   The stage of the microscope supports the
   specimen between the condenser and
   objective, and may offer a mechanical stage
   as an attachment to provide a means of
   moving  the slide methodically during obser-
   vation.  The polarizing microscope  is
   fitted with a circular rotating stage  to
   which a mechanical stage may be added.
   The rotating stage,  which is used for object
   orientation to observe optical effects,  will
   have centering screws if the objectives are
   not centerable, or vice versa.  It is un-
   desirable to have both objectives and stage
   centerable as this does not provide a fixed
   reference axis.

I  The Polarizing Elements

   A polarizer is fitted to the condenser of all
   polarizing microscopes.  In routine  instru-
   ments,  the polarizer is fixed with its
   vibration direction oriented north-south
   (east-west for most European instruments)
   while in research microscopes,  the
   polarizer can be rotated.  Modern instru-
   ments have polarizing filters (such as
   Polaroid) replacing the older calcite
   prisms.   Polarizing filters are preferred
   because they:

   1  are low-cost;

   2  require no maintenance;

   3  permit use of the full condenser
      aperture.

   An analyzer, of the same construction as
   the polarizer, is fitted in the body tube of
   the microscope  on a slider so that it may
   be easily removed from the optical path.
   It is  oriented with its plane of vibration
   perpendicular to the corresponding direction
   of the polarizer.

J  The Bertrand Lens-

   The Bertrand lens is  usually found only on
   the polarizing microscope although some
   manufacturers are beginning to include it
   on phase microscopes.  It is located in the
   body tube above  the analyzer on a slider
   (or pivot) to permit quick removal from
   the optical path.  The  Bertrand lens is used
   to observe the back focal plane of the objective.
   It is  convenient  for checking quickly the type
   and quality of illumination, for observing
   interference  figures of crystals, for adjust-
   ing the phase annuli in phase  microscopy
   and for adjusting the annular and central
   stops in dispersion staining.

K  The Compensator Slot

   The compensator slot  receives compensators
   (quarter-wave, first-order red and quartz-
   wedge) for observation of the  optical prop-
   erties of crystalline materials.   It is usually
   placed at the  lower end of the body tube just
   above the  objective mount, and is oriented
   45° from the  vibration directions of the
   polarizer and analyzer.

L  The Stereoscopic Microscope

   The stereoscopic microscope, also called
   the binocular, wide-fie Id,  dissecting or
                                                                                        6-11

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        and the Microscope
    Greenough binocular microscope, is in
    reality a combination of two separate
    compound microscopes.  The two micro-
    scopes, usually mounted in one body, have
    their optical axes inclined from the  vertical
    by about 7   and from each other by twice
    this angle.  When an object is placed on the
    stage of a stereoscopic microscope,  the
    optical systems view it from slightly
    different angles,  presenting a stereoscopic
    pair of images to the eyes, which fuse the
    two into a single  three-dimensional  image.
                           «.
    The objectives are supplied in pairs,  either
    as separate units to be mounted on the
    microscope or,  as in the  new instruments,
    built into a rotating drum.  Bausch and
    Lomb was the first manufacturer  to have a
    zoom lens system which gives a continuous
    change in magnification over the full range.
    Objectives for the stereomicroscope run
    from about 0. 4X to 12X, well below the
    magnification range of objectives  available
    for single-objective microscopes.

    The eyepieces supplied with stereoscopic
    microscopes run from 10 to 25X and have
    wider fields than their counterparts  in the
    single-objective microscopes.

    Because of mechanical limitations, the
    stereomicroscope is limited to about 200X
    magnification and usually does not permit
    more than about  120X.  It is most useful
    at relatively low  powers in observing
    shape and surface texture, relegating the
    study of greater detail to the monocular
    microscope.  The stereomicroscope is
    also helpful in manipulating small samples.
    separating ingredients of mixtures,  pre-
    paring specimens for detailed study at
    higher magnifications  and  performing
    various mechanical operations under micro-
    scopical observation, e. g. micromanipulation.
Ill  ILLUMINATION AND RESOLVING POWER

 Good resolving power and optimum specimen
 contrast are prerequisites for good microscopy.
 Assuming the availability of suitable  optics
 (ocular, objectives and substage condenser)
 it is still of paramount importance to use
 proper illumination.  The requirement for a
good illumination system for the microscope
is to have uniform intensity of illumination
over the entire field of view with independent
control of intensity and of the angular aperture
of the illuminating cone.

A  Basic Types of Illumination

   There are three types of illumination
   (Table 5) used generally:

   1  Critical.  This is used when high levels
      of illumination intensity are necessary
      for oil immersion,  darkfield,  fluores-
      cence,  low birefringence or photo-
      micrographic studies.  Since the lamp
      filament is imaged in the plane of the
      specimen, a ribbon filament or arc
      lamp is required.  The lamp must be
      focusable and have an iris diaphragm;
      the position of the filament must also
      be adjustable in all directions.

   2  Kohler.  Also useful for  intense illumi-
      nation,  Kohler illumination may be
      obtained with any lamp not fitted with a
      ground  glass.  The illuminator must,
      however, be focusable,  it must have an
      adjustable field diaphragm (iris) and the
      lamp filament position must be adjust-
      able in all directions.

   3  "Poor man's".  So-called because a low-
      priced illuminator may be used, this
      method gives illumination of high quality
      although of lower intensity because of the
      presence of a ground glass in  the system.
      No adjustments are necessary on the
      illuminator or lamp filament although
      an adjustable diaphragm on the illuminator
      is helpful.

   All three types  of illumination require that
   the microscope substage condenser focus
   the image of the illuminator aperture in the
   plane of the specimen.  In each case, then,
   the lamp iris acts as a field diaphragm and
   should be closed to just illuminate the field
   of  view. The differences in these three
   types of illumination lie in the adjustment
   of  the lamp condensing lens.  With poor
   man's illumination there is no lamp conden-
   ser,  hence no adjustment.  The lamp should
   be  placed close  to the microscope so that
  6-12

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                                                                 Optics and the Microscope
                         Table 5.  COMPARISON OF CRITICAL,
                       KOHLER AND JfOOR MAN'S ILLUMINATION
                                    Critical
   Kohler
Poor man's
Lamp filament
Lamp condensing lens
Lamp iris
Ground glass at lamp
Image of light source
Image of field iris
Image of substage iris
ribbon filament
required
required
none
in object plane
near object
plane
back focal plane
of objective
any type
required
required
none
at substage
iris
in object
plane
back focal plane
of objective
any type
none
useful
present
none
near object
plane
back focal plane
of objective
the entire field of view is always
illuminated.  If the surface structure of the
ground glass becomes apparent in the field
of view the substage condenser is very
slightly defocused.

Critical Illumination

With critical illumination the lamp conden-
ser is focused to give parallel rays;  focus-
ing the lamp filament on a far wall is
sufficient.  Aimed, then, at the substage
mirror,  the substage condenser will focus
the lamp filament in the object plane. The
substage condenser iris will now be found
imaged in the back focal plane of the ob-
jective; it serves as a control over con-
vergence of the  illumination.   Although the
substage iris also affects the light intensity
over the  field of view it should most  decid-
edly not be used for this purpose.  The
intensity of illumination may  be varied by
the use of neutral density filters and, unless
color photomicrography is anticipated, by
the use of variable voltage on the  lamp
filament.
  u
Kohler illumination (Figure 14) differs
from  critical illumination in the use  of the
lamp  condenser.   With critical illumination
the lamp condenser focuse^ the lamp
filament  at infinity; with Kohler illumination
the lamp filament is focused in the plane of
the substage condenser iris (also coincident
with the anterior focal plane of the substage
condenser).  The functions of the lamp
condenser iris and the substage  condenser
iris in controlling, respectively, the  area
of the illuminated field of view and the
angular aperture of the illuminating cone
are precisely alike for all three types of
illumination.

Critical illumination is seldom used because
it requires a special lamp filament and be-
cause, when used,  it( shows no advantage
over well-adjusted Kohler illumination.
  It
Kohler Illumination

To arrange the microscope and illuminator
for Kohler illumination it is well to proceed
through the following steps:

   a  Remove the diffusers and filters
      from the lamp.

   b  Turn the lamp on and aim at a con-
      venient wall or vertical screen  about
      19 inches away. Open the lamp
      diaphragm.

   c  By moving the lamp condenser,  focus
      a sharp image of the filament.   It
      should be of such a size as  to fill,
      not necessarily evenly, the microscope
                                                                                       6-13

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Optics and the Microscope
                Critical
Kohler
    Eye

  Eyepoint


    Ocular



  Focal plane
  Focal plane
  Objective
  Preparation

  Substage
    condenser

  Substage  —•
      iris
  Lamp iris —j
  Lamp
    condenser

  Light source
Poor man's
6-14

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                                                              Optics and the Microscope
   substage condenser opening.  If it
   does not,  move the lamp away from
   the wall to enlarge the filament image;
   refocus.

d  Turn the lamp and aim it a I the micro-
   scope mirror so  as to maintain the
   same 18  inches (or adjusted  lamp
   distance).

e  Place a specimen on  the microscope
   stage and focus sharply  with a l(i-mm
   (10X) objective.   Open fully the
   aperture diaphragm in the substage
   condenser.  If the light is  too bright,
   temporarily place a neutral density
   filter or  a diffuser in the lamp.

f  Close the lamp diaphragm, or field
   diaphragm,  to about a 1-cm opening.
   Rack the microscope  substage con-
   denser up and down to focus the
   field diaphragm sharply in the same
   plane as  the specimen.

g  Adjust  the mirror to  center the field
   diaphragm in the  field of view.

h  Remove the 16-mm objective  and
   replace with a 4-mm objective.  Move
   the specimen so that  a clear area is
   under observation.  Place the
   Bertrand  lens in  the optical path,  or
   remove the eyepiece  and insert an
   auxiliary  telescope (sold with phase
   contrast accessories) in its place,
   or remove the eyepiece and observe
   the back aperture of the  objective
   directly.   Remove any ground glass
   diffusers from the lamp.  Now
   observe the lamp filament through
   the microscope.

i  If the filament does not appear to be
   centered,  swing the lamp housing in
   a horizontal arc whose center is at
   the field diaphragm.  The purpose
   is  to maintain the field diaphragm on
   the lamp  in its centered  position.   If
   a vertical movement of the filament
   is  required, loosen the buib base and
   slide it up or down.  If the base is
   fixed, tilt the lamp housing in a
   vertical arc with  the field diaphragm
      as the center of movement (again
      endeavoring to keep the lamp dia-
      phragm in the centered position).
      If you have mastered this step, you
      have  accomplished the mast difficult
      portion.   (Belter microscope lamps
      have  adjustments to move the bulb
      independently of the lamp housing to
      simplify this step. )

   j  Put the specimen in place, replace
      the eyepiece and the desired objec-
      tive and  re-focus.

   k  Open  or close the field diaphragm
      until  it just disappears from the field.

   1  Observe the back aperture of the
      objective,  preferably  with the Bertrand
      lens or the.auxiliary telescope,  and
      close the aperture diaphragm on the
      substage condenser until it is about
      four-fifths the diameter of the back
      aperture.  This is the best position
      for the aperture diaphragm, a posi-
      tion which  minimizes glare and maxi-
      mizes the resolving power.  It is
      instructive  to vary  the  aperture dia-
      phragm and observe the image criti-
      cally  during the manipulation.

   m If the illumination is too great,
      insert an appropriate neutral density
      filter between the illuminator and
      the condenser. Do not use the con-
      denser aperture diaphragm or the
      lamp  field  diaphragm to control the
      intensity of illumination.

Poor Man's Illumination

Both critical and Kohler illumination  re-
quire expensive illuminators with adjust-
able focus,  lamp iris and adjustable lamp
mounts. Poor man's illumination requires
a cheap illuminator although an expensive
illuminator  may be used if its expensive
features are negated by inserting a ground
glass diffuser or by using a frosted bulb.
Admittedly  an iris diaphragm on the lamp
would be a help though it is not necessary.

   a  The illuminator must have a frosted
      bulb or a ground glass dif?user.
                                                                                 6-15

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Optics and the Microscope
         It should bo possible to direct it in
         the general direction of the substage
         mirror, very close thereto or in
         place thereof.

      b  Focus on any preparation after
         tilting the  mirror to illuminate the
         field.

      c  Remove the top lens of the condenser
         and, by racking the condenser up or,
         more often,  down, bring into focus
         (in the  same plane as  the specimen)
         a finger, pencil or other object placed
         in the  same general region as the
         ground glass diffuser  on the lamp.
         The glass  surface itself can then be
         focused in the plane of the specimen.

      d  Ideally the ground glass surface will
         just fill the field of view when centered
         by the substage mirror; adjustment
         may be made by moving the  lamp
         closer to or farther from the micro-
         scope  (the position might be marked
         for each objective used) or by cutting
         paper  diaphragms of fixed aperture
         (one for each objective used).  In this
         instance a lamp iris would be useful.

      e  Lower the condenser just sufficiently
         to defocus the ground  glass surface
         and render the  field of illumination
         even.

      f  Observe the back aperture of the
         objective and open the  substage con-
         denser iris about 75 percent of the
         way.  The final adjustment of the
         substage iris is made while observing
         the preparation; the iris should be
         open as far as possible,  still giving
         good contrast.

      g  The intensity of illumination should
         be adjusted only with neutral density
         filters or by changing the lamp voltage.

   Proper illumination  is one of the most im-
   portant operations in microscopy.  It is
   easy tojwdge a microscopist's ability by
   a glance at his field  of view and the objec-
   tive back lens.
H  llcsolving Power

   The resolving power of the microscope is
   its ability to distinguish separate details
   of closely spaced microscopic structures.
   The theoretical limit of resolving two
   discrete points,  a distance X  apart, is:
         „    • • •~«*rx
         X    2 N.~A~.

      where X  - wavelength of light used to
                 illuminate the specimen
          N. A. = numerical aperture of the
                 objective

   Substituting a  wavelength of 4, 500
   Angstroms and a numerical aperture of
   1. 3, about the best that can be done with
   visible light, we  find that two points about
   2, OOOA (or 0. 2 micron) apart can be seen
   as two separate points. Further increase
   in resolving power can be achieved for the
   light microscope by using light or shorter
   wavelength.  Ultraviolet light near 2, 000
   Angstroms lowers the limit to about 0. 1
   micron, the lower limit for the light
   microscope.

   The numerical aperture of an objective is
   usually engraved on the objective and is
   related to the angular aperture, AA
   (Figure 15), by the formula:
         N. A. = n sin
                      AA
                      —
      where n - the lowest index in the space
                between the object and the
                objective.
                           Angular aperture
      Object
                                                                   Figure 15

                                                           ANGULAR APERTURE OF
                                                           MICROSCOPE OBJECTIVE
   6-16

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                                                                 Optics and the Microscope
1  Maximum useful magnification

   A helpful rule of thumb is that the use-
   ful magnification will not exceed 1, 000
   times the numerical aperture of the
   objective (see Tables 3 and 4).  Although
   somewhat higher magnification may be
   used in specific cases,  no additional
   detail will be resolved.

   It is curious, considering the figures
   in the table, that most, if not all, manu-
   facturers of microscopes furnish a 10X
   eyepiece as the highest power.  A 10X
   eyepiece is useful but anyone interested
   in critical work should  use a  15-25X  eye-
   piece; the 5-10X eyepieces are best for
   scanning purposes.

2  Abbe's theory of resolution

   One of the most cogent  theories of
   resolution is due to Ernst Abbe,  who
   suggested that microscopic objects act
   like diffraction gratings (Figure  16) and
   that the angle of diffraction,  therefore,
   increases with  the fineness of the detail.
   He proposed that a given microscope
   objective would resolve a particular
   detail if at least two or three  transmitted
   rays (one direct and two diffracted rays)
   entered the objective.   In Figure 16 the
   detail shown would be resolved in A and
   C but not in B.   This theory,  which can
   be borne out by simple  experiment, is
   useful in showing how to improve resolu-
   tion.  Since shorter wavelengths will
   give a smaller diffraction angle, there
   is more chance of resolving fine  detail
   with short wavelengths. Also, since
   only two of the transmitted rays are
   needed,  oblique light and a high N. A.
   condenser will aid in resolving fine detail.

3   Improving resolving power

   The following list summarizes the
   practical approaches to higher resolu-
   tion with the light microscope:

   a  The specimen should be illuminated
     by either critical or  Kohler
     illumination.
                               /
             Figure  16

 ABBE THEORY OF RESOLUTION
b  The condenser should b^e well-
   corrected and have a numerical
   aperture as high as the objective to
   be used.

c  An apochromatic oil-immersion
   objective should be used with a com-
   pensating eyepiece of at least 15X
   magnification.  The  immersion oil
   should have an index close to 1. 515
   and have proper dispersion for the
   objective being used.

d  Immersion oil should be placed
   between the condenser and slide and
   between cover slip and objective.
   The  preparation itself should be
   surrounded by a liquid having a
   refractive index of 1. 515 or more.

e  The  illumination  should be reasonably
   monochromatic and as short in wave-
   length as possible. An interference
   filter transmitting a wavelength of
   about 480-500 millimicrons is a
   suitable answer to this problem.
   Ideally, of cpurse, ultraviolet light
   should be used to decrease the wave-
   length still further.

The practical effect of many of these
factors is critically discussed  by
Loveland^2) in a paper on the optics of
object space.
                                                                                    6-17

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 Optics and the Microscope
IV  PHOTOMICROGRAPHY

 A Introduction

    Photomicrography, as distinct from micro-
    photography, is the art of taking pictures
    through the microscope.  A microphoto-
    graph is a small photograph; a photomicro-
    graph is a photograph of a small object.
    Photomicrography is a valuable tool in
    recording the results of microscopical
    study.  It enables the microscopist to:

    1  describe a microscopic field objectively
       without resorting to written descriptions.

    2  record a particular field for future
       reference,

    3  make particle size counts and counting
       analyses easily and without tying up a
       microscope,

    4  enhance or exaggerate the visual micro-
       scopic field to bring out or emphasize
       certain details not readily apparent
       visually,

    5  record images in ultraviolet and infra-
       red microscopy which are otherwise
       invisible to the unaided eye.

    There are two general approaches to photo-
    micrography; one requires only a plate or
    film holder supported above  the eyepiece
    of the microscope with a light-tight bellows;
    the other utilizes any ordinary camera with
    its own lens system,  supported with a light-
    tight adaptor above the eyepiece.  It is
    best, in the latter case,  to use a reflex
    camera so that the image can be carefully
    focused on the ground glass.  Photomi-
    crography of this type can be regarded
    simply as replacing the eye with the camera
    lens system.  The camera should be  focused
    at infinity, just as the eye is for visual
    observation, and it should be positioned
    close to and over the eyepiece.

    The requirements for photomicrography,
    however, are more rigorous than those
    for visual work.  The eye can normally
    compensate for varying light intensities,
   curvature of field and depth of field.  The
   photographic plate, however,  lies in one
   plane; hence the greatest care must be
   used to focus sharply on the subject plane
   of interest and to select optics to give
   minimum amounts of field curvature and
   chromatic aberrations.

   With black and white film,  color filters
   may be used to enhance the contrast of
   some portions of the specimen while mini-
   mizing chromatic aberrations of the lenses.
   In color work, however, filters cannot
   usually be used for this purpose and better
   optics may be  required.

   Photomicrographic cameras which fit
   directly onto the microscope are available
   in 35-mm or up to 3-1/4 X 4-1/4  inch sizes.
   Others are made which accommodate larger
   film sizes and which have their own support
   independent of the  microscope.  The former,
   however, are preferred for ease of handling
   and lower cost.  The latter system is pre-
   ferred for greater flexibility and versatility
   and lack of vibration. The Polaroid camera
   has many applications in microscopy and
   can be used  on the microscope directly but,
   because of its weight, only when the micro-
   scope has a  vertically moving stage for
   focusing rather than a focusing body tube.

B  Determination of Correct Exposure

   Correct exposure determination can be
   accomplished by trial and error,  by relating
   new conditions to previously used  successful
   conditions and by photometry.

   With the trial and error method a  series of
   trial exposures is  made, noting the type of
   subject, illumination, filters, objective,
   eyepiece,  magnification, film and  shutter
   speed.  The best exposure  is selected.  The
   following parameters can be changed and
   the exposure time  adjusted accordingly:

   1  Magnification.  Exposure time  varies
     as the square of the magnification.

      Example:   Good exposure  was  obtained
                 with a 1/10-second  exposure
                 and a magnification of  100X.
                 If the magnification is now
      6-18

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                                                             Optics and the Microscope
           200X,  the correct exposure
           is calculated as follows:

new exposure time = old exposure time
   .new magnification.2 =  ,/in /200v2 =
   \>ld magnification  '  ~J/1U1100'
4/10 or, say, 1/2 second.
                                                               Kodachrome II Type A
                                                               Professional is 40.

                                                    new exposure time = old exposure time

                                                    X A.S.A. of old film  = 1/100(400/40) =
                                                      A.S.A. of new film

                                                    10/100 or 1/10 second.
   It should be noted, however,  that the
   above calculation can be made only when
   there has been no change in the illumi-
   nation system including the condenser
   or the objective.  Only changes in magni-
   fication due to changing eyepieces or
   bellows extension distance  can be hand-
   led in the above manner.

2  Numerical aperture.  Exposure time
   varies  inversely as the square of the
   smallest working numerical aperture
   of the condenser and objective.

   Example:   Good exposure  was obtained
              at 1/10 second  with the 10X
              objective, N.A. 0.25, at
              full aperture.   With a 20X
              objective, N.A. 0. 25, at
              full aperture and  the same
              final magnification, what  is
              the correct exposure  time?

   new exposure time = old exposure time

   v (         )2 = 1/10 (-^—;r)2 = 1/40 or,
     vnewN. A.           0.50

   say,  1/50 second.

   It is seen that more light reaches the
   photographic film with higher numeri-
   cal apertures at the same  magnification.

3  Film.  Exposure time varies inversely
   with the American Standards  Association
   speed index of the film.

   Example:   A good picture  was obtained
              with Eastman Tri-X  film at
              1/100 second.   What is the
              correct exposure for
              Eastman Kodachrome II
              Type A.  The A.S.A. speed
              for Tri-X is 400 and for
                                               4  Other parameters may be varied but the
                                                 prediction of exposure  time cannot be
                                                 made readily.  Experience and photo-
                                                 electric devices are the best guides to
                                                 the proper exposure.

                                               Photoelectric devices are excellent for
                                               determining  correct exposure.  Since
                                               ordinary photographic exposure meters
                                               are not sensitive enough for photomi-
                                               crography, more sensitive instruments,
                                               having a galvanometer or  electronic
                                               amplifying circuit, are required.   Some
                                               photosensitive cells are inserted in the
                                               body tube in  place of the eyepiece for
                                               light intensity readings.  This has the
                                               advantage of detecting the  light level at  a
                                               point of high intensity but  does not take
                                               into account  the eyepiece,  the distance to
                                               the film or the film speed.

                                               The cell may be placed just above the eye-
                                               piece so that  it registers the total amount
                                               of light leaving the eyepiece. Again, the
                                               effects of film speed and the projection
                                               distance are  not accounted for.  The prin-
                                               cipal drawback with the total light
                                               measuring photometer is the difficulty of
                                               taking into account the area of field covered.
                                               Take,  for example,  a bright field in which
                                               only a few crystals appear; perhaps 1 per-
                                               cent of the light entering the field of view is
                                               scattered by  the crystals and the photometer
                                               shows close  to a maximum reading.  Now
                                               assume that  everything remains constant
                                               except the number of crystals and, conse-
                                               quently,  the  amount of light scattered.
                                               The photometer reading could easily drop
                                               by 50 percent, yet the proper exposure  is
                                               unchanged.  The situation  is similar for
                                               photomicrography with crossed polars since
                                               the photometer reading depends on the
                                               intensity of illumination,  on the bire-
                                               fringence and thickness of the crystals and
                                                                               6-19

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Optics and the Microscope
   on the number and size of the crystals in
   the field or,  alternatively, on the area of
   the field covered by birefringent crystals.
   One of the best solutions to this problem
   is to measure the photometer reading with
   no preparation on the stage.  A first-order
   red compensator or a quartz wedge is  in-
   serted when crossed polars are being used
   to illuminate the entire field.

   An alternative is to place the cell on the
   ground glass where the film will be
   located.  However, although all variables
   except film speed are now taken into
   account, measurements in the image plane
   have the disadvantage of requiring a more
   sensitive electronic photoelectric apparatus.

   No matter what method is used for placing
   the photocell, the exposure  time  can be
   determined by the general formula:
      exposure time =  meter reading •

   The constant k will depend on the physical
   arrangement and film used.  To determine
   k for any particular system, first set up
   the microscope to take a picture.  Record
   the meter reading and take a series of
   trial exposures.  Pick out the best exposure
   and calculate k.  Then the k which was
   determined holds as long as no change is
   made in the light path beyond the photocell,
   e. g.  changing to a faster film or changing
   the projection distance.  Thus the objective,
   condenser position or illuminator may be
   changed without affecting k  if the cell is
   used as described above.

   Example:  With one particular arrange-
              ment of photocell and  film,
              the meter reading is  found to
              be 40.  A series of photographs
              are taken at 1/2,  1/5,  1/10,
               1/25 and 1/50 seconds.   The
              photomicrograph taken at 1/5
               second is judged to be the best;
               hence k is calculated as follows:

               k = meter reading X exposure
               time = 40 X 1/5 = 8.

               Assume now that a new picture
               is to be taken at another
               magnification (but with the
               same film and projection
               distance) and that the new
               meter reading is 16; therefore:

               exposure time = k/meter
               reading = 8/16 = 1/2 second.
V   MICROMETRY

 A  Particle Size Determination

    Linear distances and areas can be
    measured with the microscope.  This
    permits determination of particle size
    and quantitative analysis  of physical
    mixtures. The usual unit of length for
    microscopical measurements is the  micron
    (1 X 10-3mm or about 4 X 10~5inch).
    Measuring particles  in electron microscopy
    requires an  even smaller unit,  the milli-
    micron (1 X  10~3 micron or 10 Angstrom
    units).   Table 6 shows the approximate
    average' size of a few common airborne
    materials.
 Table 6.  APPROXIMATE PARTICLE SIZE OF
      SEVERAL COMMON PARTICULATES
 Ragweed pollen

 Fog droplets
 Power plant flyash
 (after precipitators)
 Tobacco smoke


 Foundry fumes
  25 microns
  20 microns
 2-5 microns


   0. 2 micron
  (200 millimicrons)
   0. 1 - 1 micron
(100-1000 millimicrons)
    The practical lower limit of accurate
    particle size measurement with the light
    microscope is about 0. 5 micron.  The
    measurement of a particle smaller than
    this with the light microscope leads to
    errors which, under the best circum-
    stances, increase to about + 100 percent
    (usually +).

    One of the  principal uses of high resolving
    power is in the precise measurement of
  6-20

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                                                                Optics and the Microscope
particle size.  There are, however,  a
variety of approximate and useful proce-
dures as well.

1  Methods of particle size measurement

   a  Knowing the magnification of the
      microscope (product of the magni-
      fication of objective and eyepiece),
      the size of particles can be esti-
      mated.  For example,  with a 10X
      eyepiece  and a 16-mm (or 10X)
      objective, the total  magnification
      is 100X.  A particle that appears to
      be  10-mm at 10  inches from the eye
      has an actual size of 10 mm divided
      by  100 or 0. 10 mm  or  100 microns.
      This is in no sense  an accurate
      method, but it does permit quick
      estimation of particle size; the error
      in this estimation is usually 10-25
      percent.

   b  Another approximate method is also
      based on  the use of  known data. If
      we know approximately the diameter
      of the microscope field, we can
      estimate  the percentage of the
      diameter occupied by the object to
      be measured and calculate from
      these figures the approximate size
      of the object.  The size of the micro-
      scope field depends on both the objec-
      tive and the  ocular although the latter
      is a minor influence.  The size of
      the field should be determined with
      a millimeter scale for each objective
      and  ocular.  If this  is done,  esti-
      mation of sizes by comparison  with
      the entire field diameter can be quite
      accurate  (5-10%).

   c  The movement of a  graduated mechan-
      ical stage can also be used for  rough
      measurement of diameters of large
      particles.  Stages are usually gradu-
      ated  (with vernier) to read to 0. 1
      millimeter,  or 100  microns.  In
      practice,  the leading edge of the
      particle is brought to one  of the lines
      of the cross hair in the eyepiece and
      a reading is taken of the stage position.
      Then the particle is moved across the
      field by moving the  mechanical stage
   in an appropriate direction until the
   second trailing edge just touches the
   cross-hair line.  A second reading is
   taken and the difference in the two
   readings is the distance moved or  the
   size of the particle.   This method  is
   especially useful when the particle
   is larger than the field, or when the
   optics give a distorted image near the
   edge of the field.

d  The above method can be  extended to
   projection or photography.  The image
   of the particles can be projected on a
   screen with a suitable light source or
   they may be photographed.  The final
   magnification, M, on the  projection
   surface  (or film plane)  is given approxi-
   mately by

         M = DXO. M.  XE. M. 125

      where  O. M. = objective magnification
             E. M. = eyepiece magnification
               D  = projection distance
                    from  the eyepiece in
                    centimeters.

   The image detail can then be measured
   in centimeters and the actual  size com-
   puted by  dividing by M. This method
   is usually accurate to within 2-5 percent
   depending on the size range of the detail
   measured.

e  The stated magnifications and/or focal
   lengths of the microscope optics are
   nominal and vary a bit from objective
   to objective or eyepiece to eyepiece.
   To obtain accurate measurements, a
   stage  micrometer is used to calibrate
   each combination of eyepiece and
   objective. The stage micrometer is
   a glass microscope slide that has,
   accurately engraved  in the center,  a
   scale, usually 2 millimeters long,
   divided into 200 parts, each part repre-
   senting 0. 01 millimeter.  Thus when
   this scale is observed,  projected or
   photographed, the exact image magni-
   fication can be determined. For
   example,  if 5 spaces of the stage micro-
   meter measure 6 millimeters when
   projected, the actual magnification is
                                                                                     6-21

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Optics and the Microscope
              5 (0.01)
                       = 120 times.
        This magnification figure can be
        used to improve the accuracy of
        method 4 above.

      f  The simplest procedure and the most
        accurate is based on the use of a
        micrometer eyepiece.  Since  the
        eyepiece magnifies a real image
        from the  objective,  it is possible
        to place a transparent scale in the
        same plane as  the image from the
        objective and thus have a scale
        superimposed over the image.  This
        is done by first placing an eyepiece
        micrometer scale disc in the  eyepiece.
        The eyepiece micrometer has an
        arbitrary scale and must be cali-
        brated with each objective used.  The
        simplest way to do this is to place
        the stage micrometer  on the stage
        and note a convenient whole number
        of eyepiece micrometer divisions.
        The value in microns for each eye-
        piece micrometer division is then
        easily computed.   When the stage
        micrometer is removed and replaced
        by the specimen,  the superimposed
        eyepiece  scale can be  used for accu-
        rate measurement of any feature in
        the specimen by direct observation,
        photography or projection.

   2  Calibration of eyepiece micrometer

      Each micrometer stage scale has
      divisions lOOn (0. 1 mm) apart; one
      or two of these are usually subdivided
      into 10u  (0. 01-mm) divisions.  These
      form the standard against which the
      arbitrary divisions in the micrometer
      eyepiece are to be calibrated.  Each
      objective must be calibrated separately
      by noting the correspondence between
      the stage scale and the eyepiece  scale.
      Starting with the lowest power objective
      focus on the stage scale,  arrange the
      two scales parallel and in good focus.
      It should be possible  to determine the
      number of eyepiece divisions exactly
      equal to  some  whole number of
      divisions of the stage scale, a distance
      readily expressed in  microns.
       The calibration consists, then, of
       calculating the number of microns per
       eyepiece scale division.  To make the
       comparison as accurate as possible, a
       large part of each scale must be used
       (see Figure 17).  Let's assume that
       with the low power 16-mm  objective
       6 large divisions of the stage  scale
       (s. m. d.) are equal to 38 divisions of
       the eyepiece scale.  This means that
       38 eyepiece micrometer divisions (e.m. d.)
       are equivalent to 600 microns.  Hence:

            1 e. m. d.  = 600/38
                      = 15. 8n.
                   Figure 17

   COMPARISON OF STAGE MICROMETER
SCALE WITH EYEPIECE MICROMETER SCALE

       Thus when that micrometer eyepiece
       is used with that 16-mm objective each
       division of the eyepiece scale is equivalent
       to 15. 8n,  and it can be used to make an
       accurate measurement of any object on
       the microscope stage. A particle,  for
       example,  observed with the 16-mm objec-
       tive and measuring 8. 5 divisions on the
       eyepiece scale  is 8. 5 (15. 8) or 135u in
       diameter.

       Each objective  on your microscope must
       be calibrated in this manner.

       A convenient way to record the necessary
       data and to calculate u/emd is by means
       of a table.
    6-22

-------
                                                               Optics and the Microscope
               Table 7
Objective
No. smd =    ^i =       \i -
 no. emd   no.  emd   1 emd
32-mm     18 = 44   1800 = 44  40. 9^

16-mm      6 = 38    600 = 38  15. 8ji

 4-mm      1 = 30    100 = 30   3. 33|ji
  Determination of particle size
  distribution

  The measurement of particle size can
  vary in complexity depending on parti-
  cle shape.  The size of a sphere may be
  denoted by its diameter.  The size of a
  cube may be expressed by the length of
  an edge or diagonal.  Beyond these two
  configurations,  the particle "size" must
  include information about the shape of
  the particle in question, and the
  expression of this shape takes a more
  complicated form.

  Martin's diameter  is the simplest means
  of measuring and expressing  the dia-
  meters of irregular particles and is
  sufficiently accurate when averaged for
  a large number of particles.  In this
  method,  the horizontal or east-west
  dimension of each particle which divides
  the projected area  into halves is taken as
  Martin's diameter  (Figure 18).
            I-P
                      '&
              Figure 18

        MARTIN'S DIAMETER
   The more particles counted,  the more
   accurate will be the average particle
   size.  Platelike and needlelike particles
   should have a correction factor applied
   to account for the third dimension since
   all such particles are restricted in their
   orientation on the microscope slide.
   When particle size is reported, the
   general shape of the particles as well as
   the method used to determine the
   "diameter" should be noted.

   Particle size distribution is determined
   routinely by  moving a preparation of
   particles past an eyepiece micrometer
   scale in such a way that their Martin's
   diameter can be tallied.  All particles
   whose centers fall within two  fixed
   divisions on  the scale are tallied.  Move-
   ment of the preparation is usually
   accomplished by  means of a mechanical
   stage but may be carried out by rotation
   of an off-center rotating stage.  A sample
   tabulation appears in Table 8.  The eye-
   piece and objective are chosen so that
   at least six,  but not more than twelve,
   size classes  are required and sufficient
   particles are counted to give a smooth
   curve.  The actual number  tallied (200 -
   2, 000) depends on particle shape
   regularity and the range of  sizes.   The
   size tallied for each particle is that
   number of eyepiece micrometer divisions
   most closely approximating Martin's
   diameter for that particle.

4  Calculation of size averages

   The size data may be treated in a  variety
   of ways; one  simple,  straightforward
   treatment is  shown in Table 9. For a
   more complete  discussion of the treat-
   ment of particle size data see Chamot
   and Mason's Handbook of Chemical
   Microscopy^',  page 26.

   The averages^ with respect to number,
   dj; surface, d$; and weight or  volume,
   d4,  are calculated as follows for the
   data in Table  9.
                                                                                     6-23

-------
Optics and the Microscope
                TmbU 8.  PARTICLE SIZE TALLY FOR A SAMPLE OF STARCH GRAINS
          Six* CUM
            (emd»)
              Number of particles
                                                  Toul
rt-*j
             rtHJ  1
             n-u  ri-w  rr+j  rt-u  rt-*j
                    n-*4  n~u  r*-»j  r*-*a
                    rt-u  r*-u  111
                                                                         16
                                                                         M



                                                                        no
rt-u  rt-*A rtna  i-t-*a  rt-u  rt-tj
rtsu
rt-*u  rtnw  rtna  it-w  rt-u  ri-*-i  r-na
rt-*u  rt-w  rtn-i  rt-w  rt-*-»  I-KU
       rt-w
                                                                        107
                      1 1
                      rt-w
                                                       r-»-*a
                            «-*a  rt-w r»-*4  I-I-M  ITHJ
                      rt-*j
                      1 1
                                                   4$


                                                   SI

                                                    s

                                                  470
             *emd • excniece micremeter.dixi«iaa*
            dj = Znd/Sn = 1758/470

              = 3.74 emdX 2.82*= 10. 5>i

            d3 = End3/End2 = 37440/7662

              = 4.89 emdX 2.82 = 13.8,1

            d4 = Znd4/Znd3 =  199194/37440

              = 5.32 emdX  2.82 = 15. Op.

            *2. 82  microns per emd
            (determined by calibration of the
            eyepiece-objective combination
            used for the determination).

      Cumulative percents by number,
      surface and  weight (or volume) may be
      plotted from the data in Table 9.  The
      calculated percentages, e. g^
                                                   d = 15
                                                     nd4 X 100
                                                   d = 1
                                for the cumulative weight or volume
                                curve, are plotted against d.   Finally,
                                the specific surface, Sm, in square
                                meters per  gram, m. may be calculated
                                if the density, D, is known; the surface
                                average d%, is used.
                                If D
                                      1.1.  Sm= 6/d3D= 6/13.8(1.1)
                                                 0. 395m2/g.
    6-24

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                                                                    Optics and the Microscope
                 Table 9.  CALCULATIONS FOR PARTICLE SIZE AVERAGE
d
(Aver. diam. n
in emd)
1
2
3
4
5
6
7
8
16
98
110
107
71
45
21
2
nd
16
196
330
428
355
270
147
16
nd*
16
392
990
1712
1775
1620
1029
128
-»
16
784
2970
6848
8875
9720
7203
1024
nd4
16
1568
8910
27392
44375
58320
50421
8192
                                     470   1758  7662   37440    199194
B  Counting Analysis

   Mixtures of particulates can often be
   quantitatively analyzed by counting the
   total number of particulates from each
   component  in a representative sample.
   The calculations are, however, compli-
   cated by three factors:  average particle
   size, particle  shape and the density
   of the components.  If all of the compon-
   ents were equivalent in particle size,
   shape and density then the weight per-
   centage would  be identical to the number
   percentage. Usually, however, it is
   necessary to determine  correction factors
   to account for  the differences.

   When properly applied,  this method can
   be accurate to within _+ 1 percent and,
   in special cases,  even better.  It is often
   applied to the analysis of fiber mixtures
   and  is then usually called a dot-count
   because the tally of fibers is kept as the
   preparation is moved past a point or dot
   in the eyepiece.

   A variety of methods can be used  to
   simplify recognition of the different
   components.  These include chemical
   stains or dyes and enhancement of optical
   differences such as  refractive indices,
   dispersion or color.  Often, however, one
   relies on the differences in morphology.
e. g.  counting the percent of rayon fibers
in a sample of "silk".
Example 1: A dot-count of a mixture of
           fiberglass and nylon shows:
                  nylon
              fiberglass
             262
             168
Therefore:
                nylon = 262/(262 + 168)X 100
                      = 60. 9% by number.
However, although both fibers are smooth
cylinders,  they do have different densities
and usually different diameters.  To
correct for diameter one must measure
the average diameter of each type of fiber
and calculate the volume of a unit length
of each.
             aver.  diam.    volume of
                  H        l-(i slice,  \i?
   nylon
 fiberglass
18.5
13.2
268

117
The percent by volume is, then:
                     262X 268
        nylon =
               (262 X 268)+(168X 117)

               78. 1% by volume.
                     X 100
Still we must take into account the density of
each in order to calculate the weight percent.
                                                                                      6-25

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Optics and the Microscope
   If the densities are 1. 6 for nylon and 2. 2
   for glass then the percent by weight is:
      „   .     _ 262X268X1.6     _ _
      % nylon - (262 X 268 X 1.6)+(1G8X 117X2.2) * luu

              = 72% by weight.

      Example 2:  A count of quartz and
                  gypsum shows:

                    quartz       283
                   gypsum       467

   To calculate the percent by weight we must
   take into account the average particle size.
   the shape and  the density of each.

   The average particle size with respect to
   weight, d4,  must be measured for each
   and the shape  factor must be determined.
   Since gypsum  is more  platelike than quartz
   each particle of gypsum is thinner.  The
   shape factor can be approximated or can be
   roughly calculated by measuring  the actual
   thickness of a number  of particles.  We
   might find, for example, that gypsum parti-
   cles average 80% of the volume of the aver-
   age quartz particle;  this  is our shape factor.
   The final equation for the weight  percent is:

                 _ 283 X  nd4/6XDq _
      % quartz =        irg4/ 6 x Dq + 467 x w dJ/6 X 0. 80 X Dg  X 10°
   where Dq and Dg are the densities of quartz
   and gypsum_ respectively; 0. 80 is the shape
   factor and d4 and d| are the average parti-
   cle sizes with respect to weight for quartz
   and gypsum respectively.
  ACKNOWLEDGMENT:  This outline was          2   Loveland. R. P., J. Roy. Micros. Soc.
  prepared by the U. S. Public Health Service.           79. 59. (1960).
  Department of Health. Education and Welfare.
  for use in its Training Program.                3  Chamot. Emile Monnln. and Maaon.   '
                                                    Clyde Walter. Handbook of Chemical
  REFERENCES                                      Microscopy. Vol. 1. third ed.
  1   n,    r*  ,T7   ^   . , „                          John Wiley and Sons. New York (1959).
  1   Bunn. C. W.  Crystal Growth from
        Solution.  Discussions  of the Faraday      DESCRIPTORS: Microscope and Optical
        Society No. 5.132.  Gunery and Jackson,    properties
        London. (1949).
 6-26

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                                  ARTIFICIAL SUBSTRATES
 I   INTRODUCTION: THE NATURE OF
    ARTIFICIAL SUBSTRATES

 A  Artificial substrates are anything
    deliberately placed  in the water for the
    purpose of providing a place for benthic
    or attached (sessile, sedentary,  etc.)
    organisms to grow on or in.  This is  in
    contrast to "bait" which is  used as an
    attractant.
 B  Their origins for commercial use,  or human
    food production are rooted in antiquity.
    Some  examples are:

    1 Ropes,  poles, brush,  concrete
      structures,  and other objects thrust
      into the bottom, or suspended in
      estuarine waters to catch and grow
      oysters and mussels  (cultural techniques),
      known virtually around the world.

    2 Straw or reed tepees planted in shallow
      alkaline lakes (in Mexico for example)
      to catch the eggs of Corixids (Insecta:
      Order Hemiptera, back-swimmers).
      Eggs  are harvested by drying and
      brushing them off onto white sheets.
      Used  for human food.

 C  The fouling of  ships bottoms, piling, etc.
    by barnacles and other marine life  is an
    "artificial substrate in reverse".

 D  The use of aggregate to support  a zoogloeal
    mass  of micro-biota in a trickling filter,
    thus simulating a riffle area in a surface
    stream,  is a modern concept to  harness
    and make use of "consumer" and "reducer"
    elements of a community in order to
    dissipate the energy (oxidize,  exhaust  the
    food value) contained in sewage.

II   ECOLOGICAL BASIS

 A  Artificial substrates are based on the
    "laws of organismal distribution. "
    1 Any given kind of organisms tends to be
      present (inhabit) in all available  suitable
      habitats.

  *A community which has achieved a point of no further change, under a given set of
    environmental conditions. Time scale may vary with circumstances.

  NOTE:  Mention of commercial products and manufacturers does not imply endorsement
          by the Environmental Protection Agency.
   2 Any given habitat tends to be inhabited
     by all suitably adapted kinds of
     organisms.

B  A "substrate" being an object (or group
   of objects) constitutes a habitat suitable
   for sessile or attached organisms,  and
   also those that naturally burrow in,  crawl
   over,  or otherwise live associated with
   objects.  Natural objects here could mean
   the bottom, stones, sticks (floating or
   sunk),  etc.

C  Organisms that would not be attracted to
   substrates would be plankton and nekton
   (fish and larger  swimming invertebrates).

D  Ecological Succession

   Colonization is rapid  in a biologically
   productive water,  and normally reaches
   a stable climax* community in about a
   month.  A typical outline of successive
   forms to appear in a freshwater situation,
   for example,  might be as follows.

   1 Periphyton (slime forming) stage
     (see also below)
     a Bacteria - within an hour

     b Diatoms  - within the first day
     c Other micro-algae - within the first day

     d Protozoa -  within the first day

   2 Macroinvertebrate dominated stage
     (see also below)
     a Primary attached or sedentary
       colonizers  - second to third day
       1)  Net caddisflies
        2) Bryozoa
        3) Cordylophora caspia

        4) Hydra
  BI.MET.fm.7d. 2.79
                                                                                       7-1

-------
 Artificial Substrates
       b Primary foragers

         1) Mayflies

         1) Stoneflies

         3) Midges

       c Secondary attached or sedentary
         colonizers:
                                    o
         1) Sponges

         2) Filam entous alga e

       d Adventitious forms

         1) Crustaceans

         2) Flatworms            °

         3) Leeches

         4) Snails

         5) Other

    3  Artificial substrates in a marine
       environment proceed through similar
       stages,  except that the macroinvertebrate
      0 stage may be more subject to variation
       in the attachment of broods of barnacle,
       oyster,  and other larvae resulting from
    o  greater numbers of types present, tidal
       current variation,  meteorological
       conditions, etc.
Ill  ARTIFICIA L SUBSTRATES A S SCIENTIFIC
    COLLECTING EfeVICES

 A A review of the history of artificial
    substrates for collecting microorganisms
    (aufwuchs) (Cooke, 1956) indicates that
    glass microscope slides were first used
    for this purpose about 1915. Wood or
    metal panels appear, however, to have been
    deliberately exposed for the scientific
    collection of larger organisms at least
    since approximately the turn of the century,
    and probably long before that (Visscher, 1928).
B  Biological Applications

   The principles of the artificial substrate
   remain the same,  regardless  of the
   community sampled.  Two general types
   of communities and associated samplers
   have been employed:

   1 Periphyton (or aufwuchs) samplers

     Periphyton is the community of slime
     forming microorganisms which is the
     first to attach to objects newly exposed
     under water.  This community is
     generally considered to provide an
     anchor layer to which other higher
     forms of life can more  readily attach.
     It tends to persist until overgrown or
     displaced by larger organisms, and
     then in turn can be found spreading over
     the surfaces of these same  larger
     plants and animals.
                                         c
   2 Periphyton has been widely studied as
     it appears on 1 X3 glass microscope
     slides which are equally convenient  to
     expose in the field and to study in the
     laboratory.

   3 Particular studies have included:

     a  The original bacterial and fungal
        slime

     b  Diatom identification and counts

     c  Identification and counts  of other
        microscopic algae                  °

     d  Protozoans

     e  Primary productivity
              O
                                       0
   4 The macroinvertebrate community is
     sampled by a great variety  of devices
     such as those cited below.  The
     organisms are usually removed from
     the substrate for study.  Applications
     have included the following:

     a  General study of the  macroinverte-
        brate community
   7-2

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                                                                      Artificial Substrates
      b  Estimates of productivity
      c  Studies of the life cycle of particular
         species
      d  Studies of the influence of the sub-
         strate on the attachment of sessile
         forms
         1)  The influence of toxic paints for
            the prevention of fouling organisms
         2)  Wood panels to study the pene-
            tration of boring molluscs and
            crustaceans

C Effect of type of device on what is collected

   1  Wood boring organisms like teredo
      worms (Mollusca, Pelecypoda) or
      gribbles (Arthropoda, Isopoda)would
      obviously be attracted primarily to
      wood (although some are known to bore
      in other materials).

   2  Delicate forms and crawling forms
      would be most likely to be collected on
      devices having a shape to protect
      against  strong currents.

   3  Those with strong attachments could
      endure swift currents; often, surpris-
      ingly, even during periods of original
      attachment (ex.  byssus attached clams
      which are also benthic forms).

   4  Bottom burrowers would be most likely
      collected in artificially contained
      portions of bottom material.

D Effect of Location
   1  The depth at which a sampler is sus-
      pended may influence the organisms
      attracted.
   2  Location in or out of a current,  direct
      sunlight, etc.,  will influence the take.
E  Some Types of Devices
   1  Cement  plates, panels, and blocks
   2  Ceramic tiles
   3  Wood blocks
   4  Metal plates
5.  Glass slides -1X3 inch micro slides
   are used by many workers.  Numerous
   devices are employed to hold them.
   They are generally either floated
   (Weber and Raschke 1966) or sus-
   pended in racks, anchored to
   submerged bricks or other objects.

6  Plastic petri dishes

   Burbanck and Spoon utilized an
   ordinary 50 X 12 mm plastic petri
   dish for collecting sessile protozoa.
   Sickle modified this by using a
   styrofoam cup (6 oz.  size) with the
   bottom third being cut off.  The
   lower unit of the plastic dish is
   easily wedged into place in the cup
   and the device is simply held by a
   nylon line on a rope held in place by
   an appropriate anchor and float.

   The  cup which tends to float is so
   held that the petri dish bottom is in
   a horizontal position and bottom side
   up.

7  Multiple plate (Hester and Dendy,  1962)

   a  Common current procedure
      utilizes 3-inch squares of 1/4
      inch thick Masonite separated
      by 1-inch square spacers.

   These may be:

   b  Threaded on an eye bolt or long
      rod.

   c  Suspended by a loop of nylon  cord.

8  Baskets or trays of bottom-type
   material

   a  Trays of bottom material sunk in
      the surface layer of the bottom.

   b  Baskets of stones  suspended  in
      the water (Anderson and Mason,
      1966).

9  Boxes,  cages,  bundles,  etc., of
   brush,  reeds, or artificial material.
                                                                                       7-3

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Artificial Substrates
   10 Polyethylene tapes

   11 Plastic webbing

      Minnesota Mining and Manufacturing
      Company  conservation web no. 200.

   12 Styrofoam

   13 Glass cover slips

      Small slips are floated on the surface
      of the water.  Highly useful for protozoa
      and rotifers.  Remove and place on a
      micro  slide.   Examine as a wet mount.

F Retrieval is  an acute problem with all of
   these samplers.

   1  Physical factors

      a  Relocation

      b  Floods and drift

      c  High water

   2  Well marked samplers or floats are
      naturally vulnerable to the public,
      resulting in disturbed, damaged,  or
      destroyed sample gear.

      a  This has been overcome by an
         ingenious submerged float and
         recovery line device.  The weak
         link in  a submerged recovery line
         is a modified flash bulb.  An
         electronic device actuated by an
         underwater gun breaks the  bulb
         allowing the float and attached
         line to  surface.  (Ziebell,
         McConnell, and Baldwin)

      b  This unit has been further modified
        by Fox (University of Georgia
         Cooperative Fishery Unit) who
         used an inexpensive detonator,
         "Seal Salute".  The latter is an
         inexpensive fused charge designed
         for underwater explosion.
IV  ARTIFICIAL SUBSTRATES OR SAMPLERS,
    AND WATER QUA LITY

 A Artificial substrates provide a habitat
    ("place to live").  It follows from the
    laws of distribution (II A  I and 2 above),
    that the community which inhabits a
    device will be governed by the physical
    nature or structure interacting with the
    characteristics of the surrounding water
    (velocity, temperature, chemical
    characteristics, etc.).   Since the nature
    of the sampler is controlled,  it is evident
    that the characteristics of the water
    constitute the variable  factor.

 B Water Quality Surveillance

    1 Similar substrates suspended side by
      side in the same water tend to accumulate
      (essentially) the same communities and
      quantities of organisms.

    2 Similar substrates suspended in different
      waters accumulate different communities
      and quantities.

    3 Ergo: different communities and
      quantities  collected from similar
      substrates at different places and times,
      probably indicate different water qualities.

      a These may be natural (seasonal,
         diurnal,  etc.)

      b Or they may be a  result of human
         influences (pollution)

       c A series of samplers the length of a
         stream,  lake,  or  estuary can suggest
         "steady state" differences in water
         quality.

       d A  series of samplers exposed over a
         period of time at a given  site can
         suggest changes of water quality in
         time.

    4  The artificial substrate thus essentially
       constitutes an in-situ bioassay of the
       water.
7-4

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                                                                      Artificial Substrates
   Interpretation and Significance of
   Collections

   1  The unit of comparison is most
      appropriately taken as "the sampler".
      The artificial substrate by definition is
      not the natural local bottom material,
      and unless it consists of a portion of
      that bottom which has been actually
      removed and replaced in an artificial
      container (III-D-7)the composition and
      magnitude of the community it contains
      may or may not bear a definitive
      relationship to the actual natural
      problem.  The take of the artificial
      substrate thus may have relatively
      little relationship to the take  of a
      Peter sen or an Ekman grab (dredge).

   2   Comparisons between different types
      of samplers are  likewise hazardous.
      Each is what it is, and if they are
      different they are not  identical; thus
      the biota each collects cannot be
      expected to be identical (CF:  II A).

   3   Artificial substrates should generally
      be  compared on a "sampler vs sampler"
      basis,  or for periphyton,  "unit area
      vs unit area".
REFERENCES

1  Anderson,  J. B.  and Mason, William T.  Jr.
      A Comparison of Benthic Macro -
      invertebrates collected by Dredge and
      Basket Sampler.   Jour.  Water Poll.
      Cont.  Fed. 40(2):252-259.

2  Arthur, John W. and Horning, W. B. ,  II.
      The Use of Artificial Substrates in
      Pollution Surveys.  Amer.  Midi.  Nat.
      82(l):83-89.

3  Besch, W., Hoffman, W., and Ellenberger,
      W.  Das Macrobenthos auf
      Polyatchylensubstraten in Fliessgs-
      wasseren.  Annals de Limnologic.
      3(2):331-367.    1967.
4  Burbanck, W.D. and Spoon, D.M.   The
      Use of Sessile Ciliates Collected in
      Plastic Petri Dishes for Rapid
      Assessment  of Water Pollution.
      J. Protozool.   14(4):739-744.  1967.

5  Cooke, William B.   Colonization of
      Artificial Bare Areas by Microorganisms.
      Bot. Rev.  22(9):613-638.  Nov.  1956.

6  Fox,  Alfred C.   Personal Communication.
      1969.
 7  Hester, F.E. and Dendy, J.S.
      A Multiple-Plate Sampler for Aquatic
      Macroinvertebrates.  Trans.Am.
      Fish.  Soc. 91(4):420-421.  April 1962.

 8  Hilsenhoff, William L.   An Artificial
      Substrate  Device for Sampling Benthic
      Stream Invertebrates.   Limnology and
      Oceanography.   14(3):465-471.  1969.

 9  Mason, W.T.,  Jr., Anderson,  J.B.,  and
      Morrison, G.E.  A Limestone-Filled,
      Artificial  Substrate Sampler Float Unit
      for Collecting Macroinvertebrates in
      Large Streams.  Prog. Fish-Cult.
      29:74.   1967.

10  Ray,  D. L.   Marine Boring and Fouling
      Organisms.   University of Washington
      Press, Seattle.   pp 1-536.  1959.

11  Sickel, James B.   A Survey of the
      Mussel Populations (Unionidae) and
      Protozoa of  the Altamaha  River with
      Reference to their Use in  Monitoring
      Environmental  Changes.  MS Thesis.
      Emory University.   133 pp.  1969.

12  Sladeckova, A.   Limnological Investigation
      Methods for  the Periphyton ("Aufwuchs")
      Community.   Bot.  Rev. 28(2):286-350.
      1962.

13  Spoon, D.M.  and Burbanck,  W.D.   A
      New Method  for Collecting Sessile
      Ciliates in Plastic Petri Dishes with
      Tight Fitting Lids.   J. Protozool.
      14(4):735-739.   1967.
                                                                                      7-5

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Artificial Substrates
14  Visscher, J. Paul. Nature and Extent         ___
       of Fouling of Ships Bottom.  Dept.           _,.    .,.               , ,   TT  .„  _  ,
       _      „    „     -rn  u  T-L                 This outline was prepared by H. W.  Jackson
       Comm. Bur. Com.  Fish.  Doc.              _,. r _.  ,   . .   K. J,  ,, _.    .  '
       wo  10^1    nn 1Q^! 252   1928                Chief Biologist and R. M. Sinclair,  Aquatic
       No. 1031.  pp 193-252.  1928.               Biologist. National Training Center, Water
-ic  TTT T-    /-. T-,    j T,    ui   «  T              Programs Operations, EPA,  Cincinnati,
15  Weber,  C. E. and Rauschke, R. L.             ohi   4"i268
       Use of a Floating Periphyton Sampler
       for Water Pollution Surveillance             DESCRIPTORS: Artificial Substrates.
       Water Poll. Sur. Sept  Applications                       Bentho  Bottom ga
                                                  and invertebrates.
                   T               -
       FWPCA-USDI, Cincinnati,  Ohio.
       September 1966.

16  Wene,  George and Wickliff, E. L.
       Modification of a Stream Bottom and
       its Effect on the Insect Fauna.
       Canadian Entomologist.  Bull. 149,
       5 pp.  1940.

17  Ziebell, Charles D. ,  McConnell, W.  J. ,
       and Baldwin,  Howard A.  A Sonic
       Recovery Device for Submerged
       Equipment.  Limnol. and Ocean.
       13(1):198-200.  1968.
   7-6

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                  BENTHIC INTEGRITY AND MACRO INVERTEBRATE DRIFT
 I   Significant number of benthic macro
 invertebrates under certain conditions
 join stream drift.

 A  This phenomenon was only discovered
    in mid century.  The organisms as well
    as the phenomenon is termed
    collectively,  Drift.

 B  Macroinvertebrates which drift
    include are the insect orders,
    Ephemeroptera, Trichoptera, Plecop-
    tera and the crustacean order
    Amphipoda.

 C  Other invertebrate groups exhibit drift
    patterns.

II   FOUR BASIC TYPES OF DRIFT ARE
    RECOGNIZED

 A  Catastrophic  Drift

    Floods wash numerous benthic organisms
    downstream.  Application of pesticides
    may also cause such drift.

 B  Constant Drift (Incidental or Adventitious)

    Organisms are constatly being dislodged
    from the substrate during normal
    activities and carried downstream.

 C   Periodic (Diel) Drift

    In contrast to the other categories,  this
    is a specific behavior pattern and related
   to circadian activity rhythms.  Periodic
   or diel drift occurs in peaks for successive
    24-hour periods.

D  Seasonal Drift (Related to Life History
   Development)

   Seasonal drift occurs, for example, in
   some maturing stoneflies which drift
   downstream for emergence.  This is
   another reason for a serious consider-
   ation of drift in bottom fauna sampling
   since  such presence of stoneflies could
   easily be misinterpreted.
    1  Night-active.  Light intensity is the
      phase-setting mechanism.

    2  Day-active.  Water temperature
      appears to be the phase-setter.

Ill  DIEL DRIFT

A  Diel activity rhythms  generally include
    two peaks  during the 24-hour period;
    one major and the other minor.

    1  The bigeminus type in which the
      major peak occurs first (after sunset).
  §
  O
               FIGURE  1

   2  The alternans pattern with the major
      peak occurring last.
   $-,
   X!
       1200     1800    2400

                 Time
0600
          Sunset        Sunrise
                FIGURE 2

B  Drift Rate and Density (Waters,  1969)

   1  Drift rate defined is ".. .the quantity
      of organisms passing a width transect
      or portion thereof,  per unit time;
BI. ECO. 22a. 2.79
                                                                                  J-l

-------
 Benthic Integrity and Macro Invertebrate Drift
      it is a measure of displacement or
      the movement of organisms from one
      place to another."

    2  Drift density"... is the quantity of
      organisms per unit volume of water,
      in much the same way as plankton
      density can be defined. "

IV  DETERMINING BENTHIC INTEGRITY
    THRU DRIFT SAMPLING

 A  The drift from productive upstream
    reaches may support a fish population
    existing in relatively barren stream
    sections.

 B  Drift will colonize artificial substrates,
    such as  suspended rock baskets, when
    placed in such habitats.

 C  A bottom sampler such as the Surber,
    could also be  sampling drift when only
    resident benthic organisms are intended
    to be collected.   This would depend on
    the hour of collection and length of time
    the Surber sampler  is in  the water.

 D  Application of drift studies have been
    widely used in pesticide related studies
    and  routine monitoring.  Dimond
    concluded that:

    1  The status of drift is a much better
      indicator of the steady state  and of
      total productivity than is the status
      of the bottom fauna.

    2  Bottom sampling, however,  is
      superior when analyzing survival
      and recovery of the quality of popula-
      tion.

    3  A combination of both  in such a
      sampling program would be most
      likely to yield the most useful data.

 E  Drift sampling techniques have been
    useful for recovery  of large numbers of
    sand-dwelling mayflies, which were
    once rarely collected.
V  MAJOR TAXA INVOLVED IN DRIFT

A  The crustacean order Amphipoda

   1  Gammarus species

   2  Hyalella azteca

B  The Insect Orders

   1  Ephemeroptera

      Baetis species (apparently universal)

   2  Plecoptera

   3  Trichoptera

   4  Diptera
      Simuliidae

   5  Elmidae

C  The main groups exhibiting very high
   drift rates include:  Baetis, some
   Gammarus species,  and some Simuliidae.

REFERENCES

1  Anderson, N. H.  Biology and Down-
      stream Drift of some Oregon
      Trichoptera. Can.  Entom.   99:507-
      521.  1967.

2  Dimond, John B.  Pesticides and
      Stream Insects.   Bull. 23, Maine
      Forest Service,  21  pp.  1967.

3  Dimond, John B.  Evidence that drift of
      Stream Benthos is Density Related.
      Ecology  48:855-857.  1967.

4   Pearson, William D., and Kramer,
      Robert H.  A Drift  Sampler driven
      by a Waterwheel.  Limnology and
      Oceanography 14(3):462-465.

5  Reed,  Roger J.  Some Effects of DDT on
      the Ecology of Salmon Streams in
      Southeastern Alaska.  Spec.  Sci.
      Report-Fisheries 542: 1-15.  U.S.
      Bureau Comm. Fisheries.  1966.

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                                            Benthic Integrity and Macro Invertebrate Drift
6  Water, Thomas F.  Interpretation of
      Invertebrate Drift in Streams.
      Ecology 46 (3):327-334.   1965.

7  Waters, Thomas F.  Diurnal Periodicity
      in the Drift of a Day-active Stream
      Invertebrate.  Ecology 49:152.   1968.
8  Waters,  Thomas F.  Invertebrate
      Drift-Ecology and Significance to
      Stream Fishes.  (T. G.  Northco e,
      Ed. )  Symposium Salmon and Trout
      in Streams.  University of British
      Columbia,  Vancouver,  pp. 121-134.
      1969.
                                               This outline was prpared by R. M.  Sinclair,
                                               National Training Center, MOTD,  OWPO,
                                               USEPA,  Cincinnati, Ohio 45268.

                                               DESCRIPTORS:  Aquatic  Life, Aquatic Drift,
                                               and Invertebrates
                                                                                     8-3

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                  EFFECTS OF THERMAL POLLUTION ON THE BENTHOS
 I  INTRODUCTION

 A Fish may be obviously important but they
   are  not the only important organisms or
   the only ones being studied at present.
   The food organisms are just as important
   in the long run.  Lose the organisms which
   convert the energy of the primary pro-
   ducers to a form usable by the fish and
   we lose the fish themselves.

 B In a river, most of the microscopic popu-
   lation are benthic organisms, since the
   plankton have difficulty maintaining position
   in the stream flow.  The benthos is a
   stationary community which should reflect
   the action of the temperature in the area
   of influence.  Of course, bottom debris
   may serve to protect benthic organisms
   to some extent from full exposure to the
   heated water.
II   SUBLETHAL EFFECTS ON AQUATIC
    INSECTS

 A  In most western streams the stoneflies,
    caddisflies and mayflies are the primary
    fish food organisms.  At the same time,
    these organisms have definite environ-
    mental requirements and cold, well-
    oxygenated water is a prime factor.

    1  Preliminary work at the Duluth
      Laboratory indicates that temperatures
      would probably become lethal to any
      cold water fish like trout before the
      insects would die.

      a  According to Usinger (1956), the
         heat tolerance of macroscopic
         invertebrates is well above  that of
         fish.

      b  For example, soldier fly
         (stratiomyidae) larvae were found
         living in thermal waters at tempera-
         tures up to 120°F.
                    96 hour TL  values
Table 1 shows
determined for some insect species by
Nebeker and Lemke of the Duluth
Laboratory.

a  These temperatures are well above
   the  12°C suggested  as the maximum
   limit for spawning and egg develop-
   ment in salmon and trout.
                                                 b  This doesn't tell the whole story
                                                    because the insects may be harmed
                                                    in other ways.

                                           B Gaufin, formerly of Utah,  and also Nebeker
                                              of the Duluth Laboratory, have demonstrated
                                              that temperature increases can cause pre-
                                              mature emergence.

                                              1  A 10°C rise from ambient winter tem-
                                                 perature  caused one species  of stonefly
                                                 to emerge in January instead  of May.
                                                 "One must imagine how perplexed these
                                                 organisms must be as they expect nice
                                                 warm spring weather only to freeze to
                                                 death as they emerge. "

                                              2  Nebeker found that a temperature in-
                                                 crease for another species caused the
                                                 males  to emerge as  much as two months
                                                 ahead of the females!

                                           C Either situation would prevent reproduction
                                              and would be fatal to the species although
                                              not fatal to individuals prior to emergence.

                                           D Even without lethal effects we may find
                                              changes in community due to variation in
                                              optimum temperatures  between species.
                                              This has not been studied enough in the
                                              field to really determine the overall effect
                                              on a natural system but it is something
                                              which we  will have to know more about in
                                              the future.
Ill  SUBLETHAL EFFECTS ON SHELLFISH

 A Most shellfish, such as clams,  oysters,
    crabs and lobsters, which are directly
    beneficial to man as a food source, are
    marine,  stenothermal organisms.  Some
    species are stenothermal for one develop-
    mental stage and eurythermal for another.
    Generally, however, breeding and spawning
    requirements are stenothermal.

    1  The time of  mollusc, e. g. clams,
       oyster,  etc. , spawning is temperature
       dependent.

    2  Most molluscs with specific temperature
       breeding relationships spawn in the spring
       and summer, and many do not spawn until
       a certain temperature is reached.

 B The American oyster Crassostrea virginica
    spawns at temperatures between 15 and 34°C
 BI.ECO. he. 5. 2.79
                                                                                         9-1

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Effects of Thermal Pollution on the Benthos
                                       TABLE 1

               Temperatures at which 50% of the test species died after 96 hours
               exposure (TLm96) when acclimated at 10°C for one week.
Species Tested
Taeniopteryx maura (winter stonefly)
Ephemerella subvaria (mayfly)
Isogenus frontalis (stonefly)
Allocapnia granulata (winter stonefly)
Stenonema tripunctatum (mayfly)
Brachycentrus americanus (caddisfly)
Pteronarcys dorsata (stonefly)
Acroneuria lycorias (stonefly)
Paragnetina media (stonefly)
Atherix variegata (true fly)
Boyeria vinosa (dragonfly)
Ophiogomphus rupinsulensis (dragonfly)

TLm
21
21.
22.
23
25.
29
29.
30
30.
32
32.
33
96 (°Celcius)
o
5°
5°
o
5°
0
5°
o
5°
o
5°
o
               12°c (55°F) Maximum temperature recommended in Water Quality
               Criteria for spawning and egg development of salmon and trout.

               From:  Nebeker, Alan V. and Armond E. Lemke, 1968.  Preliminary
               studies on the tolerance of aquatic insects in heated waters.  Journal
               of Kansas Entomological Society 41: 413-418. July, 1968.
 9-2

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                                                  Effects of Thermal Pollution on the Benthos
   (59 and 93. 2°F) depending on its condition,
   and spawning is usually triggered by a
   rise in temperature.

 C Many species tolerate temperatures in
   excess of those at which breeding occurs.

   1  For example,  the shore crab Carcinus
      maenas thrives, but does not breed,  at
      temperatures of 14 to 28°C (57. 2 to
      82.4°F).

   2  In this case, temperature limits the
      population, but migration of organisms
      can occur from outside the heated area.

 D Physiology, metabolism and development
   are all affected by temperature.

   1  The American oyster C_.  virginica
      ceases feeding at temperatures below
      7°C (44. 6°F).

      a Above 32°c (89. 6°F) ciliary activity,
        which is responsible for water move-
        ment, is  decreased.

      b At 42°C (107. 6°F) almost all body
        functions  cease,  or are reduced to a
        minimum.

   2  The European oyster Ostrea lurida
      tends to close its shell as temperatures
      drop.

      a At 4 to 6°C (39. 2 to 42. 8°F) the
        oyster's shell remains closed most
        of the time.

      b At 6 to 8°C (42.8 to 46.4°F) the
        shell opens for about 6 hours per  day.

      c At 15°C (59°F) the shell stays  open
        for 23 hours a day.

E  Very little is known about prolonged  effects
   of temperatures above 32 to 34°C (90 to
   94 F) on oysters; however,  long exposure
   to such temperatures may impede the
   oyster's normal rate of water circulation.
   When either low or high temperatures cause
   shells to close or ciliary action to cease,
   oysters cannot feed and subsequently lose
   weight.  Thus,  temperature changes can
   produce an effect similar to chronic
   toxicity.

F  The distribution of benthic organisms is
   temperature dependent.

   1  The American oyster (T.  virginica
     is present in Gulf Coait waters that
       that may vary between 4 and 34  C
       (39. 2 and 93. 2°F),  but the European
       oyster O. edulis is restricted to water
       temperatures of 0 to 20°C  (32 to 68°F).

       The opossum shrimp Neomysis
       americana is not often found at tempera-
       tures above 31°C (87. 8°F) in the
       Chesapeake estuary.
IV  LETHAL EFFECTS

 A Studies of particular species of benthic
    macroinvertebrates have indicated that
    lethal temperatures vary considerably
    with the type of organism.

    1  Laboratory investigations on the fresh-
       water snail Lymnaea  stagnalis showed
       a lethal temperature of 30. 5UC (89. 6°F),
       while the species Viviparous malleatus
       did  not succumb until the temperature
       reached 37. 5°c  (99. 5°F).

    2  Agerborg (1932) observed a freshwater
       snail, Physa gyrina, living and repro-
       ducing nicely in  zones up to 91. 4°F in
       heated wastewater.

    3  Hutchinson (1947) reported that
       Viviparous malleatus, a freshwater
       snail, was not killed until the  tempera-
       ture reached 37. 5°C (99°F).

 B Several snails, including Australorbis
    glabratus,  suffered heat damage  at 105. 8°F
    (Von Brand, et. al.  1948).

 C Other examples show that the limpet,
    Ancylus fluviatilus, was not hurt  by a
    temperature of 96. 8°F while 87. 8*% was
    lethal to Acrolexus lacustris (Berg,  1952).

 D When an unidentified species of crayfish
    was acclimated to 45°F,  it had a  lethal
    temperature of 93°F (Trembly 1961).

 E Sprague (1963) reported a 24-hour lethal
    temperature of 94. 3°F for a freshwater
    sowbug, Asellus intermedius, and a scud,
    Gammarus fascTatus.   Another scud,
    Hyalella azteca,  was killed at 91.8°F.

 F Field work on rivers has indicated that
    benthic organisms decrease in number
    when water temperature  exceeds  30°C
    (86°F).

    1  The macroinvertebrate riffle fauna of
       the Delaware River  has decreased due
       to heated water discharges.
                                                                                       9-3

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Effects of Thermal Pollution on the Benthos
B
      a At 35°C (95°F) many caddisfly,
        Hydropsyche, were dead, and those
        which remained alive were extremely
        sluggish.

      b This  study suggests that there  is an
        upper tolerance level near 32.2°C
        (90°F) for a variety of different
        benthic forms with extensive losses
        in numbers and diversity accompany-
        ing a further increase in temperature.
POPULATION SHIFTS CAUSED BY HEAT
ADDITION

Trembley (1960) studied the bottom fauna
of the Delaware River at the Martins Creek
Power Plant.

1  In the zone of maximum temperature rise
   rise just below the outfall,  there was
   obvious reduction of species and
   individuals.

2  In the cool water unaffected by the
   thermal overflow,  there was no reduction
   in macroinvertebrates.

3  During the cooler seasons there was
   repopulation of the areas affected during
   the  hot months by thermal discharge.

4  Even during the summer, there was a
   significantly higher standing crop at the
   downstream site in comparison to the
   normal river control station.

Coutant (1962) followed Trembley's
Martins Creek research with a study of
the macroinvertebrate bottom fauna of
the riffle areas of Big Kaypush and Little
Kaypush Rapids.

1  He confirmed Trembley's conclusions.
   From July through October, there was
   substantial reduction in the number,
   diversity, and biomass of benthic
   organisms in the path of the heated
   water.

2  At a distance of one mile downstream
   from the point of discharge, he found
   a normal population structure.

3  In his traverse studies, he observed
   an increase in both variety and number
   of organisms as he progressed from
   hot to cool water,  demonstrating the
   effect of temperature as the primary
   limiting factor.
    4  The work also showed the restricted
       effect of heated discharges in  changing
       the biological communities. The data
       suggest a tolerance limit near 90°F for
       a normal population structure  with
       extensive loss in numbers and diversity
       of organisms accompanying further rise.

    Wurtz and Dolan (1960) reported a study on
    bottom organisms in the Schuylkill River
    at the Cromby Power Plant.

    1  These authors gave no  temperature data;
       however, the subcommittee of the
       Pennsylvania Electric Association (Mason,
       1962) showed severe temperature altera-
       tion in this reach of river since the plant
       used 85% of the river flow as cooling water.

    2  The river showed a very elevated tem-
       perature and slow recovery.  Wurtz and
       Dolan evaluated the effects of heated dis-
       charges in terms of biological depression,
       biological distortion, and biological
       skewness.

    3  Station 10 at Phoenixville Pumping Station,
       0. 5 miles below the plant,  showed the
       greatest deviation.

    4  At Station 13,  six miles below the power
       plant, the river biology had recovered.
       This case illustrates ultimate recovery
       from an extreme condition.
VI  SUMMARY

 It is clear from the valid biological data pre-
 sented that increased temperature  of the water
 does alter the species and individual  composi-
 tion of the benthic population which, of course,
 being generally sessile, is unable to  avoid
 exposure.
                                                 A CK NOW LEDG ME NT S

                                                 Material for this outline was taken from
                                                 The Industrial Waste Guide, Bruce A.  Tichenor
                                                 and Alden G.  Christiansen,  authors; Thermal
                                                 Pollution: Status of the Art, Frank L.  Parker
                                                 and Peter A.  Krenkel, authors; and Technical
                                                 Seminar Paper,  Biological Effects, Dr.  Ronald
                                                 Garton, author.
                                                 REFERENCES

                                                 1  Agersborg, H.  P.  K.  The Relation of
                                                       Temperature to Continuous Reproduction
                                                       in the Pulmonate Snail.  Nautilus,  45.
                                                       121.   1932.
 9-4

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                                                  Effects of Thermal Pollution on the Benthos
2  Berg, K.  On the O2 Consumption of
     Ancylidae (Gastropoda) from an
     Ecological Point of View.
     Hydrobiologia.  4. 225.  1952.

3  Coutant,  C. C.   The Effect of a Heated
     Water Effluent Upon the Macroinverte-
     brate Riffle Fauna of the Delaware
     River.  Penn. Acad.  Science.  37.  58.
     1962.

4  Hutchinson, L.   Analysis of the Activity of
     the Freshwater Snail, Viviparous
     malleatus (Reeve). Ecology 28.  335.
     1947.

5  Sprague, J. B.   Resistance of Four Fresh-
     water Crustaceans to Lethal High
     Temperatures and Low Oxygen.  Journal
     Fisheries Research Board, Canada. 20.
     387.  1963.

6  Trembley, F. J.  Research Project on
     Effects of Condenser Discharge Water
     on Aquatic Life.   Progress Report.
     1960.  The Institute of Research Lehigh
     University.  1961.
7  Usinger, R. L.  Aquatic Insects of
      California.  University of California
      Press.  1956.

8  VonBrand, T., Nolan, M. O.,  and Man,
      E. R.  Observations on the Respiration
      of Australorbis glabratus and Some
      Other Aquatic Snails.  Biology Bulletin.
      95.  199.  1948

9  Wurtz, C. B.,  and Dolan, T. A Biological
      Method Used in the Evaluation of Effects
      of Thermal Discharge in  the Schuylkill
      River. Proc.  15th Industrial Waste
      Conference. Purdue University. 461.
      1960.
This outline was prepared by John F. Wooley,
Biologist, Manpower and Training Branch,
Pacific Northwest Water Laboratory, Federal
Water Quality Administration.

DESCRIPTORS: Aquatic Life,  Benthos,
Benthic fauna,  Cooling water, Invertebrates,
Power plants, and Thermal pollution.
                                                                                       9-5

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