Atlântico. Tropical. (0 to 25º S). Brasil (NE, SE). 5. H. wrightti, H. emarginata,. H. decipiens, H. bailoni, R. maritima. > 30.000 estimated. Subtropical/. Temperado.
Seagrass distribution across Brazilian Coast Margareth S. Copertino Institute of Oceanography Federal University of Rio Grande – FURG BRAZIL
International Blue Carbon Scientific Working Group May 15-17, 2013 - Sydney, Australia
Research Group: Margareth Copertino – Federal University of Rio Grande (FURG) Joel Creed – Universidade Estadual do Rio de Janeiro Karine Magalhães – Universidade Federal Rural de Pernambuco (UFRP) Krishna V. Barros – Universidade Federal do Ceará (UFC) Paulo Horta – Universidade Federal de Santa Catarina (UFSC) Pablo Riul - Universidade Federal da Paraíba (UFPB) Ana Claudia Rodrigues – Universidade Federal de Santa Catarina (UFSC) Marianna Lanari – Universidade Federal do Rio Grande (FURG) Raquel Wigg Cunha - Universidade Federal do Rio Grande (FURG) Priscilla Rezende – Universidade Federal do Rio Grande (FURG)
Rede CLIMA
Sandy Beaches Estuaries
BC Systems
Mangroves & Salt Marshes Seagrass meadows Rodolith Beds Rock reefs Coral reefs Environmental Education
Integrates several instititutions and reserch groups along the Brazilian Coast
Large scale spatial survey:
Mapping Brazilian Seagrasses Data base: species ocurrence, abundance, areal extensions, environmental data (biological, water and sediment data) In situ verification and data collection Modeling species distribuition Estimating Carbon stocks
Long Term Monitoring Programs:
DiVAS
Dinamycs of Submerged Aquatic Vegetation
Brazilian-LTER
South America Hidrographic Basins
Flow paths of major ocean currents
SA surrounded by water masses of different origins and properties, which have a great influence on the marine ecossystems.
Disharge of river basins affect coastal geomorphology and water properties (turbidity, salinity, temperature, nutrients etc.). Plume of the Amazonas and La Plata rivers make the major coastal barriers for marine organisms.
Distribuition of Seagrasses across South America
30.000 km of Coastde linha de costa, with distinct morphology and oceanographic influence
Seagrass habitas concentrated in Caribean Region and Brazil
Distribution of seagrasses (including eurihaline species) in South America Coast
Clim. Zone
Country/ Region
N
Species (dominant in bold)
Area (ha)
Caribe
Equatorial (10º N)
Colômbia
6
Thalassia testudinum, Syringodium filiforme, Halodule wrightti, Halophila decipiens, H. bailoni, Ruppia maritima
43.225 mapped
Venezuela
6
T. testudinum, S. filiforme , H. wrightti, H. decipiens, H. bailoni, H. engelmani
~ 80.000 potential
Trinidad & Tobago
4
T. testudinum, H. wrightti, H. decipiens, S. filiforme
~ 500 potential
Tropical (0 to 25º S)
Brasil (NE, SE)
5
H. wrightti, H. emarginata, H. decipiens, H. bailoni, R. maritima
> 30.000 estimated
Subtropical/ Temperado (28 to 40º S)
Brasil Sul/ Uruguai/ Argentina/
3
R. maritima, H. wrightii, Zannichellia palustris
~15.000 mapeado/ estimated
SubAntartic (>50º S)
Magalhães/ I. Malvinas
1
Ruppia filifolia
~ 5.000 estimated
Subtropical (27 to 30º S)
Norte do Chile
1
Heterozostera tasmanica
~ 250 mapped
TOTAL South America (estimated)
11
~1/6 total species
>173.975
TOTAL Globe (estimated)
60
< 1% total area
30 - 60 Mha
Atlântico
Pacífico
Penicillius sp.
Seagrass meadows dominated by Halodule wrightii and several calcareous macraolgae around coral reefs in Brazil.
Habitat for megaherbivores (green turtle Chelonia midas)
Green turtle (Chelonia midas) grazing on seagrass meadows in Abrolhos region (BA, Brasil). Foto: ©Luciano Candisani/iLCP
Habitat for megaherbivores (manateeTrichechus manatus) Main diet: seagrasses, macroalgae, mangrove leaves and shoots Distribuition of marine manatee and amazonian manatee
A very rough estimate of South American C stocks in segrass meadows Assuming average biomasses and soil C content (estimated from OM) Above ground 0,70 – 0,95 Mg C/ ha Bellow ground 1,756 – 2.5 Mg C/ha Total biomass 2,514 – 3.0 Mg C/ ha Average soil Corg content: 2% (but in caribe values range from 8% to 20%) Soil Bulky Density: 1 % %C
Total Biomass (Mg C/ha)
2-16 2,5 – 3,5
Habitat Extent (ha)
C Stock (Mg C)
173,975
435-609
Based in a very much conservative approach, according to Fourqurean et al. 2013
Brazilian seagrasses
Distribution of seagrass species across Brazilian coast (National Data Base) Halodule wrightii
Halophyla decipiens
Ruppia maritima
Brazilian Seagrass Database (ArquiGIS)
• • • • • • • •
Studies and registers; Locations and geographic coordinates; Species; Abundances (biomasses, densities, cover) Other biotic and abiotic parameters collected; Methodologies used; Period or date of collection; Publications associated to the data;
Studies on seagrass habitats (flora and fauna) More than 250 registers
108 Publications (articles, thesis, book chapters) 100
N of studies per decade Cumulative
80
(Creed, Seeliger, Magalhães, Silva, Garcia)
60
40
20
Ocurrence, First descriptions, identifications
Occurrence Botanical Auto-ecology
Morphology Populations Ecophysiology
(Oliveira, Seeliger, Koch,)
(Creed, Seeliger, Philips, Magalhães, Asmus.
(Laborel-Deguen, Den-Hartog, Kempf, Cafruni)
Communities Ecossystem Environmental Modelling
Ecology Reviews Integration (Creed, Copertino Barros, etc )
0 1960-1969
1970-1979
1980-1989
1990-1999
2000-2009
2010-2012
Publications Type ofpublication
120
80
62%
38 %
60 40
23%
11% 4%
20
is s D & s es i Th
ta l To
ns er t
at io
gr ap hs M
ha p C k B oo
on o
te rs
le s
0 A rt ic
N° of Studies
100
42% international journals 58% Brazilian journals
80%
13 %
Review Revisão
7%
Descriptive Experimental, Descritivo Experimental Modelling
Cumulative number N de trabalhos
N of Studies N° Trabalhos
N de trabalhos
80 70 60 50 40 30 20 10 0
Tipo
Approaches Enfoque metodológico
Total Total
Species
N° Trabalhos N of Studies
50
Espécies de fanerógamas
Flora
40 30 20 10 0
Endemic Uncertain taxonomy
Colected and identified only twice (Setchell 1934, Oliveira et al. 1983)
Seagrass distribuition across Brazil: a function of coastal geomorphology, hydrology and latitudinal gradient
1)
2)
3)
4) 5)
Modelling the distribuition of Halodule wrightii (habitat suitability) Species Distribuition Model (SDM) using MAXENT algoritm (Maximum Entropy) powerful tool for reconstructing or predicting species distributions
- Seagrass occurrence (model calibration) - Environmental variables for the world’s oceans: Bio-Oracle Temperature Surface and underwater light Nutrients (N, P) Clohrophyll Turbidity Batimetry Algoritmo for the modeling: MAXENT (Maximum Entropy) - The model estimate high probability in a subtropical region (Santa Catarina), where the species did not occurred previouslly. - Species registered in 2010.
Evidences of changes (distribuition, abundance, species composition) Spatial scale
25
Fauna
20
Flora
15 10 5
0-
5 51 0 -1 10 00 11 15 50 12 20 00 12 25 50 13 30 00 13 35 50 14 40 00 14 45 50 15 50 00 15 55 50 160 0 > 60 0
0
Detection of losses and impact atributions are limited by the spatial and temporal scale of the studies and lack of historic data
20
Fauna
Timescale
4 sites with history of long term changes (> 5years)
N° of Studies
Flora 15
10
5
0 Short term
Seasonal Interannual 2 a 5 years
> 5 years
Sa em lin pe ity ra Ti da tur e l W at reg er im vi e W av sib e ex ility po s N ure ut rie nt s
at er t
% Locations 80
70
Su Ph sp O x en de yge n d So l C hl ids or op Tu hil rb id ity O rg O th an er ic Se M at di t m en er tt G ype ra W n R in si a d ze i n A di re re i r t em gim ct io p e n an era tu d re in te ns ity
W
Brazilian seagrass habitats Abiotic information for 144 georefered locations based on 172 studies (articles, thesis, reports, etc.)
100 Abiotic parameters
90
Water Sediment Meteorological
60
50
40
30
20
10
0
Historic Changes in seagrass distribuition and abundances in Cartagena Bay and surrounds (Colombia) Diaz & López 2003. Bol. Invest. Mar. Cost
Trend in losses across 6 decades in the internal and external zone of the Bay. Losses in internal zone much higher.
Evidences of changes in Brazil (distribuition, abundance, species composition) Northeast Tamandaré Island (PE) Reduction in density, changes extension, apparentelly related to climate changes or extreme events: increase in frequency of storms and changes in sediment. (Short et al. 2006) Abrolhos Bank (BA) Reduction in density and apparentelly related to an increase of the historic average temperature, inceases in rain and storms,increases of hydrodynamic e sediment transport biomass (Short et al., 2006)
Southeast Lagoa de Araruma (Cabo Frio, RJ) Cicle of 11 years , decreases in abundance under El nino years (Marques 2010). H. wrightii beds listed by Oliveira1983 and revisited ten years later: no longer found at 16 % of the places.
South Patos Laggon (Rio Grande, RS) Higher interannual and interdecadal variation, correllated to cimatic and hydorlogic variability Disapearance during strong El Nino and high discharge (Copertino e Seeliger 2010, Copertino 2010)
Araruama Lake RIO DE JANEIRO
18 years of monitoring
Abundance - cicles of 11 years and decreases under El nino (SeagrassNet site)
Extremes of maximum daily temperature
Araruama Cabo Frio Southeast Brazil,
Marques & Creed, 2010
Patos Lagoon 10.000 km2 - largest choked laggon in world South America Southern Brazil Patos Lagoon estuary
Water shed: 200.000 km2 Patos Lagoon
Mirim Lagoon
Oceano Atlântico Brazil-LTER
Drif algae biomass
Total biomass Reproductive hasts Shoot lenght Shoot density
400 350 300
4 3
250 2
200 150
1
100 50
0
0
25
80-83 91-94 08-09 81‐83 91‐9497-00 97‐0001-04 01‐0405-07 05‐0708‐09 20 River discharge Salinity
15
15
10
10
5
5
0 80-83 91-94 97-00 01-04 05-07 08-09
Year intervals
Salinity (ppt)
20
R. Maritima population index
-2 River discharge (10 3 m3 s-1) Drift algae biomass (g. m )
R. maritima
3,0
Interannual variability on abundance related to climateand hydrology Oceanic Niño Index (ONI) – baseado em anomalias térmicas ( Patos Lagoon, South Brazil, LTER site)trimestrais
2,5 2,0
ONI (oC)
1,5
Ocenaic Nino Index (Nino 3.4 region)
1,0 0,5 0,0
Brazil-LTER
-0,5 -1,0 -1,5
Bio sub
Bio aer
Precipit
Bio tot 1500
70 -2,0 60
Annual Precipitation Anomalies (mean = 1527 mm)
1250 1000
-2
Biomassa (g . m )
500
50
250 0
40
-250 -500
30
-750 -1000
20
Annual Average Biomass 10
-1250
Copertino
et al. -1500
In review
-1750 0
Precipitation (mm. ano-1)
750
-2000 11 20 10 20 09 20 08 20 07 20 06 20 05 20 04 20 03 20 02 20 01 20 00 20 99 19 98 19 97 19 96 19 95 19 94 19 93 19 92 19 91 19 90 19
Distribuition and abundance of Ruppia maritima meadows in situ and by remote sensing (Gianasi & Copertino 2011) 344 points surveyed – biotoc and abiotic parameters (depth, sediment, % cover, biomass, lenght, composition etc)
Depth
% Cover
Relevant results: - Detailed spatial survey: abundance, composition, depth, sediment - Calibration and validation of LANDSAT images - Estimating carbon stocks
Dossel High
Composition
FINAL CONSIDERATIONS -
South American seagrasses remains still understudied Based on studies and registers, seagrasses cover more than 174 ha of South America coast, a areal extention still underestimated The long coast, the fragmented meadows, unacessible sites, sites of deep or turbid waters and few seagrass experts are the main constraints
- Endangered and many comercial important species associated to the medows, but segrass habitat do not receive specific protection -
Areal extent of Brazilian seagrasses is at least 30.000 ha. Mapping and quantifications still remains to be done in most places
-
Meadows have decrease, disapeared significantly around urban areas, particularly in São Paulo and Rio de Janeiro (South East coast)
-
Signals of eutrophication and habitat modification since 1980
-
Long term changes in some monitored sites were correlated to changes in climate (temperature, precipitation) and hydrology (fluvial discharge)
-
Blue Carbon Hot Spots: - Caribean reefs (Colombia & Venezuela): Thalassia testudinum meadows - Northeast Brazil: intertidal, shallow reef laggons: Halodule wrightii meadows - Estuarine areas and shallow coastal lagoons: R. maritima & H. wrightii meadows
$upport: Brazilian Seagrasess
