frank muller-karger · 2014-06-23 · improved decision support system for coral reefs frank...
TRANSCRIPT
Frank Muller-Karger
Acknowledgements Funding provided by:
NASA Applied Sciences Program W. Turner/Ecological Forecasting
NOAA Coral Reef Conservation Program
National Science Foundation Chemical Oceanography
Environmental Protection Agency STAR
Concept Continental shelves, coastal
zones and estuaries support numerous industries:
tourism and recreation, fisheries, applications of marine bio-
molecules,
transportation, energy extraction
Many of these depend on high biodiversity, productivity
These ecosystems are showing the impact of climate change and increased human use of resources
It is possible to monitor vital signs of ecosystem function by focusing on the lowest levels of the food web in the ocean
Outline What can we really see from space?
Remote sensing Advantages Limitations
Regional to global assessments: Evaluating stress in marine ecosystems
Shallow water tropical coral reefs Phytoplankton functional groups
Seascapes Time-Series: Their critical importance
Developing a Marine Biodiversity Observation Network (MBON)
Conclusions
Scales of variation and observation
Physical processes at different scales affect different biological processes
Different technologies are suited for different observations
climate
change
Basin-
scale
variability
internal waves
and
inertial motions
barotropic
variability
internal tides
Mesoscale and
shorter scale
and
Physical-
biological interactions
coastal
upwelling
eddies
and
fronts
gravity waves
vertical
turbulent
mixing
El Niño
Seasonal cycle
Rossby
waves
surface tides
Fish
Zoo-
plankton
Phyto-
plankton
Ships &
Buoys
Aircraft
Satellites
Annual Primary Production (SeaWiFS)
Overlaid: Large Marine Ecosystems (LME; K. Sherman / 1980’s concept)
Ben Halpern et al.
F. Muller-Karger, M. Eakin, L. Guild, M. Vega-Rodriguez, R. Nemani, G. Liu, S. Heron
E. Geiger, J. Li, S. Lynds, R. Ressl, S. Cerdeira Estrada
Charles Darwin: 1846
(The structure and distribution of coral reefs)
UNEP-WCMC Reefbase (2001 & 2012) (incl. Millennium Global Coral Reef Map)
http://data.unep-wcmc.org/datasets/13
Tropical coral reef Landsat imagery at USF (collaboration with Serge Andrefouet / IRD)
Caribbean Sea highlight
http://www.imars.usf.edu/MC/index.html >1,200 Landsat images
Male, Maldives
Takebone,
Indonesia
Los Roques, Venezuela
Los Roques
(Venezuela)
Comparison between
previous products and
new Millennium
products
Florida Keys study with Landsat (collaboration with D. Palandro) Three coral reefs were chosen as representative of Keys regions.
Landsat images from 1996, 1998, 2000, 2002.
Grecian Rocks
Classification
based on benthic
spectral signal Alligator Looe Key
Coral Cover Change (collaboration with D. Palandro)
200m
200m
200m
Grecian Rocks
Looe Key
Alligator
2000
Covered Substrate
Sand
Sparse Seagrass
LEGEND
Coral
Bare Substrate
Dense Seagrass
1996
1998
In Situ Monitoring in the FL Keys (Collaboration: Maria Vega, USF, and Rob Ruzicka, Florida FWRI)
The Coral Reef Monitoring Project (CREMP) has been
conducted annually since 1996 for 43 sites
Fiberglass tape
Inshore
Offshore
Plastic chain
~22
m
2m
Terrestrial vs. Coral Cover Change
7.15
6.20
5.21
4.22
5.95
3.03
1.32 1.26
0
1
2
3
4
5
6
7
8
1995 1996 1997 1998 1999 2000 2001 2002 2003
% C
ora
l c
ov
er/
La
nd
in
de
x r
ati
o
Year
Landsat Land vegetation index
Coral Bleaching: Impact of Climate Change Collaboration with
M. Eakin (NOAA/NESDIS), L. Guild (NASA/Ames)
Most of coral nutrition comes
from photosynthesis
Scott R
. S
anto
s
Symbiotic algae
Corals exposed to
high temperatures
and/or high light
become stressed
Corals eject their
algae; coral appears
“bleached”
If stress is mild or
brief, corals recover,
otherwise they die
zooxanthellae
Mass bleaching can
cover 100-1000’s km2
Nighttime Satellite-Derived Sea Surface Temperature (SST)
Coral Reef Watch Satellite-Based Products
22
Coral – specific
SST Anomaly
HotSpot
Degree Heating Week
Bleaching Alert Areas
Improved Decision Support System for Coral Reefs Frank Muller-Karger, USF and Mark Eakin, NOAA
• Next-generation, near-real-time global coral bleaching alert products
• 100x finer spatial resolution than NOAA operational products
• 5x5 km global products blend geostationary and polar orbiters from multiple countries
• Running daily at NOAA Coral Reef Watch since May 5
5 km Oct. 2013 bleaching alert area in Guam and Marianas Islands
http://coralreefwatch.noaa.gov/satellite/bleaching5km/index.php
Event at 50 km resolution
•1x1 km regional products using MODIS Sea Surface Temp
•Gulf of Mexico/Caribbean Sea are served by CONABIO in Mexico in a bi-national collaboration
•Florida Keys NMS newsletter already using new products
•NASA-University of South Florida-NOAA collaboration
Guam Guam
Northern Marianas
Islands
Northern Marianas Islands
New Coral Reef Watch Next-Generation 5-km Degree Heating Weeks
5 km
USF 1-km HotSpot products for the West Florida Shelf (August 29, 2011)
NASA MODIS HotSpot Based on Pathfinder 4km MMM climatology
Florida Keys: Time series of HotSpots and Degree-Heating Week products and In situ coral reef diversity estimates since 1996 (CREMP)
High SST in 1997-1998 and 2009-2010 led to decrease in H’ Patch reefs in the Middle Keys show less change compared to Upper Keys
Work with Maria Vega-Rodriguez (USF), R. Ruzicka (FWRI) Shannon diversity Index vs. Maximum DHWs (A) Upper Keys (B) Middle Keys
In situ: Coral Reef
Monitoring Project
(CREMP)
CHLA SSHA SST Current Speed (alt.)
Oceanographic Parameters and Larval Pelagic Fish Abundance (Collaboration with M. Roffer/ROFFS, J. Lamkin/NOAA, D. Lindo and B. Muhling/U Miami, S.
Habtes/USF)
Larvae of bluefin tuna, little tunny, and Auxis spp. were located within the boundaries of anticyclonic features and in GOM common waters.
Bluefin Tuna Gulf of Mexico Habitat
Larval BFT habitat in the GOM in late 20th century (1971–’99) and projected conditions (2045–2055 and 2085–2095), for March, April, May, and June. Barbara A. Muhling, Sang-Ki Lee, John T. Lamkin and Yanyun Liu. 2011. Predicting the effects of climate change on bluefin tuna
(Thunnus thynnus) spawning habitat in the Gulf of Mexico . ICES J. Mar. Sci. (2011) 68 (6): 1051-1062. doi: 10.1093/icesjms/fsr008
Bluefin Tuna Gulf of Mexico Habitat
GOM SST evolution for 2001 - 2098 (ensemble average of IPCC-AR4 / SRESA1B scenario). Preferred period for BFT spawning (∼24–27°C) is shifted earlier (from late April to early June in 21st century to March-April in late 21st century) Issue: time needed to migrate from Canada/N Atlantic feeding grounds is shortened
Predicted overlap between oil and BFT spawning grounds
spring 2010
• Spawning habitat model used to assess overlap between oil from the 2010 Deepwater Horizon oil spill and bluefin tuna spawning grounds
• While oil contaminated extensive portions of spawning habitat in the eastern Gulf of Mexico, larvae spawned in the western Gulf likely remained unaffected
Global Chlorophyll distribution
Plankton functional types (PFTs) and their importance
Nitrogen fixation (Trichodesmium sp.)
Diatoms, dinoflagellates, other microplankton, picoplankton
Why PFT’s are Important PFT’s are groups of
phytoplankton with similar biology & biogeochemical roles, e.g.: physiology sinking CO2 sequestration DMS production silicate drawdown
Cell SIZE is a characteristic feature of
PFT’s determines structure and
function of pelagic ecosystems
Global RS retrieval of the PFT’s is needed
Chisholm, 2000
Partitioning Number (Concentration)
Picoplankton, # m-3 (0.5 mm to 2 mm)
Microplankton, # m-3 (20 mm to 50 mm)
Nanoplankton, # m-3 (2 mm to 20 mm)
Pico’s vary ~100 times
Nano’s vary ~ 10,000 times
Micro’s vary ~ 106 times
log10(particles/m3)
Courtesy of Dave Siegel et al.
(UC Santa Barbara) and Tihomir Kostadinov (Univ. Richmond)
Partitioning Biovolume – the PFT’s Picoplankton % (0.5 mm to 2 mm)
Microplankton % (20 mm to 50 mm)
Nanoplankton % (2 mm to 20 mm)
Pico’s dominate oligotrophic ocean (>90%) Nano’s in transition regions (~50%) Micro’s only found in upwelling zones & high latitudes (<60%)
Irina Marinov, Tihomir Kostadinov, Svetlana Milutinovic, in prep.
Survival of higher trophic levels is tied to food availability: quality, amount, timing, location
If the food (phytoplankton bloom) is available early, fish cohorts tend to do better
Fish recruitment improves with size of phytoplankton blooms (see 1-year
lag in recruitment index)
(Trevor Platt and colleagues)
Shrimp off Newfoundland: more shrimp with more phytoplankton
(Trevor Platt and colleagues)
Average annual particulate organic carbon flux (gC m-2 y-1) deposited on the ocean floor between 1998-2001. (Muller-Karger et al., 2005)
Global carbon budget: will depend on plankton make-up
Ocean biogeochemistry and ecology time series
Fig. 1. Center: Location of the Monterey Bay (MBARI) and the Cariaco Basin (CARIACO) time-series. Left panel: Monterey Bay interannual and decadal
variations (seasonal cycle removed) of nitrate at 60m, chlorophyll, pico-phytoplankton, large phytoplankton, oxygen, jumbo squid, and flux of material to
the seafloor. Right: Cariaco Basin monthly and annual variation in diatom (A), dinoflagellate (B), coccolithophorid (C) inventories over the upper 55 m.
(D) Sardine landings (NE Venezuela). Blue and red lines are medians of observations (1996-2004 and 2005-2009) (Taylor et al., 2012). Shifts in
phytoplankton community structure and ecosystem production at both locations are related to changes in the wind and ocean circulation.
Monterey: F. Chavez et al.
CARIACO: F. Muller-Karger et al.
Seascapes
Illustration courtesy of F. Chavez/K. Lance
(Monterey Bay Research Institute/MBARI)
-Made much progress toward measuring change in the global ocean in the past 20 years
-Made steps toward quantifying:
-habitat diversity and
-biodiversity
-Have much to do to address global scale issues:
-developing baselines of habitat, diversity
-Integrate multiple types of space-based observations with in situ observations
- Address limitations in:
-high spatial resolution, multispectral obs.
-algorithms: classify coastal habitat, water quality
-Ensure time series of medium to high spatial resolution (250 m to 2 m), highly sensitive and frequent VIS sensors/observations, multidisciplinary remote sensing series, and in situ time series;
-Support of scientific personnel (training)