To test the pore density in benthic foraminifera as a potential proxy for bottom-water oxygenation, pore density analyses were carried out on tests of living (rose Bengal-stained) specimens of the deep-infaunal and anoxia-tolerant foraminiferal species Globobulimina turgida. Three stations within and two stations below the oxygen minimum zone (OMZ) off Namibia were investigated and compared to in situ-measured bottom-water oxygen content (BW-O2). Pore density was first conventionally assessed by rather time-consuming manual pore counting on SEM photographs and measurement of the analyzed test areas. To significantly shorten the measurement time we tested and evaluated an automation of the pore density measurement using the image analysis software package analySIS (version 5.0, Olympus Soft Imaging Solutions). Pore density data from automated analyses are compared to manually acquired data from G. turgida. Our study shows almost identical results for both manually and automatically acquired data. Consequently, we assume that the new technique provides an alternative and more rapid method to analyze the pore density of foraminifera.

For both methods, our results show a distinct negative linear correlation (automatically analyzed pore density: τ = −0.50, p < 0.001; manually analyzed pore density: τ = −0.49, p < 0.001) between pore density and BW-O2, suggesting that G. turgida increases its pore density in response to decreasing oxygen. Thus, we suggest that, similar to other recently described low-oxygen-tolerant benthic foraminiferal species, G. turgida may improve its O2 uptake by increasing pore density to survive in low-oxic environments. This morphological adaption might be useful for future studies to establish an independent proxy for BW-O2. In addition, pore density has been compared to in situ-measured bottom-water nitrate concentration (BW-NO3). Our investigation of the pore density-to-BW-NO3 relationship for G. turgida suggests that nitrate seems to be a minor factor influencing pore density in this species compared to BW-O2.


Benthic foraminiferal assemblages are a valuable proxy for paleoceanographers to qualitatively estimate past bottom-water oxygenation and organic-carbon flux to the seafloor, two parameters that appear to play a major role in controlling benthic foraminiferal species composition and microhabitat structure (e.g., Lutze & Coulbourn, 1984; Mackensen & Douglas, 1989; van der Zwaan et al., 1999; Altenbach et al., 2003; Gooday, 2003). Oxygenation at the seafloor is mainly determined by the oxygen content of the respective bottom-water mass and the amount of organic-matter supply (i.e., oxygen consumption during its decomposition). Benthic foraminiferal species that are considered typical of low-oxic environments are also common in high productivity areas (e.g., Sen Gupta & Machain-Castillo, 1993; Gooday, 1994, among many others). However, there are no benthic foraminiferal species exclusively occurring in low-oxic environments (Sen Gupta & Machain-Castillo, 1993). Hence, by using assemblage data alone, it remains difficult to distinguish between the effects of these two parameters on observed changes in fossil faunas. Existing approaches of using benthic foraminiferal indicator taxa and/or faunal diversity as oxygen proxy still lack reliable calibrations on living faunas and Recent data sets (Kaiho, 1994; Schmiedl et al., 2003; Jorissen et al., 2007). Accordingly, the development of an independent paleo-oxygenation proxy would be an important step forward to separate changes in oxygenation and organic-matter flux.

Several studies suggested that variations in pore characteristics (i.e., number and size) in benthic foraminiferal tests are related to different oxygen levels of the surrounding bottom- and/or pore-waters (e.g., Corliss, 1985; Perez-Cruz & Machain-Castillo, 1990; Glock et al., 2011, 2012; Kuhnt et al., 2013). There is clear evidence that infaunal species respond to lower oxygen content within the sediment by having higher pore densities, whereas epifaunal species often produce differently sized pores on either side of the test (e.g., Corliss, 1985; Corliss & Emerson, 1990; Roshoff & Corliss, 1992; Rathburn & Corliss, 1994). Furthermore, modern assemblages of oxygen-poor habitats have been found to be dominated by highly perforated, thin-walled foraminifera, which have been interpreted as indicative of oxygen-depleted environments (e.g., Bernhard, 1986; Perez-Cruz & Machain-Castillo, 1990; Sen Gupta & Machain-Castillo, 1993; Kaiho, 1998). For example, specimens of Hanzawaia nitidula (Bandy) from low-oxic environments show higher pore densities than specimens from well-oxygenated bottom waters (Perez-Cruz & Machain-Castillo, 1990). A similar increase in pore density under dysoxic conditions has also been observed in low-oxygen tolerant species of the genera Bolivina and Fursenkoina [B. albatrossi (Cushman), Gary et al., 1989; B. spissa (Cushman), Glock et al., 2011; B. pacifica (Cushman & Culloch), Kuhnt et al., 2013; and F. mexicana (Cushman), Kuhnt et al., 2013]. Laboratory culture (Moodley & Hess, 1992) and in situ experiments (Kitazato & Tsuchiya, 1995) on Ammonia beccarii (Linné) reveal that chambers formed under dysoxic conditions have a significantly higher pore density and larger pores than chambers constructed in well-oxygenated waters. This pattern seems to indicate that a higher pore density and/or larger pores are a reaction of the foraminifera to decreasing oxygen concentrations (e.g., Corliss, 1985).

Leutenegger & Hansen (1979) and Bernhard et al. (2010) have shown that in foraminiferal specimens from low-oxic habitats mitochondria (cell organelles involved in respiration) were more abundant near the pores than in specimens from well-oxygenated environments. This co-variance implies that pores in benthic foraminiferal tests serve as conduits for gas exchange (i.e., uptake of O2 and release of metabolic CO2; Hottinger & Dreher, 1974; Berthold, 1976). Thus, increasing pore size and number of pores in the test wall increases the ability for oxygen uptake.

These different lines of evidence point to a consistent relationship between bottom-water oxygenation and test porosity. A better understanding of the factors controlling pore density and its relationship to oxygenation clearly underlines its potential to form the basis of a paleo-oxygenation proxy. However, the pore density in benthic foraminiferal tests is currently assessed by the rather time-consuming manual pore counting on SEM photographs and measurement of the analyzed test areas (Glock et al., 2011; Kuhnt et al., 2013). Automatization of pore density measurements would allow faster data acquisition, higher resolution, and a better reproducibility of data, and is, therefore, an essential prerequisite for establishing a useful bottom-water-oxygenation proxy.

In the present study, we investigated the relationship between the oxygen concentration of the overlying bottom waters (BW-O2) and the pore density for the deep-infaunal and anoxia-tolerant species Globobulimina turgida (Appendix 1) from the oxygen minimum zone (OMZ) off Namibia. In addition, pore density was compared with the bottom-water nitrate content (BW-NO3).

Another important aim of our study is to automate pore density measurement by using the image analysis software analySIS (version 5.0, Olympus Soft Imaging Solutions), developed in order to significantly shorten the measurement procedure. This approach has been tested on the SEM photographs of G. turgida and compared with the pore density values obtained by the conventional method of manual pore counting.


Sample Locations and Procedure

The relationship between pore density in tests of Globobulimina turgida and BW-O2 was analyzed on living specimens from five stations situated within (Stations 1704, 1713, 3717) and below (Stations 1712, 3704) the OMZ off Namibia in the SE Atlantic (Fig. 1). Sediment samples were collected with a Multicorer during two cruises of R/V Meteor in 1992 (M20/2) and 1996 (M34/2). For core processing onboard see Schmiedl et al. (1997) and Licari & Mackensen (2005), respectively. The selected stations cover a wide gradient in bottom-water-oxygen concentrations, ranging between 1.15–4.62 ml L−1 (Table 1).

In total, 43 rose Bengal-stained specimens were picked from the >125-μm fraction at sediment depths of 2–3 and 3–4 cm. Tests were mounted on aluminium stubs, sputtered with gold, and photographed with a JEOL JSM 6490 scanning electron microscope (SEM) at the Institute of Geosciences, Goethe-University Frankfurt.

Oxygen concentration of bottom water at the stations (Table 1) was measured from seawater overlying the sediment in Multicorer tubes taken on the same deployment as those for benthic foraminiferal analyses. Immediately after core recovery, oxygen concentration was determined using the Winkler titration method (Glud et al., 1994; Wefer et al., 1997).

Bottom-water nitrate concentrations were measured photometrically by an autoanalyser using standard methods (Wefer et al., 1997). For three sites (1704, 1712, 1713) where BW-NO3 values were not available, we used BW-NO3 values derived from Ocean Data View Version ODV4 (http://odv.awi.de; Garcia et al., 2010; Table 1).

Pore Density Measurements

Specimens of G. turgida exihibit oblong-shaped pores on the outer side of the tests (Fig. 2, this study), while the inner side of the tests has small round pores (Höglund, 1947). This particular pore morphology has to be considered when the area of pores and, therefore, the overall porosity of this species are estimated. When pore density is considered (as is the case in our study), pore morphology has no effect.

Following the measurement procedure of Kuhnt et al. (2013; Fig. 2), pore counts were carried out on SEM photographs (fields), taken with a constant magnification of ×2000. Due to the globular shape of G. turgida, pores were counted on a succession of fields along the final chamber to avoid miscounting pore numbers in the frame areas of the specimens. The final chamber was chosen assuming that the last chamber of the test was built under the sampled bottom-water oxygen and nitrate concentrations. Fields were arranged in the center of the final chamber from the aperture downwards. The analyzed field area was calculated to be 3105 μm2, using the image analysis software AxioVision 4.7 from ZEISS. Due to different test sizes, the number of fields varied between 3–15/specimen (see Appendix 2). Pore densities are expressed as pores/μm2 of measured area (Fig. 3; Table 2). The time for manual image processing (pore counting and area measurement) took about ten minutes on average, depending on the number of pores per image. Analyzed areas in the manual setup were chosen as large as possible to increase the statistical significance of the data set.

Automated pore density measurements were carried out with image analysis software (analySIS, version 5.0, Olympus Soft Imaging Solutions) on the same SEM images of G. turgida used in the manual analyses. Images in tif© format were size-calibrated. Areas of 300 μm (15 × 20 μm) were automatically analyzed for pore numbers (Fig. 2). The gray scale was adjusted individually to maximum contrast between pore area and test wall. Frames (analyzed areas) were manually positioned for an orthogonal view of the test wall and to avoid analysis of pores covered by microparticles or cut at the edge of the frame. Only images with sufficient contrast and optimum yield were included in the final data set. Automated image processing took about 90 seconds, including conversion of the tif© format, size calibration, frame selection, brightness calibration, morphometric analysis (50+ parameters), and data output in Excel® format. Frames in the automated setup were chosen as small as possible to avoid contortion of pore morphology and deviation from the original pore size (data are not shown here), which could be caused by the curved test wall. In turn, frames were chosen large enough to derive a statistically significant data set.

Data sets derived from the manual and automated counting procedures were chosen at sizes of maximum difference to test for statistical robustness of the pore density-to-BW-O2 relationship. Student’s t (1.081, at n = 42/43) and Fisher’s F (1.068, at y = 83) tests confirm that both pore-density data from manual and automated analyses are not significantly different, at normal distribution (Appendices 2 and 3), which is essential for using automated counting in future studies. Pore density measurements would naturally be applied to differently sized surface areas of foraminifers (or other biota), and therefore, would necessarily compare count areas of different sizes.

Statistical Analyses

The non-parametric Kendall-Theil robust line fitting (Kendall, 1938; Theil, 1950; Sen, 1968) was applied to approximate the strength of the relationship of the pore density measured in G. turgida to the oxygen and nitrate concentrations of the overlying bottom water. Calculations were carried out with the R software (R Development Core Team, 2011), in which the regression analysis was implemented by using the equations given in Conover (1980) and Helsel & Hirsch (2002). The slope of the linear regression is computed as the median of all possible pairwise slopes in each data set (Helsel & Hirsch, 2002), and the intercept of the linear regression lines is calculated by the median of the y values minus the line’s dip multiplied by the median of the x values (Conover, 1980). For evaluation of the correlation between pore density and bottom-water oxygen and nitrate content, Kendall’s tau (τ) was used, which is resistant to the outliers effect and enables the measurement of monotonic correlations (Kendall, 1938; Helsel & Hirsch, 2002). The significance of the Kendall-Theil linear relationship was tested by measuring the monotonic dependence of y on x with the Kendall’s S statistic, which is calculated by subtracting the number of pairs (x, y), where y decreases as x increases, from the number of pairs where y increases as x decreases (Helsel & Hirsch, 2002).


Comparison Between Automatically and Manually Measured Pore Density

The pore density of Globobulimina turgida was determined for 5–10 specimens in each of the studied stations. Comparison of mean pore density achieved by both automated and manual methods plotted against the bottom-water oxygen content is given in Figures 3a–c and Table 2.

Average pore densities produced with the image analysis software analySIS (version 5.0, Olympus Soft Imaging Solutions) vary between 0.023–0.045 pores μm−2 with a standard deviation of 0.005–0.009 pores μm−2 (Fig. 3a; Table 2). Average pore densities resulting from manual measurement, range from 0.020–0.043 pores μm−2 (standard deviation: 0.005–0.010 pores μm−2; Fig. 3b; Table 2). Direct comparison of both data sets shows that automatically measured mean pore densities are only slightly higher (about 0.001–0.002 pores μm−2) than the manually calculated pore densities (Fig. 3c). In addition, the automatically measured densities show a similar significant relationship with declining BW-O2 (τ = −0.50; p < 0.001) as the manually derived pore densities (τ = −0.49; p < 0.001). Hence, although the automatically analyzed area (300 μm2) is considerably smaller than the manually analyzed one (3105 μm2), pore density values derived from both methods are not significantly different from each other (Figs. 3a–c; Table 2). This strongly suggests that both techniques provide similar results for benthic foraminiferal pore density.

Relationship Between Pore Density and BW-O2

Comparison of pore density to bottom-water oxygen content reveals a negative linear correlation with increasing pore densities as BW-O2 concentration declines (Figs. 3a–c; Table 2). This is in good agreement with previous studies that report increasing pore density with decreasing dissolved-oxygen content for low-oxygen tolerant species of the genera Bolivina and Fursenkoina (Gary et al., 1989; Glock et al., 2011; Kuhnt et al., 2013). A functional relationship between pores and BW-O2 is also inferred by the fact that specimens of low-oxygen tolerant species from oxygen-depleted habitats show clusters of mitochondria near the inner pore terminations, whereas in specimens from well-oxygenated environments mitochondria are more evenly distributed throughout the cytoplasm (Leutenegger & Hansen, 1979; Bernhard et al., 2010). In specimens of B. pacifica from low-oxygen habitats in the Santa Barbara Basin, Bernhard et al. (2010) further discovered previously undescribed cytoplasmic membrane invaginations within the pore plugs, which supposedly facilitate efficient transport of oxygen to the mitochondria.

For G. turgida, little is known about the intracellular structure. Transmission electron microscopy (TEM) examination of individual G. pseudospinescens (Emiliani) specimens (= G. turgida after a more thorough taxonomic analysis, according to Piña-Ochoa et al., 2009) revealed mitochondria within the cytoplasm (Risgaard-Petersen et al., 2006). However, these authors investigated neither the relationship between the mitochondria and pores, nor the distribution of mitochondria under different dissolved-oxygen levels.

According to our data, it seems likely that similar to the low-oxygen tolerant species B. pacifica and F. mexicana (Kuhnt et al., 2013), G. turgida might also increase its pore density to improve mitochondrial oxygen uptake in response to decreasing oxygen levels. In addition to interpretations based on benthic foraminiferal assemblage counts and geochemical proxies, using pore density counts of specific benthic foraminifera might provide the possibility to enhance the reliability of paleoceanographic recontructions, where it is at present difficult to separate changes in oxygenation and organic-matter flux. Distinguishing between those factors which influence benthic foraminiferal assemblage patterns would be an important step forward for future paleoceanographic and paleoecological reconstructions.

Influence of BW-NO3 on Pore Density

A linear relationship also exists between pore density and BW-NO3, showing a decrease in pore density with increasing BW-NO3 concentration (Figs. 4a–c; Table 2). Recent studies have demonstrated that G. turgida is able to accumulate intracellular nitrate stores, which can be used for anaerobic respiration through complete denitrification to dinitrogen (N2) gas (Risgaard-Petersen et al., 2006; Piña-Ochoa et al., 2009; Koho et al., 2011). Additional studies suggest that the specific advantage of the denitrification process appears to be present among many other benthic foraminiferal genera as well (Høgslund et al., 2008; Glud et al., 2009; Piña-Ochoa et al., 2010; Bernhard et al., 2012a, b). These intracellular nitrate stores subsequently facilitate respiration when oxygen is absent, and thus may be one of the reasons why these taxa survive temporary anoxia (Risgaard-Petersen et al., 2006; Høgslund et al., 2008; Piña-Ochoa et al., 2009). Risgaard-Petersen et al. (2006) estimated that G. turgida can survive anoxia for approximately 25 days on average, if respiring through the intracellular nitrate pool only, while, in a laboratory experiment on G. turgida, some specimens were observed to survive up to 56 days (Piña-Ochoa et al., 2009).

The process of denitrification in benthic foraminifera has not been clarified yet (Høgslund et al., 2008). Koho et al. (2011) presumed that G. turgida may perform nitrate respiration via pseudopodia (i.e., through the presence of mitochondria over the pseudopodial network and its periphery), while Risgaard-Petersen et al. (2006) suggested that this species may use its mitochondria within the cytoplasm for nitrate respiration. The involvement of pores in denitrification has been recently suggested as a third option for B. spissa from the OMZ on the continental slope off Peru (Glock et al., 2011).

According to these observations, it could be hypothesized that pores may play a role in the nitrate metabolism of G. turgida, and therefore, BW-NO3 may be an important factor controlling pore density, as has been suggested for B. pacifica and F. mexicana from the OMZ off Namibia (Kuhnt et al., 2013). Our investigation of the pore density-to-BW-NO3 relationship for G. turgida reveals a strong linear correlation (automatically analyzed pore density: τ = −0.51, p < 0.001; manually analyzed pore density: τ = −0.49, p < 0.001; Figs. 4a–c; Table 2). Similar to a scenario recently proposed for B. spissa (Glock et al., 2011), G. turgida possibly optimizes its denitrification abilities by accumulating more mitochondria to efficiently use the remaining nitrate when less nitrate is available, resulting in higher pore densities. A laboratory experiment on G. turgida (Koho et al., 2011), however, revealed higher total nitrate accumulation rates under well-oxygenated conditions. This is related to the significantly higher energy yield of O2 respiration, facilitating concentration of more nitrate with less effort. Thus, as G. turgida shows lower pore density values under well-oxygenated conditions (Fig. 3, Table 2), it would be difficult to explain the higher nitrate uptake when the pore density is low. Furthermore, the anoxia-tolerant and nitrate-collecting (Piña-Ochoa et al., 2009) species Chilostomella oolina (Schwager) did not show any significant relationship between its pore density and BW-NO3 (Kuhnt et al., 2013). According to these observations we assume that nitrate may have only a minor influence on the pore density of G. turgida. According to our limited data set, however, the role of pores in the denitrification process of G. turgida and other benthic foraminiferal species requires additional studies, and needs to be further clarified.

Inter-Specific Comparison on the Pore Density-to-BW-O2 Relationship

Comparison of the pore density and pore density-to-BW-O2 relationship of G. turgida with B. pacifica and F. mexicana (Kuhnt et al., 2013) shows that the three species exhibit interspecific differences in mean values and linear slopes (Fig. 5). While the shallow-infaunal species B. pacifica shows a steep pore density-to-BW-O2 gradient, both deep-infaunal taxa G. turgida and F. mexicana exhibit more flat and nearly parallel trendlines. Furthermore, B. pacifica shows higher pore densities if BW-O2 is <2 ml L−1. These interspecific differences in pore density and the pore density-to-BW-O2 relationship might reflect different tolerance thresholds due to species-specific microhabitat preferences.

The deep-infaunal F. mexicana appears to be more resistant to persistent oxygen deficiency as shown by its usual microhabitat around the anoxic boundary in better-oxygenated sediments (Jorissen et al., 1998; Licari et al., 2003). A higher adaption to low-oxic conditions than B. pacifica has also been presumed for G. turgida, since Globobulimina species are common inhabitants of anoxic environments (e.g., Sen Gupta & Machain-Castillo, 1993), and often occur in deep-infaunal habitats below the oxic sediment layers (Mackensen & Douglas, 1989; Rathburn & Corliss, 1994; Fontanier et al., 2005). This assumption is corroborated by studies on eastern Mediterranean sapropels, where high abundances of Globobulimina spp., F. mexicana and F. cf. F. mexicana were found directly below and even within sapropel layers (e.g., Jorissen, 1999; Casford et al., 2003; Schmiedl et al., 2003; Kuhnt et al., 2007).

The shallow-infaunal B. pacifica, on the contrary, is well-known to dominate low-diversity assemblages inhabiting oxygen-depleted habitats (O2 < 0.5 ml L−1) within OMZs (Sen Gupta & Machain-Castillo, 1993; Schmiedl et al., 1997), but apparently thrives within a wide range of dissolved-oxygen concentrations (Sen Gupta & Machain-Castillo, 1993). This large range of tolerated oxygen concentrations might result in a pronounced morphological adaptation (i.e., pore density change) as recently suggested by Kuhnt et al. (2013). According to the above mentioned lines of evidence, we speculate that deep-infaunal species may be less susceptible to changes in BW-O2 and, therefore, exhibit a less pronounced increase in pore density than shallow-infaunal taxa that are more susceptible to oxygen deficiency.

In addition, the observed interspecific differences in pore density-to-BW-O2 relationship may be attributed to the species-specific ability for vertical microhabitat changes in response to different BW-O2 and related pore-water oxygen gradients. According to the TROX model of Jorissen et al. (1995) and confirmed by numerous observations (e.g., Shirayama, 1984; Alve & Bernhard, 1995; Fontanier et al, 2002; Koho & Piña-Ochoa, 2012), deep-infaunal taxa are able to shift their preferred microhabitat to shallower intervals under the influence of lower BW-O2. Accordingly, deep-infaunal taxa, such as G. turgida, may be able to compensate for some oxygen decrease by moving to a shallower sediment depth, avoiding the necessity for strong morphological adaptations (i.e., a steep increase in pore density). In contrast, shallow-infaunal taxa, such as B. pacifica, are not able to change their preferred microhabitat significantly in response to decreasing BW-O2, because they already thrive close to the sediment-water interface. Consequently, they respond to BW-O2 decreases with a stronger increase in pore density.


We successfully tested an automation of pore density measurements on SEM photographs of G. turgida by using the image analysis software analySIS (version 5.0, Olympus Soft Imaging Solutions GmbH), which generated similar pore density values as those obtained by manual pore counting and area measurement. The automated image analysis takes about 90 seconds, and is much more time efficient than manual counting, which takes about ten minutes per analysis.

Comparison of pore density in tests of the deep-infaunal and anoxia-tolerant benthic foraminiferal species G. turgida with in situ bottom-water oxygen concentrations exhibits a significant negative linear correlation, indicating that this species may increase its pore density in response to decreasing oxygenation. We suggest that G. turgida may optimize its mitochondrial oxygen uptake by increasing its pore density to survive in low-oxic environments. Our results on the pore density-to-BW-NO3 relationship for G. turgida suggest that nitrate seems to be a minor factor influencing pore density when compared to BW-O2.

Comparison of the pore density and the pore density-to-BW-O2 relationship in G. turgida with available data for the taxa B. pacifica and F. mexicana reveals interspecific differences that may be due to species-specific microhabitat preferences. We speculate that the shallow-infaunal B. pacifica is more strongly affected by oxygen depletion than the two deep-infaunal species G. turgida and F. mexicana, which appear better adapted to low-oxic environments.

Overall, our results are in good agreement with previous studies on low-oxygen-tolerant species, suggesting that pore density in certain benthic foraminiferal species could provide the potential to form the basis for a bottom-water oxygenation proxy. Additional studies and testing of this proxy on recent and fossil assemblages will hopefully enhance the reliability of paleoceanographic reconstructions of low-oxygen environments.


We are grateful to Barbara Donner and Jürgen Pätzold ( University of Bremen, Geosciences Department and MARUM, Bremen) for providing sediment samples and to Ronnie N. Glud ( Scottish Marine Institute, Dunbeg) for providing geochemical data. W. Schiller and B. Schminke ( Institute of Geosciences, Goethe-University Frankfurt) are acknowledged for technical support at the SEM. Manuel Weinkauf (University of Bremen) is thanked for supporting statistical analyses. We thank J. Bollmann (University of Toronto) for his support in the automated analysis. The associate editor and two anonymous reviewers are acknowledged for their comments that helped to improve a previous version of the manuscript. This work was financially supported by the German Science Foundation ( Emmy Noether research grant Fr 2544/2-1 to OF) and partly from the Hessian initiative for the development of scientific and economic excellence (LOEWE) at the Biodiversity and Climate Research Centre (BiK-F), Frankfurt am Main.


Taxonomy of Globobulimina turgida.

Family Buliminidae Jones inWright, 1875

Genus GlobobuliminaCushman, 1927

Type species: Globobulimina pacificaCushman, 1927

Globobulimina turgida (Bailey, 1851)

Bulimina turgidaBailey, 1851, p. 12, pl. 1, figs. 28–31.

Globobulimina cf. turgida (Bailey). Phleger et al., 1953, p. 34, pl. 6, figs. 33, 34.

Globobulimina turgida (Bailey). Haake, 1980, p. 12, pl. 2, figs. 24–26.