ENVIRONMENTAL MANAGEMENT
Supporting Information for
The western South Atlantic Ocean in a high-CO2 world: current
measurement capabilities and perspectives
Rodrigo Kerr1, Letícia C. da Cunha2, Ruy K. P. Kikuchi3, Paulo A. Horta4, Rosane G.
Ito5, Marius N. Müller5, Iole B. M. Orselli1, Jannine M. Lencina-Avila6, Manoela R. de
Orte7, Laura Sordo8, Bárbara R. Pinheiro9, Frédéric K. Bonou9, Nadine Schubert4,10,
Ellie Bergstrom4, and Margareth S. Copertino1
1
Instituto de Oceanografia, Universidade Federal do Rio Grande (FURG), Rio Grande,
RS, 96203-900, Brazil.
2
Faculdade de Oceanografia, Universidade do Estado do Rio de Janeiro (UERJ), Rio de
Janeiro, RJ, 20550-900, Brazil.
3
Departamento de Oceanografia/INCT AmbTropic/CNPq1D, Instituto de Geociências,
Universidade Federal da Bahia (UFBA), Salvador, BA, 40170-115, Brazil.
4
Departamento de Botânica, Centro de Ciências Biológicas, Universidade Federal de
Santa Catarina (UFSC), Florianópolis, SC, 88010-970, Brazil.
5
Instituto Oceanográfico, Universidade de São Paulo (USP), São Paulo, SP, 05508-120,
Brazil.
6
IMAGES ESPACE-DEV, Université de Perpignan Via Domitia (UPVD), Perpignan,
66860 CEDEX, France.
7
Departamento de Ciências do Mar, Universidade Federal de São Paulo (UNIFESP),
Santos, SP, 11030-400, Brazil.
8
Grupo de Ecologia e Plantas Marinhas (ALGAE), Centro de Ciências do Mar,
Universidade do Algarve (UALG), Campus Gambelas, Faro, 8005-139, Portugal.
9
Departamento de Oceanografia, Universidade Federal de Pernambuco (UFPE), Recife,
PE, 50670-901, Brazil.
10
Programa de Pós-Graduação em Oceanografia, Centro de Filosofia e Ciências
Humanas, Universidade Federal de Santa Catarina (UFSC), 88040-900 Florianópolis,
SC, Brasil
Contents of this file
Section S1.3.
Tables S1, S2, S3
Introduction
This support file provides additional information to Section 1.3 and information
regarding the current stage of the Brazilian OA Network.
1
Supporting Material
S1.3. Key Sensitive Brazilian ecosystems
S1.3.1. Large to Medium Rivers
Here, we assess the main features of the four most important rivers in Brazil (Fig. 1B)
based on basin area and discharge. On the northern Brazilian coast, the Amazon River
discharges a large amount of freshwater (average 163,000 m3 s-1, or 18% of the total
freshwater input to the world's oceans by rivers; Labat et al. 2004), sediments (1.2 Pg
yr-1, DeMaster et al. 1986), carbon (43 Tg organic C yr-1 and 26 Tg inorganic C yr-1,
Probst et al. 1994, Coynel et al. 2005), and nutrients directly to the Tropical Western
Atlantic Ocean continental shelf. In this region, a large, low-salinity, nutrient-rich river
plume area off the coast (up to 2 × 106 km2, Cooley et al. 2007) enhances primary
production, creating a regional CO2 sink in the equatorial Atlantic Ocean (Subramaniam
et al. 2008). However, all the biogeochemical processes within the plume are not well
constrained. Other threats to the Amazon River Basin (~6,890 × 103 km2) include
deforestation, damming, contamination from gold mining and sewage, and overfishing
(Castello et al. 2013).
Small quantities of freshwater are discharged along the remaining Brazilian
continental shelf. Three more important medium-sized riverine inputs are located on the
NE and E shelf (Fig. 1B), namely, the São Francisco, Doce and Paraíba do Sul Rivers,
with average discharges of 28-120 km3 yr-1. Over the last century, these rivers have
suffered the impacts of urbanization (cities, industries, and mining plants), aquaculture,
dam construction, and agriculture along their drainage basin. However, these rivers have
preserved areas, and their basins support discontinuous patches of Atlantic Rain Forest
(UNEP, 2004). These riverine plumes and their influences (sediment and nutrient
2
inputs) are restricted to a narrow area in the oligotrophic NE and E shelf region
(Bernardes et al. 2012, de Oliveira et al. 2012).
S1.3.2. Estuarine ecosystems
Coastal areas, including estuaries and lagoons, play important roles in the marine
carbon cycle because of their high productivity over a small surface area (~8% of the
global ocean surface; Chen & Borges, 2009). In estuaries, all the materials that are
transported from the drainage basin are transformed before being exported to the
adjacent ocean. Because of the biogeochemical processes in sediments and the water
column, many estuarine areas act as sources of CO2 to the atmosphere (Borges & Abril,
2011). However, exporting carbon and nutrients to the coastal ocean may increase local
primary production and vertically transport of carbon to open ocean waters. These
processes characterize the so-called continental shelf pump and are responsible for the
average atmospheric CO2 sink over shelf areas (Chen & Borges, 2009).
Most of the Brazilian population lives in cities along portions of the coast or
within estuaries, bays or lagoons that provide services, such as harbours, tourism,
aquaculture, and fisheries (UNEP 2004). In these areas, natural eutrophication is
enhanced by heavy cultural eutrophication, and related scientific literature covers the
physical and biological features of the main Brazilian coastal ecosystems (Fig. 1B).
From a marine biogeochemistry perspective, an insufficient amount of literature is
available regarding the carbonate system parameters and the roles of ecosystems as CO 2
sinks or sources.
Noriega et al. (2015) and Araújo et al. (2014) recently demonstrated that the
tropical estuaries along the N/NE Brazilian coast behave as sources of CO2 to the
atmosphere. Additionally, the partial pressure of CO2 (pCO2) in surface estuarine waters
3
is negatively correlated with dissolved oxygen saturation, which indicates control by
biological processes, particularly organic matter degradation, resulting in greater
dissolved CO2 concentrations and the further acidification of coastal waters. Southwards
along the coast, Cotovitz et al. (2015) showed that Guanabara Bay (the metropolitan
area of Rio de Janeiro) behaves as a net sink for atmospheric CO2 despite its heavy
eutrophication and daily/seasonal variability. This behaviour is possible because of the
combination of light and nutrient availability triggers primary production and high
organic matter burial rates in the sediments. The N/NE Brazilian estuaries (CO2
sources) and Guanabara Bay (a CO2 sink) reinforce the need for additional field data on
the full carbonate system in the coastal ecosystems of Brazil to understand the possible
interplay between OA and eutrophication.
S1.3.3. Coastal lagoons
Coastal lagoons constitute approximately 13% of the world’s coastline and vary
considerably in shape, size, climate, hydrology, and trophic state (Nixon 1995, Windom
et al. 1999). In addition, these ecosystems are efficient sediment and nutrient traps and
nursery areas to many marine species and are becoming increasingly important as
tourism zones (Knoppers et al. 1999).
A series of choked coastal lagoons, often separated from the ocean by a sand
bar, and with limited water exchange with the adjacent ocean exist along the Brazilian
coast (Kjerfve 1986). Densely populated areas are found around their , and the lagoons
are often heavily affected by human activities (da Cunha & Wasserman 2003,
Niencheski et al. 2014). As examples we may cite the Patos Lagoon (S Brazil, Fig. 1B),
the largest choked lagoon in the world (10,200 km2), houses harbours for the cities of
Porto Alegre and Rio Grande, and the Araruama Lagoon, one of the largest hypersaline
4
lagoons (210 km2, salinity range from 42 to 56) in the world, part of the Fluminense
Lagoon complex (SE Brazil, Fig. 1B) (Kjerfve et al. 1996, Souza et al. 2003).
High primary production rates in Brazilian coastal lagoons increase
autochthonous organic matter production and benthic microbial activity. Higher oxygen
consumption results in temporary hypoxic to anoxic (and thus acidic) conditions in the
sediment-overlying water column and the concomitant release of sulphides (Souza et al
2003, Cunha & Wasserman 2003). Currently, no studies exist that detail the effects of
acidification on water or biota.
S1.3.4. Mangroves
Mangroves are dominant coastal ecosystems that cover more than 200,000 km2 of
sheltered tropical and subtropical coastlines. Currently, approximately 50% of this area
has been lost because of anthropogenic pressures (Duke et al. 2007). In Brazil,
mangrove forests occur along the coast from the north up to a latitude of 28.5o S,
covering approximately 91.6% of the Brazilian coastline (Fig. 1B, Schaeffer-Novelli et
al. 2000). Brazilian mangroves represent 7.1% of these ecosystems worldwide (Magris
& Barreto 2010).
Estimations of photosynthetic rates indicate that mangroves are more productive
over a given area than other coastal ecosystems (Alongi 2002). Therefore, mangroves
are efficient carbon sinks that are collectively referred to as blue carbon along with
seagrasses and saltmarshes (UNEP 2009). If the maximum estimates of the globally
covered area are combined with the upper estimates of the buried carbon per unit area,
the carbon capture capacity of blue carbon sinks is more than 300 Tg C year–1. In
addition, mangroves are important for controlling floods; protecting against erosion,
5
storms, and wave damage; maintaining water quality and serve as nurseries and feeding
areas for several fish species (Alongi 2002).
Mangroves are impacted by distinct components of climate change, including
changes in sea level, extreme events and atmospheric CO2 concentrations. Increasing
CO2 concentrations may result in some positive changes for these ecosystems, as it may
lead to increasing photosynthesis and mangrove growth rates (UNEP 1994). Soares et
al. (2012) proposed a conceptual model where the southern limit (latitude 28° S) for
Brazilian mangrove forests would be pushed southwards in response to the trend in
increasing average SST and air temperature.
S1.3.5. Seagrasses
Seagrass meadows form complex habitats that influence the physical, chemical and
biological characteristics of coastal environments (Orth et al. 2006). By increasing the
primary production and complexity of the sediment, seagrasses provide food and
breeding/nursery areas for invertebrates and fish (Waycott et al. 2009). Together with
mangroves and salt marshes, seagrass ecosystems are important carbon sinks that
represent a potential reservoir of up to 19.9 Pg of organic C globally (Fourqurean et al.
2012).
Seagrass habitats have significantly decreased in size (by at least 30%, with loss
rates between 2 and 7% yr-1) during the last century (Waycott et al. 2009) because of
coastal urbanization, eutrophication, land reclamation, overfishing and recent global
climate change (Duarte 2002). The conservation status of Brazilian seagrasses is
critical. The unsustainable exploitation and occupation of coastal areas and the multifold
anthropogenic footprints that remain from the last 100 years have resulted in
degradation losses, particularly in estuarine areas and coastal lagoons (Copertino et al.
6
under review). Few studies have investigated the responses of Brazilian seagrasses to
climate change (Copertino et al. under review, Sordo & Lana under review), although
seagrass species are highly vulnerable to global climate changes (e.g., Duarte 2002).
Specific investigations of the effects of OA on seagrasses in Brazil have not been
conducted; however, an initiative is currently underway to investigate the metabolic
feedbacks between seagrasses and rhodoliths in order to monitor their community
structure and review community carbon budgets under current conditions and future
scenarios.
S1.3.6. Salt marshes
Salt marshes are major coastal ecosystems in the intertidal depositional areas of
prograding coasts in temperate climates (Davy & Costa 1992). Similar to mangroves,
salt marshes shelter coasts from erosion and support fisheries by acting as important
spawning and nursery habitats (Pennings & Bertness 2001).
South-western Atlantic coastal saltmarshes develop on areas that are dominated
by the tidal flats of rivers, lagoons, creeks, coves and bays, or in association with
mangroves (Davy & Costa 1992) At latitudes greater than 28.5° S, salt and brackish
marshes occupy extensive areas off the coast of southern Brazil, Uruguay and northern
Patagonia and at riverine and estuarine margins with large freshwater discharge and
prevailing brackish conditions (Isacch et al. 2006).
Salt marshes are among the most extreme marine habitats in terms of natural pH
and dissolved oxygen variability (Duarte et al. 2013). Despite the physiological
tolerance and theoretical adaptation potentials of many salt marsh species (Parker et al.
2011), decreasing pH and dissolved oxygen may be deleterious, particularly to shellfish
animals and juvenile fish. Thus, these ecosystems may be largely insensitive to elevated
CO2 levels (Hendriks et al. 2010). However, such organisms may already live near the
7
edge of their physiological potential and could respond negatively to any further
changes that increase the environmental extremes in their habitat (Hofmann et al. 2011).
No studies have been conducted to determine the effects of CO2 and OA in
Brazilian salt marshes. The exposure of viable ecosystems to extreme conditions
presents unique and natural experimental opportunities that are near the heart of the
following current OA research questions: Are these ecosystems more likely to be
pushed past ‘tipping points’ by continued anthropogenic acidification? Alternatively,
are these ecosystems more likely to adapt to changing conditions?
Reference list for Support Section 1.3 (S1.3.)
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Conserv 29:331-349
Ball MC, Cochrane MJ, Rawson HM (1997) Growth and water use of the mangroves
Rhizophora apiculata and R. stylosa in response to salinity and humidity under ambient
and elevated concentrations of atmospheric CO2. Plant Cell Environ 20:1158-1166
Castello L, McGrath DG, Hess LL, Coe M, Lefebvre PA, Petry P, Macedo MN et al.
(2013) The vulnerability of Amazon freshwater ecosystems. Conserv Lett 6:217–229,
doi: 10.1111/conl.12008
Coynel A, Seyler P, Etcheber H, Meybeck M, Orange D (2005) Spatial and seasonal
dynamics of total suspended sediment and organic carbon species in the Congo River,
Global Biogeochem Cy 19(4):GB4019, doi:10.1029/2004GB002335
Da Cunha LC , Wasserman JC (2003) Relationships between nutrients and macroalgal
biomass in a Brazilian coastal lagoon: the impact of a lock construction. Chem Ecol
19:283–298. doi: 10.1080/0275754031000095732
DeMaster DJ, Kuehl SA, Nittrouer CA (1986) Effects of suspended sediments on
geochemical processes near the mouth of the Amazon River: examination of biological
silica uptake and the fate of particle-reactive elements, Cont Shelf Res 6(1-2):107–125,
doi:10.1016/0278-4343(86)90056-7
de Oliveira EN, Knoppers BA, Lorenzzetti JA, Medeiros PRP, Carneiro M, de Souza
WFL (2012) A satellite view of riverine turbidity plumes on the NE-E Brazilian coastal
zone. Braz J Oceanogr 60(3):283–298, doi:10.1590/S1679-87592012000300002
Duarte CM (2002) The future of seagrass meadows. Environ Conserv 29:192-206.
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Duarte CM, Losada IJ, Hendriks IE, Mazarrasa I, Marbà N (2013) The role of coastal
plant communities for climate change mitigation and adaptation. Nature Clim Change
3:961–968
Duke NC, Meynecke J-O, Dittmann S, Ellison AM, Anger K, Berger U, Cannicci S et
al. (2007) A world without mangroves? Science 317:41–42
Fourqurean JW, Duarte CM, Kennedy H, Marba N, Holmer M, Angel Mateo M,
Apostolaki AT et al. (2012) Seagrass ecosystems as a globally significant carbon stock.
Nature Geosci 5:505–509.
Hendriks IE, Duarte CM, Álvarez M (2010) Vulnerability of marine biodiversity to
ocean acidification: A meta-analysis. Estuar Coastal Shelf S 86:157–164
Hofmann GE, Smith JE, Johnson KS, Send U, Levin LA, Micheli F, Paytan A, et al.
(2011) High-frequency dynamics of ocean pH: A multi-ecosystem comparison. PLoS
One 6:e28983
Isacch JP, Costa CSB, Rodríguez-Gallego L, Conde D, Escapa M, Gagliardini DA,
Iribarne OO (2006) Distribution of saltmarsh plant communities associated with
environmental factors along a latitudinal gradient on the south-west Atlantic coast. J
Biogeogr 33:888–900
Jiang Li‐Q, Cai W‐J, Wanninkhof R, Wang Y, Luger H (2008) Air‐sea CO2 fluxes
on the U.S. South Atlantic Bight: Spatial and seasonal variability. J Geophys Res–
Oceans 113:C07019, doi:10.1029/2007JC004366
Kjerfve B (1986) Comparative oceanography of coastal lagoons. In Estuarine
Variability., pp. 63–81. Ed. by DA Wolfe. Academic Press, New York.
Kjerfve B, Schettini CAF, Knoppers B, Lessa G, Ferreira HO (1996) Hydrology and
Salt Balance in a Large, Hypersaline Coastal Lagoon: Lagoa de Araruama, Brazil,
Estuar Coastal Shelf S 42:701–725, doi:10.1006/ecss.1996.0045
Knoppers B (1994) Aquatic Primary Production in Coastal Lagoons. In Elsevier
Oceanography Series, pp. 243–286. Ed. by B Kjerfve. Elsevier Science Publishers B.
V., Amsterdam.
Knoppers BA, Carmouze JP, Moreira-Turcq PF (1999) Nutrient dynamics, metabolism
and eutrophication of lagoons along the East Fluminense coast, state of Rio de Janeiro.
In Environmental Geochemistry of Coastal Lagoon systems of Rio de Janeiro, Brazil.,
pp. 123–154. Ed. by BA Knoppers, ED Bidone, JJ Abrão. UFF - FINEP, Niterói.
Labat D, Ronchail J, Callede J, Guyot JL, de Oliveira E, Guimarães W (2004) Wavelet
analysis of Amazon hydrological regime variability. Geophys Res Lett 31(2):L02501,
doi:10.1029/2003GL018741
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in Brazil. Panam J Aquat Sci 5(4):546-556
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37:575–591, doi:10.1006/ecss.1993.1074
Orth RJ, Carruthers TJB, Short FT, Dennison WC, Duarte CM, Fourqurean JW, Heck Jr
KL et al. (2006) A Global Crisis for Seagrass Ecosystems. BioScience 56 (12):987–996.
Parker VT, Callaway JC, Schile LM, Vasey MC, Herbert ER (2011) Climate Change
and San Francisco Bay-Delta Tidal Wetlands. San Francisco Estuary and Watershed
Science 9(3):1-15
Pennings SC, Bertness MD (2001) Salt marsh communities. Marine community
ecology: 289–316. Sinauer Associates, Sunderland, MA.
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consumption in the Congo and Amazon river basins. Appl Geochem 9(1):1–13,
doi:10.1016/0883-2927(94)90047-7
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mangroves. Aquat Ecosyst Health Manag 3(4):561-570
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Western South Atlantic mangroves: Assessment of the potential effects of global
warming from a biogeographical perspective. Estuar Coast Shelf Sci 101:44–53. doi:
10.1016/j.ecss.2012.02.018
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Nutrient budgets and trophic state in a hypersaline coastal lagoon: Lagoa de Araruama,
Brazil, Estuar Coastal Shelf S 57(5-6):843–858, doi:10.1016/S0272-7714(02)00415-8
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AB et al. (2008) Amazon River enhances diazotrophy and carbon sequestration in the
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Response Assessment. Rapid Response Assessment. GRID-Arendal.
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A et al. (2009) Accelerating loss of seagrasses across the globe threatens coastal
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11
Support Tables
Table S1. Acronyms of Brazilian states and institutions that were cited within the text.
Brazilian States
Amapá
Bahia
Maranhão
Pará
Paraná
Pernambuco
Rio de Janeiro
Rio Grande do Sul
São Paulo
Santa Catarina
Brazilian Institutions
Universidade de São Paulo
Universidade do Estado do Rio de Janeiro
Universidade Estadual de Santa Cruz
Universidade Federal Fluminense
Universidade Federal da Bahia
Universidade Federal de Pernambuco
Universidade Federal de Santa Catarina
Universidade Federal de São Paulo
Universidade Federal do Rio de Janeiro
Universidade Federal do Rio Grande
Acronyms
AP
BA
MA
PA
PR
PE
RJ
RS
SP
SC
Acronyms
USP
UERJ
UESC
UFF
UFBA
UFPE
UFSC
UNIFESP
UFRJ
FURG
12
Table S2. Summary of the carbonate system parameters, methodology, and study regions of the Brazilian Ocean Acidification Network participants.
Oceanic regime
Parameter
State Institution
Methodology
Compartment
Main Focus
Open
Measured
Shelf Slope
Ocean
RS
SC
FURG
UFSC
USP
SP
UNIFESP
UFRJ
Coral Vivo
UERJ
RJ
Cont. pCO2
LI-COR 7000
Surface Ocean and
Atmosphere
yes
yes
yes
AT / CT
pH
Closed Cell
Electrode (NBS)
Water Column
yes
yes
yes
yes
yes
yes
pCO2
Equilibrator
AT
pH
AT
Open Cell
Electrode (NBS)
Open Cell
-
-
CT
LI-COR 7000
-
-
13C - 18O
IRMS
Seabed / Sediment
AT
Open Cell
pH
Electrode (NBS)
AT
Open Cell
pH
Electrode (NBS)
Water Column and
Seabed / Sediment
Rock Shore
Seabed
Corals, Rhodolith Beds
and Seagrass
AT
pCO2
AT
pH
Open Cell
Electrode (NBS and
potentiometry)
LI-COR 7000
EGM4pp-systems
Gas Chromatography
Open Cell
Electrode (NBS)
Cont. pCO2
LI-COR 7000
AT
Open Cell
pH
pCO2 and Cont.
pCO2
AT
Electrode (NBS)
PIRATA Buoys
CARIOCA Buoys
Open Cell
Electrode(NBS)
Spectro (Total)
pH
Cont. pCO2
UFF
UESC
BA
UFBA
PE
UFPE
pH
Several*
SiMCosta*
pCO2
pH
CARIOCA Buoys
Seabed
Rhodolith Beds and
Seagrass
Inner
Surface Ocean
-
-
-
-
Inner
-
-
yes
yes
yes
yes
yes
yes
-
-
-
yes
yes
-
-
Surface Ocean and
Atmosphere
-
-
-
Seabed
Corals and Seaweed
-
-
-
Surface Ocean and
Atmosphere
yes
yes
yes
Water Column
Inner
-
Atmosphere
Surface Ocean
yes
yes
-
Water Column
Surface Ocean and
Atmosphere
Surface Ocean
Carbonate System
CO2 Net Flux
Anthropogenic Carbon
Field Observations
Experiments with Field
Incubation
Experimental Factors: OA, T,
Nutrients and Metals
Experiments with
phytoplankton
Experimental Factors: OA
Mineralized organisms:
Foraminiferous
Experiments with invertebrates
Experimental Factors: OA and
Metals
Mesocosm Experiments
Experimental Factors: OA, T,
Nutrients and Metals
Carbonate System / Field
Observations
Study Region
Brazilian continental shelf and slope
from RJ to RS States
Patos Lagoon Estuary
Antarctic Peninsula
Florianópolis Coast (SC)
Ubatuba City (SP)
South Atlantic Ocean
Santos Estuary (SP)
Arraial d’Ajuda City (BA)
Estuarine and coastal systems (RJ)
Guanabara Bay (RJ)
CO2 Net Flux / Field
Observations
Coastal Lagoons (RJ)
Antarctic lakes, bays and Coastal
zones
yes
CO2 Net Flux / Field
Observations
Experiments with Corals and
Seaweed
Experimental Factors: OA, T
Ocean Modelling / Monitoring
Programme
Experiments with Corals
yes
Experimental Factors: OA, T
NE Brazil and
Oceanic Islands
Monitoring Programme
SE to S of Brazil
-
Estuarine systems
Estuarine systems
and Coral reefs
Tropical Atlantic and
Oceanic Islands
*Including FURG (RS), USP (SP), UFPR (PR) and UFSC (SC).
13
Table S3. Summary of OA-related Brazilian oceanographic cruises over the last seven years. The
majority of the works remain unpublished or are currently in preparation.
Study Area
Antarctic
Peninsula area
(Bransfield Strait
and NW Weddell
Sea)
Patagonian
Continental Shelf
(PATEX cruises I
to VII; only
PATEX IV and
VI measured all
parameters
listed)
South Atlantic
Ocean – sections
along 20º S and
30ºS
South Brazil
Bight (shelf/slope
zone)
Ship
Sampled
Year
Cont. pCO2
Jan. 2008, Jan.
2009, and Jan.
2010
N.Ap.Oc.
Ary Rongel
(H44)
Cont. pCO2,
AT/CT and pH
(Total)
Nov. 2004 (I),
Oct. 2006 (II),
Mar. 2007 (III),
Oct. 2007 (IV),
Jan. 2008 (V),
Oct. 2008 (VI),
and Jan. 2009
(VII)
NHo
Cruzeiro do
Sul (H38)
Cont. pCO2
Nov. to Dec.
2009
NHo
Cruzeiro do
Sul (H38)
Cont. pCO2
Dec. 2010 to
Jan. 2011
South Atlantic
Ocean – section
along 35ºS
NHo
Cruzeiro do
Sul (H38)
Cont. pCO2
and pH (NBS)
Oct. to Dec.
2011
South Shetland
Islands, Antarctic
Peninsula (coastal
areas)
NPo.
Almirante
Maximiano
(H41)
Cont. pCO2
Jan. 2013
NOc.
Antares
(H40)
Cont. pCO2
and AT
Jul. to Sep. 2014
AT/CT and pH
(NBS)
Jul. to Sep. 2014
AT/CT and pH
(NBS)
Sep. to Oct.
2014
Cont. pCO2
AT/CT and pH
(NBS)
Oct. 2014
South Atlantic
Ocean – section
along 38ºW
(PIRATA cruise)
Tropical Atlantic
Islands (NE
Brazil)
Amazon River
Plume
South Brazil
Bight (shelf/slope
zone; EstARteSul cruise)
South Brazilian
shelf (INCTMAR-COI
cruise)
Antarctic
Peninsula Area
(Bransfield and
Gerlache Straits)
South Atlantic
Ocean – section
following Agulhas
eddies
N.Ap.Oc.
Ary Rongel
(H44)
CO2-related
Parameters
Measured
NHo
Cruzeiro do
Sul (H38)
NHo
Cruzeiro do
Sul (H38)
NHo
Cruzeiro do
Sul (H38)
Outcome
Ito et al. (in
prep.)
BrOA
Action
PI
No
Dr. C.A.E.
Garcia
No
Dr. C.A.E.
Garcia
No
Dr. C.A.E.
Garcia
No
Dr. C.A.E.
Garcia
No
Dr. C.A.E.
Garcia
-
No
Dr. H.
Marotta
(Invited to
cooperate)
Dr. R. Vieira
(cruise PI)
Processing
AT analysis
Yes
Dr. M. Araújo
No
Dr. R.
Schwamborn
Yes
Dr. M. Araújo
Yes
Dr. R. Kerr
Orselli et
al. (in
prep.)
Ito et al. (in
prep.)
Ito et al.
(under
review)
LencinaAvila et al.
(under
review)
Processing
AT/CT
analysis
Processing
AT/CT
analysis
AT/CT
analysis
done
NOc.
Atlântico
Sul
AT/CT
Jan 2015
AT/CT
analysis
done
Yes
Dr. R. Kerr
(Invited to
cooperate)
Dr. L. F.
Niencheski
(cruise PI)
NPo.
Almirante
Maximiano
(H41)
AT/CT and pH
(NBS)
Feb. 2015
AT/CT
analysis
done
Yes
Dr. R. Kerr
NPqHo.
Vital de
Oliveira
Cont. pCO2
AT/CT and pH
(Total scale)
Jul. 2015
Processing
AT/CT
analysis
Yes
Dr. L. C. da
Cunha & R.
Kerr
14