598


CAITLIN R. KEATING-BITONTI AND JONATHAN L. PAYNE


occurrences in the Culver and Buzas data set. Because the vast majority of morphological variation in foraminifera is among species not within species (Rego et al. 2012), we used these data to identify patterns in the biogeographic distribution of test size and shape. To calculate test volume and surface area, we assumed that the test roughly approximates a three- dimensional ellipsoid. Following Payne et al. (2012a), we calculated volume as 4/3 · π · a · b · c and surface area as 4 · π · [( a z · b z + a z · c z + b z · c z )/3]1/z,where a, b,and c represent the radii and z=1.6075.Generalizing testmorphology as a three-dimensional ellipsoid is not an important source of error on the data set because our size data span more than five orders ofmagnitude in (log10-transformed) biovolume, whereas errors introduced by approximations of cell shape are unlikely to yield more than 0.3 log10 (hereafter “log”) units of uncertainty. In the extreme case of using the generalized ellipsoid equation to determine the volume of a cube, the resulting error is less than 0.3 log-units difference. Although the cytoplasm of the foraminifera might not occupy the entire test (Gerlach et al. 1985; Murray 1991), the dimensions of the test are the best approach for estimating cell volume and volume–to–surface area ratio because expanded cell protoplasm can completely fill all the chambers of the test (Hohenegger and Briguglio 2014). Several studies of foraminiferal


respiration rates estimate that the cell cytoplasm fills approximately 3/4 of the internal test volume (Hannah et al. 1994; Geslin et al. 2011), and the error introduced by using this estima- tion is less than 0.13 log units.As this appears to be aconsistentsourceofbias with testsize overestimating cytoplasm volume, this effect is expressed by changes in the intercept of the regression equations rather than in the slope. Because our interest is in the slope of these relationships, this consistent bias across all measurements is likely to have an even smaller effect on our results.


Oceanographic Data We compiled data for four oceanographic


parameters that could affect organism morpho- logy through their effects on metabolic physiology. These parameterswere temperature,


dissolved oxygen concentration, the calcite saturation state of seawater, and POC flux to the seafloor. Because specific metabolic rate scales positively with temperature (Peters 1983; Gillooly et al. 2001), test volume is expected to correlate inversely with ambient temperature (DeLong et al. 2010). The vast majority of foraminiferal species are presumably primarily aerobes (e.g., Sen Gupta and Machain-Castillo 1993; Sen Gupta 1999; Heinz and Geslin 2012); thus, dissolved oxygen concentration in the ambient seawater can constrain overall size and the volume–to–surface area ratio of the cell. The flux of POC to the seafloor is an important nutrient resource for benthic life, and therefore the concentration of POC in the environment has the potential to limit the size of the foraminifer. Because Rotallid foraminifera use metabolic energy to secrete predominantly low-Mg calcite tests (Blackmon and Todd 1959; Sen Gupta 1999; Erez 2003; Armstrong and Brasier 2005) and produce the associated organicmatrix, the calcite saturation state of the ambient seawaterwould be expected to correlate positively with test volume (deNooijer et al. 2009). We compiled mean annual temperature


(Locarnini et al. 2010), dissolved oxygen concentration (Garcia et al. 2010), and salinity (Antonov et al. 2010) from the 2009 World Ocean Atlas for each locality by matching its unique latitude and longitude coordinates to the nearest environmental 1° grid point at the appropriate bathymetric depth; 1° is approxi- mately 111 km. Although these environmental data were compiled during the early 2000s and data included in the biogeographic data set extend back to the 1920s, the temporal variation in the environmental conditions at any site due to anthropogenic climate change is small compared to the total variation we observe across the 60° latitude and 1600m of water depth included here. The saturation state with respect to calcite is a function of the temperature and pressure of seawater and the dissolved inorganic carbon concentration (DIC), alkalinity, and salinity (Dickson 1990). We compiled mean annual values of seawater alkalinity and DIC from the Global Ocean Data Analysis Project (Key et al. 2004) and carbon dioxide in the Atlantic Ocean (CARINA Group 2009) data sets and matched foraminiferal


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136  |  Page 137  |  Page 138  |  Page 139  |  Page 140  |  Page 141  |  Page 142  |  Page 143  |  Page 144  |  Page 145  |  Page 146  |  Page 147  |  Page 148  |  Page 149  |  Page 150  |  Page 151  |  Page 152  |  Page 153  |  Page 154  |  Page 155  |  Page 156  |  Page 157  |  Page 158  |  Page 159  |  Page 160  |  Page 161  |  Page 162  |  Page 163  |  Page 164  |  Page 165  |  Page 166  |  Page 167  |  Page 168  |  Page 169  |  Page 170  |  Page 171  |  Page 172  |  Page 173  |  Page 174  |  Page 175  |  Page 176  |  Page 177  |  Page 178  |  Page 179  |  Page 180  |  Page 181  |  Page 182  |  Page 183  |  Page 184  |  Page 185  |  Page 186  |  Page 187  |  Page 188  |  Page 189  |  Page 190  |  Page 191  |  Page 192