Bermuda Institute of Ocean Sciences, 17 Biological Lane, Ferry Reach, St. Georges, Bermuda GE 01. Presentation Number: A44A-2679. Conclusions. Physical.
Physical and Biogeochemical Factors Affecting Deep Oxygen Minimum Zone Variability at the Bermuda Atlantic Time Series Site Samuel W. Stevens, Rodney J. Johnson, Nicholas R. Bates, Rachel J. Parsons Bermuda Institute of Ocean Sciences, 17 Biological Lane, Ferry Reach, St. Georges, Bermuda GE 01 Presentation Number: A44A-2679
Methods
Introduction
As the earth’s oceans continue to equilibrate with a warming and CO2 rich atmosphere, the study of growing Oxygen Minimum Zones (OMZs) is becoming increasingly critical in helping us comprehend the potential effects of our changing climate upon biogeochemical cycles within the oceans interior (Keeling et al, 2009). At the Bermuda Atlantic Timeseries Site (BATS), an assessment of dissolved oxygen profiles from 1988-2016 has revealed substantial variability in the thickness, form and depth of the deep OMZ in the Sargasso Sea. Local physical and biogeochemical forcing are hypothesized to play a significant role in OMZ variability and a number of different physical and biogeochemical parameters have been assessed to attempt to account for this variance.
This study was performed using hydrographic data collected within 18km of BATS between 1988 and 2016. These data were collected using a Sea-Bird Electronics 911plus CTD, with Dissolved Oxygen (DO), conductivity, temperature and pressure being the primary variables that were assessed. DO and conductivity sensors were calibrated using discrete bottle samples. Following this, the Dynamic Height Anomaly (DHA) was derived using a reference pressure of 1010 db. AVISO Sea Surface Height (SSH) data from 1998-2013 was also used to support the DHA statistics in the study. Discrete water samples to analyze nutrient content and bacterial abundance were taken during the BATS CTD casts. For further information on BATS sampling go to http://bios.edu/uploads/BATS_report_methods.pdf. A review of the subject literature did not elucidate an accepted method to define the OMZ in the Sargasso Sea. After substantial sensitivity analysis, the OMZ in this study is defined as the depths between which DO levels fall below 200 μmol kg-1 (fig. 2). The DO minima is defined as the least oxic point in the water column and the upper and lower oxycline depths are defined as the depths at which the oxygen profile falls below/above 200 μmol kg-1. Surface anomalies that fell into this threshold were removed computationally. Apparent Oxygen Utilisation (AOU) profiles were computed for all casts by subtracting the measured DO from the DO solubility (defined by Weiss, 1970). The integrated AOU within the OMZ was calculated using a trapezoidal integration method.
Figure 1: BATS location.
Figure 2: Composite DO profiles with OMZs in red.
Results
Figure 3: DO contour plot. Upper and lower oxycline and marked with thin white dash, DO minima marked with thick white dash, DHA marked with red dash
Table 1: R and P values for variables of interest
Discussion The depth of the DO minima in fig. 3 varies between 626m and 978m, with an average depth of 795m. This depth correlates positively with calculated DHA and SLA (table 1), whereby an increase in DHA will increase DO minima depth. This relationship can also been seen in the depths of the upper and lower oxycline (table 1), though the correlation is much stronger between the latter (r= 0.45) than the former (r= 0.21). Fig. 5a shows the long term trends in the oxycline data and it is shown that both the upper and lower oxyclines are shoaling at different rates, leading to a net increase in OMZ thickness of 2.7m yr-1. An overall deoxygenation rate of -0.29 μmol kg-1 yr -1 is seen at the DO minima (fig. 5b). No trends are seen in the temperature of the DO minima (fig. 5c) and no significant correlation is seen between this data and the DO minima (table 1). The DO minima is negatively correlated with the AOU at the DO minima (r= -0.8409). The integrated AOU within the OMZ is increasing by 76 mmol m2 yr-1 (fig. 4a). The integrated AOU has a positive correlation with bacterial abundance (r= 0.27) and negative correlation with nitrate & nitrite (r= -0.46) (table 1). There is also a net increase in bacterial abundance by 1.9 x 10-6 kg yr-1 (fig. 4b). Apart from nitrate & nitrite (fig. 4c), all variables have statistically significant long term trends (p values
