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Dissertations, Theses, and Masters Projects Theses, Dissertations, & Master Projects

1971

Distribution and structure of benthic communities in a gradient estuary

Donald F. Boesch College of William and Mary - Virginia Institute of Marine Science

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Recommended Citation Boesch, Donald F., "Distribution and structure of benthic communities in a gradient estuary" (1971). Dissertations, Theses, and Masters Projects. Paper 1539616575. https://dx.doi.org/doi:10.25773/v5-ag1e-8h38

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BOESCH, Donald Friedrich, 1945- DISTRIBUTION AND STRUCTURE OF BENTHIC COMMUNITIES IN A GRADIENT ESTUARY.

The College of William and Mary, Ph.D., 1971 Marine Sciences

University Microfilms, A XEROX Company , Ann Arbor, Michigan DISTRIBUTION AND STRUCTURE OF

BENTHIC COMMUNITIES IN A GRADIENT ESTUARY

A Dissertation

Presented to

The Faculty of the School of Marine Science

The College of William and Mary in Virginia

In Partial Fulfillment

Of the Requirements for the Degree of

Doctor of Philosophy

By

Donald F. Boesch

1971 APPROVAL SHEET

This dissertation is submitted in partial fulfillment

of the requirements for the degree of

Doctor of Philosophy

Donald F. Boesch

Approved, June 1971

Marvin L. Wass, Ph.D.

*

Q^-VVY l( - 771i/

Maynard M. Nichols, Ph.D.

(-1 PldiCAjM^ Jdrvh J. Nohcross, M. S.

Webster VanWinkle, Jr., Ph.D. ’’ Department of Biology PLEASE NOTE:

Some Pages have indistinct print. Filmed as received.

UNIVERSITY MICROFILMS TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS ...... v

LIST OF TABLES ...... vii

LIST OF FIGURES ...... viii

ABSTRACT ...... X

INTRODUCTION ...... 2

METHODS ...... 5 Sampling ...... 5 Sediment Analyses ...... 7 Ordination Analyses ...... 8 Structural Analyses ...... 11

DESCRIPTION OF THE E S T U A R Y ...... 16 Geomorphology ...... 16 Salinity Structure ...... 17 Temperature and Dissolved Oxygen ...... 20 S e d i m e n t s ...... 24 E c o l o g y ...... 30 Alteration by M a n ...... 31

RESULTS ...... 32 Distribution of the Fauna ...... 32 Q-matrix Analyses ...... 34 R-matrix Analyses ...... 37 Direct Gradient Analysis ...... 45 Diversity ...... 48 Dominance and Dominants ...... 52 Species-Importance Distributions ...... 57

DISCUSSION ...... 6 5 Fauna1 Distribution ...... 65 The True Estuarine Component ...... 70 Community Continuity ...... 74 The Structure of Estuarine Benthic Communities .... 81 Relationships of Diversity Measures ...... 89 The Estuarine Ecosystem ...... 90

iii Page

APPENDIX ...... 9 5

LITERATURE CITED ...... 110

VITA ...... 120

iv ACKNOWLEDGMENTS

Invaluable field assistance was rendered by my colleagues

Thomas D. Cain, Michael D. Richardson, and Robert J. Orth. To these individuals, and especially to Mr. Orth, go my appreciation and an apology for the inconveniences suffered.

Dr. David G. Cook of the National Museum of Canada identified representatives of the oligochaete species collected.

Mrs. Sarah Q. Eckhause wrote most of the computer pro­ grams and must be thanked for her uncomplaining efficiency.

Richard Moncure and Robert J. Diaz readily supplied assistance with programming problems. Dr. Edward W. Fager of the Scripps

Institution of Oceanography provided listings of his recurrent group programs.

I am grateful to the members of my graduate committee, especially Drs. Marvin L. Wass and John A. Musick, for critically reviewing the manuscript. I am in appreciation of the skills of the illustrators, under the direction of Mrs. Jane Davis, and the typist, Mrs. Barbara Kerby.

The extensive groundwork on the and distribution of Chesapeake Bay benthos by Marvin L. Wass freed me of many taxo­ nomic problems and allowed more time to think about ecology. I am grateful for the support of the Federal Water Pollution Control

Administration (now Office of Water Quality, Environmental Protection Agency) in the form of a predoctoral research fellowship.

Finally, to my wife, Mike, go special thanks for her material assistance and her great understanding and support during

the course of this study.

vi LIST OF TABLES

Table Page

1. Descriptions of variables and subscripts used' in formulas...... 10

2. Estimated bottom salinity range at each station and classification according to the Venice System . . 21

3. Water depth, mean sediment size parameters, and percent organic carbon for the stations at each sampling period...... 2 5

4. Recurrent groups of species and species with affinities only with members of single groups...... 40

5. Diversity measures for each station at each sampling period...... 50

6. Rank score dominants at each station ...... 54

7. The TTestuarine endemic" macrobenthos of Chesapeake B a y ...... 71

8. Taxonomic parallels of common estuarine endemic species of Chesapeake Bay ...... 72

vii LIST OF FIGURES

Page

Lower Chesapeake Bay and the York River estuary. . . 6

Bottom salinity structure of the Chesapeake-York- Pamunkey estuary ...... 19

Bottom temperature at the mouth, head, and middle reaches of the estuary ...... 23

Sand-silt-clay ratios...... 28

Relationship of organic carbon content and clay content of sediments ...... 29

A) The number of species known from four segments of the estuary ...... 33 B) Representation of five distribution types in the estuary...... 33

Trellis diagrams of similarity values of T0 and R0 . 35

Overlap between stations 4 and 9 and all other stations ...... 38

Distribution of recurrent groups and intergroup affinities ...... 44

Direct gradient analysis of abundant taxa ...... 46

Distribution of informational diversity, species richness, and evenness in the estuary...... 49

Ranges and medians of the dominance index at each station ...... 53

Distribution of relative importance by octaves at station 4 ...... 59

Dominance diversity plots for four sampling periods at station 4 ...... 61

Dominance diversity plots for stations 1-5 ...... 62

viii Figure Page

16. Dominance diversity plots for stations 6-10...... 63

17. Hypothetical distribution of species abundance and faunal congruity ...... 77

18. Faunal congruity curves for each station ...... 79

19. Rarefaction curves for and bivalve species...... 83

20. Hypothetical dominance diversity curves...... 85

ix ABSTRACT

The macrobenthos of soft-bottoms was sampled quarterly throughout the estuary formed by the lower Chesapeake Bay and the York and Pamunkey Rivers. This is a long and stable, gradient estuary in which salinity fluctuations are mild and seasonal.

An investigation of the known distributions of 360 macro- benthic species showed that most species are distributed throughout the polyhaline portion of the estuary. There are few truly steno- haline species and the numbers of species diminish in the mesohaline and oligohaline zones. Grades of euryhalinity of species are dis­ tinguishable. There are only a few estuarine endemic species; however, these dominate in the upper and middle reaches of the estuary. Freshwater species are of very minor importance in the estuary.

Analyses of station similarity and faunal affinity showed that communities are virtually continuous along the estuarine gradient and that species are generally distributed independently. The distribution of communities is predominantly in response to a continuous complex gradient, although a noticeable distributional discontinuity exists at the border between polyhaline and mesohaline zones. This estuarine gradient is more appropriately termed an ecocline than an ecotone.

Analyses of community structure (i.e. species diversity and its components, dominance, and species-importance distributions) indicated that community complexity is constant throughout the long polyhaline zone but decreases continuously into the mesohaline and oligohaline zones. Despite the limitations of small sample size, species abundance data indicated that species-importance is dis­ tributed lognormally among species in both high diversity and low diversity communities.

x DISTRIBUTION AND STRUCTURE OF BENTHIC

COMMUNITIES IN A GRADIENT ESTUARY INTRODUCTION

Beginning with Peterson's classic investigations on

Danish benthic communities, a substantial proportion of the many studies on marine benthic "communities" has been conducted in estuarine waters (Thorson 19 57). Coastal areas of the Baltic and

North Seas have been most extensively studied (Remane 1934, 19 58,

Caspers 1948, Sergerstraale 19 57, Redeke 1933, Thamdrup 1935,

Muus 1967). British estuaries have been investigated by Alexander et al. (1935), Spooner and Moore (1940), and Milne (1938, 1940).

J. H. Day and his colleagues have described the biota of South

African estuaries in a series of papers (Day 1951, 1959, 1964, Day and Morgans 1956, Day et al. 19 52). In North America studies on estuarine benthos have been mostly in New England (Dexter 1947,

Burbanck et al. 19 56, Sanders, Mangelsdorf, and Hampson 196 5), with others conducted in North Carolina (Wells 1961) and California

(Painter 1966, Hazel and Kelley 1966).

These studies have shown that there are some ecological characteristics common to the estuarine environment, on a world­ wide basis, which have largely been summarized by Hedgpeth (1957),

Remane (19 58), Carriker (1967), and Green (1968). Two particularly basic principles have emerged. The first is that the fauna of estuaries is derived principally from the sea, with a small number of species restricted to estuaries, and a few typically freshwater species invading the estuary. The second principle is that of the 2 3

diminution of taxa along the estuarine gradient from a high at

the mouth to a low in the upper reaches where salinity change

is greatest.

Many investigations of estuarine benthos were under­

taken in boreal environments and involved only intertidal or

very shallow water organisms. The interpretations of patterns ob­

served have been largely subjective and qualitative. There has

been no attempt to apply numerical techniques used in plant community

ecology, many of which have been outlined by Grieg-Smith (1964),

Whittaker (1967) and Pielou (1970). Recent investigations of

benthic communities in truly marine environments have employed

numerical techniques of ordination (G. Jones 1969, Lie and Kelley

1970, Cassie and Michael 1968, Barnard 1970, Stephenson et al.

19 70, Day et al. 1971) and mathematical analyses of community

structure (Lie 1968, Sanders 1968, Phelps 1964, Grassle 1967).

I shall examine the classical principles of estuarine

faunal distribution and taxa diminution in the more modern context

of the community. The term "community" as used in this paper re­

fers to an assemblage of macrobenthic populations at a specific

sampling location and does not imply species recurrence or functional self-regulation. Patterns of estuarine community distribution and

structure will be quantified through the use of various mathemati­ cal analyses in an attempt to form descriptive models which are also, hopefully, predictive. The macrobenthos of York River estuary, a major subestuary of the Chesapeake Bay system, was studied. This estuary is a long, deep, and stable estuary which is yet relatively unpolluted and in which distributional phenomena 4

are developed. Although the "estuarine gradient" extending from

the ocean to fresh water is basically a salinity gradient, many

other environmental factors vary simultaneously. Thus, the

estuarine gradient is a "complex gradient" (Whittaker 1967) and

it is not correct, for all species, to equate estuarine distri­

bution and salinity tolerance range. Nonetheless, the nature of the distribution of communities along the estuarine gradient should supply evidence of the nature of community change along environmental gradients in general. METHODS

SAMPLING

Ten sampling stations were established, from the mouth of

Chesapeake Bay through the York River and into the Pamunkey River

(Fig. 1), the most up-estuary station being 104 km from the mouth of the Bay (Chesapeake Bay Bridge-Tunnel). Three replicate samples were taken from an anchored small craft with a modified van Veen grab which covered an area of 0.07 m^. Each station except one

(Station 5) was sampled on four separate occasions, in August and

November, 1969, and February and May, 1970. Station 5 was sampled only during the February and May periods. Samples were taken from bottoms at shallow channel depths, ranging from 6 to 14 meters.

The grab used is of a similar design to that pictured in

Holme (1964) and has a continuous warp running through sheaves at the ends of the arms. The leverage action of the arms together with the considerable weight of the grab (25 kg) allowed penetration of up to 17 cm in all but the sandy sediments at station 1. In the muddier sediments at the remainder of the stations the grab almost always filled to capacity (6.8 liters).

The filled grab was brought aboard, set on a hopper and its contents deposited in large plastic pails. A small sample of sediment was taken from the top 5 cm of the sediment for particle size analysis. A second sediment sample was taken of surface ooze

5 7 7 ° 00 7 6 ° 00 ■n£»4 ■. 38° 33 ° m m - £%■ ii# ocT 00 ' V ^ y -'f y 'j M ( h V W :.■*% f A .■■■’ V 7 it. : CO RICHMOND • \ ,K ~ ^ y&sih v io ”"- - ° © ? ::v Li ■ a V'. ■ ::■: : *0*' *•* T? ■ ’'v' - ki O ' . . X| V - -•I*'* A i A / 57° 37‘ / oo1 0 0 ' ^ z i ^ w -

HAMPTON ROADS '- V.,NORFOLK i

7 7 ° 00 76 ° 0 0 '

Figure 1. Map of lower Chesapeake Bay showing stations occupied in the Chesapeake-York-Pamunkey estuary.

o 7

from one of the three replicate grabs for organic carbon analysis.

The samples were brought back to the laboratory, and the sediment was put in a large galvanized can and elutriated in a manner

similar to that described by Sanders, Hessler, and Hampson (1965) through 1 mm and 0.5 mm opening screens. The fraction retained by the screens was preserved in a buffered 10% formalin solution.

The 0.5 mm screen material is incompletely analyzed and not re­ ported herein.

All non-colonial were removed from the preserved debris by examination under a dissecting stereo-microscope and were identified and counted.

SEDIMENT ANALYSES

Sediment particle size distribution was determined by sieving and pipette analysis following the procedures outlined by

Folk (1961). The portion of the sediment coarser than -1, 0, 1,

2, 3, 4, 6, and 8 phi (0) units was determined and median particle size diameter determined by plots on probability paper (Folk 1961).

Sedimentary organic carbon content was determined by the potassium dichromate-sulfuric acid wet oxidation method detailed by Maciolek

(1962). Sediment samples were frozen the day of collection and later lyophilized and a portion weighed out for the oxidation analysis. Chloride ion interference was avoided by complexing the chlorides by the addition of Ag 2 SC>4 (Quinn and Salomon 1964).

As Coull (1970) pointed out this method oxidizes only the labile organic fraction, i.e. the fraction including those compounds theoretically directly available to benthic deposit feeders, and not the refractory portion. The resulting values are then not of total organic carbon but of "labile organic carbon."

Samples of surface and bottom water were collected at the time of sampling and were analyzed for salinity by an induction salinometer and for dissolved oxygen by the Winkler method. Tem­ perature of the sediment and of the surface water was also recorded.

ORDINATION ANALYSES

Large amounts of multispecies, multisample abundance data may be analyzed by similarity measures and classificatory techniques.

This analytical approach has been named comparative ordination by

Whittaker (1967). One may compare the taxonomic similarity of samples, compute some similarity index between all pairs of N samples, and thus develop a N x N matrix of similarity values.

This approach is Q-matrix (Margalef 1967), Q-mode (Lie and Kelley

1970), or site-group (Stephenson et al. 1970) ordination. Alter­ natively, the distributional similarity of S species may be compared and a S x S matrix of some affinity measure computed. This is

R-matrix (Margalef 1967), R-mode (Lie and Kelley 1970), or species- group (Stephenson et al. 1970) ordination.

Within each of these two basic approaches to ordination, measures may be computed using either some measure of species relative abundance or the presence or absence of the species, i.e., the criteria may be either quantitative or qualitative

(Pielou 19 70). R-matrix-qualitative, Q-matrix-qualitative, and

Q-matrix quantitative ordinations were used in this investigation.

The R-matrix-qualitative analysis was the recurrent group analysis of Fager (19 57) as modified by Fager and McGowan

(1963). An index of species affinity was computed for all pairs 9 of species which is the geometric mean of the proportion of joint occurrences of the two species,

Xij = qj/CAiAj)1/2 - l/2(Aj )1/2

(see Table 1 for variable and subscript descriptions), where

Aj >Aj_. An arbitrary level of significance is chosen (Fager sug­ gested I >0.5), and the species are grouped into the largest possible groups in which all members have significant affinity

(Fager 19 57).

Stations were compared on the presence or absence of species (Q-matrix-qualitative) using a method based on a modifi­ cation of Kendall's rank correlation coefficient for maximally tied ranks (Looman and Campbell 1960, Lie and Kelley 19 70). For a given pair of stations an index of station similarity is computed

To(kl) = (cklwkl-vkvl)/(xkskxlsl)1//2-

Because the basic computation is based on a 2 x 2 contingency table, the index has the advantage over the more familiar coef­ ficients of Sorenson, Jaccard, and others (Whittaker 1967) that appropriate values of chi2 at a given probability level may be used to compute significant levels of T0 . The significant level of TQ at p = 0.05 is

Te = (chio.o5/z)1//2> (df ~ and therefore any TQ >Te is significant at the 0.05 level.

Horn's (1966) informational overlap measure was employed as a Q-matrix-quantitative similarity analysis. This analysis Table 1. Descriptions of variables and subscripts used in formulas, i species i j species j k station k

1 station 1 n ^ number of individuals of species i(j) at station k(l)

Nv number of individuals of all species found at station k k(l)

number of species found at k(l)

Cj_j number of co-occurrences of i and j

number of occurrences of i(j )

Z total number of species from all stations (=192)

number of species out of Z which did not occur both at k and 1

number of species found at k(l) but not at l(k)

number of species out of Z not found at k(l)

10 11 generates indices expressing the relative amount of information content shared by all pairs of stations, and is directly related to measures of diversity based on information theory. The amount of overlap, RQ, between samples k and 1 is given by

S S S X . ■ X > " R0(kl) = i=l (nik+nil> log(nik+ni:L) - i=1 nik log nik - £rg ngg log ngg (%+Ng) log (Nfc+Ng) - log % - Ng log Ng

None but an arbitrary level of ,Tsignificance,r may be assigned to this index, however relative similarity may be demonstrated.

STRUCTURAL ANALYSES

Methods of analysis of community structure employed in this study include a variety of measures of species diversity and its components. Information-content diversity measures have re­ ceived wide use recently. They express the degree of uncertainty of predicting the identity of an individual selected from a series.

This uncertainty is dependent on 1) the number of species in the series from which the prediction is made, and 2) the evenness of distribution of individuals among species in the series. These features have been termed the "species richness" and "evenness" components of informational species diversity.

Average information content or diversity per individual is given by the formula (Shannon and Weaver 1963)

,S_ H' = -£lPi l09 Pi C1) where pg is the proportion of the i-th species in the population and thus ng/N may be considered a sample estimate of pg. Alter­ 12

natively, population diversity per individual is given by Brillouin's

(1962) formula,

1 N ’. H = r,N log a —nj_T. f------n 2 . r------• • • ngl r (2)^

Pielou (1966b) reviewed the theoretical implications of

these two measures as applied to different types of biological

collections. There is probably some justification in considering

these collections of benthic organisms as either 1) collections

from which a random sample can be drawn but the total number of

species is unknown (Type C or D) or 2) collections from which a

random sample cannot be drawn (Type E). If interpreted as Type C

or D collections (depending on whether the species-abundance curves

are smooth), the appropriate measure is H r, but it should be

estimated according to Good's (1953) formula and the use of equation

1 with the substitution of n^/N for pj_ is not theoretically justified.

A more realistic interpretation of the type of collection

represented here is that because of the patchy spatial pattern of

sessile organisms, a truly random sample is not obtainable (Type E).

Pielou recommends the application of H (formula 2) as an estimate

of the community diversity. By computing H for successively pooled

replicates we have H^, k=l, 2, . . z. will increase with k

and will level off, if a large enough z has been chosen. Hz, the

estimate based on the largest pooled sample, is then an estimate of

H'pop; i*e. the true average diveristy of the multispecies popu­

lation (Pielou 1966b). In this study three replicate grab samples were taken at each of the stations (for each of the sampling periods) and Hz (z=3) computed by formula 2 was used as an estimate of H'p0p. 13

Boesch (1971) has shown that the sample size (number of individuals)

usually produced by three replicate grabs in a comparatively di­

verse environment yielded H T estimates of at least 90% of the

asymptotic value that H' achieves with increasing sample size.

Thus Hz values computed herein may be considered slightly low

estimates of H Tp0p.

I have also computed values of HT (formula 1) for the

3 pooled replicates at each station for purposes of comparison with

other studies, most of which have employed Shannon’s formula.

H and H' can be computed using any convenient base logarithms

since only the size of the unit is affected. Base two logarithms are most frequently used and were employed here yielding units of

"bits per individual". Conversion can be made to any other base units by multiplication by a constant, for example H(base e) =

0.69314 x H(base 2).

Theoretical maximum diversity for a given multispecies population, i.e. the value of the index when the individuals are most evenly distributed among the species, is given by

_ 1 ______Nj______(3) Hmax N °g [n /S]'. s_r (Cn /S] + l 0 r where Cn/S] is the integer part of N/S and r=N-SLN/s3, and

^'max - -*-°9 g

(Pielou 1966a). The ratio of H to Hmax and H ’ to H ’max are ex­ pressions of the evenness component of informational diversity

(Pielou 1966a),

J = H/IW J' = H'/H'max- 14

Although these evenness measures were computed on data obtained in

this investigation, their use is not completely valid theoretically

because in formulas 3 and 4, S, the "population" value is unknown.

Sample S values yield evenness values which are not necessarily

equivalent to the "population" evenness, however they are useful

in comparing evenness in similarly collected samples.

Two other "evenness" measures have received considerable

useage, "redundancy" (Patten 1962) and "equitability" (Lloyd and

Ghelardi 1964). If the theoretical minimum H for a multispecies

population is

N T. Blmin - 1/N log (N_s+1)(

then redundancy is expressed as

r = Hmax - H Hmax - fynin

Equitability is

£ = S ’ / S

in which S' is the number of species predicted by McArthur's (19 57)

"broken stick" model, assuming the observed diversity H ’ (see Lloyd

and Ghelardi for a table of S'). These indices were computed to

assess their relationship to the evenness component as expressed

by J.

The simplest expression of the "species richness" com­

ponent of informational diversity is S, the number of species in

a sample. However, because of varying numbers of individuals in

samples, some expression of the relationship of the number of species to the number of individuals is more appropriate. The number of species in collections from the same community often varies directly with the logarithm of the number of individuals in the collection

(Odum et al. 1960). Margalef proposed the ratio (S-l)/ln N as a measure of the species richness component. Sanders’ (1968)

"rarefaction" method was also employed as a measure of species richness. This is a graphical method which predicts the number of species that would theoretically be taken in increasingly rarefied samples. Curves describing the relationship of sample size and number of species may be generated for different collections and may be visually compared, or the number of species predicted for an arbitrary small sample size may be used as an index of species richness.

The ordination analyses were performed by an IBM 360/50 computer at the Computer Center of the College of William and Mary.

The recurrent group analysis programs were supplied by E. W. Fager of the Scripps Institution of Oceanography. Sarah Q. Eckhause wrote programs for the remainder of the ordination analyses and the various utility programs and converted the recurrent group program to the William and Mary system. Programs for structural analyses, for predicting species-abundance distributions, and for non-parametric tests were written by me for the IBM 1130 system at the Virginia Institute of Marine Science. DESCRIPTION OF THE ESTUARY

GEOMORPHOLOGY

The Chesapeake Bay estuarine system is a drowned river valley or "coastal plain estuary" (Pritchard 1967b). Major sub­

estuaries of the Chesapeake Bay include the Susquehanna, James,

Potomac, Rappahannock and York Rivers. The York River drains a

basin of 2,661 square miles (6, 892 km^) of Piedmont and Coastal

Plain Virginia (Virginia Division of Water Resources 1970). It

contributes only a small fraction, 2%, of the total Chesapeake

Basin freshwater inflow, the mean annual discharge being approxi­ mately 2,200 cfs (Brehmer 1970). The York River, an estuary throughout its length, is 55 km long and is characterized by its

straightness above the Gloucester Point-Yorktown constriction

(Fig. 1). Two main tributaries, the Pamunkey and Mattaponi Rivers, meet to form the York at West Point. The meandering Pamunkey is the larger tributary and is tidal for 73 km above West Point. The limit of saltwater intrusion, i.e. the upper limit of the estuary in the sense of Pritchard's (1967a) definition, is about 30 km above West Point.

The tributaries of the York estuary, especially the

Pamunkey and Mattaponi Rivers, possess extensive tidal wetlands, particularly salt- and freshwater marshes. Wass and Wright (1969) estimated that 23,482 acres (9,510 ha.) of marshes are present in the York estuarine system.

16 17

Lower Chesapeake Bay is characterized by sandy shoals

(7-9 m) interrupted by deeper (>13m) mud bottom channels leading

from the upper bay and the larger river sub-estuaries. Four

natural channels separated by shoals lead through the Virginia

capes to the continental shelf. These channels are deep and have

sandy bottoms scoured by swift tidal currents. The York River is

broad and straight with extensive shoals of muddy sand on either

side of a deep (9-25m) central channel with a mud bottom. The

lower Pamunkey River is narrow and meandering with essentially no

marginal shoals and a bottom of variable texture in the channel

of 5-20 m.

SALINITY STRUCTURE

The York estuary is a weakly stratified, horizontal

boundary estuary (Pritchard 1967b). Salinity decreases gradually

from the mouth to the head and is slightly higher on the right

side, looking upstream, than on the left. Because of the low

ratio of tidal prism to the volume of the estuary, the salinity variation during a tidal cycle is small. The term "gradient

estuary" may be applied to this type of system, as opposed to a

"fluctuating estuary" in which salinity change at one point during a tidal cycle is large (Sanders et al. 1965).

The York, as other gradient estuaries, has a "gradient zone" near its upper end, where longitudinal salinity change is more abrupt than elsewhere (Rochford 1951). The abruptness of the gradient zone is related to the amount of freshwater inflow; therefore, this zone is usually less abrupt in the York than in the James or Rappahannock estuaries. 18

Predominant salinity variations at fixed locations are seasonal, and are related to the periodicity of freshwater runoff.

The monthly longitudinal salinity structure of "bottom waters” in the Chesapeake-York-Pamunkey estuary is summarized for December

1967 to May 1970 in Figure 2, compiled from unpublished data col­ lected by personnel of the Virginia Institute of Marine Science.

Generally, peak runoff in spring and low runoff in late summer and fall shift the isohalines 10-20 km down-estuary and up-estuary respectively. Salinities in the upper estuary during the faunal sampling period, August 1969 to May 1970, were aberrant, because heavy rainfalls in the drainage basin in July and August and to a lesser degree in September and October displaced the isohalines down-estuary from their usual late summer and fall positions. Heavy rainfall in Piedmont Virginia associated with the passage of the remnants of Hurricane Camille caused flood conditions in the Pamunkey River. The effect of this freshet was felt well down-estuary and vertical stratification became quite m a r k e d .

In deeper estuaries the environment of the benthos, except those in the shallows, is buffered against catastrophic salinity changes by density-related circulation phenomena. In­ creases in stratification and oxygen depletion of bottom waters may be especially deleterious when temperatures are high, and thus oxygen solubility low, and when freshet transported organic material is transported into the system. This occurred in the aftermath of the Camille flood and dissolved oxygen concentrations became very low in the upper estuary. PAMUNKEY RIVERj YORK RIVER- -- -CHESAPEAKE BAY

130 120 110 100 90 80 70 60 50 40 30 20 10 0

F

10 15 20

0 • - 25 3 0 C D —

M ~ A - M -

S~ 0 ~

J- F - O f-. M " (ft A -

130 120 110 100 9 0 8 0 70 60 50 40 30 20 10 0

« S l£ S - ■DISTANCE FROM BAY MOUTH (km)'

Figure 2. Bottom salinity structure of the Chesapeake-York-Pamunkey estuary for 1968, 1969, through May 1970. Isohalines in parts per thousand are indicated.

-19- 20

Although salinity fluctuations are predominantly seasonal, salinity changes at one locality during a tidal cycle may be great in the upper estuary. Van Engel and Joseph (1968) reported tidal salinity changes of about S % 0 within a 12-hour period at a location near my station 10. This is equivalent to the total annual vari­ ation. However, the tidal salinity range at down-estuary locations is very small (<3$0) (V. G. Burrell, Personal Communication).

A classification of estuarine environments based on salinity regimes was adopted by an international symposium

(Symposium on the Classification of Brackish Waters 19 58) and has become known as the Venice System (Carriker 1967). Under this system, estuarine waters are classified as euryhaline (30-40&), polyhaline (18-30&), mesohaline (5-18&) and oligohaline ( 0. 5- 5 %>).

Using this terminology, the salinity regime of each of the ten stations in this study was determined on the basis of their esti­ mated salinity ranges during the sampling year (Table 2). Stations

1-5 were polyhaline, station 6 was both polyhaline and mesohaline, station 7 and 8 were mesohaline, station 9 had meso- and oligohaline salinities and station 10 was oligohaline.

TEMPERATURE AND DISSOLVED OXYGEN

Temperature and temperature stability affect the global distribution of species and species diversity and other facets of community structure (Sanders 1968). Additionally, temperature and salinity may operate synergistically, thus temperature may affect the degree of penetration of estuaries by organisms (Kinne 1964).

Odum and Copeland (1969, Copeland 1970) have classified coastal ecosystems by characteristically predominant energy sources Table 2. Estimated bottom salinity range at each station during the sampling year, June 1969 to May 1970, and classi­ fication according to the Venice System (Symposium of the Classification of Brackish Waters 19 58).

Station Distance from Mouth of Salinity Range Classification Chesapeake Bay (km) (ppt)

1 2 24-31 polyhaline

2 22 22-28 polyhaline

3 37 19-25 polyhaline

4 47 18-23 polyhaline

5 54 17-22 polyhaline

6 62 16-20 meso-polyhaline

7 76 10-18 mesohaline

8 84 7-15 mesohaline

9 91 5-12 oligo-mesohline

10 102 0-5 oligohaline

21 22 and referred to temperate estuaries as "natural temperate ecosystems with strong seasonal programming." The strong and predictable nature of temperature seasonality in the York estuary (Fig. 3) indicates that temperature is a predominant programming stimulus.

The annual temperature range in this system is extreme (2-28 C) and these extremes are often exceeded in shallow waters.

Temperature at the mouth of the bay is slightly more stable than in the rest of the estuary; because of the influence of continental shelf water, the bottom temperature usually does not exceed 2 5 C. There is a time lag in vernal warming among different segments of the estuary. Up-estuary areas warm more rapidly in the spring (Fig. 3). Temperature provides stimuli to insure reproductive synchrony (Carriker 1967, Kinne 1964). Because the Chesapeake Bay fauna includes elements with southern and northern limits in the area, reproductive cycles of different benthic invertebrates may be cued by vastly different temperatures.

Thus, recruitment to benthic communities occurs year round.

Dissolved oxygen concentrations in the York estuary are usually greater than 75% of saturation concentrations, because of weak vertical stratification and strong tidal mixing. In the upper portion of the estuary, where organic loading from surrounding marshes is great, oxygen levels may drop below 50% saturation during the night in warmer months. Dissolved oxygen may be less than

3 mg/1 and oxygen stress conditions may exist for benthic organisms.

During the flood conditions of August 1969, vertical stratification in the upper York River was strong and D.O. concentrations in bottom water were low (<1 mg/1). However, no evidence of mass O i h- 0 cr> rd CD & rd CD CD O

CD & P m o

CD CO CD O rd CD P CD 10 H cn TJ s 6 T)C CM rd m TJ rd CD P - u P P 0 g 0 & P -P rd 0 P P to -P rd P 0 i* co 0 u> P cr> 1 p Jo

pp York-Pamunkey estuary for 1968, 1969, through May 1970.

0 p p u. tn •H IP I— o in m to Cvl CM Oo 3 Hn±VU3 d W 3 1 24

mortalities of benthic species was detected in the November

sampling.

There is no particular longitudinal pattern of dissolved

oxygen concentration, although it is generally slightly greater

down-estuary. A pronounced "oxygen sag" exists in the lower

Pamunkey River (Brehmer 1970), probably attributable to organic

loading by pulp mill effluent at West Point.

SEDIMENTS

An attempt was made to sample the benthos at locations

with approximately similar sediment types. Silts and clays are

the most widely distributed sediments in the estuary, so "muddy"

sediments were chosen for sampling. In the nearby polyhaline

Hampton Roads, the faunal assemblage found at stations having

sediments with more than 30% silts and clays was different from

that found at stations with less than this amount (Boesch 1971).

Thus, the presence of 30% or more silts and clays was assumed to

indicate mud bottoms.

The results of the sediment particle size analysis

yielded percentages by weight of gravel and shell, five 0-size

classes of sand, two of silts, and total clays for samples from

each replicate grab sample. These values for the three replicates at each station were compared and variability among replicates was relatively insignificant. The mean percentage (for three repli­ cates) of each size fraction was computed and median particle diameter determined using these mean values. These data are summarized in Table 3 as percentages of gravel/shell, sand, silt and clay and median particle diameter. Sand-silt-clay ratios were Table 3. Water depth, mean sediment size parameters, and percent organic carbon for the stations at b H <4-t Hr—l •H u nO o •H •r—I «4 G •«-4 t"' r—4 i—4 eT-- o no r—1 r—4 T5 CO t a 0*1 an cn •r—l o -U J-J Um •U -u 4J W u oCO to W JC cO CO CJ c0 Oc CO cd CO o G (30 OXl X O cO G CJ Cu OJ O O O O o x Oh Oh o CO CO n t O cc CO »—i r—4 CO o CM — r-4 r—4 ON CO M M — - r r—4 r—4 > M M CO cO £ • • • • « % • • % • • • • « • • • » • • • • • • o o VC x> o 5T "D T? T5 CM <■—4 o o O Oh CO CO CM o I”“1 r—l — r—4 r—4 r—l o X CO r-4 r—4 H ><; H cn CO c C • , k x 0 0 -O' a> o o O O CO r—4 X r-* Oh -. r CO X — >C - Oh r-* CM o> i—4 r-i O MoC CM CM o CM M Ocn CO OCO CO • • • • • • • • • • • X o o o o Oh r—4 o CO - CM r-H CO CO CM i~4 r—4 —1 r— m r^. CM CO > G 0C on a o a no no CJ ”0 Oh M0 X 00 CM X CM t < 0 00 <0* Oh o o co CO -. r r—4 r—4 T—1 CO CO CO o > H H <1* a cn G cu >h >h i r—4 <1* ) X CO ^ r m oo oo O o o o r—4 r—4 i—4 r—1 oco co n i r—4 o o X H r-4 CO r—4 r4•r4 •r-4 U Jo >, > >> OCO CO >> 25 • 4 — 4r—4i—*4 00 t < CO oo r < CM o o r—4 - - 3W 03 r-4 r-4 r—4 1—4 CO X X 00 m Oh H H 4J CO • • • • 4 4 « « m <1- <1- no • J r-4 CM r-. CM Oh 0Xo X 00 Oh r—4 o CM r-4 x CM x > u 03 CO G CO 1 1 J- 00 00 X o r-4 o co CO r—4 r—4 CM X r—4 n i CM X 4 - o —4r O r—i r-4 Oco CO M > H H H CO CJ h CO cn ncn cn c • • • • • * • • • • • 4 4 n i CM 0 0 o Oh r—4 — - r-4 r-4 r—4 CM r—4 CO 00 o o no O CO r-4 00 Oh > n t G cO cn 1 i • I MCO CM r < t—4 i—4 o Oh X oo n t OCM CO Oh CO o o f v o O o o o o o o ^ r 1—H r—4 -. r CO ♦r-4 > M H — ^ CO r^- T—4 XJ CO Po cn u 1 * • * * • • • • • • 4 o X hOh Oh o o X O 00 Oh m CM CM r—4 CO Oh OC X CO CO no —4 H n i - r •r-4 X 4J ncn cn cn OC OcO cO CO CO • > c G «0 1 • • • • • • • • « • • OX vO CM CM o MCO CM - c o CO o X no o n • CNJ i"-- — » 4•r4i• r-4 i •»—4 • r-4 H H —4 u ■j >> OG CO CJ U \ 1 ■ 1 : • ^ « • • • « vO oo CM CM X X X CM o o G3 r—4 OCM CO ho Oh > r < r*. CM r-4 — Oh r—4 4-J cn G cn rO t 1 r-4 Oh <1* r-4 CO CO r < o o o no X m - o o r-4 »-4 X •:r> cn ^ r-4 r^- st- o O o o o o r-4 ^ i X H H OC cO X o a) X cO cn C • • * • • CO 'i0 O O o o o CO r-4 CM Oh CM CM CO o - O00 CO 1-^ o X - r r—4 CM cn cn VO o X no > iJ o cn cO in >» i 1 Oh X CO Oh Oh o Oo•oo •:o o VO — r—4r—4 Oh r—4 X X n i •r4 cn cn X > H M M H M X — (—4r—4 4J ncn cn X Oc to co cO X CJ X 1 1 CO o X o o o CM } X <}■ 1—1 CO oo no X X X X r-4 X Ch X •r4 i/3 >h u OOh CO vO —4r X t-4 o VO X o CO X vM '.X 1'-. 3 X (30 X X r—J H r**. r-4 •H 4J u ncn cn u ■Oh CO X O Oh r—4 CO r—4 o o X X CM r-l 00 Oh •rl > CM <0 o * * Table 3, continued t JO TJ O ^ 5 rC ^ 5 u-l -r-4 T i r • i co r-4 r—4 •r4 G r CO *TD 2 1 1 1 •1^ O C/3 Q r-4 r/l *r-l u —1 4J •U J.i —1 u •w co cn cn CO CO O o; o co o d . O C co a o 0 0 a 0) <0 o i—• GvO jG o a U 0) 6 c0 > CO - r 0 0 CO OC CO CO CO VO > H H »-4 H cn -•» cj OCO CO >> j • »••»•••••I• I • • • • • » • • •» « • • • • • • * i • •r-4 l i » pn JCJ CJ X « • • » • • • • • • • • • « \ • • < * oo O vO W O CN CN cn -> CJ % oo r^* H M r > 1—4 1—4 n c n c 0 0 un cn un r~- U”'l GO o t < fr < Qcn vQ LT, cm v£) o r—l — •r4 r—l XJ ncn cn X CJ cO j 1 • » « » « « 26 X M M o o co r-*4 n c CD - r 00 o O r-4 un n i vO o CN cn n c r—l T—4 •rl ON -U >1 cO u X 1 » vO o r—l o M cn '.O o 0 0 vO CN CO o o vO CN r—l o o o o vO un TO NCN CN 1—1 r—l •r-4 cn —1 4_l nc cn cn cn CO X cti X c cn o i 1 « • % vO CN r-l > P O O U*5 5 0 CN m r-l CN r— OCN NO \—i vO ON r—l r-* un o o nCN cn 0 0 i—i r— •H 4J CJ >1 cC x 1 05 r*- f N 0 0 > > M CO cn H H CN CO CN vO cn Nt- o 0 0 CN cn O cn OX TO r—l «—J ^ r o • r-l u d CO cO d Jno CJ 1 i t O v X un 0 0 M 5 0 5 0 5 0 cn o CO CN r-l G5 m CN 5r^r-'cn ' - r ^ r 05 n c n c o o o VO t v 05 1 vO CN '- " - r-l r-i OJ ncn cn d a »XX X >» CO c CJ i • « » « * • t • n i cn r-l un r-4 cn C-J un o r-» CN r—l o o r—l n c o 0 0 m n a oo - r T TO —1 o co cu 05 1 O OCO CO VO M W t v •rH H O ,sit’ ncn cn CN CN CN CM 0 0 o O o O o r—- O ,•— CO un r— i t N • —> ■Li ntn in . > 1 X u CO —' 1 * < * X GO CN cn o O 0 0 o oON co C5 CN r—l un o on . - r un r-l -H r-l 4-> o s r X d J • « • • • • • » > a i-£ h-i en Mi­ i - r cn CN CO vO i—i nVO cn o o o 0 0 vO o r—1 vO t—i un H (—1 •r-l 4J ocn to o X CO > 1 05 > vO o 5 0 o LO Mj‘ m un 0 0 o CN o cn r-4 o un •rl r—4 r—l U CJ X >> ! «

Median particle sizes less that 3.0 o' were detained by extrapolation. 27

plotted on triangular coordinates (Fig. 4) and the sediments

classified according to Shepardrs (19 54) descriptive nomenclatural

scheme (Table 3).

A wide range of sediment types were sampled, but only

the four samples at station 1 and two of those at station 3 had

less than 30% silts and clays. Station 1 was located at the mouth

of Chesapeake Bay where no "muddy" bottom sediments were found.

The sediments there were very-fine sand and, although the silt-

clay content was low, the modal size class was 3-40. The two

samples at station 3 both had more than 2 5% silts and clays and

appeared muddy.

The effect of sediment size on faunal distributions re­

ported herein was great, especially at station 1, and some

reservations must exist regarding the interpretation of the

effect of salinity on these distributions. The sediment of stations

2, 5 and 9 also had considerable sand fractions. The sediment at

the remainder of the stations was mostly silty-clay.

Comparisons of organic carbon content (Table 3) and

various sedimentary size parameters showed that organic carbon

content was most highly correlated with the clay content (Fig. 5).

This is related to the great sorptive capacities of clay particles

(Rae and Bader 1960) which allow them to trap and retain dissolved

and particulate organic matter. Another factor related to the

organic content of the sediments was the position of the station

in the estuary. Up-estuary stations (cf. stations 9 and 10) had more sedimentary organic material and down-estuary stations (cf. 2)

had less than predicted by the regression line in Fig. 5. This is CLAY

|\S ILTY- CL AY-

CLAYEY -SAND ©, SAND-SILT - CLAY

SAND SILT

Figure 4. Sand-silt-clay ratios of samples from each station during each sampling period.

-28- Figure 5. Relationship of organic carbon content and clay content of York estuary sediments. The samples f r o m stations 2, 9 , and 10 are indicated to show the effect of position in the estuary on organic content. Product- moment correlation coefficient is indicated. CM GO

/ O N

\Q ~ l O

\ CM

\° ) PERCENT PERCENT CLAY

lO CM Noaavo oiNV9ao iNaoaad

29 30 because the up-estuary stations are closer to attached sources of carbon fixation (mainly tidal wetlands) than are the down-estuary stations. On occasion, sediments in one grab sample from station

10 yielded more than one-half liter of vascular plant debris.

These organic carbon data are within the range found by

Tietjen (1969) in estuarine sediments in New England using identi­ cal analytical techniques. Those values from the middle reaches of the York River are similar to those found by D. S. Haven

(personal communication) for a station near Station 4, using a combustion analyzer.

ECOLOGY

The York estuary is relatively well known biologically.

Wass (1965) listed distributional records of many invertebrates in the lower Chesapeake Bay region, particularly in the York estuary.

McHugh (1967) described the distribution of fishes in the Chesapeake-

York-Pamunkey system. Patten et al. (1963) described phytoplankton succession in the lower York River. Warinner and Brehmer (1966) studied benthic community structure in the vicinity of a heated water effluent at Yorktown. Feeley (1967) investigated the dis­ tribution of amphipods in the York-Pamunkey estuary. Marsh (1970) studied the epibiota and the structure of epifaunal communities of

Zostera above Gloucester Point. Wulff and Webb (1969) described seasonal succession of attached macro-algae at Gloucester Point.

Wass and Wright (1969) included the York estuary in their survey of the coastal wetlands of Virginia.

Much ecological information resulting from work done by personnel of the Virginia Institute of Marine Science is unpublished. 31

M. L. Wass, D. S. Haven, and R. J. Orth have studied various

benthic communities in the lower York River. W. A. Van Engel and

E. B. Joseph and V. G. Burrell have investigated the hydrology and

zooplankton of the York estuary. M. L. Brehmer has studied nutrients

and phytoplankton in the James, York and Rappahannock Rivers.

ALTERATION BY MAN

The York estuary has been affected by man less than most

of the Chesapeake sub-estuaries, and indeed less than most Atlantic coast estuaries. There is a moderate human population of approxi­ mately 117,000 living in the York drainage basin. The largest single source of domestic waste addition is by the town of West

Point and there are three main sources of industrial waste addition: a kraft-pulp mill at West Point and a steam-electric-generating station and an oil refinery at Yorktown, just above the mouth of the York River. The only major dredged area is the channel running from the mouth of the York River to the Chesapeake Channel in the lower bay. A large cooling-water reservoir being built for a nuclear power plant on the North Anna River (tributary of Pamunkey

River) will considerably reduce the freshwater inflow into the estuary and may cause some ecological changes in its upper reaches. RESULTS

DISTRIBUTION OF THE FAUNA

The 114 grab samples contained 12,120 macrofaunal indi­

viduals identifiable as 192 taxa, 176 of which could be determined

to the species level. This basic information on the distribution

of benthos in the estuary was supplemented with distributional

information in Wass (1965) and unpublished records of M. L. Wass,

R. J. Orth and myself for free-living, non-colonial species of macrobenthos. The result was a rather accurate picture of the

distributional ranges of 360 species in the Chesapeake-York-

Pamunkey estuary (Appendix).

A large number of taxa are known only from the lower

York River because of the disproportionate sampling effort in this

area by personnel of the Virginia Institute of Marine Science.

These species are all "marine" forms and therefore I have assumed

implied distributions into the lower bay and to the ocean.

The number of species found in four segments of the estuary are totaled and presented in Fig. 6A. The lower bay area is the most speciose, even if species with implied distributions are eliminated, but a very large portion of the fauna is also known from the lower York River. A large decrease in taxa occurs past 60 km from the mouth of the bay (roughly the upper boundary of the polyhaline regime). Another large decrease occurs in the

32 Figure 6. A) The numbers of macrobenthic non-colonial species known from four segments of the Chesapeake-York-Pamunkey estuary. Segment of bar above broken line indicates species with implied distributions. B) Representation of five estuarine distri­ bution types among the same species. 1 '••1

300 A

20 0 - LOWER cn UJ o CHESAPEAKE UJ a. to B AY POLYHALINE

YORK 100

M ESOHALINE

YORK OLIGOHALINE

PAMUNKFV O 4 0-30 30-60 60-90 90"1! 0

KM FROM MOUTH OF BAY

200 -•

co w o UJ 1 0 0 - CL 00

o - - LOWE R LOWER L 0 W £ R LOWE R MESO BAY 8 A Y BAY BAY OLIGO­

ONLY POLY­ M £50* 0113 0 - HALINE HALINE h a l in e HA L INE

33 34

last interval, which roughly corresponds to the oligohaline zone,

to a low of 40 species.

The ranges of the species may be divided into five types:

1) lower bay only, 2) lower bay into the polyhaline York River,

3) lower bay into the mesohaline York, 4) lower bay into the

oligohaline regime, and 5) only in the meso- and oligohaline

regions of the estuary. The first four distribution types repre­

sent the distributions of marine animals which are, in varying

degrees, euryhaline, and the fifth, the "true estuarine" fauna

plus some fresh-water forms. The most common distribution type

is from the mouth of the bay into the polyhaline York but not past

60 km up-estuary (Fig. 6B). Type 1 and type 3 distributions are

well represented, but only a few species live along the full range

of estuarine salinity regimes and only a slightly larger number

are "true estuarine" species. Truly fresh-water environments

were not sampled during this investigation and only three fresh­

water taxa, fasciatus and two insect larval types, are

included in this analysis.

Q-MATRIX ANALYSES

Q-matrix similarity coefficients based on species presence

or absence (Kendall’s index, T0 ) and relative abundance (Horn's

overlap, R0 ) were computed for all sample pairs in the 38-sample

set. For each sampling period stations were compared using a

"trellis diagram" (Fig. 7) with T0 values above and RQ values below the principal diagonal so that the two sets of results could be directly compared. AUGUST NOVEMBER

To To I 23456789 10 I 23456789 10

^

FEBRUARY MAY

T o > 0 .3 6 ■ R o >0.40 O.I8>To>O.IO | | | 0 .2 0 > R o > 0 .!0

0.36>To>0.l8 0 0.40>Ro>0.20 To

Figure 7. Trellis diagrams showing station x station matrix of similarity values (Q-matrix) based on species presence (T0) and relative abundance (RQ).

-3 3- In Fig. 7 index value intervals are indicated by shading.

Although the bounds of these intervals may seem arbitrary, there were reasons for assigning them. The significant level of T0, when

z = 192, df = 1, and p = 0.01 (see Methods) is 0.18, however too many station pairs had indices above this level, and much infor­ mation was lost by not differentiating species pairs at a higher

index level. Consequently, an index level roughly double the p = 0.01 value, or 0.36, was used as the lower bound of the highest

T0 interval. For RQ, the lower bound of the highest index interval

0.40, was assigned because it was approximately equal to the lowest mean index between sampling period pairs for a single station.

Station 3 had this lowest mean index for inter-period sample pairs; most stations had a value of 0.6 or greater.

Given an environmental gradient on which stations are ordinated, two possibilities exist. Either the stations all show consistent similarities with adjacent stations throughout the gradient and the "black squares" in the trellis diagram are evenly distributed along the principal diagonal, or there may be discon­ tinuities in station similarity, in which case the black squares are clumped around certain segments of the principal diagonal.

The trellis diagrams for the stations in the York estuary show a mixed pattern. The distribution of black squares along the diagonal ranged from quite even (e.g. RQ in February) to clumped into black triangles of "station groups" (e.g. RQ and T0 in August)

This indicates a pattern of unidirectional faunal change throughout the estuary with some zones of relative homogeneity, or more pre­ cisely, more gradual change. Thus stations 2, 3, 4, and perhaps 5 37 can be considered one "station group" and stations 7, 8, 9, and 10 another. Station 6 shared similarities with both of these "station groups", and station 1 was different from the others because of the quite different sediments found there. Of the two techniques, that based on relative abundance showed a slightly more gradual pattern, whereas that based on species presence or absence showed more reticulated, less-continuous relationships.

These similarity relationships can also be demonstrated by drawing curves connecting index values between a given station and all others (Whittaker 1967). Figure 8 shows such curves for each sampling period for overlap values between station 4 and all other stations and similarly for station 9. Stations within their respective "station groups" had great overlap with station 4 or 9, while those outside had rather little overlap. Station 6 showed intermediate' overlap with both 4 and 9. These curves also indicate an underlying gradual gradient of faunal composition in the estuary, on which these "station groups" are superimposed. The "station groups" do not really represent zones of homogeneity, but zones of more gradual change.

R-MATRIX ANALYSIS

Pager's recurrent group analysis was performed on the

192 species x 38 station data set, with the arbitrary level of affinity set at 0.5, as suggested by Fager. The analysis yielded

35 groups of which 14 were composed of species occurring only once, but then together. These 14 groups were eliminated from further consideration and the remaining 21 groups, together with those species not grouped but having affinities with group members OVERLAP (Ro 0.2 0.0 0.4 0.0 0.2 0.6 0.8 0.4 0.8 0.6 1.0 1.0 - - - - iue . vra (0) ewe sain 4 A ad (B) 9 and (A) 4 stations between ) (R0 Overlap 8. Figure r d l ohr stations. other arid all 2 3 -38- STATION 4

5 6 o © ® ------..... ——1 ©NOV. eAUG. MAY FEB.

39 are listed in Table 4. The largest recurrent group contained ten species and ten of the groups contained only two species.

Intergroup relationships were computed by the CONNEX program in the REGROUP package. The relationships were expressed as the ratio of the number of intergroup affinities (number of pairs of species from the two groups which had affinities) to the possible number of intergroup combinations. The distribution of the recurrent groups over the stations was determined by the

STATION program. A group was defined as being present at a station if at least 2/3 of its members were found at that station at least once. This meant that for group 1 to be "present", seven of its ten members had to be present and for any of the groups con­ taining two members, both members had to be present.

The distribution of the recurrent groups and intergroup relationships are illustrated in Figure 9. A number of groups were present only at station 1 and consisted mostly of sand- specific species, with a small component of species probably limited to the mouth of the bay by salinity. Mostly sand-preferring species were found in the groups found from station 1 into the lower York River (e.g. groups 18, 7, and 9). Those groups found only at stations 2, 3, 4 and 5 consisted of mud dwelling species limited to polyhaline salinities. A stepwise progression of wide- ranging groups penetrating deeper into the estuary is evident.

Two groups (3 and 16) were very widely distributed and are composed of very euryhaline species. A few groups were limited to the meso- haline and oligohaline zones. Table 4. Recurrent groups of species and species with affinities only

with members of single groups.

RECURRENT GROUP MEMBERS SPECIES HAVING AFFINITIES ONLY WITH MEMBERS OF GROUP

GROUP 1

Amphiodia atra Elasciiojjuj1 laevis Pseudeurythoe paucibranchiata Ca rno me 11 a lac tea Tharyx setigera Listrie11a cylmenellae Phoronis ■I1-'c_hi.tec_ta Unc1ola irrorata Circatulus ,Sf;md_is Exogoile d Lspar Lo j.mia medusa Clymerella torquata Uarmothoe sp. A Pec tin ari a gouIdi_ Cerapus tubul ar is

GROUP 2

Oligochaete B Coryy hi um 1 ecu s tre Maeoma balthica Scoleco 1_-• o i des vir 1 dis Macoma mitchelli I.ep toe he inis p lumosus Wernertean A Gamraarus daiberi M o n o c u 1 o d a s e d w a r d s i

GROUP 3

Heteromastus filiformis Eteone heteropoda Pa rapr iono spio pinnata Glyc inde solitaria Nereis suec inea Leucon americanus Streblospio benedicti

GROUP 4

Pr ion ospio m almg reniTellina agi.lis Pr ionospio malmgreniTellina pro:-: ima Aglaophamus verrilli S I. itenela is Loa Paranthus rapiformis Glyc era dibranchiata 40 Table 4 continued.

RECURRENT GROUP MEMBERS SPECIES HAVING AFFINITIES ONLY WITH MEMBERS OF GROUP

GROUP 5

Retusa canaliculata Peloscolex gabriellae ^ephtys inc isa Sarsiella zostericola Sigambra tentaculata Mulinia lateralis

CROUP 6

Palaeonotus heteroseta Macoma tenta Edward s i.a elegims Diopatra cnprea Ceriantheopsis airiericana Anc istrosyl. 1 is jonesi

GROUP 7

Nephtys magellanica Sn i ophan c s bf'”ibvx Owenia las I for mis

CROUP 8 Melinna maculata Neopanope texana Prioiio.sp i o cirri_fera Tubulanus pe1lucidus

GROUP 9

My sella Mden_t a t a Arnpel isca vadorum Sp i.oc han top I;erus oculatus

GROUP 10

Paraphoxus epistomus Mangelia cerina Magelona rosea

GROUP LI

Chiri do tea almvra Oligochaete C Cyathura po t lea 41 t

Table 4, continued.

RECURRENT GROUP MEMBERS SPECIES HAVING AFFINITIES ONLY WITH MEMBERS OF GROUP

GROUP 12

Pinnixa sayana Batea catharinensis

GROUP 13

Lineus pallidus Neph tys pic ta

CROUP 14

Ogvrides 1imicola Atdelisca abd i. ta

GROUP 15

Yo 1 d i a 1 itnatula Glycera americana Cerithiopsis greeni

;roijp 16

i s amer irana Edo tea triloba

GROUP 17

Corophium acherusicuin Turbonilia interrupta transversa

GROUP 18

Ampelisca verrilli Luc ina multilineata Clymenella zonalis Euceratnus praelongus

GROUP 19

Tendipedidae (unident.) Ilarpacticoida (unident.)

42 Table 4, continued.

RECURRENT GROUP MEMBERS SPECIES HAVING AFFINITIES ONLY WITH MEMBERS OF GROUP

GROUP 20

Nassarius vibex Gyptis vittata

GROUP 21

Spio fitlcornis Mercenaria mercenaria

43 STATION

6 8 10

10 2/6 r iD 13 6 ^ 3/18

M ~ ? 4 c r ~ — J 18

1 /1 2 CZ==)2I 2/6 7/18

3 7 £ - y

1/9 ^ _ j j _ ____ JL__ 1 9 l/,6 m 17 z p a z g : — H a — i™ — I 8 i/si j i I jJL 2 0

g $ I I . 12 X f e i l m 1— |-- ]UiJ 6

0 / 3 0 3 / 2 0 ] S/30 2/30 2/20 |4-— i v—— t-- ua~_J L i V i — r~ 24/40J 1/12J..~ __ 4/121_ □ 5 ~ ' f ---- 1--- 3/8 3/20 4 7/12 15/60 14/24 C —B-- ~y~~ 9/12 □ 16 2/36 C □ 2 3^I8~ C O II

c m is

Figure 9. Distribution of recurrent groups of species in the estuary and the number of intergroup affinities compared with the possible number of such affinities between recurrent groups. Numbers to the right refer to the recurrent groups in Table 4.

-44- 45

The patterns of recurrent group distributions and inter­

group affinities are compatible with those found in the Q-matrix

analyses and also indicate a gradient of overlapping faunal dis­

tributions with groups of recurrent groups distributed over similar

ranges. This is indicative of estuarine segments with some degree

of internal homogeneity.

DIRECT GRADIENT ANALYSES

Species abundance, or some other measure of species im­

portance, can be plotted along an environmental gradient and

employed in a "direct gradient analysis" (Whittaker 1967). Whittaker

proposed that, the distribution of importance (numerical or other­

wise) of a particular species is generally binomial along an

environmental gradient. Also the shape and extent of a species

importance value curve is independent of the distribution of any

other species. Communities as traditionally defined are, therefore,

but segments of distributional continua consisting of species each

having independent binomial distribution patterns.

The median of the quarterly numerical abundance values

(number/0.2m2 ) for those species with significant numerical abun­

dance was plotted against distance up the estuary. Medians were more descriptive of average conditions than means because of the

great temporal population fluctuations exhibited by many species.

The resulting curves were subjectively ordered on the basis of

range of distribution and position of modes and are presented in

Figure 10. The abundance curves, while sometimes erratic and multimodal, did resemble the binomial curves of Whittaker. However

it would be difficult in some cases to separate the effects of L o im io

P arapboxus Sigam bro Aglaophomus

N ucu lo

— Owonio

Tattina

Spfophanes

Ampolisca xadorum

Nephtys mogellanica Harmothoe sp- A.

i * T u rb o n ft/a Ampe/isca ’ abdita

Rotusa M u/inio

100 90 Heteromastus 8 0 P h o ro n is 70 Edotea 6 0 Pataeonotus 50 4 0 30 Macomo tenfa

20 ^ C/ymeneHo torquata 10 0

Nephtys incise

Am phiodia Paraprionospio

Pseudeurythoa

Neomysis

Pefosco/ex gabriellae Otigo 3 A

i I l l l l I I i I I I i I I i i i i i i i i I i I i l i i I i i 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 00 90 fOO DISTANCE FROM MOUTH (km) DISTANCE FROM MOUTH (km )

T7 gure 10. Direct gradient analysis (median abundance distributions) of more abundant benthic taxa in the estuary.

46 Leucon

100- co £ 9 0 - Macoma balthica w 80 — Macoma m itchelli ° 7 0 -

£ 6 0 - Corophium iocustre 3 5 0 - 1 4 0 - Gammarus daiberi 2 3 0 - I 20“ Mcnocuiodas

X i0" 0- N e ' n e r f e a n A

Scolscolepides

Oligochaete C

Cyafhura poiita

Oligochaete 8 Chaoborus

Tandipedidue

I i i i i i i i ( I i I I I I I I I i i I 0 10 20 30 40 50 60 70 80 90 100 DISTANCE FROM MOUTH (km)

Figure 10, continued.

47 48 sediment type and other factors from the implied gradient factor, salinity.

The species abundance curves are independent and show a wide variety of ranges, shapes and modes. There are no groups of species similarly distributed and faithful to one internally homogeneous "community". Rather there are "ecological groups"

(Whittaker 1967) whose distributions are largely overlapping and whose modes are coincident or nearly so. These "ecological groups" show great similarity to the recurrent groups formed by Pager's analysis. For example, Paraphoxus, Aglaophamus, Nucula and Tellina are members of recurrent groups 4 or 10; Owenia, Spiophanes, and

Nephtys magellanica are in recurrent group 7; Clymenella torquata,

Amphiodia, Pseudeurythoe, Tharyx, Loimia, Cirratulus, Pectinaria,

Cerapus and Harmothoe sp. A. are in recurrent group 1; and Macoma balthica, M. mitchelli, Gammarus daiberi, Monoculodes, and Nemertean

A are members of recurrent group 2.

SPECIES DIVERSITY

The patterns of informational diversity (H), species richness (S-1/lnN) and evenness (J) along the estuarine gradient are given for the four sampling periods in Figure 11. Informational diversity was relatively constant throughout the polyhaline zone

(stations 1-5) at about 3.5 bits/indiv. although it usually peaked slightly at station 4. Up-estuary from station 5, H dropped off sharply to about 2 bits/indiv. but peaked again at station 9 in three of the sampling periods. The repetitious overall pattern indicates uniformly high levels of diversity in the middle reaches to erratically declining levels in the upper estuary. 1 Distribution o informational diversity (H), ) H ( y t i s r e v i d l a n o i t a m r o f n i of n o i t u b i r t s i D 11. e r u g i F

INFORMATIONAL DIVERSITY-- H (BITS/1NDSV.) - 4 2 o-J 3- 4- „ 4 3- 2 - - ITNE RM OT O BY (km) BAY OF MOUTH FROM DISTANCE MAY n h estuary. y r a u t s e the in FEB pce rcness (-/n ) n evenness (J) s s e n n e v e and N) (S-l/ln s s e richn species AUG NOV 0 0 0 0 0 100 0 9 0 8 70 60 0 5 0 4 30 20 10 2 v / 4 5 8 10 9 8 7 6 5 4 3 T STATION 'I r --- nr i -3 0 - -5 4 - -6 -8 9 - -7 - -3 4 - -6 -8 -9 -4 -7 -8 -5 f ;

CO Q_ UJ C > O w 7 3' *7 CO tr co o ! 2 j u co co CO — 0 X 10 2 \ a c: J

UJ j u

50

Curves describing the richness and evenness components

show directly the cooperative effect these components have on in­

formational diversity. Species richness is the more important

component relative to the decline in diversity up-estuary as in­

dicated by the more consistent decline in S-1/lnN than in J. An

increase in evenness alone accounted for the rise in H at station

9. Notwithstanding, evenness declined up-estuary and contributed

to the lowering of H.

These relationships were further quantified by the

application of SpearmanTs rank correlation test (Siegel 19 56)

which compared distance from the mouth of the bay with each of

the three measures of diversity. Distance and H and distance

and S-1/lnN were highly negatively correlated (rs = -0.76 and

-0.78, respectively, p < 0.001). The rank correlation between

distance and J was high but considerably less significant (rg =

-0.50, p<0.01).

No distinct seasonal patterns in diversity were apparent.

Tests for concordant seasonality of each of the three measures

over all stations or "station groups" yielded only one signifi­

cant value of W (Kendall’s concordance coefficient, Siegel 19 56),

that for H over stations 1-4. This was due to the coincidence of

high H values in August at these four stations. However there is

little evidence for any seasonal trends in diversity or its com­ ponents due to recruitment periodicity or other phenomena.

Values of the remaining diversity measures calculated are presented in Table 5. Table 5. Diversity measures for each station at each sampling period (1 August; 2 November; 3 3 February; 4 May). Rarefaction index is indicated as spp/100 and equitability by EQUTT . — h ^ t- h l— 4 -4 rH .--4 •si ^4 O 14 O •-■« m u- l X i v UJ o o z CO X __>5_to O- £UUJ o o >: iZ *-4 JJ X I sTT o :0 “r ^r r ^ -r~ r^ -^ r^ 4“ m i m ac o c a o c ^ n r o c r a O < _ u cn a£ <-«cror\ivrrvjf*- O 0'<7'aDm.Tr-«—tm <|-inxcoirLO m(T‘ C7'—<jmr\jinNrr-(Njr-40os O ’-C'(or-mrvj>Osj-f‘- i H H z z D a n ^ ^ ' r H M ( o o r i O > o c ^ ) . j a ^ i CT ^ ' N r\ ^ - » n j O ^ - 4 0 * « J -* - £*inr->0»-4N0rvji-4r-<^'<-4inr0v0r~mr^N0 m - r o j \ r _i . mrnrgcgrgmrnrgrgmrj -gfn f g .- g r g jf r m g r g r n r m g r g c g r n r jm n g c j o Q. 4 - 1 o * P- A N :1 A b' h »0 n s" i in - F sj" in »'0 ih b"' lA :<1 N iA ^ O P*- - b o h* Z> I n in • . -) H ^ r* -4 * r ^ J.JH l-C) « I N j q vf q- j N IQ >

o o o o o o o o o o o o o o o o o o o o o o o ••••••«»»•»■••«••• o o o o o o o o o o o o o o o -> 1

o o o o o o \vOO'hO'oncoNHiA^DcO'na' a n ' O c D ^ A i H N o c n o ' O h ' O O i\ v N H m ^ o c h i O ) X ' N T ' ■f rg (N) ^ l\ ^ l^ m f -f ff'^'rO'irir'vOiC^vfNCOOm'O'JffiOIrOfftO^H^ONO^rj'JDWO^'r-f'J-CTH 0 0 0 0 0 0 0 0 r n "O ^ f' \ ;A (j \ .g i\ rj \ i ^ h M ( r\j \ i g . r\j 4 ^ (\j A ; f\j o r ^ n r f*' ^ O " n rr. m n f \ rn on g* ro rn ro eg g- rg «- j in r< - cr in 0 i 0 r c 0 r-- o 0 r 0 - r 0 g r 0 j o 0 r~< 0 n i 0 .j- o 0 c 0 n i 0 0 o r 0 - 0 T s 0 n i 0 o r 0 n i 0 ~ r 0 «g- r s 0 n g i r n i 0 - m g o c 0 g o c e - 0 r j o a r 0 n r 0 o 0 r 0 * g 0 n o 0 n r 0 <\j 0 o r 0 n r 0 n r 0 g p 0 g 0 r n r n r g e o n j o a - r ^ - s f o s } ' — 4 C T ‘ r * r o » - 4 0 ' ' . o c o o i n - j - » , O f O f ^ o G ' , ' i n r > - r ‘ - m > 3 ' 0 ' h - ' v o o ' * 4 ' r f c m r s j > } ' •••••• •••««>> •••#•••• *- ^-4 h r i *' so r*'' in rg o ? o n m r m in ^ co a? co m m -4 n rg p j ru M m g g- g- g- g- g m M ru j p rg n

- o >o >o o O O ‘J ‘'J O O O g r i r x ncor- g r g r T s m r -c r o c in OD h « i ) N O I s * > • - g - g o < o r o r - g 1 0 o r j t N o•j- o tA N 0 0 0 0 0 0 > in n i r>j 0 > h • .j j \ r i .-o in rg ij- (\j ^ .nj f*>lT, f*>lT, «•«••••

h 0 0 0 0 0 0 0 0 0 g r 0 r g m in D g o r m ^ n i g o X O N O ' N S ^ N O v O C • «•••••••• .r n j g - r 0 T, n T T 4 \ r ^ H ^ h h r i\ i rH h h ^ H ^ rO f\j -4 N sT N vT in ^ IT', (\ j } g ^ n i pj -4 6\ rsi r \j ^ co O' O' co ^ \j r --4 o o g o r o g ro sr ro eg rr- h

j —1 n i m r s 1 — g >j- r r < - r if' - r « ff' -» (\) fO W f f«W Is- O sO Avff'JOfflm 1/M gj c- g j j g c- gj O O o C O O O O a i — 4 - - O 'T O -T --i 4 *—* 4 wA i/\ x . c gj o o gj c . x i/\ o - sf O' in i ' O f s 1-4 o ' O rO * — cm c - c* m m o * c r-* ec r - t r o > 4 " a o co co

0 0 0 0 0 0 o 0 n i 0 m O 0 s n 0 i n i D g m m - r ' o \ f i i < ( O t « ? a ® n ' O j x ( o c ''O a , < N N ' o m o > N ' O N l ' O O N » r n i M < M l O » n , gj ',n *n r» C s J H H H ^4 r—4 rH f—4 ^ H r—4 H ^4 r—4 H rH f—4 H ^ H CsJ 4 ^ • ••••••••• -t i/\ rg i/\ -t h O g i h o r C ' v C ® C (vj N 'O C rO ro oh in rg f - m ^ t rO -.0 * f- r- : -' x x -i' :o - r - f f*~

n n r ^ ri u i r ^ o n i r ' O X o c A o i r r g i r x j • g x b. o T n «f « :n * b n i vT >o n i . lb g .-i r g r g r COCO^OfOOCT'CD 0 0 0 0 0 0 0 0

> rin - o o < O ' c s O n cr>

0 0 0 0 0 0 0 0 0 0 ' rg cn « to t < «— - p n c *-< g o r c O'- - r g r - r o - c r m x u*'* -.r - p r c • •••«••»•* 4 . . 4 - » rj - (N « O ^ O « N ( •-* r\j f»^ m 0 -*i -*i o o U > m o o o m >r U' o o j u srxmmr-mom i n r o r g t r »-< r o r g m g r o m r rr »-< m r t g r ( o r - N C n i J J i h ' C ^ ( 1 o -g- *n r- o o o *-« o r- o r— o x o com o o o O C O o o o s —4 g m —4 -o m rg -t —* r — - o eg o 1-1 r o>-»o rg h g I- n m in Is- rg r-t rg

52

DOMINANCE AND DOMINANTS

A measure of species dominance, the sum of the proportion

of the total number of individuals at a station attributable to

the two most abundant species (i.e. p^ + pg), was calculated

(McNaughton 1967, McNaughton and Wolf 1970). This measure has been

criticized by Austin (1968), but the application of Austin's sug­

gested transformation changed the results little, so this simpler

index was used.

The distribution of dominance values along the estuarine

gradient (Fig. 12) was the inverse of that of diversity. There

was a consistent low level in the lower estuary, a precipitous rise between stations 5 and 6 and a slight dip at station 9.

Particularly, dominance is highly correlated with the evenness

component, largely because the abundance of the two most abundant

species affects evenness.

Species were ranked by their abundance within each replicate grab sample and the top five species were assigned rank

scores, 5 for the most abundant species, 4 for the next, etc.

These scores were summed for each species over the three repli­ cates and four sampling periods (two for station 5) at each station

(12 or 6 total replicate samples). The seven species which achieved the highest scores at each station were termed dominants and are listed in Table 6 with their mean scores and relative frequencies.

At many stations there was a sharp break in the mean scores between the seventh and eighth ranked species.

The mean score and frequency values indicate the constancy and strength of dominance. Thus, Paraprionospio at station 6, DOMINANCE (P .+ Pg0.7- J 0.9- 0.3 0 0 0 0.5- 0.4 H I.O- 0.1 . . . 6 8 2

- - -

iue 2 Rne ad ein o te oiac idx at index dominance the of medians and Ranges 12. Figure

ah station. each 3 -53- STATION 4 5 ~ T 6 nr 7 9 8

“1 10 Table 6. Rank score dominants at each station with mean scores (5-point

system) and relative frequencies in replicates.

STATION 1 STATION 2

Species Mean Score f Species Mean Score f

Retusa 3.08 1.00 Nephtys incisa 2.88 1.00 Paraphoxus 2.88 0.75 Retusa 2.67 1.00 Spiophanes 1.54 0.83 Heteromastus 1.96 1.00 Mytilus 1.25 0.25 Pseudeury thoe 1.88 0.83 Ampelisca verrilli 0.96 0.25 Phoronis 1.57 1.00 Turbonilla 0.88 0.83 Amoelisca vadorum 1.25 0.50 Tellina 0.79 0.75 Clymenella zonalis 0.83 0.33

STATION 3 STATION 4

Spec ies Mean Score f Species Mean Score f

: 11_- LC L U'lld a LU o 2.75 1.00 Tharyx 3.83 1 .00 Retusa 2.25 1.0'J Peeudeurythoe 2.1/ 0.92 Phoronis 1.63 0.50 Cirratulus 1.92 1.00 Nephtys incisa 1.25- 0.75 Amphiodia 1.63 1.00 Paraprionospio 1.25 0.92 Heteromastus 1.00 0.92 S trtblospio 1.25 0.92 Nephtys incisa 0.96 1.00 Pseudeurvthoe 1.21 0.67 Hannothoe sp. A 0.67 0.92

STATION 5 STATION 6

Spec ies Mean Score f Species Mean Score f

Paraprionospio 3.75 1.00 Paraprionospio 4.75 1.00 Harmothoe sp. A 3.58 1.00 Pseudeurythoe 2.92 1.00 Tharyx 2.21 1.00 Leucon 2.00 0.75 Amphiodia 2.17 1.00 Glycinde 1.08 0.67 Photonis 1.04 0.50 Macoma balthica 1.00 0.42 Ogyrides 1.00 0.83 Ogyrides 0.83 0.67 Heteromastus 0.50 0.83 Heteromastus 0.63 0.92

5^ Table 6, continued.

STATION 7 STATION 8

Spec ies Mean Score f Species Mean Score f

Leucon 4.25 1.00 Hacoma balthica 3.75 1.00 Macoma balthica 3.50 0.83 Oligochaete B 2.54 0.83 Paraprionospro 2.46 1.00 Leucon 2.46 0.92 Oligochaete B 0.96 0.83 Nemertean A 1.71 0.92 Streblospio 0.89 0.83 Streblospio 1.13 0.42 Nereis 0.83 0.57 Parapr ionospio 0.92 0.50 Corophium lacustre 0.54 0.50 Neotnysis 0.71 0.75

STATION 9 STATION 10

Species Mean Score f Species Mean Score f

Macoma balthica 2.92 1.00 Oligochaete B 4.38 1.00 Seolecolepides 2.71 0.83 Oammarus daiheci 2.1.7 0.50 Oligochaete B 2.00 0. S3 Nemertean A 1.17 0.58 Oligochaete C 1.63 0.50 Neomysis 1.50 0.58 Gam?.arus daiberi 1.17 0.67 See 1ecolepi des 1.04 0.42 Nemertean A 1.05 1.00 Corophium Lacustre 0.67 0.25 Hucuuici mj-leiiclli. 0.75 VM • UCl / » lo fr O C It 1 wli t- 3 0.53 0 25

55 56

Leucon at station 7, and oligochaete B at station 10 were consis­ tently strong dominants, while Mytilus at station 1 and Phoronis at

station 3 were infrequent but strong dominants, and Nephtys incisa at station 4 and Nemertean A at stations 8 and 9 were frequent, but weak, dominants.

These patterns of dominance did not necessarily prevail from season to season or even from replicate to replicate. Instead, in each replicate at least the top two or three ranked species are among those included in Table 6 for that station and there was considerable variability in rank position among the dominants within replicates. A concordance test of the ranks of the seven dominants over the four seasons for each station yielded no sig­ nificant values of the concordance coefficient, W. There was no evidence for maintenance of strict dominance hierarchy among the dominant species.

Examination of the dominants shared by stations shows a gradual pattern of faunal change similar to both Q- and R-matrix analyses. Station 1 shared only one dominant, Retusa, with any other station. Stations 2 and 3 shared five dominants, Nephtys incisa, Retusa, Heteromastus, Pseudeurythoe and Phoronis. Of these, three were dominants at station 4 and two at station 5. The latter two stations shared three additional dominants. Stations 5 and 6 shared the highest ranked species and two lesser dominants.

Paraprionospio, Macoma balthica, and Leucon were dominants at stations 6, 7, and 8, and stations 7 and 8 shared two additional dominants.. Oligochaete B, Macoma balthica, Nemertean A, and Gammarus daiberi (members of recurrent group 3) were among the dominants of 57

at least two of the four most up-estuary stations. The distribution

of dominants again indicates a gradual compositional gradient with

a segment of more rapid change, in the polyhaline-mesohaline border

z o n e .

SPECIES-IMPORTANCE DISTRIBUTIONS

A number of hypothetical models have been suggested which

describe how the resources of an environment are divided among the

constituent species. A species’ portion of the environment can be

described by some measure of its ”importance”, such as numbers,

biomass, or productivity (Whittaker 1969, 1970). Three of these

models are:

1) the random niche boundary hypothesis of MacArthur

(1957, 1960), also known as the ”broken-stick model”, in which the

importance values of species are distributed according to the series

r = E -fe 1 -4? s 1 s-i+1 ’

where Ir is the importance value of species r and i is the number

of the species in the sequence of species -- from least important

(i=l), through the species in question (i=r), to the most important

species (i=s);

2) the niche pre-emption hypothesis, in which the im­ portance values of species will form geometric series (Montomura

1932), with terms of

In = Nk(l-k)n-1 = Acn-1, k = 1-c, where n is the number of species in the sequence from the most to the least important, c is the ratio of the importance value of a 58 given species to that of its predecessor in the sequence, and A is the importance value of the most important species;

3) the lognormal distribution (Preston 1948), which predicts that the base 2 logarithms of importance values are nor­ mally distributed. The frequency distribution of species importance values is predicted by

S = S e~ ^ r o >

in which Sr is the number of species in an octave (log2 interval)

R octaves distant from the modal octave, which contains SQ species, and 3. is a constant which often approximates 0.2.

Analysis of the 38 sample set showed that in almost every instance, the percent importance octave containing the largest number of species was that including the smallest importance value sampled (i.e. one individual). The samples taken were too small to produce all of those species in the modal octave of a lognormal distribution. Attempts at artificially enlarging the samples by combining quarterly samples for each station or combining adjacent stations as Lie (1969) did yielded distributions more confusing than that of the component samples. Plotting the frequency of importance values by octaves for individual samples gave distributions roughly similar to the right tail of normal curves (Fig. 13) with a "veil line" (that line truncating the curve indicating the lower limit of importance values sampled) to the right of the modes of fitted curves. Therefore the goodness-of-fit of the observed distribution to the lognormal was not directly testable. CM ro

o o/o c

co if) UJ > f? o o

h-

UJ o PC IU a.

UJ CL

h- rr.: o 10 a. CM

Lei in > CM p O < UJ in a: CM size. (4 (4 sampling periods) Veil line and a indicates fitted truncation lognormal curve of the (a distribution = 0.2, S G = 16). due to small sample in CM fO Q o m CM

in Figure 13. Distribution of relative importance (percent) by octaves at station 4 in m CM 3 A V 1 0 0 U36 S3103dS 30 y3QWflN

-59- 60

Whittaker (1965, 1969, 1970) used "dominance diversity curves" as another method of demonstrating the distribution of im­ portance values. The importance values of a species sequence arranged from most to least important are plotted on a logarithmi­ cally scaled ordinate of relative species importance. Curves describing distributions predicted by the random niche boundary, niche pre-emption, and lognormal hypotheses may also be plotted and directly compared with observed patterns.

Dominance-diversity plots were compiled for the quarterly samples at each station. As an example, the dominance diversity plots for station 4 are given in Fig. 14 with curves predicted by each of the three hypotheses. The curve best fitting the points was a lognormal distribution (SD = 16, a = 0.2), the same distri­ bution conventionally presented in Fig. 13. The random niche boundary model overestimated the importance of "middle range" species and underestimated the importance of dominant species.

The geometric series predicted far too few species of low impor­ tance, but fit well for the first ten species in the sequence.

Almost without exception, data points for the four sam­ pling periods for each station were contained in a narrow envelope.

The means of the four quarterly importance values for each se­ quential species at a station were replotted as scatterpoints on an all-station plot. These mean importance value distributions fell in two envelopes, one containing points from stations 1-5

(Fig. 15), the other containing points from stations 6-10 (Fig. 16).

The lognormal distribution (SG = 16, a = 0.2) fit the points for stations 1-5 very well. The points for stations 6-10 approached iue 4 Dmnne iest po o pret relative percent of plot diversity Dominance 14. Figure RELATIVE IMPORTANCE PER CENT - 0 0 1 - 0 5 0 yohss A, onra () ad niche-pre-emption and distributions. (C) (B), lognormal hypothesis (A), hypothesis tto 4 Cre dsrb rno ih boundary niche random describe Curves 4. station motne o h fu smln pros at periods sampling four the for importance 10 PCE SEQUENCE C N E U Q E S SPECIES 20 -61- Me\ STATION 30 ©esfc'M©©&« \ O O O o o b O O O O O O O O O O - FEB - o - A - A G U ” A © MAY NOV 40

* » © ©as & ® e e » » ©o ®» 50

60

RELATIVE IMPORTANCE PER CENT i - O O l 0.5 50 iue 5 Dmnne iest pos f ecn relative percent of plots diversity Dominance 15. Figure 10 0 k® & ecie a onra itiuin a 0.2 = (a distribution lognormal a describes = 16). = 0 S eunil pce) o sain 15 Curve 1-5. stations for species) sequential motne mda o saoa aus for values seasonal of (median importance PCE SEQUENCE SPECIES 20 -62- STATIONS ©•yc«, ®e t f ^ O o e t a etc • e G> c fr® @ ^ d 9 © © © 0 ft © O 9 ft © 9 0 © & © d 0 ^ G> @ e • fr® c 4030 eo©o» \ 50 cce«s©£^©®e 60

}

1 0 0 —

50

h- 2T LU O c c LiJ 0 - CL

LjJ O 2: b C Or: o 0.

UJ > b-

£ 0 30 40

SPECiES SEQUENCE

Figure 16. Dominance diversity plots for stations 6-10 (as in Fig. 15). Curves describe a geometric series (A) and a lognormal distribution (a = 0.2, SQ = 5).

-63- 64 a geometric series but there were more species with relative im­ portance values of 0.1 to 1 percent than predicted. A better fit was achieved by a low amplitude lognormal distribution (SQ = 5, a = 0.2). DISCUSSION

FAUNAL DISTRIBUTION

Analysis of the distributions of 360 species of macro­

benthos (Appendix) showed a small reduction in total taxa from the

mouth of the estuary throughout the polyhaline reaches (Fig. 6A).

Successive sharp reductions in numbers of taxa occurred in the

mesohaline and oligohaline zones. This pattern is similar to that

commonly observed for European estuarine organisms (Remane 1934,

Alexander et al. 1935). However, there was no increase in numbers

of taxa at the most up-estuary station from an increased represen­

tation of freshwater taxa as is characteristic of comparable

salinity regimes in some European estuaries (Remane 19 58). Only

three strictly freshwater benthic taxa are found with any consis­

tency in the lower 30 km of the Pamunkey River: Gammarus fasciatus,

tendipedid larvae, and larvae of Chaoborus sp. The oligohaline-

freshwater transition zone is exceptionally long and salinities

of 5 % 0 have occurred as far as 140 km from the mouth of the bay --

36 km above station 10. Most species of the completely freshwater portions of the Pamunkey River do not extend down into this long

segment of salinity instability. Farther up the Pamunkey River,

beyond the influence of oceanic salinity but where there is still

some tidal influence, a large benthic fauna exists, including a

full complement of larval insect taxa, sphaeriid and unionid clams, crayfishes, etc.

65 66

A number of classificatory schemes have been proposed to

describe major estuarine distributional patterns and have been

summarized by Hedgpeth (1957). Day's (1951, 1964) classification

has been most widely used: 1) stenohaline marine, 2) euryhaline

marine, 3) estuarine, 4) freshwater, and 5) migratory components

of the estuarine fauna. The stenohaline component includes those

species generally not penetrating the estuary below ca. 30 % > , and

the euryhaline marine species are those occurring in the ocean,

but which penetrate the estuary to a greater extent. The estuarine

component consists of the "true estuarine" (Carriker 1967) or

estuarine endemic species which live in estuaries but not in the

sea or freshwater, whereas the freshwater component includes those

freshwater species capable of tolerating varying degrees of salinity.

Remane (19 58) divided the euryhaline marine and fresh­ water components into sub-groups or "grades" by the degree to which the organism could penetrate fresher or more saline waters, respectively. On the basis of my data, there is justification for the subdivision of the euryhaline marine component, because it en­ compasses a wide variety of distributional types, from species restricted to the mouth of an estuary to those which cover the entire range of estuarine conditions. Remane distinguished four

"grades" of euryhalinity -- those species penetrating to ± 5 % 0, 8&,

1 % o , and below 3 % > . To make the boundaries of the grades consis­ tent with the Venice System, I have distinguished three grades: organisms penetrating into polyhaline ( > 1 Q % 0), mesohaline (>5$o), and oligohaline (<5$°) waters. These grades correspond to the central three classes in Fig. 6B. 67

The euryhaline marine species constitute by far the

largest component of the benthic fauna of the Chesapeake-York

estuary. Most of these species are "grade 1" species and do not

extend more than 60 km up-estuary (salinity ca. 18&). Grades 2

and 3 euryhaline marine components contain progressively fewer

species. Most species found only in the lower Chesapeake Bay are

stenohaline or weakly euryhaline marine forms. Distinction between

the stenohaline and euryhaline marine components or among eury­

haline marine "grades" is arbitrary, because there is a continuum

of individual species distribution types.

Species largely confined to the meso- and oligohaline

zones are mostly "true estuarine" species. Only three freshwater

taxa are included. The true estuarine component is small, approxi­

mately 20 species, butmany of these species are widespread and

abundant in the meso- and oligohaline zones.

Members of the migratory component of the estuarine

fauna are generally large and very motile organisms such as fishes

and portunid . However, Feeley (1967) has shown that many

amphipods are capable of migration up and down the York estuary in

response to seasonal salinity and/or temperature fluctuations, and

other semipelagic species as Neomysis and Leucon, are also probably

capable of longitudinal movement in the estuary.

Although the pattern of species distributions is one of a continuum of overlapping ranges, it is not without some discon­ tinuities. An especially prominent feature is the great change in

species composition between 50 and 60 km from the mouth of the

bay. Many euryhaline species, including most of those classed as 68

,Tgrade-l euryhaline”, have their upper distributional limits in this segment, and most of the true estuarine species have their lower limits in this segment. Thus, the border zone between polyhaline and mesohaline regimes is a prominent faunal discon­ tinuity in the estuary.

The distribution of the recurrent groups of species, as determined by FagerTs analysis, shows a similar pattern to that just discussed. There were a large number of recurrent groups of grade-1 euryhaline species (groups 9, 17, 8, 20, 12, 6 and 1), a few groups of grades 2 and 3 euryhaline marine species (groups 5,

14, 3, and 16), two groups of true estuarine species (groups 2 and

11) and a group of freshwater species (group 19). This analysis shows a rather sharp faunal discontinuity between stations 1 and 2, but this is predominantly attributable to substrate differences.

The sandier substrates at stations 1, 2, and 3 accounted for some of the recurrent groups found there. Tellina, Glycera dibranchiata,

Sthenelais, Spio, Mercenaria, Nephtys magellanica and Spiophanes are more euryhaline than the position of their respective recurrent groups indicates but are generally psammophyllic (Boesch 1971,

Wass 1965). Nucula, , Owenia, Paranthus and Mangelia cerina, on the other hand, are relatively stenohaline (Wass 196 5).

Temperature is an additional factor limiting the distri­ bution of animals in the estuary. Chesapeake Bay is approximately the southern terminus of the Virginian faunal province and many boreal species have their geographic southern limits in the Virginia

Capes - Cape Hatteras area. Most of these species cannot tolerate the warm summer temperatures of the Chesapeake estuary and conse­ 69

quently are only found on the continental shelf or at the mouth of

the bay. An example is Mytilus edulis which penetrates estuaries

extensively in more northern climates (Remane 1958) but has year-

round populations here only at the Bay Bridge-Tunnel at the mouth

of Chesapeake Bay. Numerous small individuals were present at

stations 1, 2, and 3 in May and Wass (personal communication) found

large numbers at Gloucester Point, near station 4, in June 1962,

but their populations had been decimated one month later, presumably

because of rising temperatures.

From the data generated by this study it is impossible

to describe either seaward limits or abundance for that large group

of species common in both the lcwer bay and lower York River.

There is an absence of comparable "muddyTt substrates at the mouth

of the bay and on the adjacent continental shelf. Surely most,

if not all, of the euryhaline marine species have been found at

one time or another in oceanic conditions. My investigations have

shown that some muddy-sand substrates on the continental shelf off

Virginia have a large number of species in common with the soft- bottom in the lower York estuary. However, there are some important members of the York .stuary fauna (e.g. Amphiodia, Pseudeurythoe,

Cirratulus, Loimia, Nereis, Nephtys incisa and Mulinia) which are absent or rarely found offshore. These ,rpredominently estuarine" species include some important members of the high salinity estuarine fauna and they may be tied to the estuarine environment for their existence. Viable reproducing populations of these species are maintained in the Chesapeake estuary and do not depend 70 primarily on reinforcement from the sea for repopulation as suggested by Carriker (1967).

THE TRUE ESTUARINE COMPONENT

The true estuarine species are few in number (ca. 22 taxa) but are numerically important in the meso- and oligohaline zones of the Chesapeake Bay estuarine system. A list of these estuarine endemics from the Chesapeake Bay estuary is presented in Table 7. The estuarine endemic fauna of the York estuary is similar to that of other meso-oligohaline Chesapeake estuaries

(Pfitzenmeyer 1970, T. Cain and R. Peddicord, personal communi­ cation) except that the abundant clam Rangia cuneata is absent in the York.

Many estuarine species are widely distributed globally

(Hedgpeth 19 57); others have taxonomic and ecological equivalents in separate areas of the world. Common true estuarine species of the York estuary are listed in Table 8 with their equivalents (if any) in Western European and central Californian estuaries. The parallels between the Chesapeake estuarine fauna and that of

European estuaries are particularly striking and indicate a his­ torically close ancestry of the two faunas. Hedgpeth (19 57) suggested that climatic cooling drove the common parent species down both sides of the Atlantic and effectively isolated western and eastern populations. Subsequently, speciation has occurred.

Estuarine endemics seem to be primitive forms and, except in certain instances such as the Gammarus species-complex, seem to be evolving very slowly. Hedgpeth (1966) suggested that the fluctuating estuarine environment acts as a braking mechanism Table 7. The "estuarine endemic" macrobenthos of Chesapeake Bay.

RHYNCOCOELA ART1IR0P0DA - Crustacea

Nemertean A Cumaeea

Leucon americanus ANNELIDA Polychaeta Cyathura polita Scolecolepides vir id is Ch ir idotea almyra Hypaniola gray! Cassidinidea lunifrons T.aeonereis culveri 01igochaeta Gammarus daiberi Peloscolex heterochaetus (oligochaete B) Gatnmarus palus tris

Oligochaete C Gammarus ti.grinus (Peloscolex nr. gabriellae) Melita nitida

MOLLUSCA Leptocheirns plumosus

Gas tropoda Corophium lacus tre

Hydrobiae (few species ?) Corophium 1 1 . sp, (a pri.mative species being described from Georgia and Virginia)

Congeria leucophaeta

Rangia cuneata Rhithropanopeus harrisi

Macoma balthica

Macoma mitchelli

71 Table 8. Taxonomic parallels of common estuarine endemic species of Chesapeake Bay in European estuaries (Remane 1958, Muus 1967) and San Francisco Bay area (Hazel and Kelley 1966, Painter 1966).

CHESAPEAKE KAY EUROPE SAN FRANCISCO BAY

Nemertean A Prostomatell a obscura ?

Pelosco1 ex heterochactus Peloseo1ex hetcrochartus '01igochaeta' Oligochaete C (Peioscolex) £• benedeni

Hypaniola grayi Hypania i.nval Ida

Scolecolepides vir idis

Kydrobiae Hydrobi_a ’ylyyae comp 1 ex

Macoma balthlca Macoma bat thica Macoma ineonsp icua Macoma mi tche11i

Leucon amcricanus

Cyathura polita Cyathura carinata

Chlridotea almvra Mesidotea cntomon Svnidotea laticauda

Gammarus daiberi Gammarus duebevii G . t i gr inus G . zaddachi G . pal us tris G , salinus

Leptocheirus g1urnosus Leptocheirus pilosus

Me 1 i ta r> i t ida Melita plamata

Corophi uni n. sp. Corophium volutator Coroph ium spinicerne

C. lacustre C. lacustre £ • stimpsoni

» 72 73

to speciation and thus, in some manner, estuaries serve as a genetic trap. Although individual estuaries may be geologically transitory, the estuarine environment as such has had a long unin­ terrupted history. It is generally held that the invasion and

colonization of freshwater by marine taxa ancestral to present day freshwater forms has occurred via estuaries. However, except in a few cases (e.g. Gammarus and palaemonid and atyid shrimps), this does not seem to be happening now and estuaries hardly seem to be cradles of evolution in our time (Hedgpeth 1966).

Many true estuarine species (e.g. Macoma balthica and

M. mitchelli, Gammarus palustris, Cyathura polita, Melita nitida, and Corophium lacustre) have close relatives in the higher salinity environments of the estuary, and it is obvious that true estuarine species have evolved from euryhaline marine stock. Ecological specialization of estuarine endemic species has developed through continued selection in the direction of physiological generali­ zation (McNaughton and Wolf 1970) in order to take advantage of the unexploited resources of the species-poor environment in low salinity. The species have become ecologically specialized to the point where they are no longer able to live under polyhaline or euryhaline conditions either for physiological reasons or by biotic exclusion. Although competition, predation, and parasitism are usually cited as the factors limiting the down-estuary range of estuarine endemics (Carriker 1967), the quite complete nature of this exclusion suggests that biotic factors are not the only, or necessarily the most important ones determining the distribution of these species. 74

COMMUNITY CONTINUITY

The results of the Q-matrix analyses, direct gradient

analysis, recurrent group analysis, and the analysis of dominants

all indicate that the faunal change along the estuarine gradient

is of a gradual and generally continuous nature. Disregarding the

T,aberrant" faunal assemblage at station 1, which is primarily

attributable to grossly different sediment type, only one discon­

tinuity in the gradual faunal change is apparent. That is at the

border of the polyhaline and mesohaline zones (between stations 5

and 6). There, the fauna does not become entirely disjunct but

changes more rapidly than in other sections of the estuarine

g radient.

A number of divergent views about the nature of com­ munities have developed, especially in plant ecology. The Uppsala

school and other European ecologists described communities as con­

crete quantifiable units based on dominants. The Zurich-Montpellier

school of southern Europe regarded communities as largely abstract

and based on mosaics of vegetation (Whittaker 1962, Mills 1969).

Early twentieth century American ecologists, influenced mainly by the northern school, expanded the idea of concrete communities, added some information on succession and ecosystem function, and developed the idea of communities as functional, evolving analogs of organisms -- "superorganisms" (Clements and Shelford 1939,

Allee et al. 1949). A third school of plant ecologists have de­ veloped the "principle of species individuality", which holds that communities are not real ecological units but, rather, are abstrac­ tions of continua of independent distributions of individual species (Whittaker 1962, 1970, McIntosh 1967).

Most students of marine benthic communities have until recently used a "dominance approach" to the describtion of com­ munities by classifying them by their "characterizing species"

(Thorson 1957). Others have classified communities on the basis of predominant environmental characteristics, such as temperature, substrate, and salinity (N. S. Jones 1950, Peres and Picard 19 58,

1964). These two approaches have been frequently referred to as biocoenosis and biotope classifications, respectively (Longhurst

1964).

Recently, investigators of marine benthos have found that the distribution patterns demonstrated by objective statis­ tical techniques lend evidence supporting the continuum concept of independent species distributions (G. Jones 1969, Mills 1969,

Barnard 1970, Stephenson et al. 1970, Johnson 1970). Many investi­ gators have found that the actual patterns are not described by either extremes of a continuum without discontinuities or a con­ crete recurring species association, or biocoenosis. Rather, some intermediate explanation is most plausible. Although discrete biocoenoses have not been found, patterns of distributional associations of species do exist. Whittaker (1967) explained that such "ecological groups" or "commodia" exist because species often have similar binomial population distributions and coinciding im­ portance value modes along environmental gradients. He believed that this is most often in response to abiotic environmental factors. Biotic interactions limiting the distributions of marine benthos have been documented (Thorson 1966, Ziegelmeier 1970), and 76 distributions of species importance along abiotic environmental

gradients should not be considered to be completely independent.

The distribution of species abundances along an estuarine gradient (a complex gradient in which the predominant factor is

salinity), as shown by direct gradient analysis (Fig. 10), indi­

cates that a generally continuous ’'compositional gradient" exists.

Abundance distribution curves approach the binomial shapes pre­ dicted by Whittaker much more closely than those for California continental shelf benthos along a depth gradient (G. Jones 1969).

The curves are relatively independent although considerable range overlap and modal coincidence exist for "ecological groups" of species which correspond well with the recurrent groups formed by

Pager’s analysis.

Terborgh (1971) has proposed tests of three models of species distributions along environmental gradients. Measures of

"faunal congruity" or assemblage similarity between all possible pairs of stations are differently distributed depending on the distributions of the component species (Fig. 17). Model I is that the distributional limits of species on a gradient are determined by factors in the abiotic or biotic environment that vary continu­ ously and in parallel with the gradient. Model II predicts that the distributional limits of species are determined by competitive exclusion. Model III is that distributional limits are determined by habitat discontinuities (ecotones). Further discussion of the causes and consequences of such multi-species distributional patterns can be found in Whittaker (19 70, p. 35-37). iue 7 Hpteia itiuin o seis abundance species of distributions Hypothetical 17. Figure ABUNDANCE ABUNDANCE ABUNDANCE A GRADIENT GRADIENT RDET > — GRADIENT RDET » GRADIENT distribution (see text, after Terborgh 1971). Terborgh after text, (see distribution n fua cnriy smlrt bten sample between (similarity congruity faunal and ar) codn otre oes f gradient of models three to according pairs) •> — H L E D O M H L E D O M I L E D O M >- 2 CD (T u. > u O < : U. 3 2 < 2 < -j <3 3 d GRADIENT — « RDI T—> GRAD — IE NT RDET > — GRADIENT > 1 1 ( 1 ECOTONE! — — . . y * --- ^ •

T ! 78

Means of the four seasonal values of Kendall's index of affinity (TQ ) between each station and all other stations were used as measures of faunal congruity and plotted as were Terborgh's

"faunal congruity" measures (Fig. 18). Peaks of the congruity curves, i.e. values corresponding to the average similarity between samples at one location, were assigned so as to make the curves less acute. These intra-station congruity values were set at three different levels: 0.6 at stations 1-5, 0.7 at station 6, and 0.8 at stations 7-10. These graduated levels reflect the inverse re­ lationship between species richness and expected levels of intra­ station similarity of samples. It appears that the shape and form of these congruity curves can be explained by either models I or II.

There is some evidence for competitive exclusion in estuaries among congeneric copepods (Jeffries 1967) and amphipods

(Kinne 1954). Competitive exclusion is suggested in some cases of partitioning of the York estuarine gradient by congeners, for example, Macoma tenta--M. mitchelli and M. balthica; Cyathura burbancki--C. politaj Melita appendiculata--M. nitida; and Pelo- scolex gabriellae--P. heterochaetus. However, no one has rigorously investigated this phenomenon in estuaries and the subdivision of estuaries by congeners offers only circumstantial evidence of com­ petitive exclusion. Although it is probable that exclusion plays at least a small role in observed distribution patterns, composites of species abundance curves (Fig. 10) indicate that Terborgh's

Model I predicts distributions which best fit these data and that species distributional patterns are primarily in response to en­ vironmental factors that vary continuously with the gradient. CO H m CD o > CD X H CD \ / TJ X) G cd •H ■p C § CD •H X CO o CO a,p TJ P CD CD CO P o •p CO ■H G O OH EH ■P Hi H • O G P O P •H CD ■P •P rtS c ■P CO iO CD ,G -p o cD CTS O CD •H P G O •H CO >, co CO *H P P H tn P C O TP o CD o >>,g 4J cn G •H cD O p n •H p ■P tn CO C ■P O >, co O 4-> m •H p OJ T—| cD P? •pG G tp *ri ij o m fc o o

00 H 0) P P to •H

(O tO OJ

0 -79- 80

Congruity curves in Fig. 18 have patterns which indicate discontinuities similar to those for TerborghTs bird species at vegetational ecotones along a montane gradient. Up-estuary tails of congruity curves for stations 2-5 are greatly broadened from that for station 1. Likewise, the up-estuary tail of station 6 is broadened from that of station 5, and curves for stations 7-10 are even more broadened. In the opposite direction, down-estuary tails of congruity curves for stations 2-6 are broadened from those of stations 7-10. These curves indicate internal similarity of stations

2-5 and 7-10 with a discontinuity -- an ecotone, of sorts -- in the vicinity of station 6, which has considerable similarity with both down-estuary and up-estuary station groups.

The distribution of macrobenthos along the estuarine gradient has characteristics of all three of Terborgh’s models, but the predominant response is apparently to a continuous gradient

(Model I). This is parallel to Terborgh's findings for montane birds .

Estuarine communities have been called ecotonal by

Burbanck et al. (19 56) and Carriker (1967) in the sense that estuaries are border zones between freshwater and marine environ­ ments, much as the more familiar vegetational ecotones are on land.

However, when applied to such long gradients as the York estuary, the concept of the ecotone is misleading and an oversimplification.

Many estuarine compositional gradients develop unique characteris­ tics not like those of the systems on either end of the continuum.

In addition, application of the ecotone concept incorrectly pre­ supposes the existence of communities as discrete recurrent units. 81

It is more consistent and instructive to use Whittaker's (19 70) terminology and refer to estuarine ecosystems as ecoclines extending

from fresh waters to the sea. The community gradient, or living part of the ecocline, is a coenocline and the multifactor environ­ mental gradient is a complex gradient.

THE STRUCTURE OF ESTUARINE BENTHIC COMMUNITIES

I have elsewhere (Boesch, in press) described the patterns of benthic species diversity in some Virginia coastal environments using H’, S-1/lnN, and £ as measures of informational diversity, species richness, and evenness (equitability). Although species diversity was greatest on the outer continental shelf, sur­ prisingly high diversity was recorded from the polyhaline zones of the Chesapeake estuary.

The decline of all three diversity parameters from stable levels in the polyhaline zone to lower levels in the meso- and oligohaline zones indicates that the discontinuity in community structure coincides with that in faunal distribution. The re­ duction in the species richness component may be predicted from patterns of faunal distribution and taxa diminution. The reasons for the change in the equitability component are less obvious, but apparently are related to changing patterns of dominance.

Loucks (1970) and Margalef (1968) have shown that diversity increases during a successional sequence to a high in late suc­ cession, followed by a decline to submaximal levels at climax stages.

The rather high species diversity in the polyhaline estuary might be due in part to sub-stable community structure, maintained by continuing environmental stress, including both temperature and 82 salinity stress. Species diversity may consequently be maintained above the hypothetical "steady-state1' levels for these habitats.

Sanders (1968, 1969) has described the global patterns of marine benthic species diversity and has explained the factors in­ fluencing them. He correlated species diversity with environmental stability and restated the "theory of climatic stability" as the

"stability-time hypothesis." Very stable environments present little physiological stress, thus allowing specialization and, given an adequate time span, evolution of a very speciose biota. The species in such environments develop complex biological interactions and are consequently "predominantly biologically accomodated." Un­ stable conditions support a species-poor biota in which the spscies are "predominantly physically controlled," because of the great physiological stress. Sanders found that tropical shallow water benthos was most diverse and that diversity in the deep sea was also very high. Lower diversity was characteristic of tropical estuarine, boreal shallow water, and boreal estuarine benthos.

Sanders analyzed the diversity of the bivalve and polychaete fraction of the fauna, using the "rarefaction method" to graphically demon­ strate diversity patterns. Rarefaction curves for and bivalve species only were drawn for York estuary benthos (Fig. 19) and compared to curves describing diversity on the outer continen­ tal shelf of Virginia (unpublished data), tropical shallow water, and the deep sea (Sanders 1968). The richness of species in these

Virginia environments is far below that of the more stable tropics and deep sea and approximates the species richness described for comparable cold temperate environements by Sanders. POLYCHAETE AND BIVALVE SPECIES 40- 70H 80- - 0 3 50- - 0 6 90-i 20 10 ] ) , 1 ) r ] 1 Q - iue 9 Evlps otiig aeato cre for curves rarefaction containing Envelopes 19. Figure 0 20 0 40 0 60 700 600 500 400 300 200 100 (unpublished data), and the York estuary. York the and data), (unpublished ; 98, h otrcnietl hl of Virginia off shelf continental outer the 1968), hlo ae n de sa niomns (Sanders environments sea deep and water shallow * x ' s polychaete and bivalve species from trooical from species bivalve and polychaete ;; UBR F INDIVIDUALS OF NUMBER SUR (MESO-OLIGOHALINE) ESTUARY -83- YORK-PAMUNKEY d^^-VkKV • ■d^^-VkKV AT A * v k h T c i “ < t ' \ ' v - - \ ' ' lOIA , TliOPICAl Ht LSHAt SUR (POLYHALINE) FSTUARY ZZ'y///Ow\i.n'///?, HSPAE-YORK - CHESAPEAKE OTNNA. SHELL CONTINENTAL. EPSEAgp g : A E DEEP S ' ’.v 0 s; - v" r r r v w /. {/ s T

T

84

Salinity is but one of many factors influencing species diversity in estuarine environments. The nature of the substrate,

food abundance, oxygen stress and other factors may also be impor­ tant. The fauna of sandy sediments is generally more diverse than that living in mud (Sanders 1968, Boesch 1971) and the ,Tinordinately" high levels of species diversity at station 9 were probably attri­ butable to the presence of sandy sediments.

Dominance diversity curves reflect species diversity and its richness and equitability components, show the extent of dominance, and detail the distribution of commonness and rarity.

The distribution of importance (abundance) among the species is best described by two truncated lognormal distributions -- one for poly­ haline communities and another for meso- and oligohaline communities.

These lognormal distributions are truncated near the modes because of the relatively small sample sizes, but if they are extrapolated past the "veil lines", the theoretical structure of the complete community can be illustrated. Using the lognormal distributions, where S0 = 16 and a = 0.2 for lower estuary communities and S0 = 5 and a = 0.2 for upper estuary communities, hypothetical complete dominance-diversity curves can be drawn (Fig. 20). These curves predict that if sample size is large enough (10,000 to 100,000 individuals) approximately 115 species would be represented in an average lower estuarine community and 45 in an upper estuarine com­ munity. These numbers seem reasonable and compatible with the demonstrated patterns of faunal diminution and with practical ex­ perience. The species richness indices (S-1/lnN) for these hypothetical communities are roughly 9 and 4 for the lower and RELATIVE IMPORTANCE PER CENT 0.001 r - O O I 50 - 0 1 i—p-r-p-rT~(~1 _ T - ( . - r - * r - r n r . - 1. ~ ( ~ T r - p - r - p — i [ ■ i | j — j — T - j ‘ - T - T — j - 1 2 04 5 0 70 90 10 50 8060100 20 30 40 1100 120 iue 0 Hpteia oiac dvriy uvs for curves diversity dominance Hypothetical 20. Figure POLYHALINE PCE SEQUENCE SPECIES macrobenthic communities in the York estuary. York the in communities macrobenthic oyaie A ad eo ad lghln (B) oligohaline and meso- and (A) polyhaline -85- EO- OLIGOHALINE MESO - PCE SEQUENCE SPECIES

86

upper estuarine communities, respectively. These values are

generally higher than those actually observed, but because this

particular index is itself based on a model of commonness and rarity different than the lognormal, this has no necessarily-

significant ecological meaning. Values of H and J computed for the hypothetical communities are very similar to those actually

observed (H = 4, J = 0.75, for the lower estuary community; H == 3,

J = 0.65 for the upper estuary). Both indices are heavily in­ fluenced by the relative abundance of small numbers of important species which constitute the extreme right tail of the lognormal distribution.

Importance value distributions approach a random niche- boundary model (broken stick distribution) for small samples of taxonomically related organisms from narrowly defined homogeneous communities in severe environments (Whittaker 1969, 1970). These two distributions represent limiting extremes of minimum dominance and maximum equitability in the random niche boundary hypothesis, and maximum dominance and minimum equitability in the niche pre­ emption hypothesis. Samples containing large numbers of phylo- genetically diverse species, many of which have no effective competitive contact with one another usually approach a lognormal distribution. Thus, the distribution of importance among species in multi-strata forest communities (Whittaker 196 5, 1969) and benthic macroinvertebrates (Lie 1969, and this study) approaches lognormal.

The exact form of observed importance distributions is variable and depends on sample size (Hairston 1969) and the particular importance measure used. Predictions of the lognormal distribution 87

may take many forms depending on the value SQ, the constant and

the boundaries of the modal interval, and lognormal curves approaching

both the random niche boundary and geometric models are possible.

Only by investigation of the importance distribution with­

in taxocenes (e.g. polychaetes) or feeding type groups (e.g.

selective deposit feeders) can these models yield information about

biotically maintained structure within macrobenthic communities.

For example, Whittaker (1965, 1969) found that although forest plant communities usually have lognormally distributed importance values, within individual vegetational strata (e.g. trees and

shrubs) importance was often distributed geometrically.

Concepts of dominance and the niche have been used widely in ecology to explain community structure, evolution, com­ petition, and other phenomena. Theories of ''dominance" and "the niche" are controversial (McNaughton and Wolf 1970, Levin 1970) and their rigorous discussion is beyond the scope of this paper.

However, it must be pointed out that these concepts are frequently misused through the application of dependent definitions and circular reasoning.

Numerical dominance increases proceeding up-estuary.

Measurable numerical dominance may not correspond to functional dominance, which implies that "certain species so pervade the eco­ system that they exert a powerful control on the occurrence of other species" (McNaughton and Wolf 1970). There are some instances where this clearly happens; for example, oysters control the occur­ rence and abundance of members of the oyster reef epibiotic assem­ blage. It is difficult to imagine such pervasive influence by any 88

soft-bottom macrobenthic species. If there are functionally

dominant organisms in these deposit-feeder dominated communities,

they are the microorganisms which control food supply

The direct relationship of dominance and ,fniche size" is

often assumed and a proof of this relationship was attempted by

McNaughton and Wolf (1970). Their measures of "niche width" and

dominance seem contrived and interrelated, and key statistical

arguments are weak. It seems less than adequate to describe average

dimensions of multidimensional niche hypervolumes on the basis of

single factor gradient distributions. However, if the extent of

a species' range along a gradient reflects one of the n-widths of

its niche, that is, the extent of that species' exploitation of a

particular dimension of the environment, then those species in the

estuary with the "largest" niches are the members of the euryhaline marine-grade 3 faunal component. These species, e.g. Neomysis,

Edotea, Monoculodes, Nereis, and Heteromastus, were seldom, if ever,

numerically dominant species.

One can in qualitative terms compare "niche size" of estuarine and strictly oceanic species. The fundamental niches

(Hutchinson 196 5) of estuarine organisms are larger than those of their stenohaline counterparts, because they can tolerate a wide variety of environmental conditions and are less resource- specific . The proportion of the fundamental niche that is actually realized may be smaller for species in the unstable estuarine en­ vironment, but generally the realized niche is, in absolute terms, larger than that of a stenohaline counterpart. For estuarine species there is "r-selection" toward reproductive exploitation of 89

unoccupied or incompletely occupied niche space, whereas, in more

stable environments "K-selection" results in increasing speciali­ zation and reduction of niche size and amount of niche overlap

(MacArthur and Wilson 1967). Euryhaline species with large fun­ damental niches may be able to exploit only a fraction of the niche and live in estuaries where biotic interactions are less intense.

The euryhaline species can then be considered "opportunistic"

(Hutchinson 1967, Grassle 1967) and some, such as Mulinia and

Streblospio, are truly "fugitive" (Hutchinson 1951).

RELATIONSHIPS OF DIVERSITY MEASURES

The use of a number of indices of species diversity or its components (Table 5) is redundant. Rank correlation analyses

(Spearmanrs correlation test, Siegel 19 56) show that although values of informational diversity computed by Brillouin's and

Shannon's formulas (i.e. H and H T) were different, they were very highly correlated (rs = 0.994). The respective indices of evenness

(J and JT) yielded virtually identical values. Other measures of evenness ( £ and the redundancy measure) were also highly rank- correlated with J (p< 0.001) -- in the case of the redundancy measure the correlation was of course negative.

The primary index of species richness, S-1/lnN, was highly rank-correlated with both the number of species in the sample and the rarefaction measure, spp/100 indiv. The number of species was correlated (p<0.01) with the number of individuals in the sample.

Values of spp/100 indiv. as compared to values of S-1/lnN showed a higher correlation with H and a lower one with the number of species in the sample. The form of rarefaction curves predicted 90 for small sample sizes reflects in part the evenness of the distri­ bution of individuals among species. Thus, an index such as spp/100 indiv. is dependent on this evenness. Therefore, the S-1/lnN index is the best of these three richness measures.

Comparisons of values of the various indices of infor­ mational diversity, species richness, and evenness show that, although valid distinctions regarding theoretical appropriateness exist, in practice it makes little difference which measures are used. Similar conclusions regarding community structure are drawn if, instead of using H, S-1/lnN, and J, other indices, for example

H ’, spp/100 indiv., and£, are employed (Boesch 1971 and in press).

THE ESTUARINE ECOSYSTEM

Although the macrobenthos includes a wide variety of taxa, it is but a portion of the estuarine ecosystem. Other meta- zoans, microorganisms, algae and vascular plants inhabit the bottom and compose the benthos. Additionally, there are planktonic and nektonic components of estuarine ecosystems. It has been necessary to compartmentalize ecosystems into ecological or taxonomic com­ ponents to simplify analysis of these ecosystems. One must keep in mind, however, that these compartments are open ended, continuous and functionally dependent.

Similarly, spatial compartmentalization of ecosystems is artificial since most systems are continuous and ecoclinal. Useful classifications of coastal ecological sub-systems exist, such as the Venice Systen, based on salinity regimes, and Odum and Copeland’s

(1969) classification, based on energy flow characteristics (e.g. marshes, oyster reefs, worm and clam flats, benthic vegetation, 91 oligohaline systems, and medium salinity plankton estuary). These sub-systems are continuous compartments and functionally inter­ dependent.

Only mild community discontinuities exist longitudinally in the York estuary and sharp sub-system boundaries cannot be placed. However, the structural and distributional discontinuity at the broad border zone between polyhaline and mesohaline regimes provides as realistic a boundary as any for the general classifi­ cation of ecological sub-systems. Benthic macro-organisms provide good criteria for such classification because they are long-lived and sessile as opposed to plankters, whose populations are season­ ally dynamic and transported by currents, and nektonic organisms, which are largely migratory.

Macrobenthos, while good indicators of sub-systems, are not important in terms of gross energy flow in marine systems. In shallow waters, the macrobenthos is responsible for 10% or less of benthic respiration (Pamatmat 1968, Carey 1967). These organisms are nonetheless important as energy flow regulators, because they function as packagers of organic matter (Haven and Morales-Alamo

1966), agents of mechanical breakdown of organic material (Heald and W. Odum 1969), food links to predators (Marshall 1970), biomass reservoirs, and biogeochemical agents (Kuenzler 1961). As Margalef

(1968) pointed out, the benthos is the more driving and controlling subsystem, and the plankton is the more driven and pays the major part of the energy bill.

Because the benthos is a major sub-system for storage of energy and structural information in coastal systems, the structure 92 of the benthic compartment yields clues to the structure and function of the entire estuarine ecosystem. The continuum of community structure complexity along the estuarine gradient is analagous to the temporal continuum of structure in ecological succession, and much of the theory of ecosystem development during succession is applicable to the estuarine ecocline. E. P. Odum (1969) listed

24 trends in ecosystem development in a model which describes well the trends in community energetics and structure, nutrient cycling, life histories, selection pressures, and overall homeostasis ob­ servable along the estuarine ecocline. Communities in low salinity portions of the estuary show attributes like those of early serai stages. For example, species diversity and pattern diversity

(spatial heterogeneity) are low and species are generally small and have broad niches responding to r-selection (for rapid growth).

Proceeding seaward, ecosystem attributes approach those described for mature serai stages. Species diversity and pattern diversity increase and the niches of species narrow in response to K-selection

(for feedback control). Trends in the functional attributes of estuarine ecosystems also proceed as those described for succes- sional development. The ratio of gross production to community respiration may depart greatly from unity in the upper reaches, whereas down-estuary the ratio usually approaches one. Gross pro­ duction is higher relative to standing crop biomass in the upper estuary and food chains are short and linear (H. T. Odum 1967). In short, sub-system characteristics are toward production, growth, and quantity up-estuary and toward protection, stability and quality toward the sea (E. P. Odum 1969). 93

An understanding of these trends in estuarine ecosystems

is important to their successful management, both regarding main­

tenance of environmental quality and the management of fisheries.

Pollutants, or more generally environmental perturbation, eliminates less resistant species, thus favoring eurytolerant forms and re­

sulting in lowered species diversity. Put in terms of energetic theory, the addition of stress requires the utilization of energy to maintain homeostasis and less energy is available to maintain community diversity.

One expects that estuarine communities of varying diver­ sity will respond in varying degrees to pollution stress. Copeland

(1970) developed a model which predicts that perturbation of a given magnitude causes less relative loss in diversity in low diversity communities than in high diversity ones. Thus, one would expect that the effect of such disturbances on meso- and oligohaline sub­ systems to be less than that on polyhaline sub-systems. On the other hand, W. E. Odum (1970) indicated that in estuaries T,the flow of energy is particularly susceptible to alteration because of the low diversity of species present.” He reasoned that estuarine organisms are naturally stressed to their tolerance limits and that the removal of a species through perturbation "may leave an empty niche or else a niche which has been claimed by ecologically less desirable species." The response of estuarine sub-systems to stress depends on the type of disturbance. For example, the effect of an equivalent amount of loading of oxygen demanding material may have a greater effect on an oligohaline sub-system in which low oxygen conditions normally develop. Dredge spoil or turbidity 94 disturbances may have a greater effect on polyhaline sub-systems than

on the strongly sedimentary sub-systems in the oligohaline estuary.

In general, I suspect that low-salinity systems are more resistant to limited environmental perturbation than the more diverse high

salinity systems. However, species (including some important to man) which use low salinity sub-systems as nursery areas may be particularly susceptible to certain kinds of disturbance.

The meso- and oligohaline sub-systems might seem more amenable to fisheries management because, with their low diversity and high productivity, they are analogs of terrestrial agricultural systems. Competition and predation are minimal, but the physical environment is variable, unpredictable, and uncontrollable. Many of the species now "harvested" are migrants and dependent on other sub-systems, and thus management of migrant species stocks is much more complicated. However, potential exists for utilizing and managing the detritus-based estuarine trophic system, which is simple and linear, particularly for the production of molluscan and species. APPENDIX

Distribution of non-colonial macrobenthic species known from the Chesapeake- York-Pamunkey estuary. Dashed lines indicate an implied distribution to the mouth of Chesapeake Bay. Asterisks indicate species taken in this study.

______KM FROM MOUTH OF BAY 0______20 ______40______60______80 100

ANTH0Z0A

Edwardsia elegans*------

Haloclava producta ______

Paranthus rap iformis* ---

Diadumene leucolena* ------

Aiptasla eruptaurantia

Aiptasiomorpha luciae

Ceriantheopsis amoricanus* ______

Astrangia danae ___

TURBE1.T ARTA

C’oronadena mu tab i lis* ______

Stylochus ellipticus* ______

Euplarta gracilis*______

RHYNCHOCOELA

Tubulanus pelluc idus* — — ------

Carinoma tremaphoros

Carlnotnella lac tea* ------

Cerebratulus lacteus* ------

Cerebratulus luridus* ' ------

Linens bicolor* •

Lineus pallidus* ---

Lineus socialis — ------

Micrnra leidyi ------

Micrura rubra* ------

P.vgeupolla rubans ---

Nemertean Av ------

95 KM FROM MOUTH OF BAY 0 20 40 60 80 100

Nemertean B*

Nemertean C*

Amphiporus bioculatus*

Amphiporus caecus

Amphiporus ochraceus

Amphiporus rubropunctus

Tetrastemma candidum

Tetrastemma elegans

Tetrastemma jeanl

Tetrastemma vermiculus

Zygor.eroertes virescen.s

PliORONIDA

Phoronlj archttccta*

ECHIUPA

Echiuran A (white)*

Echiuran B (red)

0LT.G0CHAETA1

Peloscolex gabriellae*

Oligochaete A*

Oligocbaete B*

Oligcchaete C*

POLYCHAETA

Asabellides oculata*

Hypaniola grayi*

Melinna maculata*

Pseudeurythoe pane ibranch i.ata';

Arabella ir ieolor*

Drilonereis filum KM FROM MOUTH OF BAY 0 20 AO____ 60 8 0 _____ 100

Drilonerels longa*

Arenlcola cristata

Capitella caplcata

Heterowastus fillformis*

Notomastus lataricius*

Chaetopterus variopedatus*

Splochaetopterus oculatus*

Palaeonotus heteroseta*

Cirrafculus grandis*

Cossura sp.

Tharyx setigera*

F tautoncrsi, s runn j

Marphysa sanguinea

Phcrusa a f f i n i s*

Glyccra americana*

Give era dibranchiata*

Glyc inde so 1 i.Caria-

Amphldura sp.

Gypt is vittata*

Podarke obscura*

Lumbrineris tenuis

Magelona rosea*

Clymetieila torquata*-

Clyrcenella zonal is*

Maldanopsis elongata*

Aglaophamus verr i_l 1 i*

Nephtys inc_i£a

97 ______KM FROM MOUTH OF BAY __0 20 40 60 80 100

Nephtys magellanlca* —

Nephtys picta* —

Laeonereis culveri*

Nereis arenaceodonta _

N ereis succLnea* . —

Nereis grayi . —

Platynereis dumerilli —

D iopatra cuprea* —

Ophelia hicornis —

Travisia carnea

Orbinia ornata

3colop1os acutus

Sc olop I o s arrr.igc.r

Scoloplos fragilis* —

Scoloplos robustus —

Owen ia fus ifermis* —

Aricidea jeffreysi*

Arieidea wassi

Pec tinaria gouldi*

Eteone lac tea —

Eteone heteropoda* —

Eumida sanguinea*

Nereiphylla fragilis —

Paranaitis speciosa —

Phyllodoce arenae* —

Phyllodoce mucosa

Ancistrosyllis bar tm.-mnae KM FROM MOUTH OF BAY 0 20 40 60 80 100

A n d s i r osyl lis jonesi*

Cabira incerta

S iganibra tentaculata*

Sigambra wass1

Harmothoe acanellae

Harmothoe extenuata*

Harmothoe sp. A*

Lepidametra coimnensalis

Lepidonotus sublevls*

Sabellaria vulgaris*

F brie ia sabel la

1' u l u i.i L 11 t q

Sabella mlcrophtha ltna*

Hydro ides dianthus

S chenelais boa*

Polydora commensa1 is

Polydora ligni*

Polydora websteri

Prionospio c irrifera*

Prionospio heterobraachiata

Pr ionospio malrngreni*

Paraprionospio pinnata*

Scolecolepides viridis*

Scolelepis bousfieldi*

Spio filicornis*

Spio setosa

Splopbanes bombyx* ______KM FROM MOUTH OF BAY 0______20______40______60______80______100

Streblosplo benedicti*______

Autolytus c o r n u t u s ______

Autolytus prolifer______

Brania clavata*______

Brania v/elifleetensis ______

Exogotte d i s p a r * ______

Odontosyllis fulgurans*______

Parapionosyllis longicirrata______

Amphitrite ornata* ______

Enoplobrancbus sanguineus______

Lolmia medusa* — ------

Xj_ySiil.a alba _ ...----

Pista cristata —------

Pista maculata ------

Pista palmata ------

Polyc irrus cximlus ------

BIVALVIA

Solemya velum------

Nucula proxima*------

Yoldia limatula* ------

Anadara transversa* ------

Anadara ovalis* ------

Noetia ponderosa ------

Brachidontcs recurvus ------

Amygdalum papyrla ------

My til us edulis* ------

Modiolus demlssus KM FROM MOUTH OF BAY 0 20 40 60 80 100

Anomia simplex

Crassostrca virginica

Congeria leucophaeta

LacIna multilineata*

Montacnta elevata

Mysella bident.ata* ’

Mysella planulata

Lcevicardiutn m ortoni

Moreen,-jria mercenaria*

P itar m orrhuana*

Astarte sp.*

r ... l : ..-11.. 1-

Do_s_i a j a discu_s

Cfimtna gemma

Potricola pholadiformls

tp L j ina agil Is*

.'a corn a balthlca*

Macor.ia mj.tchelli*

Macoma tenta*

Abra aequalis

Tagelus plabeius

Tagelus divisus

Ensis di rec tus*

Sp tsula solidisslma*

M ulinia ]a tera 1Is* t-'va arenaria* KM FROM MOUTH OF BAY 0______20______40______60______80______100

Barnea truncata , ______

Lyonsia hyalina*______

Pandora trilineata*______

Cardiomya glypta — —------

GASTROPODA

Littorina irrorata______

Cyclostremiscus pentagona------

Solariorbis infracarinata------

Teinostoma cryptospira ------

Caecum pulchellum------

B i 11 i urn var ium------— ------

Get i. Ill iop is eculi-’; ------

Pciphora nigrocincta ------

F.pitonium mult is tr iatum------>------

Epitonium rupicolum* ------

Melanella intermedia* ------

Crepidula fornicata ------

Crepidula convexa ------

Crepidula plana —

Po 1 inices dupiicatus*------

Tectonatica pusilla*. ------

Eupleura caudata* ------

Urosalpinx cinerea ------

Anachis avara ------

Anachis translirata~'------

Mi_trel_la 1 unata* —

Busycon carica ______

102 KM FROM MOUTH OF BAY _0______20______40______60______80______100

Busycon canaliculatum ------

Nassarius vibex* ------

Nassarius trivittatus* ------

Nassarlus obsuletus ------

Marginella dentlculata ------

Terebra dlslocata* ------

Mangelia cerina* ------

Mangelia plicosa* ------

Acteon punctostriatus* ------

Haminoea solitaria ------

Retusa canaliculata*------

Cylichna alba* ------

Odoslomia bi.suUuralis* ------

Odostomia impressa* — :------— ------

Odostomia dux ------

Pyramidelta Candida*------

Pyraroidella fusca.------

Turbonilla inberrupta*------

Turbonilla stricta------

Doridella obscura*------

Doris verrucosa*------

Cratena pllata* — — ------

Elysia catula

Stiliger fuseaba

Polycerella conyina*

Tenellia fuscata

Hermaea cruciata

103 KM FROM MOUTH OF BAY 0______20______40______6 0 ______. 80______100

MEROSTOMATA

Limulus polyphemus______

PYCNOGONIDA

Ancplodactylus parvus ______

Anop lodac ty ltis p y g m a e u s * ______

Calllpallene brevirostris ______

Tanystylum orbiculare ------

OSTRACODA

CylindroleberIs marinae*------

Sarsiella texana*------

Snrslella zostericola* ------

CIRPTPFDIA

Chthamalus fragilis

Balanus — J--

Balanus eburneus ______

Balanus improvisus______

MYSIDACEA

Mysidopsis bigelowi ------

Neomysis a m e r i c a n a * ------

CUMACEA

Cyclaspis varians------

Leptocuma minor ----

Leuc on amer icanus* — . . — - ■ ■ - •

Diastylus politus______

Oxvurostylis smithi* ______

TAKAibACEA

LeptochelLa savignyi------

104 KM FROM MOUTH OF BAY 0______20______40______60______SO______100

ISOPODA

Cyathura polita*------

Cyathura burbancki* .------

Ptllan thura tenuis------

Ci.rolana polita______

Anc inus d e p r e s s u s ------

Paracerceis caudata------

Sphaeroma q u a d r l d e n t a t u m ------

Chiridotea almyra* ------

Chiridotea coeca------

Chlridotea f.uftsl------

Er:ichsonella at tanuata------

Idotea balthica------

Edotea triloba* — ------

Ligia exotica------

AMPHIP0DA

Ampelisca abdita* ------

Ampelisca vadorum* ------

Ampelisca verrilli* ------

Ampithoe longimana ------

Ampithoe valida —

Cymadusa compta------

Atylus minikoi------

Batea catharinensis* —------

Cerapus tubularis* ------

Cotophi um acherusicum*------:------

Corophium lacuotre* KM FROM MOUTH OF BAY 0 20 40 60 80 100

Corophium simile______

Corophium tuberculatum*______

Erichthonius brasiliensis ___

Unclola irrorata* ---

Ur.ciola serrata ---

Elasmopus levis------

Gammarus daiberi*

Gammarus fasciatus

Gammarus muc.ronatus*------

Gammarus palustris

Melifca appendiculata* ---

Melita nitida*

Ac an thohaus tor ius miilsi ---

Acanthohaustorius intermedius r

Protohaustorius deichraannae ---

Ilaustcr ius sp . ---

J a s s a falcata ---

Listriella barnardi

Listriella clymenellae*

Lysianassa alba

Honoculodes edwardsi* ---

Leptocheirus plumosus*

Paraphoxus epistomus* ----

Sympleustes glaber ----

Parametopella cypris

Stenotboe minuta* ---

Orchestia platensls KM FROM MOUTH OF BAY 0______20______40______60______80______100

Orches tia uhleri

Talorchestia longicornis

Caprella equilibra* ______

Caprella penantis ______

Paracaprella tenuis* ______

DECAPODA

Alpheus heterochaelis ______

Alpheus normaimi ______

Ogyri des 1 itnicola*______

Crangcm s e p t e m s p i n o s a ______!______

Callianassa atlantica ------

Upogebia affinis ------

Polyonyx g i b b u s i ------

Euceramus praelongus* — ------

Pagurus longicarpus* ------

Pagurus pollicaris------

Cancer irroratus* ------

Eurypanopeus depressus ------

Hexapanope augustifrons ------

Neopanope texana* ------

Panopeus herbsti ------

Rhithropanopeus harrisii ------

Dissodactylus mellitae------

Pinnixa chaetopterana* ------

Pinnixa cylindrica ------

Pinnixa retinens* — — ------

Pinnixa rayana* ______KM FROM MOUTH OF BAY 0 ______2 0 ______40 60 80 100

Pinnotheres maculatus

Pinnotheres ostreum

Sesarma clnereum

Sesarma reticulatum

Ocypode quadrata

Uca mlnax

Uca pugnax

Uca pugilator

Libinla dubia*

Libinla emarglnata

ST0MAT0P0DA

Squil la eoipusa

INSECTA

Tendipedidae *

Chaoborus sp.*

ECHINODERMATA

Asterias forbesl

Luldia clathrata

Leptosynapta tenuis

Cucumaria pulcherrlma*

Thyone briareus

Ophioderma brevlsplna

Amphioplus abdltus*

Amphiodia atra*

Ophiothrlx angulata

Mel 1ita guinquiesperforata Echinarachnius parma

HEMICHORDATA

Saccoglossus kowalewskii

Balanoglossus sp.*

UROCHORDATA

Kolgula manhattensis*

CEPHALOCHORDATA

Branchiostoma caribaaum

Oligochaetes have been identified by Dr. D. 0. Cook: Oligochaete A--mainly immature Peloscolex gabrtellae OligochaeLe B--Peloseoiex heterochae tus Michaelson, 19?6 Oligochaete C — P. gabrleilae-1 ike (may be distinct species, subspecies, or ecotype).

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Dona Id Friedrich Boesch

Born on 14 November 1945 in New Orleans, Louisiana.

Graduated from the Holy Cross School in New Orleans. Received a

B.S. in Biology from Tulane University in 1967. Enrolled as a graduate student in the School of Marine Science, College of William and Mary, in September, 1967. Held various research assistantships at the Virginia Institute of Marine Science from 1967 to 1969 and a research fellowship from the Federal Water Pollution Control

Administration during 1970 and 1971. Received a Fulbright-Hays postdoctoral research fellowship at the University of Queensland,

Australia, commencing July, 1971.