Recent initiatives have established cabled ocean observatories from the subtidal zone down to abyssal depths, including sites in the North Pacific (Ocean Networks Canada, U.S. Ocean Observatories Initiative, DONET-Japan, MACHO-Taiwan), the Arctic (Ocean Networks Canada), the Atlantic (EMSO-Azores), the northwestern Mediterranean (EMSO-OBSEA) and in coral reef habitats (OCTOPUS-Okinawa; QIMOS-Australia). Cabled observatories enable real-time, continuous monitoring of seawater properties and ocean currents, and biological features that can be detected using video and still cameras and hydrophones. These integrated sensor systems provide opportunities for long-term observations of biodiversity change, in relation to environmental variables. The planned, multi-decadal lifetimes of cabled observatories should allow seasonal and inter-annual variability to be 'filtered' from longer term trends that could be related to ocean change. International organizations such as the Group on Earth Observations' Biodiversity Observation Network (GEO-BON) and the European Multidisciplinary Seafloor and water-column Observations (EMSO) network are developing monitoring programs and suites of "Essential Biodiversity Variables" that are intended to establish a standardized, global framework for detecting biodiversity change, based on scientific principles. This presentation will consider how some of these essential variables can be monitored continuously, using current cabled observatory technologies, with the aim of encouraging the development of a coordinated international program. We will use examples from the VENUS, NEPTUNE and Arctic observatories operated by Ocean Networks Canada, the EMSO OBSEA and Azores test sites, and the OCTOPUS coral reef observatory, to illustrate how underwater cameras and sensors can be used to quantify seasonal shifts in community composition, responses to rapid changes in oceanographic conditions, and ecosystem service activities such as seafloor bioturbation. Ultimately, observatory technologies could become valuable tools for managing human impacts on marine ecosystems, through the provision of baseline information and the detection of acute and long-term ecosystem responses to disturbance.

1. Arctic Change 2014 | Ottawa
Cabled ocean observatories as tools
for studying ecosystem change
S. Kim Juniper1, Fabio De Leo Cabrera1, Jacopo Aguzzi2, Jozée
Sarrazin3, Marjolaine Matabos3, Mary. M Grossmann4, Satoshi Mitaria4,
Laurenz Thomsen5
1Ocean Networks Canada, University of Victoria, Victoria, British Columbia V8W 2Y2 Canada
2Instituto de Ciencias del mar (ICM-CSIC), 08003 Barcelona, Spain
3IFREMER EDROME, REM/EEP/Laboratoire Environnement Profond, 29280 Plouzané, France
4Marine Biophysics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa 904-

2. Arctic Change 2014 | Ottawa
What are cabled ocean
observatories?
• Power and communications cable to
shore
• Single or multiple instrument platforms
• Data archived in near-real-time
• Data accessed through online interface

3. Arctic Change 2014 | Ottawa
Node module Instrument platforms

4. Arctic Change 2014 | OttawaOCTOPUS Coral Reef
Observatory – Okinawa

5. Arctic Change 2014 | Ottawa
www.obsea.es
OBSEA (Spain)

6. Arctic Change 2014 | Ottawa
Essential biodiversity variables
(EBVs)
Standardized, global framework for detecting biodiversity change, based
on scientific principles
EBV Category Measurable with cabled
observatory technology
Genetic composition not yet
Species populations **
Species traits *
Community composition **
Ecosystem function *
Ecosystem structure *

7. Arctic Change 2014 | Ottawa
EBV studies using cabled
observatory technology
Advantages
• Continuous and real-time observations
• Co-located imagery and sensor data
• Few power or data storage limitations
Constraints
• Fixed locations, limited spatial footprint
• Species IDs often require sampling
• Installation and maintenance costs

8. Arctic Change 2014 | Ottawa
EBV studies using time-series
imaging coupled with oceanographic
sensors
Community Dynamics
• Species presence/absence &
abundance versus oceanographic
variables
• Community responses to
perturbations – experimental
manipulationsEcosystem Processes
• Quantifying ecosystem services
(eg. surface bioturbation)
• Chronobiology – activity and
abundance rhythms

9. Arctic Change 2014 | Ottawa
Vent fauna in a dynamic habitat

10. Arctic Change 2014 | Ottawa
Tidal periodicity and microhabitat
preferences
Cuvelier et al. (2014) PLOS ONE 9 (5)
Periodogram – tubeworm extension/retraction
Period (hours) Pycnogonid distribution heat map (23 days)

11. Arctic Change 2014 | Ottawa
Events
- Barkley Canyon
Pod 3 – camera and
oceanographic sensors
Surface storm drives water mass
change and megafaunal species
shift at 900 m depth
Matabos et al. (2014) J. Mar. Syst. 130, 56-68
Water mass shift
shrimp
whelk

12. Arctic Change 2014 | Ottawa
0
100
200
300
400
500
01Jan.2014
01Mar.2014
01May.2014
01Jul.2014
01Sept.2013
01N ov.2013
*1000Trichomes/m3
/Hr
20.0
22.5
25.0
27.5
Temperature (°C)
01Jan. 2014
01Mar. 2014
01May. 2014
01Jul.2014
01Sept. 2013
01N ov. 2013
Hourlyabundance
Typhoon
Neoguri
Okinawa
Phytoplankton response to typhoon
Okinawa - Trichodesmium bloom

13. Arctic Change 2014 | OttawaSeasonal patterns
Juniper et al. (2013) Deep-Sea Res. II 92, 114-12
Seasonal presence/absence trends
in benthic megafauna at 900 m

14. Arctic Change 2014 | OttawaSeasonal Migrations – diapausing copepods
Ongoing study - matching abundance peaks with
environmental triggers

15. Arctic Change 2014 | Ottawa
Pod 1 – canyon axis
at 1000 m depth
Seasonal Migrations – Tanner crabs

16. Arctic Change 2014 | OttawaSeasonal patterns
- annual hypoxia cycle

17. Arctic Change 2014 | OttawaQuantifying Ecosystem Services
- Surface bioturbation
Robert & Juniper (2012)
MEPS doi: 10.3354/meps09623
Number of days required to turn over 8.8 m2 study area
Frequency
Sea urchin + flatfish bioturbation
Bayesian model output
Upper slope
400 m depth

18. Arctic Change 2014 | Ottawa
Current meter
Microsensors
Camera
Methane
CTD
Turbidity
Fluorescence
Wally – mobile sensor platform

19. Arctic Change 2014 | OttawaInter-Annual Change on Methane
Hydrate Mounds
- comparing image mosaics from Wally‘s camera
Methods in Oceanography
5 (2013): 1-18..

20. Arctic Change 2014 | OttawaExperimental use of cabled
observatories
Deep-water forensics
Whale bone
colonization
Organic
enrichmen
t
Deep-sea recruitment
(INDEEP)

21. Arctic Change 2014 | OttawaEarly benthic successional processes
on implanted substrata
me-lapse video from frame grabs (8 months of data): May 2014 – Jan 201
Authigenic carbonate
Wood - Douglas Fir
3 Humpback ribs
Bacterial mat growth over time

22. Arctic Change 2014 | Ottawa
Imagery - a key source of
biological information

23. Arctic Change 2014 | Ottawa
Aguzzi et al., 2015.
Rev. Fish. Biol. Fisher. Accepted
Detecting change - How many observations?
Number of images

24. Arctic Change 2014 | Ottawa
Addressing the image
analysis bottleneck
• Computer vision
 Object recognition algorithms
• Crowd sourcing
 Citizen science
Number of images

25. Arctic Change 2014 | Ottawa
slightly from the fish detection stage due to slow moving fish
and heavily crowded scenes. The false positives decreased
significantly; the few which occurred were mainly due to fish
over counting from failed tracking. Thefalse negatives(missed
counts) were typically caused by occlusion which caused the
tracking algorithm to fail, or as a result of the aforementioned
failed segmentation. An example of a failed tracking result
due to occlusion is shown in Figure 7.
Fig. 7. A sample frame with a failed tracking due to fish occlusion (note
that both fish in bottom right are contained in one bounding box).
Thetracking method showed someability to detect occluded
fish, but only if at some point the fish swim in different di-
rections and enough information is gathered from the separate
tracks to conclude they are two separate fish.
V. CONCLUSION AND FUTURE WORK
This paper presented a novel approach for detecting, track-
ing, and counting fish in noisy deep-sea videos. The method
was developed using an experimental database provided by
Ocean Networks Canada, recorded at the Barkley Canyon
Detection module:
• Precision: 65.8%
• Sensitivity: 84.5%
Tracking and Counting
module:
• Precision: 83.8%
• Sensitivity: 77.9%
. Fier et al.
IEEE Oceans 2014
Failed tracking
Successful tracking
Fish counting algorithms

26. Arctic Change 2014 | Ottawa
A
B
Aguzzi et al., 2011.
Sensors-Basel 11: 5850-5872
Automated time-series fish counts
Combined with sensor data

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Crowd Sourcing
Comparative Study
• Crowd sourcing, computer algorithm, expert, 3rd year biology class
• Same video clip time series analyzed by all

28. Arctic Change 2014 | Ottawa
Preliminary results
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0.45
Expert Algorithm Student advCrowd novCrowd
Absolutedifferencefromglobalmean
vs. global mean
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ExpertAlgorithmStudentadvCrowdnovCrowd
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75
Period (1 hour)
Whittaker−RobinsonStatistic
Periodogram

29. Arctic Change 2014 | Ottawa
A nested collaborative
approach?
0
5
10
0
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10
0
5
10
0
5
10
0
5
10
ExpertAlgorithmStudentadvCrowdnovCrowd
Oct 17 Oct 24 Oct 31 Nov 06
SablefishCounts
Algorithm scans time series for trends/events
Focused crowd sourcing to improve data
Expert analysis for research publication

30. Arctic Change 2014 | Ottawa
Summary
Studying ecosystem change with cabled ocean
observatories
Community Dynamics
• Species presence/absence & abundance
 versus oceanographic variables
• Community responses to perturbations
 natural and experimental
Ecosystem Processes
• Quantifying ecosystem services
 surface bioturbation
• Chronobiology
 activity and abundance rhythms
Challenge – image analysis bottleneck

31. Arctic Change 2014 | Ottawa
Acknowledgements
• Canada Foundation for Innovation
• British Columbia Knowledge Development Fund
• Natural Sciences and Engineering Research
Council of Canada
• University of Victoria

32. Arctic Change 2014 | Ottawa
Data Access and Data Tools
• all sensor data and imagery archived
• free and open access to all data and imagery
• online graphical previews of scalar data
• online viewing of annotated, archived video
• downloads of all data
Seatube
Plotting utility
Data Acquisition Parser, Calibration
Data QA/QC
Data Storage
File Management
Archive
Database
Data Archiving
www.oceannetworks.ca

33. Arctic Change 2014 | Ottawa
Kirill Dudko -
Donestk, Ukraine
Citizen Science
- the unexpected
“I saw a monster eat a
hagfish…”
January 2013

34. Arctic Change 2014 | Ottawa

35. Arctic Change 2014 | Ottawa
New Main Instrument Platform
Arctic
• Less studied than other
Arctic marine habitats.
• More likely to be
impacted by human
disturbance

36. Arctic Change 2014 | Ottawa
Main Instrument
Platform
PAR sensor
CTD pump outlet
HD video camera
Preliminary Results
- seasonal trends in species
presence/absence and activity