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1 Running Head: Methods for studying stratification
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3 Title: Alternative methods for studying stratification dynamics on discrete and continuous time
4 scales
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6 Katherine Hudson, Northeastern University, Marine and Environmental Sciences, 430 Nahant
7 Road, Nahant, MA 01908
8 2
9 Abstract
10 Stratification is an important driver for many biological and ecological processes across
11 benthic and pelagic habitats in the world ocean. However, stratification dynamics are still
12 undersampled due to limitations of current methods. Current methodologies rely primarily on
13 CTD and Niskin bottle data to develop stratification profiles, that are then compared over time.
14 Here, we describe two new methodologies which utilize remote sensing technologies for
15 examining stratification dynamics on discrete and continuous time scales. The first, focusing on
16 thin layers and zooplankton distributions in the water column, utilizes a Remotely Operated
17 Vehicle (OpenROV version 2.8) to record vertical transects in discrete time using a low-power
18 lens placed periodically over an HD imager. The second utilizes a customizable mooring system
19 and thermistor strings to continuously observe stratification as well as dynamic phenomena such
20 as internal waves. Using these methods, physical phenomena such as internal waves and thin
21 layers were observed with the continuous and discrete methods, respectively. These
22 methodologies allow for the observation of stratification dynamics on a variety of time and
23 spatial scales. A model was constructed in R to examine the effects of perturbations of the
24 stratified layer on downwelling that could have consequences for deeper-water pelagic and
25 benthic organisms. Understanding stratification dynamics and their impacts on water column
26 biota and the benthos across temporal and spatial scales will become increasingly important as
27 climate change impacts the dynamics of the surface layer of the world ocean.
28 Key Words: stratification, dynamics, zooplankton population dynamics, remote sensing,
29 temporal scales, internal waves, thin layers
30 Introduction 3
31 The stratification of the water column, or the distribution of bodies of water according to
32 their relative densities, has been shown to impact physical and biological phenomena throughout
33 the world ocean (Li 2002; Leichter et al. 1996; Wang et al. 2007). Changes in stratification
34 dynamics have been shown to influence species distributions, drive physical events in the water
35 column, and even influence events such as hurricanes and tropical cyclones above the ocean
36 (Greer et al. 2014; Butman et al. 2006b; Kunze et al. 2002; Holligan et al. 1985)
37 Despite the importance of stratification dynamics to species distributions across the world
38 ocean, stratification dynamics remain poorly sampled (Eickstedt et al. 2007). Sampling of ocean
39 stratification primarily occurs with CTDs, a group of ocean instruments capable of measuring
40 conductivity, temperature, and depth (Thompson and Emery 2014). These instruments can be
41 used to construct discrete temperature, salinity, and density profiles as a function of depth
42 (Thompson and Emery 2014). Data from CTD casts have been used previously to construct
43 reliable, long-term time series datasets that describe the seasonal changes in water column
44 structure and stratification (Steinberg et al. 2001). These data have been extremely influential to
45 describing the ocean circulation system present throughout the world ocean (Steinberg et al.
46 2001). However, these measurements are discrete (Thomson and Emery 2014). As a result, the
47 data they can collect are ultimately limited by their sampling frequency (Thomson and Emery
48 2014).
49 For example, the Bermuda Institute of Ocean Sciences (formally the Bermuda Biological
50 Research Station) has been following this sampling regime since 1954 with the development of
51 the Bermuda Atlantic Time-Series (BATS) study (Steinberg et al. 2001). While the data
52 collected at BATS is extremely valuable and has resulted in a wide-range of publications, the
53 sampling frequency of approximately once a month limits the researchers and scientists from 4
54 drawing concrete conclusions on what occurs at the study locations, or extrapolating those
55 results, on small time scales (Doney et al. 1996; Thompson and Emery 2014).
56 Currently, there are very few methods available for collecting data on continuous time
57 scales. One of the most popular of these are temporary mooring systems that can be deployed
58 with instrumentation specific to the needs of the researcher and the questions at hand (Butman et
59 al. 2006a). Such mooring systems have been used to study physical and biological phenomena
60 such as internal waves in Stellwagen Bank and harmful algal blooms in the Gulf of Maine
61 (Butman et al. 2006a, K. Hudson, pers. obs.). Instrument platforms and underwater vehicles,
62 autonomous or otherwise, have also been deployed to collect continuous data on the world ocean
63 (Eriksen et al. 2001). However, these systems are often only deployed for a single season and are
64 difficult to recover in inclement conditions (Pillsbury et al. 1969).
65 Another significant limitation to current stratification sampling methods is the cost of
66 instrumentation and ship time (Eriksen et al. 2001). CTD instruments, often included with
67 sampling bottle arrays, cost thousands of dollars, depending on the depth rating of the instrument
68 (Thompson and Emery 2014). Instruments capable of taking continuous measurements range can
69 cost upwards of $5,000 (Pillsbury et al. 1969). Research cruises to collect these data and deploy
70 the necessary instruments also can cost as much as $25,000 per day at sea (K. Hudson, pers.
71 obs). The high costs of both instruments and ship time often make up a significant portion of
72 grant budgets. Therefore, there is a significant need to develop relatively low-cost
73 instrumentation that can produce high quality and reliable data.
74 This study aims to address this need for data to be produced on a continuous time scale
75 and be relatively low cost when compared to traditional methods. Using northern Massachusetts
76 Bay as a study site, moorings like those used to study internal waves off Stellwagen Bank were 5
77 constructed (Butman et al. 2006). These moorings included thermistor strings of Onset HOBO
78 temperature loggers, low-cost temperature loggers ranging between $50 - $200 per device.
79 Inspired by the Massachusetts Bay Internal Wave Experiment in 1998 and work by John Witman
80 in the Gulf of Maine, three moorings were deployed off Nahant, MA and Rockport, MA to
81 observe stratification dynamics, including internal wave phenomena, during the summer months
82 of 2016 (Butman et al. 2006; Witman et al. 1993; Witman et al. 2004).
83 Internal waves occur in stratified waters and propagate along the stratification boundary
84 (Haury et al. 1979). They are formed by a disturbance in this boundary layer, which is usually
85 created by the movement of water due to tides over a large geographic feature, such as a ridge or
86 seamount (Haury et al. 1979; Helfrich and Melville 2006). These phenomena, in addition to
87 other stratification processes, have been shown to have significant impacts on plankton
88 distributions throughout the water column and can induce