1. Problems and Challenges Working In an Observationally Poor Environment
Scott Glenn and Oscar Schofield
Rutgers Coastal Ocean Observation Laboratory
Special acknowledgements to my partners Bob Chant (RU COOL)
Mark Moline (Cal-Poly), Paul Bissett (FERI), and Trisha Bergmann,
Josh Kohut, & Matt Oliver

2. Our Long Term Goal: To Build a Nested Coastal
Observation Network
l Why?
l Monitoring Global Change and
Phytoplankton Communities
l Sediment Transport in Estuaries
l THIS AFTERNOON:
Integrated Systems and the Future
Ocean Observatories

3. In Situ Research- ‘The Early Years’

4. The Problem for Aquatic Sciences
(Lots of processes interacting over many time/space scales)
Horizontal Spatial Scales
1mm
1cm 1m
10m
100m
1km
10km
100km
AUVs
1 sec
molecular
processes
1 min
research vessels
Turbulent mixing
& physiological acclimation
satellites
1 hour
Individual
Movement
1 day
Temporal Scales
Phytoplankton
bloom
Fisheries
and
aquaculture
1 week
moorings
1 month
seasonal
1 year
fishermen
10 year

5. Case Example 1: Importance in Monitoring Phytoplankton
Community Composition
Study Site
The Antarctic Penisula
64 48’ S
Hermit Island E B
Janus Island
Litchfield
Island
Torgersen
Anvers Island
Palmer
64 46’ S
Bonaparte
Point
64 04’ W

7. Integrated Chlorophyll a vs. Upper Mixed Layer Depth
350
Station B
300
Mitchell & Holm Hansen (1991)
250
200
Integrated UML Chl a (mg m-3)
150
100 50 10 20 30 40 50 60 70 80
Upper Mixed Layer Depth (m)

8. Thalassiosira antarctica
100m
Thalassiosira antarctica
Cryptomonas cryophila
Corethron criophilum
Palmer Cryptophytes --> 8 ± 2m
10m
SEM Micrographs fromMcMinn and Hodgson 1993

9. Cryptophytes in the Coastal Ocean (Antarctica) Palmer Station1
Palmer Station
(n=162)
0.8
0.6
Proportion of total chlorophyll a associated with diatoms
Ocean warm
low salinity
0.4
Ocean cold-salty
0.2
0.2
0.4
0.6
0.8 1
Proportion of total chlorophyll a associated with cryptophytes

11. The Ice-melt Wall % Cryptophytes 100 80 60 40 2020 40 60 80
100
-15
-10 -5 5 10
Mean Air Temperature (°C)
% Cryptophytes

12. Antarctic Peninsula Salinity 33.3 33.6 33.8 Palmer Station 65°S
% Crypts 25 50
65°S
64°W

13. Where have all the good krill gone?
100 6
Krill:Salp 10 1
Ice Index 4
0.1 2
0.01
YEAR
0.001 80 82 84 86 88 90 92 94 96
100 10 1
Krill:Salp
0.1
0.01
Ice Index
0.001 2 4 6
100 10
Krill:Salp 1
0.1
0.01
0.001 -4 -2
Mean Air Temperature (°C)
From Loeb et al., 1997

14. Phytoplankton Size (m)
McClatchie and Boyd 1983
Boyd et al. 1984
Quetin and Ross 1985
100
100 50 80 80 40
% Retention by Krill 60 60 30 40 40 20 20 20 10
5-10
>15
5-10
>15
5-10
>15
Phytoplankton Size (m)

15. Changes over the last 50 years
1.2
0.8
0.4
Mean Summer Air Temperatures (°C)
Faraday Station
R2 = 0.64
-0.4
Signy Station
R2 = 0.73
-0.8
1945
1955
1965
1975
1985
Year
From Smith (1994)

16. (fish, penguins, whales)4%
62%
12%
22%
33.3 (Krill:Salp)
15%
33%
24%
28%
0.06 (Krill:Salp)
Higher Trophic Levels
Recycled carbon
Respiration
Autotrophic Losses
Other
Grazers
(copepods)
Diatoms
& Other
Phytoplankton
Cryptophytes
Autotrophic
Carbon
Production
Krill
Salps
Sedimentation
(Microbial Loop)
Respiration
(Other Losses)
Higher Trophic Levels
(fish, penguins, whales)
Partitioning Model
Autotrophic Losses
(Not Grazing)

18. Conclusions for Case 1: 1) Phytoplankton community composition is
impacted by glacial melt
2) Small cryptophytes dominate the meltwater.
3) Small cryptophytes cannot be grazed efficiently
by krill, salps replace the krill
4) This impacts the food web
5) The traditional sampling without context is useless.
6) Long term monitoring is needed to provide context,
7) Real-time data is needed to allow for adaptive sampling

19. Case Example 2: Newark Bay Contaminant Assessment and
Reduction Program

20. NB1 KVK PA New York Bight Hudson River Manhattan Hackensack River
Passaic River
Newark Bay
Kill Van Kull
Arthur Kill
Raritan Bay
Raritan River
Manhattan
Staten Island
New Jersey
Brooklyn
Sandy Hook
= Mooring
NB1 PA
KVK
Bight
New York

22. Newark Bay
Perth Amboy
cm/s

23. Transect Distance (km) Transect Distance (km)
Transect Distance (km)
Transect Distance (km)

24. NB1 KVK PA CTD ADP OBS Battery Pack LISST Hudson River Manhattan
Hackensack River
Passaic River
Newark Bay
Kill Van Kull
Arthur Kill
Raritan Bay
Raritan River
Manhattan
Staten Island
New Jersey
Brooklyn
Sandy Hook
= Mooring
NB1 PA
KVK
ADP
LISST
Battery
Pack
OBS
CTD

25. Perth Amboy (PA) Mooring
Flood
Ebb
8th th th th th th th nd

26. OBS
ABS
Lisst

27. Ebb
Flood PA

28. ebb
flood
Particle Sizes
Sediment Transport
flood
ebb
PSA Transport

29. Emptying/filling mode
Flow through mode
Day 63
Emptying/filling mode
Day 81.8
Staten
Island
Staten
Island

30. Conclusions for Case 2: 1) Sediment transport is dominated by tides.
2) Greatest concentrations during spring tides.
3) At Perth Amboy, transport is greatest during floods
indicating a net transport into the Bay
4) Long term records indicate 2 modes to the subtidal flow
5) The traditional sampling without context is useless.
6) Long term monitoring is needed to provide context,
7) Real-time data is needed to allow for adaptive sampling

31. So, lets build system to do this
We need to know:
What is in the water.
Where it is going.
Where it will be tomorrow.
So, lets build system to do this

32. New Jersey Shelf Observing System (NJ-SOS)