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SMITHSONIAN CONTRIBUTIONS TO THE MARINE SCIENCES • NUMBER 36

Foraminiferal Densities and
Pore Water Chemistry in the
Indian River, Florida

Martin A. Buzas
and Kenneth P. Severin

SMITHSONIAN INSTITUTION PRESS
Washington, D.C.
1993

ABSTRACT

Buzas, Martin A., and Kenneth P. Severin. Foraminiferal Densities and Pore Water Chemistry in the Indian River, Florida. Smithsonian Contributions to the Marine Sciences, number 36, 38 pages, 32 figures, 29 tables, 6 appendices, 1993.—Two stations were established about 10 m apart at a depth of about 1 m at Link Port, Florida. One consisted of quartz sand and the other of quartz sand with a dense stand of seagrass. At the surface of each station and at a depth of 10 cm at the grass site, four replicate samples consisting of 5 ml each were taken every fortnight from 27 March to 6 November 1978 (17 sampling times, 204 samples). The taxa Quinqueloculina, Elphidium, Ammonia, Bolivina, and Ammobaculites comprising 98% of the fauna were enumerated. In addition, pore water chemistry was measured for temperature, salinity, oxygen, pH, Eh, NH_3, PO_4, Si, NO_2, and NO_2 + NO_3.

General linear models were used to analyze the bare surface-grass surface, and grass surface-grass 10 cm data sets. Foraminiferal densities were evaluated for differences between sites, periodicity, sites × periodicity (interaction), and environmental variables.

Differences in overall density between the bare surface-grass surface sites were not significant for the three most abundant taxa (Quinqueloculina, Elphidium, and Ammonia). At the grass site the density for all taxa were significantly lower at 10 cm than at the surface (very few individuals were observed at 10 cm).

Hypotheses for periodicity and interaction were significant for all taxa in all comparisons except for Bolivina in the bare surface-grass surface analysis. At the bare surface, maximum densities occurred in spring while at the grass surface in summer. Although densities were low at 10 cm, no synchronization between the grass surface and 10 cm was evident.

The environmental variables were significant for all taxa in both comparisons. The environmental variables are, however, highly correlated. To alleviate this difficulty, a principal component analysis was performed on these variables. The first three components included all of the 10 variables. Subsequent multiple regression of foraminiferal densities and the principal components indicated that usually at least two components, accounting for most of the variables, were statistically significant. Thus, no simple relationship between pore water chemistry and density is apparent. The very large difference in density between the grass surface and 10 cm depth is much more strongly related to the pore water chemistry than the smaller differences with time at the surface sites.

OFFICIAL PUBLICATION DATE is handstamped in a limited number of initial copies and is recorded in the Institution's annual report, Smithsonian Year. Series cover design: Seascape along the Atlantic Coast of eastern North America.

Library of Congress Cataloging-in-Publication Data

Buzas, Martin A.

Foraminiferal densities and pore water chemistry in the Indian River, Florida / Martin A. Buzas and Kenneth P. Severin. p. cm.—(Smithsonian contributions to the marine sciences ; no. 36) Includes bibliographical references (p. ).

1. Foraminifera—Florida—Indian River. 2. Protozoan populations—Florida—Indian River. 3. Population density—Florida—Indian River. 4. Pore water—Florida—Indian River. I. Severin, Kenneth P. II. Title. III. Series.

QL368.F6B875   1993   593.1′204526323′097592-dc20   92-46076

The paper used in this publication meets the minimum requirements of the American National Standard for Permanence of Paper for Printed Library Materials Z39.48–1984.

Contents

Introduction

Acknowledgments

Methods

Field

Laboratory

Statistical

Bare Surface and Grass Surface

Environmental Variables

Species Densities, Station Differences, Periodicity, and Environmental Variables

Quinqueloculina

Elphidium

Ammonia

Bolivina

Ammobaculites

Grass Surface and Grass 10 cm

Environmental Variables

Species Densities, Station Differences, Periodicity, and Environmental Variables

Quinqueloculina

Elphidium

Ammonia

Bolivina

Ammobaculites

Comparison of Analyses

Comparison with Other Studies

Appendix 1: Bare Surface

Appendix 2: Grass Surface

Appendix 3: Grass 10 cm

Appendix 4: Bare Surface

Appendix 5: Grass Surface

Appendix 6: Grass 10 cm

Literature Cited

Foraminiferal Densities and
Pore Water Chemistry in the
Indian River, Florida

Martin A. Buzas
and Kenneth P. Severin

Martin A. Buzas, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, D.C. 20560. Kenneth P. Severin, Department of Geology and Geophysics, University of Alaska-Fairbanks, Fairbanks, Alaska 99775-0760.

Introduction

A basic variable for ecological studies is density, the number of individuals per volume or area. Densities of foraminiferal species, like those of all organisms, vary in space and time. Geographic changes in foraminiferal species densities have been documented between all marine environments from marshes to the abyss. Large differences in space like those between a marsh and the abyss or the Arctic and the tropics are easily recognized. A general qualitative correlation between observed species densities and the environment is easily accepted as an explanation for these changes. Similarly, differences over vast amounts of geologic time are easily recognized, and explained by the interplay of evolution and the environment. As we decrease the scale of our observations in space and time, however, and, at the same time, increase our effort to achieve quantitative results, differences in species densities and their explanation become much more difficult. Nevertheless, densities do vary over a matter of meters and within a time scale measured in weeks, months, or years. The present study is an analysis of quantitative measurements of species densities and environmental variables observed at two stations about 10 m apart which were sampled every fortnight for 9 months.

During 1978 the chemistry group of the Harbor Branch Oceanographic Institution, Ft. Pierce, Florida monitored 10 pore water chemistry variables on a continual basis at two sites (stations) about 10 m apart at a depth of about 1 m in the Indian River (a shallow lagoon of nearly normal marine salinity on the central east coast of Florida). One station was located on bare quartz sand, the other on quartz sand with a covering of seagrass (mostly Halodule wrightii and Thalassia testidium). We viewed their study as an ideal opportunity to conduct a study of the foraminifera with an experimental design allowing us to test statistically for differences in density between stations and with time as well as for the statistical significance of 10 environmental variables.

Foraminiferal densities were also enumerated at a depth of 10 cm within the sediment at the grass station. Few living foraminifera were observed at 10 cm and most of the water chemistry variables exhibited a dramatic difference compared to the measurements made at the surface. To test the efficacy of the statistical procedures used in this study, and in others, the same statistical analyses were employed in evaluating the differences between the grass surface and at 10 cm as for the two surface stations.

ACKNOWLEDGMENTS.—We thank the former Chemistry group at the Harbor Branch Oceanographic Insititution, especially J. Montgomery, M. Hucks, G. Peterson, M. Price, and C. Zimmermann. In the field and laboratory K. Carle, D. Mook, and H. Sheng were most helpful. J. Jett prepared the tables, figures, and appendices. L.S. Collins, L.C. Hayek, and B.K. Sen Gupta offered helpful suggestions on the manuscript. We thank J.C. Warren for his careful copy editing. This is contribution No. 319 from the Smithsonian Marine Station at Link Port.

Methods

FIELD.—Two stations were established about 100 m south of the Link Port jetty at a depth of about 1 m. The stations were marked with four poles encompassing an area of about 1 m^2 so that the same area could be re-occupied easily. The sediment at one station consisted of bare quartz sand with a silt-clay content of about 2%. The other was on the same substrate, but had a dense stand of Halodule wrightii with some Thalassia testidium. The sediment was sampled by pushing plastic coring tubes (inner diameter 3.5 cm) into the substrate. At each station four sediment samples were taken indiscriminately (not statistically randomized) at each sampling time which consisted of every fortnight from 27 March until 6 November 1978 (17 sampling times).

The temperature, salinity, oxygen, pH, Eh, NH_3, PO_4, Si, NO_2, NO_2 + NO_3 were measured on pore waters by the chemistry group of the Harbor Branch Oceanographic Institution throughout the field experiment (Montgomery et al., 1979).

LABORATORY.—Immediately upon return to the laboratory (within a half-hour), 5 ml of sediment was removed from each core top, and at a depth of 10 cm. Each 5 ml sample was washed over a 63 μm sieve and preserved in 95% ETOH. Prior to examination for foraminifera the sample was stained overnight in rose bengal, dried, floated in a mixture of tetrabromine and acetone (specific gravity 2.3), and re-wet using “photo-flo” as a wetting agent. The foraminifera were enumerated while underwater, a procedure which facilitates the recognition of vividly stained protoplasm. The taxa counted were Quinqueloculina (mostly Q. impressa and Q. seminulum), Elphidium (mostly E. mexicanum and E. gunteri), Ammonia (A. beccarii), Bolivina (B. striatula), and Ammobaculites (A. exiguus). These taxa are sufficiently dissimilar so that they can easily be identified under a binocular microscope and account for 98% of the foraminiferal fauna. The second replicate sample taken at the grass surface on 22 May 1978 was destroyed in a laboratory accident. The mean number of individuals from the other three replicates was used to estimate the missing data (Appendix 2). The systematics of the taxa used here are treated by Buzas and Severin (1982). Enumeration was made by Severin.

STATISTICAL.—We have, then, two stations: one bare sand and the other with a stand of seagrass. For this study, the bare surface, the grass surface, and a depth of 10 cm within the sediment at the grass station were sampled for foraminifera. These three sites were sampled 17 times with four replicates of 5 ml each taken for examination. There are, then, N = 68 replicates or observations at each of the three sites. The number of individuals counted for each of five taxa and the total (the five taxa accounted for over 98% of the total) for each replicate is tabulated for the bare surface in Appendix 1, for the grass surface in Appendix 2, and for grass 10 cm in Appendix 3.

We obtained the measurements made by the chemistry group for 10 water chemistry variables at each of the three sites at each sampling time. These measurements for the bare surface are tabulated in Appendix 4, for the grass surface in Appendix 5, and for the grass 10 cm in Appendix 6.

The data were divided into two sets for statistical analyses, bare surface-grass surface, and grass surface-grass 10 cm. For each analysis we wished to test the following hypotheses; difference between sites (bare surface vs. grass surface or grass surface vs. grass 10 cm), differences with time (periodicity), different periodicities at each site, and the significance of the environmental variables. To accomplish this, we constructed a general linear model (GLM) similar to the one used by Buzas et al. (1977). In matrix notation the GLM is written as

where x, the “dependent” variable is a vector of observed species densities for the n = 136 observations (n_1 = n_2 = 68), Z′ is a matrix of q “independent” variables, the composition of which will be discussed below, is a vector of q parameters “regression coefficients” explaining the observations, and e is a vector of “errors” or “residuals,” assumed to have a normal distribution. The original counts × were transformed to ln(x + 1) to make the data more Normal and stabilize the variance.

Restricted Ω models containing s parameters are constructed by equating the appropriate individual or groups of to 0. The sum of squares of the residuals, e′e, for each model is a scalar and is estimated by a least squares solution (Buzas et al., 1977, give the equations). Restricted models can be compared to the general model by the ratio

The mglh program of “SYSTAT” was used to calculate the sum of squares of the residuals for each model, and these residuals were then used to calculate the F-ratio given above. The results of the analysis are most easily displayed in the standard ANOVA table.

The composition of the matrix Z′ of the ω model is given in Table 1. The vector z_1 is composed of l's so that 1 is a constant, z_2 contrasts the difference between sites by assigning +1 to one site and −1 to the other. The vectors z_3 and z_4 are made up of sin (m × π/3) and cos (m × π/3), respectively, where m = 1,…,17. The vectors z_5 and z_6 are composed of sin (m × π/6) and cos (m × π/6), respectively. These vectors are components of a periodic regression (Bliss, 1958) and account for a possible overall periodicity in the observations. Figures 1 and 2 illustrate these vectors over the period of our observations. The possibility exists that the two sites may exhibit periodicity, but that the periodicity differs at the two sites. The interaction vectors z_7 = z_2 × z_3, z_8 = z_2 × z_4, z_9 = z_2 × z_5, and z_10 = z_2 × z_6 account for this. We have, then, 8 vectors to examine the possible periodicity in our data. Had we constructed instrumental variables to examine the differences between the 17 sampling times and their interaction, we would have required 32 vectors, and made the model much more complicated. Finally, vectors z_11 through z_20 contain the water chemistry variables completing the Z′ matrix for the GLM.

TABLE 1.—Composition of the Z′ matrix.

z_1 =

a vector of units

z_2 =

+1 for bare surface, −1 for grass surface

z_3 =

sin (m ×π/3), m = 1,…,17

z_4 =

cos (m × π/3), m = 1,…,17

z_5 =

sin (m ×π/6), m = 1,… ,17

z_6 =

cos (m ×π/6), m = 1,… ,17

z_7 =

z_2 ×z_3

z_8 =

z_2×z_4

z_9 =

z_2×z_5

z_10 =

z_2×z_6

z_11 =

temperature

z_12 =

salinity

z_13 =

oxygen

z_14 =

pH

z_15 =

Eh

z_16 =

NH_3

z_17 =

po_4

z_18 =

Si

z_19 =

NO_2

z_20 =

NO_2 + NO_3

FIGURE 1.—π/3 periodicity.

FIGURE 2.—π/6 periodicity.

Bare Surface and Grass Surface

ENVIRONMENTAL VARIABLES.—The recorded temperature values are plotted in Figure 3. The results of a two-way ANOVA with one observation per cell (no replicates were measured for the environmental variables) is shown in Table 2. The hypotheses for differences in mean temperature between stations and with time are both significant at the .05 level, even though the mean temperature at the bare surface is only 1°C higher. The minimum at the bare station was 23°C and at the grass station 22°C. The maximum at each was 32°C and 31°C, respectively. Table 2 shows the mean square for time is higher than for station differences, and, as might be expected, Figure 3 shows summer temperatures were higher than spring and fall.

The recorded salinity values are shown in Figure 4 and the ANOVA results in Table 2. The slightly higher salinities recorded at the bare station were not statistically significant. Differences with time, however, were highly significant with minimum salinities of 20°/00 and 22°/00 recorded at the bare and grass stations, respectively, in August.

Oxygen measurements are plotted in Figure 5 and ANOVA results are presented in Table 2. Differences between stations were not statistically significant, but differences with time were. As expected, there is an inverse relationship with temperature, and generally the oxygen values are higher in the spring and fall. Minimum values occurred at the bare station in May, June, and July, and at the grass station in July.

TABLE 2.—Analysis of variance for chemical variables on bare surface and grass surface.

Values for pH are plotted in Figure 6 and ANOVA results are presented in Table 2. Differences between recorded values between stations were small and not statistically significant. Differences with time were significant and, like oxygen, the highest values occurred in spring and fall. Minimum values at both stations were 7.5.

Eh values are plotted in Figure 7 and ANOVA results are presented in Table 2. Although the difference in the mean value between stations was relatively large (Figure 7) it was not statistically significant. On the other hand, differences with time were highly significant, and fluctuated greatly between sampling times. Minimum values at the bare station and grass station were −208 and −128 mV, respectively.

NH_3 values are plotted in Figure 8 and results of the ANOVA are presented in Table 2. No significant difference was observed between stations, but, once again, differences with time were highly significant. Very low to zero values were recorded in the spring and fall with maxima at both stations in the summer.

FIGURE 3.—Temperature measurements in °C.

PO_4 values are plotted in Figure 9 and ANOVA results are presented in Table 2. No statistical difference was observed between stations or with time. The measured values were generally very low to zero with the exception of the bare station in September which appears to be an outlier.

The measured Si values are plotted in Figure 10 and the ANOVA results are presented in Table 2. No statistical difference was observed between stations, but differences with time were significant. Zero values were recorded at both stations in August; however, values generally increase from March to November.

FIGURE 4.—Salinity measurements in 0/00.

FIGURE 5.—Oxygen measurements in mg-at/1.

FIGURE 6.—pH measurements.

FIGURE 7.—Eh measurements in mV.

FIGURE 8.—NH_3 measurements in μg-at/1.

FIGURE 9.—PO_4 measurements in μg-at/l.

FIGURE 10.—Si measurements in μg-at/1.

FIGURE 11.—NO_2 measurements in μg-at/l.

FIGURE 12.—NO_2 + NO_3 measurements in μg-at/l.

NO_2 values are plotted in Figure 11 and the ANOVA results are presented in Table 2. Significant differences were again noted only with time. In general, values are low with maxima in summer and fall at the bare station and spring, summer, and fall at the grass station. Both stations had minima values from late August until early October.

NO_2 + NO_3 values are plotted in Figure 12, and ANOVA results are presented in Table 2. No significant differences were observed between stations or with time. An unexplainably high value was recorded in April at the grass station.

Table 3 shows the correlation coefficients between the environmental variables. Temperature and NH_3 are positively correlated with one another and negatively with oxygen, pH, and Eh which are all positively correlated with one another. Consequently, any hypothesis concerning the significance of a particular variable on species density is not independent of the others.

A way to avoid this difficulty is to transform the original variables to principal components. Principal component analysis is a technique which produces a succinct parsimonious summarization of many correlated (non-zero covariance) variables by transforming the original variables to independent (zero covariance) variables called principal components. An additional advantage of the technique is that the first principal component will account for most of the variability in the data, the second less, and so on (Seal, 1964). Eigenvalues were calculated from the correlation matrix (Table 3) using the SYSTAT statistical package. The first three eigenvectors account for 63.43% of the variability. The factor score coefficients (standardized vectors which when multiplied by the original standardized variables produce the principal components) indicate that all the environmental variables contribute substantially to the first three principal components (Table 4). The coefficients (Table 4) indicate that the first principal component (PCI) accounting for 31% of the variability contrasts temperature and NH_3 with oxygen, pH, and Eh. The second principal component (PC2) accounting for 18% of the variability consists mainly of salinity, Si, and NO_2 + NO_3, although PO_4 NH_3, and Eh also contribute and a line of demarkation is not as clear cut as for PCI. The coefficients (Table 4) indicate that the third principal component (PC3) accounting for 14% of the variability consists mainly of NO_2, Si, and temperature, but again there is no dramatic demarkation. The most highly correlated variables (Table 3) are all concentrated on PCI.

TABLE 3.—Correlation matrix for chemical variables for bare surface and grass surface. 0.05 level is underlined.

TABLE 4.—Factor score coeffecients for chemical variables for bare surface and grass surface.

Chemical
variable

Factor

PC 1(31%)

PC2(18%)

PC3(14%)

Temperature

–0.24

0.05

–0.30

Salinity

0.01

–0.45

0.04

Oxygen

0.29

0.00

0.04

pH

0.24

–0.07

–0.19

Eh

0.25

0.12

0.13

NH_3

–0.22

–0.18

0.22

PO_4

–0.02

0.24

–0.16

Si

–0.05

0.39

0.34

NO_2

–0.03

0.01

0.59

NO_2 + NO_3

0.06

–0.31

–0.17

FIGURE 13.—Mean number of individuals of Quinqueloculina per 5 ml of sediment (density).

SPECIES DENSITIES, STATION DIFFERENCES, PERIODICITY, AND ENVIRONMENTAL VARIABLES.—Quinqueloculina: Quinqueloculina was the most abundant taxon making up about 75% of the total living foraminifera at the surface stations. A plot of the mean densities observed at the bare and grass surface at the two stations is shown in Figure 13. The ANOVA table for six hypotheses is shown in Table 5. We recall that each hypothesis is formulated by equating the desired to zero. For example, the Ω model used to test for station differences deletes 2, for π/3 periodicity and interaction 3 = 4 = 7 = 8 = 0, and so on. Table 5 indicates that all hypotheses except for station differences are significant. The overall mean density at the bare station is higher than at the grass station, but is not statistically significant at the chosen 0.05 level. Figure 13 shows that the bare station had high densities in spring while the grass station had high densities in summer. The environmental variables are significant as a group. Because they are not independent, testing for the significance of each individually is risky. Nevertheless, using the standard errors of the 's from the ω model for calculating confidence limits indicates oxygen, Eh, PO_4, Si, and NO_2 + NO_3 are significant. Again, emphasizing that the variables are not independent, the ease of calculation using “SYSTAT” made the calculation of simple regressions for each of the variables vs. density irresistible. The results shown in Table 6 indicate the regressions for oxygen, pH, PO_4, Si, and NO_2 are significant. A way of avoiding the correlations between variables is to calculate a multiple regression using principal components instead of the original variables. Because the principal components are orthogonal, each hypothesis is independent and the analysis is similar to a one-way ANOVA. The results of an analysis on the log densities of Quinqueloculina and the first three PC's of the environmental variables are shown in Table 7. The overall F-ratio is significant and the test for the significance of each PC, which are independent, indicates that PCI and PC3 are significant at the 0.05 level while PC2 is nearly so. We recall from Table 4 that temperature, oxygen, pH, Eh, and NH_3 all contribute nearly equally to the first PC, and the third PC is weighed heavily on temperature, Si, and NO_2. Thus, the analysis using principal components requires seven of the 10 environmental variables for two PC's and 10 for three to explain the results. All of the above analyses indicate that the identification of one or two variables as solely significant for the observed densities is impossible.

TABLE 5.—Statistical analysis of GLM for Quinqueloculina for bare surface and grass surface.

TABLE 6.—Values of F-ratio's for simple regressions on species densities and environmental variables at bare surface and grass surface. (+ indicates signficant (.05 level) positive value of β; - significant negative value of β.)

Elphidium: Elphidium constitutes about 14% of the total living population and mean densities at the bare and grass stations are plotted in Figure 14 and the results of the GLM analysis is presented in Table 8. Although the mean density at the bare station is again higher than at the grass station, it is not statistically significant. The π/3 periodicity and interaction hypotheses are significant, but the π/6's are not. Figure 14 indicates a spring high at the bare station, but no pronounced summer high at the grass station as was observed with Quinqueloculina. The group of environmental variables are significant, and the 's for Eh, PO_4, NO_2, and NO_2 + NO_3 were significant. Regressions of density vs. each individual environmental variable yielded a significant F-ratio for temperature, salinity, oxygen, pH, and Si (Table 6). The results of multiple-regression of Elphidium densities and the first three PC's of the environmental variables are shown in Table 9. The first two PC's are significant and these account for all of the environmental variables except NO_2. Here, we note that individual tests of the 's from the ω model and individual 's from simple regressions do not agree testifying to the difficulty encountered when variables are highly correlated.

TABLE 7.—Regression of Quinqueloculina and principal components for bare surface and grass surface.

Ammonia: Ammonia makes up about 8% of the total living population and mean densities at the bare and grass stations are plotted in Figure 15. The results of the GLM analysis are presented in Table 10. The overall mean density is slightly higher at the bare station, but not significantly so. The π/3 periodicity and interaction hypotheses are significant and Figure 15 indicates an early spring maximum at the bare station while both stations have summer and fall maxima. Environmental variables are significant as a group and the 's for Eh, NO_2, and NO_2 + NO_3 were significant. Individual simple regressions on density vs. environmental variables yielded significant F-ratios for salinity and NO_2 (Table 6). The results of the multiple regression on densities of Ammonia and the PC's of the environmental variables are shown in Table 11. The results present us with a small dilemma because the F-ratio for the overall analysis has a probability of 0.06 which is slightly above our chosen level, and, therefore, is not significant. On the other hand, PC3 is significant (Table 11). If we choose to regard the third principal component as significant, then temperature, Si, and NO_2 are the major contributors, especially NO_2 (Table 4). The F-ratio for environmental variables in the ω model, while significant, is the smallest encountered for any of the five taxa analyzed. Ammonia appears, then, to be the least influenced by the 10 variables measured in this study.

Bolivina: Bolivina constitutes about 1% of the total living population and mean densities at the bare and grass stations are plotted in Figure 16. The results of the GLM analysis are shown in Table 12. Although the differences in densities between stations are small, they are, nevertheless, statistically significant, and the highest density is at the grass station. None of the hypotheses for periodicity are significant. There does appear to be a decrease in density over the course of sampling, but the fluctuations in density shown in Figure 16 are small compared to those considered previously (note the difference in the scale of the ordinate). The environmental variables are significant as a group, and the 's for salinity and Si were significant. F-ratios for simple regressions are significant for salinity, PO_4, Si, and NO_2 + NO_3 (Table 6). Multiple regression on densities of Bolivina and the first three PC's of the environmental variables are shown in Table 13. Only PC2 consisting mostly of salinity, Si, and NO_2 + NO_3 (Table 4) is significant. The relationship with salinity and to a lesser extent with Si are notable for this species.

FIGURE 14.—Mean number of individuals of Elphidium per 5 ml of sediment (density).

Ammobaculites: Ammobaculites also constitutes about 1% of the total living population and mean densities for the bare and grass stations are plotted in Figure 17. The results of the GLM analysis are shown in Table 14. The hypothesis for station differences is significant with the highest densities occurring at the grass surface. The π/3 periodicity and interaction hypotheses are significant, and Figure 17 indicates the now familiar spring maximum was observed at the bare station after which time the densities remained very low (Appendix 1). At the grass surface the densities increased overall during the sampling duration (Appendix 2). The hypothesis for the environmental variables is significant. The 's of the ω model for the variables pH, PO_4 Si, NO_2, and NO_2 + NO_3 were significant. The F-ratios for temperature, salinity, oxygen, and NH_3 were significant for simple regressions on density and environmental variables (Table 6). The results of a multiple regression on the densities of Ammobaculites and the first three PC's of the environmental variables are shown in Table 15. The first two PC's are significant indicating that all the variables except for NO_2 (Table 4) are important contributors. Again, we note the inconsistencies obtained by testing the environmental variables individually.

TABLE 8.—Statistical analysis of GLM for Elphidium for bare surface and grass surface.

TABLE 9.—Regression of Elphidium and principal components for bare surface and grass surface.

In summary, we recognize no station differences for the three most abundant taxa. For the rare species Bolivina and Ammobaculites which together constitute only about 2% of the total living population, densities are higher at the grass station. All of the taxa except for Bolivina exhibited periodicity. Quinqueloculina, Elphidium, and Ammonia all showed high densities in spring at the bare surface station and in summer at the grass surface. Bolivina exhibited an overall decreasing density from spring onward at both stations while Ammobaculites increased at the grass surface station and decreased at the bare surface. The environmental variables were significant as a group for all taxa, however, individual variables cannot be evaluated with confidence.

FIGURE 15.—Mean number of individuals of Ammonia per 5 ml of sediment (density).

Grass Surface and Grass 10 cm

ENVIRONMENTAL VARIABLES.—The recorded temperature values are plotted in Figure 18, and the results of a two-way ANOVA testing for differences between surface and 10 cm and with time are shown for temperature and all the other environmental variables in Table 16. The hypothesis testing for differences in mean temperature between the surface and 10 cm depth is not significant, however, the hypothesis testing for time is. As everyone knows, the water is warmer in the summer and cooler in spring and fall. A very high temperature was recorded in June and a very low one in August at 10 cm.

The measured salinity values are shown in Figure 19. Only the hypothesis for time is significant. Salinities were highest in spring except for the first observation in March at 10 cm. Both stations experienced a dip in salinity in August.

TABLE 10.—Statistical analysis of GLM for Ammonia for bare surface and grass surface.

TABLE 11.—Regression of Ammonia and principal components for bare surface and grass surface.

The recorded oxygen values are shown in Figure 20. The mean square for differences between surface and 10 cm is large and highly significant, and the mean square for time, although relatively much smaller, is nearly significant. Figure 20 illustrates and Appendix 6 tabulates zero recordings for oxygen during spring and summer at 10 cm making the difference between the surface and 10 cm (depth hypothesis) so dramatic.

The measured pH values are plotted in Figure 21. The depth hypothesis is significant, and the pH is always lower at 10 cm (Figure 21, Appendix 5, 6). Even at 10 cm, however, only one reading (November) recorded a value below 7.

Eh values are plotted in Figure 22. The depth hypothesis is significant. Values of Eh at 10 cm are always negative, and usually highly so, while the values at the surface fluctuate from positive to negative with a slightly negative mean (Figure 22, Appendix 5, 6).

FIGURE 16.—Mean number of individuals of Bolivina per 5 ml of sediment (density).

NH_3 values are plotted in Figure 23. The depth hypothesis is significant. The values at 10 cm are usually two orders of magnitude greater than at the surface (Appendix 5, 6). Two zero values were recorded at 10 cm, one in April and one in October. We suspect these anomalies are due to problems with instrumentation.

PO_4 values are plotted in Figure 24. The hypothesis for depth is significant. The values for PO_4 were very low at the surface, and one or two orders of magnitude higher at 10 cm (Appendix 5, 6). A very high value was recorded at 10 cm in June.

Si values are plotted in Figure 25 and the hypothesis for depth is significant. The values for Si at the surface are an order of magnitude smaller than at 10 cm (Appendix 5, 6). At 10 cm zero values were recorded in April, August, and October. Except for the zero value in August, the pattern is very similar to that observed for NH_3 at 10 cm.

NO_2 values are plotted in Figure 26. The hypothesis for depth is significant, and values for NO_2 are low. At 10 cm very low values were recorded in all months except October.

TABLE 12.—Statistical analysis of GLM for Bolivina for bare surface and grass surface.

TABLE 13.—Regression of Bolivina and principal components for bare surface and grass surface.

NO_2 + NO_3 values are plotted in Figure 27. There is no significant difference with depth or with time. Except for one measurement at the surface in April (Figure 27, Appendix 5) all the measurements were low.

The two-way ANOVA's for environmental variables at the bare surface vs. grass surface showed most significant differences are with time (Table 2). In contrast, the analysis for grass surface vs. grass 10 cm shows most of the significant differences are with depth (Table 16). Moreover, the F-ratios for the latter are usually much higher. We have, then, a situation where, except for temperature, salinity, and NO_2 + NO_3, there are much larger differences than at the surface stations.

The environmental variables are highly correlated as shown in Table 17. High positive values occur between oxygen and Eh, oxygen and NO_2, pH and Eh, Eh and NO_2, NH_3 and PO_4, NH_3 and Si, and PO_4 and Si. High negative values occur between oxygen and NH_3, oxygen and PO_4, oxygen and Si, pH and NH_3, pH and Si, Eh and NH_3, Eh and PO_4, and Eh and Si. The correlations differ from those at the bare and grass surface (Table 3) in that PO_4, Si, and NO_2 now are highly correlated so that the matrix of correlation coefficients has many more high values. To succinctly summarize the environmental variables, and remove the covariance between them, a principal component analysis was calculated on the correlation matrix. The first three eigenvalues account for about 70% of the variability. The factor score coefficients are given in Table 18. The first vector accounting for 45% of the variability has high values for oxygen, pH, Eh, NH_3, PO_4, Si, and NO_2. The second vector accounting for 15% of the variability has the highest values for salinity and NO_2 + NO_3, and the third accounting for 10% of the variability has a high value for temperature. Thus, all of the water chemistry variables are accounted for by using the first three principal components, and PCI accounts for all of them except temperature, salinity, and NO_2 + NO_3 which, interestingly, are the variables without significant differences with depth (Table 16).

FIGURE 17.—Mean number of individuals of Ammobaculites per 5 ml of sediment (density).

SPECIES DENSITIES, DEPTH DIFFERENCES, PERIODICITY, AND ENVIRONMENTAL VARIABLES.—Quinqueloculina: Quinqueloculina mean densities are plotted in Figure 28, and analysis by the GLM is shown in Table 19. As noted earlier, the densities for Quinqueloculina at the grass surface exhibited a summer maximum in July and August (Appendix 2). At 10 cm maxima were observed in March and November. The large increase in density observed in the summer at the surface is not reflected at 10 cm.

TABLE 14.—Statistical analysis of GLM for Ammobaculites for bare surface and grass surface.

TABLE 15.—Regression of Ammobaculites and principal components for bare surface and grass surface.

All of the hypotheses tested by the GLM were significant (Table 19). The mean square for differences with depth is very large reflecting the two orders of difference in magnitude of the mean density between the surface and 10 cm. The set of environmental variables are significant and in the ω model 's for oxygen, Eh, and NH_3 were significant. Simple regressions on density vs. environmental variables indicate the F-ratios for all variables except temperature are significant (Table 20). The results of a multiple regression on the densities of Quinqueloculina and the first three PC's of the environmental variables are shown in Table 21. The first and third PC's are significant indicating that only NO_2 + NO_3 did not contribute substantially to the significance of the analysis. The F-ratios for the simple regressions are much larger than for the bare surface and grass surface (compare Tables 6 and 20). Similarly, the F-ratio and R^2 for the multiple regression using the PC's is much larger for the grass surface and grass 10 cm than for the bare surface and grass surface (compare Tables 7 and 21). This is, of course, a reflection of the very large differences between densities and environmental variables between the surface and 10 cm. The signs of the factor score coefficients for PCI (Table 18), the correlation matrix (Table 17), and the 's of the simple regressions (Table 20) show that the analysis contrasts oxygen, pH, Eh, NO_2 with NH_3, PO_4, Si.

TABLE 16.—Analysis of variance for chemical variables on grass surface and 10 cm.

Elphidium: Elphidium mean densities at the grass surface and grass 10 cm are plotted in Figure 29. The summer maximum observed at the surface for Quinqueloculina was not observed for Elphidium (Appendix 2). Minima at the surface were observed in June and November which is similar to the pattern of Quinqueloculina (Appendix 2). At 10 cm a maximum occurred in March due to high number of individuals in two of the four replicates (Appendix 3). Once again, however, the densities at 10 cm were very low, averaging less than two individuals.

FIGURE 18.—Temperature measurements in °C.

Table 22 indicates the largest mean square is for the hypothesis contrasting depth. The π/3 periodicity with interaction is significant while the π/6 is not. The set of environmental variables are significant, and individual 's of the ω model for Eh and NH_3 were significant. F-ratios of all variables except temperature and salinity are significant for simple regressions (Table 20). The results of a multiple regression on the densities of Elphidium and the first three PC's of the environmental variables indicate that all three PC's, and, consequently, all the environmental variables contribute substantially (Table 23).

Ammonia: Ammonia densities for the grass surface and grass 10 cm are plotted in Figure 30. A maximum density was observed at the surface in July. Like Quinqueloculina and Elphidium, a minimum occurred in June (Appendix 2). Similar to the aforementioned taxa, at 10 cm the maximum was observed in March (Appendix 3). In general, densities were very low at 10 cm averaging slightly less than two individuals.

FIGURE 19.—Salinity measurements in °/00.

FIGURE 20.—Oxygen measurements in mg-at/1.

FIGURE 21.—pH measurements.

FIGURE 22.—Eh measurements in mV.

FIGURE 23.—NH_3 measurements in μg-at/l.

FIGURE 24.—PO_4 measurements in μg-at/l.

FIGURE 25.—Si measurements in μg-at/l.

FIGURE 26.—NO_2 measurements in μg-at/1.

FIGURE 27.—NO_2 + NO_3 measurements in μg-at/l.

Table 24 shows the results of the GLM analysis. Again the hypothesis for depth has a very large mean square and is highly significant. The π/3 periodicity with interaction is significant while the π/6 is not. The set of environmental variables are significant and the 's of the ω model for NH_3 and NO_2 + NO_3 are significant. The results of a multiple regression on the densities of Ammonia and the first three PC's of the environmental variables indicate that the first and third PC's are significant (Table 25). Consequently, all the variables except for salinity and NO_2 + NO_3 are involved. The analysis for the grass surface and 10 cm stands in marked contrast to the analysis for bare surface and grass surface where the F-ratio and R^2 was relatively small (compare Tables 11 and 25).

Bolivina: Bolivina mean densities at the grass surface and grass 10 cm are plotted in Figure 31. At the surface the maximum occurred in May and the June minimum observed for the three previously discussed taxa is also shown by Bolivina (Appendix 2). From July to September the density steadily decreased at the grass surface (Figure 31). At 10 cm the maximum occurred, similar to the previous taxa, in March. The average number of individuals observed was slightly less than one, and at seven sampling times no individuals were observed at 10 cm (Appendix 3).

Table 26 shows the statistical analysis of the GLM. The mean square for depth is once again large and highly significant. The hypotheses for π/6 periodicity and interaction, and π/3 interaction are significant. This combination is not observed for any of the other taxa analyzed. The set of environmental variables are significant, and the 's of the ω model for temperature and salinity are significant. The F-ratios for simple regressions on densities vs. environmental variables are all significant (Table 20). The results of a multiple regression on the densities of Bolivina and the first three PC's of the environmental variables (Table 27) indicate that all three PC's (all the environmental variables) are significant. Comparison of Tables 13 and 27 indicate that for the bare surface and grass surface only PC2 was significant while at the grass surface and 10 cm all three PC's were significant. Simple regressions for the bare and grass surface had four variables significant (Table 6), while at the grass surface and 10 cm all were significant (Table 20). The F-ratio for salinity at the bare surface and grass surface is significant and the 's for the ω model's for salinity in both analyses is significant. We recall that at the bare surface and grass surface the densities of Bolivina decrease during the period of our observations (Figure 16) and salinity exhibits the same trend (Figure 4). Salinity, then, may be important in regulating the density of Bolivina, but at 10 cm the decrease and increase in other variables probably overshadows its importance.

TABLE 17.—Correlation matrix for chemical variables on grass surface and 10 cm. 0.05 level is underlined.

TABLE 18.—Factor score coefficients for chemical variables for grass surface and 10 cm.

Chemical
variable

Factor

PC 1(45%)

PC2(15%)

PC3(10%)

Temperature

0.08

–0.25

0.76

Salinity

0.07

0.44

0.28

Oxygen

–0.17

0.11

–0.20

PH

–0.14

0.16

0.51

Eh

–0.21

–0.02

0.07

NH_3

0.20

0.17

0.03

PO_4

0.16

0.24

–0.03

Si

0.19

0.08

–0.18

NO_2

–0.12

0.23

–0.10

NO_2 + NO_3

–0.07

0.47

0.09

FIGURE 28.—Mean number of individuals of Quinqueloculina per 5 ml of sediment (density).

Ammobaculites: Ammobaculites mean densities for the grass surface and grass 10 cm are shown in Figure 32. In keeping with the low densities observed in June for the other taxa at the grass surface station, no living individuals of Ammobaculites were observed on 19 June (Appendix 2). At 10 cm, the maximum number of individuals (three) were observed, as with the other taxa, in March (Appendix 3). One living individual was observed in April and one in June (Appendix 3).

Table 28 displays the results of the statistical analysis of the GLM. The hypothesis for depth has the highest mean square and is significant. All of the periodicity hypotheses are significant except for π/3 interaction. The set of environmental variables are significant, and the 's of the ω model for salinity, oxygen, NO_2, and NO_2 + NO_3 are significant. The F-ratios for simple regressions on densities vs. environmental variables are significant for all variables except temperature and NO_2 + NO_3. Multiple regression of the densities of Ammobaculites and the first three PC's of the environmental variables (Table 29) indicate that the first and third PC's are significant. Therefore, all the environmental variables except for salinity and NO_2 + NO_3 are contributors according to the multiple regression analysis. As with most of the other taxa the F-ratio and R^2 for the multiple regression at the bare surface and grass surface are much smaller than at the grass surface and 10 cm (Tables 15 and 29).

TABLE 19.—Statistical analysis of GLM for Quinqueloculina for grass surface and 10 cm.

TABLE 20.—Values of F-ratio's for simple regressions on species densities and environmental variables at grass surface and grass 10 cm. (+ indicates signficant (.05 level) positive value of β; - significant negative value of β.)

Comparison of Analyses

For the three most abundant taxa, Quinqueloculina, Elphidium, and Ammonia, the difference in overall densities at the bare surface and grass surface stations is not significant. In contrast, at the grass surface and 10 cm the differences in overall density for all taxa are significant. This is not at all surprising. The “living zone” for foraminifera in this area was previously determined to be about 6 or 7 cm (Buzas, 1977). Clearly, a depth of 10 cm in this area is an inhospitable environment for foraminifera, and the observed living individuals may be due to haphazard excursions or to bioturbation by other organisms (Severin et al., 1982; Severin, 1987; Wetmore, 1988). The statistical analyses of the GLM for the grass surface and 10 cm confirm what is abundantly clear by glancing at the plots of densities at the grass surface and at 10 cm (Figures 28–32).

TABLE 21.—Regression of Quinqueloculina and principal components for grass surface and 10 cm.

In both comparisons hypotheses for periodicity are significant for all taxa except Bolivina at the bare surface and grass surface. Except for the aforementioned case, the periodicites differ (interaction hypotheses) for all taxa between the areas being compared. At the surface stations there was a spring maximum at the bare station which was not observed at the grass station where maximum densities occurred in summer. Densities were very low at 10 cm, but nevertheless, the significance of the interaction hypotheses indicates no synchronization between the surface and 10 cm.

Two-way ANOVA's on 10 environmental variables indicate that at the bare surface and grass surface most of these differ significantly with time while at the grass surface and 10 cm with depth. The analyses of both GLMs indicate that the environmental variables are significant for all taxa. The environmental variables are highly correlated so that the significance of any one is difficult to determine. In general, oxygen, pH, and Eh are positively correlated with one another, and negatively with NH_3. Principal component analyses on both data sets indicate that the first three PC's account for all of the variables. Multiple regression of the first three PC's and densities of taxa indicate higher F-ratios and R^2 for the grass surface and 10 cm analysis. In this analysis, PCI and PC3 are always significant, and all three are for Bolivina. On the other hand, for the bare surface and grass surface PCI and PC2 are significant for Elphidium and Ammobaculites, and PCI and PC3 for Quinqueloculina. Although these PC's also account for most of the variables and are significant, the strength of the regression relationship as judged by R^2 and F-ratios are much smaller. For Bolivina only the F-ratio for PC2 is significant and salinity contributes heavily to this PC. This species also has a very high F-ratio for salinity on simple regression and is further identified as a significant in the ω model. At the bare surface and grass surface only PC3 (accounting for 14% of the variability) is significant for Ammonia. NO_2 is the largest contributor to this PC, and like salinity for Bolivina, is also identified by simple regression and in the ω model.

Thus, no simple relationship between one or two environmental variables and density emerges. In both analyses oxygen, pH, and Eh are contrasted with NH_3, and in the grass surface and 10 cm NO_2 is added to the former and PO_4 and Si to the latter. Except for Bolivina, the most commonly considered variables, temperature and salinity, have little involvement, and any attempt to predict faunal densities from them is futile. The very large change in density between the surface and 10 cm, perhaps, equivalent to a faunal change, is much more strongly related to the environmental variables than the smaller significant change with time at the surface sites.

FIGURE 29.—Mean number of individuals of Elphidium per 5 ml of sediment (density).

Comparison with Other Studies

Quinqueloculina is the most abundant taxon making up about 75% of the total living foraminifera at the surface stations. The fortnightly observations of mean densities from March until November, 1978, exhibit a pronounced periodicity. The differences between maxima and minima densities are two orders of magnitude at both stations. At the grass station the maximum was recorded in summer and at the bare station in spring. In Aransas Bay, Texas, Phleger and Lankford (1957) also observed a summer maximum for Quinqueloculina. Jones and Ross (1979) found Quinqueloculina only during the summer months in Samish Bay, Washington. The temperature regimes in Aransas Bay (19°−30°C) and in the Indian River (22°–32°C)are similar. However, the waters of Samish Bay are much colder (5°–20°C),and the maximum at Samish Bay is the equivalent to the minimum at the other two areas.

TABLE 22.—Statistical analysis of GLM for Elphidium for grass surface and 10 cm.

TABLE 23.—Regression of Elphidium and principal components for grass surface and 10 cm.

Elphidium is the second most abundant taxon comprising about 14% of the total number of living individuals at the two surface stations. The genus is composed mainly of E. mexicanum and E. gunteri. This taxon did not have significant differences between stations, but did exhibit a π/3 periodicity and interaction. Maxima occurred at the bare surface in early spring and at the grass surface in early summer. The spring maximum at the bare surface was much larger than at the grass surface. A number of researchers have demonstrated through observation of juveniles and density changes that E. excavatum reproduces all year round, often at different rates with maxima varying from year to year (Buzas, 1965, 1969; Haake, 1967; Haman, 1969; Wefer, 1976). Other species of this genus follow a similar pattern (Boltovskoy and Lena, 1969). The different timing between stations (interaction) observed here was also observed by Buzas (1969) in the Choptank River, Maryland. Thus, the results of the present study are in accord with earlier observations.

FIGURE 30.—Mean number of individuals of Ammonia per 5 ml of sediment (density).

The environmental variables for Elphidium were significant as a group. Simple regressions on individual variables were highest for salinity and pH, however, the first two PC's proved significant and they account for all the variables except NO_2. Buzas (1969) using a similar analysis concluded the environmental variables were significant as a group as did Wefer (1976).

Ammonia, consisting of A. beccarii (most of the individuals belong to the form called tepida), constitutes about 8% of the total living population at the bare and grass surface stations. More information is available for this species than any other, much of which is summarized by Walton and Sloan (1990). In this study, A. beccarii showed a π/3 periodicity with interaction. The bare surface had maxima in spring, summer, and fall while the grass surface had maximum densities in summer. This species also exhibited periodicity in the Choptank River, Maryland (Buzas, 1969), Texas Bays (Phleger and Lankford, 1957), Samish Bay, Washington (Jones and Ross, 1979), and Puerto Deseado (Boltovskoy and Lena, 1969). As in this study, Phleger and Lankford (1957) and Buzas (1969) reported different densities with time between stations, while Boltovskoy and Lena (1969) between years. On the other hand, in Narragansett Bay, Rhode Island, Brooks (1967) found no difference in densities between monthly sampling during 1963, and, likewise, Buzas et al. (1977) found no difference in densities between monthly sampling during 1969–1970 in Jamaica. Most authors agree that reproduction takes place throughout the year. Given enough data, it seems likely that a particular station could show periodicity in some years, and not in others, while a nearby station might behave in an altogether different manner.

TABLE 24.—Statistical analysis of GLM for Ammonia for grass surface and 10 cm.

TABLE 25.—Regression of Ammonia and principal components for grass surface and 10 cm.

FIGURE 31.—Mean number of individuals of Bolivina per 5 ml of sediment (density).

In the present study of Ammonia, analysis by the GLM showed that the environmental variables were significant as a group. Simple regressions on density vs. individual environmental variables indicated that only salinity and NO_2 were significant. Regression analysis on the PC's indicated that only the third PC accounting for 14% of the variability in the environmental variables was significant. The largest factor score coefficients for PC3 are NO_2, Si, and temperature. Interestingly, the sign of the simple regression coefficient for temperature, although not significant, was negative. In the Choptank River, Maryland, Buzas (1969) found the group of measured environmental variables were significant for Ammonia; however, in Jamaica, they were not (Buzas et al., 1977). The laboratory work of Bradshaw (1961) and Schnitker (1974) indicate a temperature of at least 17°−22°C is required for reproduction (Walton and Sloan, 1990, give an extensive discussion). The temperatures in Jamaica and in the present study are always above these limits. In the Choptank River, however, the temperature is below 15°C for 7 months of the year (Buzas, 1969), and Ammonia exhibits significant increases in density during this period. In Narragansett Bay where temperatures vary from 0°−20°C, Brooks (1967) found no significant difference in density with time over the period of a year. Both of these authors sampled with replicates to offset the variation inherent because of spatial distribution. In Puerto Deseado, Argentina, Boltovskoy (1964) and Boltovskoy and Lena (1969) report, through observations of juveniles, continuous reproduction of this species where the maximum temperature is only 15°C. These observations suggest to us that populations of A. beccarii can adjust to lower temperatures for reproduction than were observed in the laboratory. The alternative suggested by Walton and Sloan (1990) is that seasonal trends may be an artifact due to the sampling of patchy distributions. We believe the replication and use of independent hypotheses through the analysis of variance technique (Brooks, 1967; Buzas, 1969) and observations of juveniles (Boltovskoy, 1964) make this conclusion unlikely.

TABLE 26.—Statistical analysis of GLM for Bolivina for grass surface and 10 cm.

TABLE 27.—Regression of Bolivina and principal components for grass surface and 10 cm.

FIGURE 32.—Mean number of individuals of Ammobaculites per 5 ml of sediment (density).

TABLE 28.—Statistical analysis of GLM for Ammobaculites for grass surface and 10 cm.

TABLE 29.—Regression of Ammobaculites and principal components for grass surface and 10 cm.

Bolivina, consisting mainly of B. striatula, makes up about 1% of the total living population. The mean number of individuals at the grass station was about 7 and at the bare station 3, which was statistically significantly different. At both stations there appears an overall decrease in density during the sampling period. However, none of the hypotheses for periodicity in the GLM were significant. In Jamaica (Buzas et al., 1977), B. striatula was the most abundant species and it did exhibit an overall periodicity, even though most of the species analyzed in that study did not. No other data are available. Perhaps, as more data becomes available, this species will exhibit the same unpredictable behavior cited above for Ammonia.

In the GLM for Bolivina the environmental variables are significant as a group. Simple regressions indicate salinity, PO_4, Si, and NO_2 + NO_3 are significant. Multiple regression of densities and PC's found only PC2 significant and the factor score coefficients indicate these same variables are the main components of PC2. Buzas et al. (1977) found no statistical relationship between environmental variables and densities for this species in Jamaica.

Ammobaculites, consisting mainly of A. exiguus, makes up about 1 % of the total living population. At the grass surface the mean density is about 6 and at the bare surface 1, which is statistically significantly different. The π/3 overall periodicity and interaction hypotheses are also significant. At the grass surface there is an increasing trend in density during the sampling period while at the bare surface a spring maximum is followed by very low densities during the sampling period. In the Choptank River, Maryland, Buzas (1969) also found a π/3 overall periodicity and interaction hypotheses significant for this species. Maximum densities occurred in all seasons. Based on size distribution histograms which showed mixed age groups throughout the year, Phleger and Lankford (1957) also concluded that A. salsus (probably the same or a closely related species) reproduced during all seasons of the year.

The null hypothesis for the environmental variables in the GLM for Ammobaculites was rejected. Simple regressions on density and individual environmental variables indicated temperature, salinity, oxygen, and NH_3 were significant. Regression analyses of density and the PC's indicated PCI and PC2 were significant. These two components account for all the variables except NO_2. Buzas (1969) also found the environmental variables were significant for this species in the Choptank River, Maryland.

The life cycle of some foraminifera such as Elphidium crispum and Glabratella ornatissima produces a marked yearly (often spring and summer) increase in density (Myers, 1942; Erskian and Lipps, 1987). The majority of species such as those studied here apparently reproduce continuously, although they need not do so at the same rate. The interplay of life cycle behavioral characteristics and environmental variables may be more favorable at some particular times than at others. Furthermore, predation severely depletes foraminiferal densities (Buzas, 1978), and differential predation may decrease density at a particular location. Indeed, the density of potential predators often varies from season to season and year to year (Young et al., 1976). On the other hand, these causes of density regulation may offset each other and the same species may sometimes not exhibit periodicity. The observations of various researchers cited above for Ammonia which sometimes shows periodicity and sometimes not is best explained in this fashion.

Appendix 1

Bare Surface

Number of individuals per 5 ml of sediment

Appendix 2

Grass Surface

Number of individuals per 5 ml of sediment.

Appendix 3

Grass 10 cm

Number of individuals per 5 ml of sediment.

Appendix 4

Bare Surface

Pore water chemistry.

Appendix 5

Grass Surface

Pore water chemistry.

Appendix 6

Grass 10 cm

Pore water chemistry.

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Manuscripts intended for series publication receive substantive review (conducted by their originating Smithsonian museums or offices) and are submitted to the Smithsonian Institution Press with Form S1–36, which must show the approval of the appropriate authority designated by the sponsoring organizational unit. Requests for special treatment—use of color, foldouts, case-bound covers, etc.—require, on the same form, the added approval of the sponsoring authority.

Review of manuscripts and art by the Press for requirements of series format and style, completeness and clarity of copy, and arrangement of all material, as outlined below, will govern, within the judgment of the Press, acceptance or rejection of manuscripts and art.

Copy must be prepared on typewriter or word processor, double-spaced, on one side of standard white bond paper (not erasable), with 1¼″ margins, submitted as ribbon copy (not carbon or xerox), in loose sheets (not stapled or bound), and accompanied by original art. Minimum acceptable length is 30 pages.

Front matter (preceding the text) should include: title page with only title and author and no other information; abstract page with author, title, series, etc., following the established format; table of contents with indents reflecting the hierarchy of heads in the paper; also, foreword and/or preface, if appropriate.

First page of text should carry the title and author at the top of the page; second page should have only the author's name and professional mailing address, to be used as an unnumbered footnote on the first page of printed text.

Center heads of whatever level should be typed with initial caps of major words, with extra space above and below the head, but no other preparation (such as all caps or underline, except for the underline necessary for generic and specific epithets). Run-in paragraph heads should use period/dashes or colons as necessary.

Tabulations within text (lists of data, often in parallel columns) can be typed on the text page where they occur, but they should not contain rules or numbered table captions.

Formal tables (numbered, with captions, boxheads, stubs, rules) should be submitted as carefully typed, double-spaced copy separate from the text; they will be typeset unless otherwise requested. If camera-copy use is anticipated, do not draw rules on manuscript copy.

Taxonomic keys in natural history papers should use the aligned-couplet form for zoology and may use the multi-level indent form for botany. If cross referencing is required between key and text, do not include page references within the key, but number the keyed-out taxa, using the same numbers with their corresponding heads in the text.

Synonymy in zoology must use the short form (taxon, author, year:page), with full reference at the end of the paper under “Literature Cited.” For botany, the long form (taxon, author, abbreviated journal or book title, volume, page, year, with no reference in “Literature Cited”) is optional.

Text-reference system (author, year:page used within the text, with full citation in “Literature Cited” at the end of the text) must be used in place of bibliographic footnotes in all Contributions Series and is strongly recommended in the Studies Series: “(Jones, 1910:122)” or “…Jones (1910:122).” If bibliographic footnotes are required, use the short form (author, brief title, page) with the full citation in the bibliography,

Footnotes, when few in number, whether annotative or bibliographic, should be typed on separate sheets and inserted immediately after the text pages on which the references occur. Extensive notes must be gathered together and placed at the end of the text in a notes section.

Bibliography, depending upon use, is termed “Literature Cited,” “References,” or “Bibliography.” Spell out titles of books, articles, journals, and monographic series. For book and article titles use sentence-style capitalization according to the rules of the language employed (exception: capitalize all major words in English). For journal and series titles, capitalize the initial word and all subsequent words except articles, conjunctions, and prepositions. Transliterate languages that use a non-Roman alphabet according to the Library of Congress system. Underline (for italics) titles of journals and series and titles of books that are not part of a series. Use the parentheses/colon system for volume (number):pagination: “10(2):5–9.” For alignment and arrangement of elements, follow the format of recent publications in the series for which the manuscript is intended. Guidelines for preparing bibliography may be secured from Series Section, SI Press.

Legends for illustrations must be submitted at the end of the manuscript, with as many legends typed, double-spaced, to a page as convenient.

Illustrations must be submitted as original art (not copies) accompanying, but separate from, the manuscript. Guidelines for preparing art may be secured from the Series Section, SI Press. All types of illustrations (photographs, line drawings, maps, etc.) may be intermixed throughout the printed text. They should be termed Figures and should be numbered consecutively as they will appear in the monograph. If several illustrations are treated as components of a single composite figure, they should be designated by lowercase italic letters on the illustration; also, in the legend and in text references the italic letters (underlined in copy) should be used: “Figure 9b.” Illustrations that are intended to follow the printed text may be termed Plates, and any components should be similarly lettered and referenced: “Plate 9b.” Keys to any symbols within an illustation should appear on the art rather than in the legend.

Some points of style: Do not use periods after such abbreviations as “mm, ft, USNM, NNE.” Spell out numbers “one” through “nine” in expository text, but use digits in all other cases if possible. Use of the metric system of measurement is preferable; where use of the English system is unavoidable, supply metric equivalents in parentheses. Use the decimal system for precise measurements and relationships, common fractions for approximations. Use day/month/ year sequence for dates: “9 April 1976.” For months in tabular listings or data sections, use three-letter abbreviations with no periods: “Jan, Mar, Jun,” etc. Omit space between initials of a personal name: “J.B. Jones.”

Arrange and paginate sequentially every sheet of manuscript in the following order: (1) title page, (2) abstract, (3) contents, (4) foreword and/or preface, (5) text, (6) appendices, (7) notes section, (8) glossary, (9) bibliography, (10) legends, (11) tables. Index copy may be submitted at page proof stage, but plans for an index should be indicated when the manuscript is submitted.