Time-Series Oceanographic Study at the Coastal Station EPEA

Time-Series Oceanographic Study at the Coastal Station EPEA

Time-Series Oceanographic Study at the
Coastal Station EPEA (Argentina)
1,2Vivian
Lutz, 2Rubén Negri, 2Ricardo Silva
Consejo Nacional de Investigaciones Científicas y Técnicas,
Argentina
Instituto Nacional de Investigación y Desarrollo Pesquero,
Mar del Plata, Argentina
Outline
• Time-Series Studies - International networks
– Antares
– ChloroGIN
• Objectives of the project DiPlaMCC – INIDEP
– Time series station EPEA
• Examples oceanographic variability at EPEA
• Future challenges
Importance Time Series
From the ‘Ocean Observing 2009 – Ocean Information for society: sustaining
the benefits, realizing the potential’
• Last two centuries Spatial exploration of the Sea.
Now emphasis on Temporal exploration.
• Need for sustained and increased high quality
observations in all regions of the ocean.
• To understand behaviour of the ocean concerted
effort from all countries involved.
– Major part of increase in temperature taken up by the
ocean.
– ~ 40% increase in atmospheric CO2 taken up by
phytoplankton.
ANTARES
• Initiative: IOCCG-training-course
University of Concepción Chile, October 2002
• Created: Workshop, INIDEP, Mar del Plata Argentina,
July 2003 (IOCCG, POGO)
• Goal: To study long-term changes in coastal ecosystems
around the Americas to distinguish natural variability from
anthropogenic perturbations.
• Part of GOOS and GEO
• Participants:
– ~ 34 researchers
– 16 institutions
– 9 countries [Argentina, Brazil, Chile, Colombia, Ecuador, Mexico,
Venezuela; Canada, USA]
• Main Subjects:
– In situ Time series stations; Remote sensing
– Capacity Building
ANTARES In situ Time Series
Cartagena
Cariaco
Ensenada
Tumaco
Inocar 1 and 2
Ubatuba
Concepción
EGI
EPEA
Remote sensing information processing and distribution
• System adopted was that developed at the Institute of Marine Remote
Sensing (University of South Florida, USA)
• Main ANTARES Portal
http://www.antares.ws ; temporally: http://antares.ens.uabc.mx
Hosted at the Universidad Autónoma de Baja California (México)
Chlorophyll Global Integrated Network
‘ChloroGIN’
• Creation: Plymouth meeting 2006
• Vision: An international network to assess the state of marine,
coastal and inland water ecosystems for the benefit of society;
promoting for that purpose in water observations, expanded in
synergy with ocean-colour and related satellite observations.
• Step forward to standardize a method for in situ Chla
determination.
– Lutz, V.A., Barlow, R., Tilstone, G., Sathyendranath, S., Platt, T., HardmanMountford, N. Report of the In situ component of the ‘Plymouth Chlorophyll
Meeting and Workshops (Extended Antares Network)’. Sponsored by GOOS, GEO,
PML and POGO. 18-22 September 2006. (Web reference:
http://www.antares.ws/publications).
• http://www.chlorogin.org
Project: ‘Marine Plankton Dynamics and
Climatic Change (DiPlaMCC)’ - INIDEP
Main objective
To understand the variability in the dynamics and the
diversity of plankton and environmental conditions in
relationship to climatic changes.
• To obtain a time series of measurements of environmental
variables (meteorological, physical and chemical) and
plankton components (all size fractions).
• Elaborate a conceptual frame of the trophic structure of
plankton and its temporal variations.
• To distinguish, in the long-term, local expected variability in
oceanographic conditions from especial events; and try to
determine if these are linked to global climate change.
Mar del
plata
Miramar
• Estación Permanente de
Estudios Ambientales
EPEA
• 38º 28’ S, 57º 41’ W.
• Started on February 2000.
EPEA
• Cruises on board INIDEPvessels with a frequency of 34 weeks.
Marine Plankton Dynamic and Climatic Change
Project PI
Rubén M. Negri (INIDEP-UNMdP)
Participants
Rut Akselman (INIDEP)
Mario O. Carignan (INIDEP)
Georgina Cepeda (CIC)
Marcela Costagliola (INIDEP)
A. Daniel Cucchi Colleoni (INIDEP)
Marina V. Díaz (CONICET - INIDEP)
M. Constanza Hozbor (INIDEP)
Ezequiel Leonarduzzi (INIDEP)
Vivian A. Lutz (CONICET-INIDEP)
Graciela Molinari (INIDEP)
Luciano Padovani (Student – CONICET)
Marcelo Pájaro (INIDEP)
Silvia Peresutti (INIDEP)
Valeria Segura (INIDEP)
Ricardo I. Silva (INIDEP)
Roxana Di Mauro (CONICET)
Brenda Temperoni (UNMdP)
M. Delia Viñas (CONICET-INIDEP-UNMdP)
Micro - Phytoplankton
Nutrients
Zooplankton
Bacterioplankton
Chlorophyll a
Ichtyoplankton
Bacterioplankton
Ichtyoplankton
Bio-optics
Physical Oceanography - Meteorology
Zooplankton
Ichtyoplankton
Bacterioplankton
Bio-optics
Pico Phytoplankton
Zooplankton
Zooplankton
Zooplankton
EPEA In situ Measurements
Physical
CTD profiles: Temperature, Conductivity
Optical
Surface Irradiance (PAR)
Downwelling PAR profile
Passive Fluorescence profile
Reflectance from the sea (occasionally)
Net tows
Phytoplankton (> 25 µm)
Zooplankton (> 60 µm; > 200 µm)
Ichtyoplankton (> 300 µm)
EPEA In situ Measurements
Sample collection at discrete depths
Chemical: • Oxygen (Winkler)
• Nutrients (multi-analyzer)
Biological: • Chlorophyll-a total and < 5 µm
(spectrofluorometry)
• Phytoplankton (microscopy – molecular)
• Bacterioplankton (epifluorescence microscopy)
Bio-optical: • Particulate material
(spectrophotometric)
- Phytoplankton
- Detritus
• Chromophoric-Dissolved-Organic-Matter
Studies of annual and interannual variations in the following variables
Physical Temperature, Salinity, Density
Meteorological Winds
Chemical Nurients, Oxygen
Optical Surface Irradiance (Io), Coefficient of attenuation of downwelling irradiance
[Kd(PAR)], Depth of 1% Io (Z 1% Io), coefficient of absorption of total particulate
material [at(λ)], coefficient of absorption of phytoplankton [aph(λ)], coefficient of
absorption of detritus [ad(λ)], coefficient of absorption of chromophoric-dissolvedorganic-matter [ay(λ)].
Plankton
• Phytoplankton ‘Bulk properties’
– Chlorophyll-a as a proxy of phytoplankton biomass
– Primary Production (13C uptake)
• Plankton structure
– Composition and abundance of all the fractions of autothrophic phytoplankton
[ultra < 5 µm > nano < 20 µm > micro]
– Composition and abundance of microplanktonic heterothrophs
– Composition and abundance of bacterioplankton
– Composition and abundance of zooplancton
• Biomass of copepods
• Diversity of copepods using molecular techniques
– Abundance of anchovy eggs and larvae
– Nutritional state of anchovy larvae
Examples of Variations in
Oceanographic Conditions at EPEA
Annual cycle 2000 - 2001
0
10
Temperature
Typical temperate regime
[9.70 – 22.09 ºC]
Stratified in summer and mixed
in winter.
20
30
40
0
50
Feb
Mar
100
Abr
May
150
Jun
200
Jul
Ago
250
Sep
300
Oct
Nov
350
Dic
Ene
400
Feb
450
Mar
Abr
10
Salinity
20
[33.8 – 34.1]
High Salinity Coastal Waters
30
40
0
50
Feb
Mar
100
Abr
May
150
Jun
200
Jul
Ago
250
Sep
300
Oct
Nov
350
Dic
Ene
400
Feb
450
Mar
Abr
10
Chlorophyll-a
[0.15 – 3.30 mg m-3]
Highest: winter, autumn
20
30
40
50
Feb
Mar
100
Abr
May
150
Jun
200
Jul
Ago
250
Sep
300
Oct
Nov
350
Dic
Ene
400
Feb
450
Mar
Abr
(Negri et al., 2003)
Annual cycle 2000 - 2001
140
0
120
Depth (m)
100
80
20
60
30
1%Io
40
Chla
40
Chla (mg m-2)
10
20
0
Jan-00 Mar-00 May-00 Jul-00
Sep-00 Nov-00 Jan-01 Mar-01
Date
Z 1% Io Deeper in summer:
•stratified,
•low phytoplankton biomass,
•low re-suspension of sediments.
(Lutz et al., 2006)
Inter-annual cycle 2000 - 2009
0
1%Io
10
20
Z 1% Io
Depth (m)
30
•Higher variability
40
0.5
0.4
aph(440)
0.3
0.2
0.1
0.0
0
1000
2000
3000
Series Day (34=03/Feb/00; 3331=12/Feb/09)
•December 2008
•Shallow Z 1% Io
•High Phytoplankton
absorption
Annual cycle 2000 - 2001
3.5
7-year-mean sat. Chla
In situ 2000
In situ 2001
High resol. sat. Chla 2000
High resol. sat. Chla 2001
Chla (mg m-3)
3.0
2.5
2.0
1.5
1.0
0.5
0.0
30
60
90
120 150 180 210 240 270 300 330 360
Day Number
Larger deviations in winter months
• few images due to cloud cover
• peak of in situ Chla
(Lutz et al., 2006)
Variations in the ultraphytoplankton community structure
during Summer 2001-2002
• Ultruphytoplankton contributed up to 90% of total Chla.
• Synechococcus dominated the community.
(Silva et al., 2009)
Variations in the ultraphytoplankton community structure
during Summer 2001-2002
Two dimensional non-metric MultiDimensional Scaling plot constructed
from similarity matrix.
Ellipses join the samples of each
group as determined by the cluster
analysis. Superimposed filled circles
(increasing in size) represent the
values of the stratification indexes for
each sample:
• Mar: 0.06
• Dec: 0.09
• Feb: 0.38
• Jan: 0.83
(Silva et al., 2009)
Especial Bloom Events
07-11-05
18-11-05
Mar del Plata
Mar del Plata
EPEA
21-11-05
EPEA
02-12-05
Mar del Plata
EPEA
Mar del Plata
EPEA
Evolution of a phytoplankton bloom at the EPEA station
as seen by MODIS Chla estimates in November 2005
(images www.antares.ws).
(Negri et al., 2006)
Especial Bloom Events
Antares
15-12-08
Antares
15-12-08
Mar del Plata
Mar del Plata
E PEA
E PEA
a
b
7,0
6,0
c
19
Clorofila (µg/L)
Temperatura (ºC)
21
17
15
13
d
5,0
4,0
3,0
2,0
11
1,0
9
0
10
20
30
40
50
60
Nº de serie
70
80
2008
90
100
0,0
0
20
40
60
Nº de serie
80
100
2008
SST and Chla from MODIS (www.antares.ws), for the 15 December 2008.
Variations in in situ values for the months October to January (2000-2009).
(Negri et al., 2009)
Future Challenges
Maintaining continuity in the frequency of field
sampling!
• Human resources
• Meteorological station onboard
• Remote sensing (SST, Ocean-Colour, Scaterometry,
Altimetry)
• Buoy
• Dynamics
– Physical (Advection, Turbulence)
– Physiological (Primary Production)
Support from Scientific Agencies to these Key
Studies!
Gracias!