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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

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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 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, , 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 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