Dataset: MO - virioplankton abundance
Deployment: HB0805

Methodology: from Parsons et al (2011):

Study site and sample collection:
Samples were collected aboard the RV Weatherbird II or the RV Atlantic Explorer at the BATS site (31° 40′ N, 64°10′ W). All cruises were conducted as part of the larger BATS program and sampled at least monthly with biweekly sampling between February and April. This sampling strategy has been successful in revealing the major temporal microbial and biogeochemical patterns at this site (Carlson and Ducklow, 1996; Steinberg et al., 2001; Morris et al., 2005; Carlson et al., 2009; Treusch et al., 2009; Lomas et al., 2010). A broader assessment of the BATS biogeochemical data is presented in Deep Sea Research II in 1996 (volume 43, issues 2–3) and 2001 (volume 48, issues 8–9).

Samples for virioplankton (0, 20, 40, 60, 80, 100, 140, 160, 200, 250 and 300 m) and bacterioplankton (0, 10, 20, 40, 60, 80, 100, 120, 140, 160, 200, 250 and 300 m) were collected at the BATS site from January 2000 to December 2009 via conductivity, temperature, depth profiling rosette equipped with 12 l Niskin bottles. The 120 m virioplankton sample was added after October 2007. Throughout the entire time-series, all virioplankton samples were fixed with 0.02 um filtered formalin (1% final concentration), placed in 5 ml cryovials and flash frozen in liquid nitrogen (Wen et al., 2004) until processing (within 12 weeks of collection). Samples for bacterioplankton abundance were fixed with 0.2 um filtered gluteraldehyde (1% final concentration) and stored at either 4 °C for 72 h or flash frozen and subsequently stored at −80 °C for up to 6 months until processing as described in Steinberg et al (2001). Storage tests demonstrated no appreciable loss of virioplankton or bacterioplankton abundance when stored in liquid nitrogen for periods up to 6 months (unpublished data). Picophytoplankton samples were collected at the same depths through 250 m from October 2001 to December 2009 (Casey et al., 2007). Samples for fluorescence in situ hybridization (FISH) of specific heterotrophic bacterioplankton lineages were collected from the upper 300 m from January 2003 to December 2005 (Carlson et al., 2009).

Biogeochemical and physical data collected at the BATS site are available at http://bats.bios.edu. The MLD was determined as the depth where potential density (sigma-t) of the water was equal to sea surface sigma-t plus the equivalent in sigma-t to a 0.2 °C decrease in temperature (Sprintall and Tomczak, 1992). Contour plots were created in Ocean Data View (R Schlitzer, http://odv.awi.de/) with VG Gridding and linear mapping adjusted to the median of each data set. Statistics (Pearson's correlation and two-tailed Student's t-test for unequal variances), ratios and percent contributions were determined using Microsoft Excel.

Virioplankton abundance:
Virioplankton abundance was enumerated according to the methods of Noble and Fuhrman (1998). Briefly, water samples were filtered on to 0.02 um Anodisc aluminum oxide filters (Whatman, Kent, UK), stained with SYBR Green I (Molecular Probes Inc., Eugene, OR, USA), and enumerated via epifluorescence microscopy using an Olympus AX70 microscope (Olympus, Tokyo, Japan) equipped with a Toshiba CCD video camera (Irvine, CA, USA) and Pro-series Capture Kit version 4.5 (I-CUBE, Crofton, MD, USA). Ten images from each sample were processed with scripts written in Image Pro Plus (Media Cybernetics, Bethesda, MD, USA) for particles sized 0.01–0.27 um2, using the clean borders function (cells touching the edge of the image or grid were omitted). We consider these estimates of viral abundance conservative because it is possible that some viral particles less than one pixel were omitted from the final count. We performed pairwise comparisons of automated versus manual enumeration of virioplankton abundance to determine any discrepancies between the two approaches. Samples collected along a gradient from offshore (BATS; n=92) to onshore waters of Bermuda (n=32) were highly correlated with automated counts being slightly greater than manual counts (slope=1.07, r=0.99, n=134). The lower estimates of viral abundance from manual counts may have resulted from image fading during enumeration and/or operator fatigue. We argue that for this study, the automated image analysis was the most reliable approach for viral particle enumeration. The coefficient of variation for the automated counts averaged 11% (n=1517).