Texas Mangrove Research Symposium - Mission

Transcription

Texas Mangrove Research Symposium - Mission
Texas Mangrove
Research Symposium
AGENDA
Thursday, February 28
9:00am - 5:00pm
University of Texas Marine Science Institute
Estuarine Research Center, Seminar Room
750 Channel View Dr.
Port Aransas, Texas
9:00 - 9:15 WELCOME AND INTRODUCTIONS
9:15 - 9:30 Dr. Kiersten Madden, Mission-Aransas National Estuarine Research Reserve
Monitoring Mangroves: Applying the National Estuarine Research Reserve Approach to Texas
9:30 - 10:00 Tom Tremblay, Bureau of Economic Geology, University of Texas at Austin
Baseline Mapping for Mangrove Monitoring in the Coastal Bend, Texas Gulf Coast
10:00 - 10:30 Dr. James Gibeaut, Harte Research Institute for Gulf of Mexico Studies, Texas A&M
University – Corpus Christi
Proposed Observatory for Understanding Coastal Wetland Change
10:30 - 10:45 BREAK
10:45 - 11:15 Dr. John Schalles, Creighton University
The Mangroves of Redfish Bay: Field surveys and high resolution imagery to map distribution, canopy
height, and vegetation response to the February, 2011 freeze
11:15 - 11:45 Chris Wilson, University of Texas Marine Science Institute
Colonization and age structure of red mangrove (Rhizophora mangle) trees along the coast of Texas
11:45 - 12:15 Dr. Anna Armitage, Texas A&M University – Galveston
Ecological implications of black mangrove expansion into Texas salt marshes: Comparisons among
marsh and mangrove habitats
12:15 - 1:00 CATERED LUNCH
1:00 - 1:30 Dr. Steven Pennings, University of Houston
Ecological implications of black mangrove expansion into Texas salt marshes: Insights from a largescale mangrove removal experiment
1:30 - 2:00 Dr. Liz Smith, International Crane Foundation
Habitat replacement by mangrove establishment: Implications for Whooping Crane use
2:00 - 2:30 Dr. Rusty Feagin, Texas A&M University - College Station
Historical Reconstruction of Mangrove Expansion in the Gulf of Mexico: Linking Climate Change with
Carbon Sequestration in Coastal Wetlands
2:30 - 2:45 BREAK
Texas Mangrove
Research Symposium
AGENDA
Thursday, February 28
9:00am - 5:00pm
University of Texas Marine Science Institute
Estuarine Research Center, Seminar Room
750 Channel View Dr.
Port Aransas, Texas
2:45 - 4:00 U.S. Geological Survey National Wetlands Research Center
Tom Doyle, USGS National Wetlands Research Center
Modeling mangrove structure and spread across the Northern Gulf Coast under climate change:
Effects of storms, sea-level rise, freshwater flow, and freeze.
Richard Day, USGS National Wetlands Research Center
Biogeography of black mangrove and freeze tolerance
Ken Krauss, USGS National Wetlands Research Center
Water use characteristics of black mangroves along the Northern Gulf Coast
Erik Yando, University of Louisiana at Lafayette
The belowground implications of mangrove forest migration: Plant-soil variability across forest
structural gradients in TX, LA, and FL
Mike Osland, USGS National Wetlands Research Center
Winter climate change and coastal wetland foundation species: Salt marshes vs. mangrove forests
4:00 - 4:30 DISCUSSION
4:30 - 4:45 WRAP UP AND ADJOURN
Initials
Name
AA
RD
Anna Armitage
Richard Day
MO
SP
JS
LS
TT
EY
Mike Osland
Steve Pennings
John Schalles
Liz Smith
Tom Tremblay
Erik Yando
TD
RF
JG
KK
KM
DA
KB
JB
EB
RC
KD
ZD
SD
MAD
ND
RD
CG
HG
BH
WH
KH
LH
CH
FK
JL
SM
DN
DO
PR
JR
Tom Doyle
Rusty Feagin
James Gibeaut
Ken Krauss
Kiersten Madden
Dan Alonso
Karen Bishop
Jorge Brenner
Ed Buskey
Rhonda Cummins
Kelly Darnell
Zack Darnell
Sayantani Dastidar
Mary Ann Davis
Nicole Davis
Richard Davis
Sarah Douglas
Catalina Gempeler
Hongyu Guo
Beau Hardegree
Wade Harrell
Kent Hicks
Lauren Hutchison
Cammie Hyatt
Felix Keeley
Ranjani Wasantha
Kulawardhana
Jessica Lunt
Shanna Madsen
Duncan Neblett
R. Deborah Overath
Patrick Rios
Jackie Robinson
Organization/Af�iliation
Email
INVITED SPEAKERS
Texas A&M University – Galveston
USGS National Wetlands Research Center
armitaga@tamug.edu
dayr@usgs.gov
USGS National Wetlands Research Center
Texas A&M University – College Station
Texas A&M University – Corpus Christi
USGS National Wetlands Research Center
Mission-Aransas National Estuarine Research
Reserve
USGS National Wetlands Research Center
University of Houston
Creighton University
International Crane Foundation
Bureau of Economic Geology – UT Austin
University of Louisiana at Lafayette
WORKSHOP PARTICIPANTS
San Antonio Bay Partnership
Texas Sea Grant
The Nature Conservancy
Mission-Aransas NERR
Texas Sea Grant
Univ. of Texas Marine Science Institute
Mission-Aransas NERR
University of Houston
The Aquarium at Rockport Harbor
Texas State University
Texas A&M University – Corpus Christi
Univ. of Texas Marine Science Institute
Univ. of Texas Marine Science Institute
University of Houston
US Fish and Wildlife Service
US Fish and Wildlife Service
Texas Parks and Wildlife Department
Texas A&M University – Corpus Christi
Mission-Aransas NERR
City of Rockport/NERR Advisory Board
Texas A&M University – College Station
Texas A&M University – Corpus Christi
Mission-Aransas NERR
Univ. of Texas Marine Science Institute
Texas A&M University – Corpus Christi
City of Rockport Water Quality Committee
Texas Parks and Wildlife Department
Doylet@usgs.gov
feaginr@tamu.edu
James.gibeaut@tamucc.edu
kraussk@usgs.gov
Kiersten.madden@utexas.edu
mosland@usgs.gov
spennin@central.uh.edu
Johnschalles@creighton.edu
esmith@savingcranes.org
Tom.tremblay@beg.utexas.edu
Erik.yando@gmail.com
dalonso@sabay.org
Karen.bishop@tamu.edu
jbrenner@tnc.org
Ed.buskey@utexas.edu
rcummins@tamu.edu
kellymdarnell@gmail.com
mzd@utexas.edu
sayantanii@gmail.com
madradrpt@gmail.com
ndavis@txstate.edu
Madradrpt@gmail.com
sarahvdouglas@utexas.edu
catalicu@utexas.edu
greatuniverse@hotmail.com
Beau_hardegree@fws.gov
Wade_harrell@fws.gov
Kent.hicks@tpwd.state.tx.us
Lauren.hutchison@tamucc.edu
Cammie.hyatt@utexas.edu
F_keeley@yahoo.com
Wasanthkula@yahoo.com
jlunt@tamucc.edu
Shanna.l.madsen@gmail.com
Deborah.overath@tamucc.edu
Prios1001@sbcglobal.net
Jackie.robinson@tpwd.state.tx.us
CR
JS
CPS
CS
JT
KT
HW
CW
DW
AW
LW
DY
Carolyn Rose
James Sanchez
Carlota Plantier Santos
Chris Shank
Jim Tolan
Kathryn Tunnell
Heather Wade
Carolyn Weaver
Dawn Whitehead
Ashley Whitt
Leslie Williams
David Yoskowitz
Mission-Aransas NERR
Texas A&M University – Corpus Christi
Harte Research Institute, Texas A&M
University – Corpus Christi
Univ. of Texas Marine Science Institute
Texas Parks and Wildlife Department
Texas General Land Of�ice
Texas Sea Grant/Mission-Aransas NERR
Texas A&M University – Galveston
US Fish and Wildlife Service
Texas A&M University – Galveston
Texas Parks and Wildlife Department
Harte Research Institute, Texas A&M
University – Corpus Christi
Carolyn.rose@utexas.edu
James.sanchz5484@sbcglobal.net
Carlota.santos@tamucc.edu
cshank@utexas.edu
James.tolan@tpwd.state.tx.us
Kathryn.tunnell@glo.texas.gov
hbwade@tamu.edu
caweaver@tamug.edu
Dawn_Whitehead@fws.gov
whitta@tamug.edu
Leslie.williams@tpwd.state.tx.us
David.yoskowitz@tamucc.edu
Texas Mangrove
Research Symposium
AGENDA
Thursday, February 28
9:00am - 5:00pm
University of Texas Marine Science Institute
Estuarine Research Center, Seminar Room
750 Channel View Dr.
Port Aransas, Texas
9:00 - 9:15 WELCOME AND INTRODUCTIONS
9:15 - 9:30 Dr. Kiersten Madden, Mission-Aransas National Estuarine Research Reserve
Monitoring Mangroves: Applying the National Estuarine Research Reserve Approach to Texas
9:30 - 10:00 Tom Tremblay, Bureau of Economic Geology, University of Texas at Austin
Baseline Mapping for Mangrove Monitoring in the Coastal Bend, Texas Gulf Coast
10:00 - 10:30 Dr. James Gibeaut, Harte Research Institute for Gulf of Mexico Studies, Texas A&M
University – Corpus Christi
Proposed Observatory for Understanding Coastal Wetland Change
10:30 - 10:45 BREAK
10:45 - 11:15 Dr. John Schalles, Creighton University
The Mangroves of Redfish Bay: Field surveys and high resolution imagery to map distribution, canopy
height, and vegetation response to the February, 2011 freeze
11:15 - 11:45 Chris Wilson, University of Texas Marine Science Institute
Colonization and age structure of red mangrove (Rhizophora mangle) trees along the coast of Texas
11:45 - 12:15 Dr. Anna Armitage, Texas A&M University – Galveston
Ecological implications of black mangrove expansion into Texas salt marshes: Comparisons among
marsh and mangrove habitats
12:15 - 1:00 CATERED LUNCH
1:00 - 1:30 Dr. Steven Pennings, University of Houston
Ecological implications of black mangrove expansion into Texas salt marshes: Insights from a largescale mangrove removal experiment
1:30 - 2:00 Dr. Liz Smith, International Crane Foundation
Habitat replacement by mangrove establishment: Implications for Whooping Crane use
2:00 - 2:30 Dr. Rusty Feagin, Texas A&M University - College Station
Historical Reconstruction of Mangrove Expansion in the Gulf of Mexico: Linking Climate Change with
Carbon Sequestration in Coastal Wetlands
2:30 - 2:45 BREAK
Texas Mangrove
Research Symposium
AGENDA
Thursday, February 28
9:00am - 5:00pm
University of Texas Marine Science Institute
Estuarine Research Center, Seminar Room
750 Channel View Dr.
Port Aransas, Texas
2:45 - 4:00 U.S. Geological Survey National Wetlands Research Center
Tom Doyle, USGS National Wetlands Research Center
Modeling mangrove structure and spread across the Northern Gulf Coast under climate change:
Effects of storms, sea-level rise, freshwater flow, and freeze.
Richard Day, USGS National Wetlands Research Center
Biogeography of black mangrove and freeze tolerance
Ken Krauss, USGS National Wetlands Research Center
Water use characteristics of black mangroves along the Northern Gulf Coast
Erik Yando, University of Louisiana at Lafayette
The belowground implications of mangrove forest migration: Plant-soil variability across forest
structural gradients in TX, LA, and FL
Mike Osland, USGS National Wetlands Research Center
Winter climate change and coastal wetland foundation species: Salt marshes vs. mangrove forests
4:00 - 4:30 DISCUSSION
4:30 - 4:45 WRAP UP AND ADJOURN
Initials
Name
AA
RD
Anna Armitage
Richard Day
MO
SP
JS
LS
TT
EY
Mike Osland
Steve Pennings
John Schalles
Liz Smith
Tom Tremblay
Erik Yando
TD
RF
JG
KK
KM
DA
KB
JB
EB
RC
KD
ZD
SD
MAD
ND
RD
CG
HG
BH
WH
KH
LH
CH
FK
JL
SM
DN
DO
PR
JR
Tom Doyle
Rusty Feagin
James Gibeaut
Ken Krauss
Kiersten Madden
Dan Alonso
Karen Bishop
Jorge Brenner
Ed Buskey
Rhonda Cummins
Kelly Darnell
Zack Darnell
Sayantani Dastidar
Mary Ann Davis
Nicole Davis
Richard Davis
Sarah Douglas
Catalina Gempeler
Hongyu Guo
Beau Hardegree
Wade Harrell
Kent Hicks
Lauren Hutchison
Cammie Hyatt
Felix Keeley
Ranjani Wasantha
Kulawardhana
Jessica Lunt
Shanna Madsen
Duncan Neblett
R. Deborah Overath
Patrick Rios
Jackie Robinson
Organization/Af�iliation
Email
INVITED SPEAKERS
Texas A&M University – Galveston
USGS National Wetlands Research Center
armitaga@tamug.edu
dayr@usgs.gov
USGS National Wetlands Research Center
Texas A&M University – College Station
Texas A&M University – Corpus Christi
USGS National Wetlands Research Center
Mission-Aransas National Estuarine Research
Reserve
USGS National Wetlands Research Center
University of Houston
Creighton University
International Crane Foundation
Bureau of Economic Geology – UT Austin
University of Louisiana at Lafayette
WORKSHOP PARTICIPANTS
San Antonio Bay Partnership
Texas Sea Grant
The Nature Conservancy
Mission-Aransas NERR
Texas Sea Grant
Univ. of Texas Marine Science Institute
Mission-Aransas NERR
University of Houston
The Aquarium at Rockport Harbor
Texas State University
Texas A&M University – Corpus Christi
Univ. of Texas Marine Science Institute
Univ. of Texas Marine Science Institute
University of Houston
US Fish and Wildlife Service
US Fish and Wildlife Service
Texas Parks and Wildlife Department
Texas A&M University – Corpus Christi
Mission-Aransas NERR
City of Rockport/NERR Advisory Board
Texas A&M University – College Station
Texas A&M University – Corpus Christi
Mission-Aransas NERR
Univ. of Texas Marine Science Institute
Texas A&M University – Corpus Christi
City of Rockport Water Quality Committee
Texas Parks and Wildlife Department
Doylet@usgs.gov
feaginr@tamu.edu
James.gibeaut@tamucc.edu
kraussk@usgs.gov
Kiersten.madden@utexas.edu
mosland@usgs.gov
spennin@central.uh.edu
Johnschalles@creighton.edu
esmith@savingcranes.org
Tom.tremblay@beg.utexas.edu
Erik.yando@gmail.com
dalonso@sabay.org
Karen.bishop@tamu.edu
jbrenner@tnc.org
Ed.buskey@utexas.edu
rcummins@tamu.edu
kellymdarnell@gmail.com
mzd@utexas.edu
sayantanii@gmail.com
madradrpt@gmail.com
ndavis@txstate.edu
Madradrpt@gmail.com
sarahvdouglas@utexas.edu
catalicu@utexas.edu
greatuniverse@hotmail.com
Beau_hardegree@fws.gov
Wade_harrell@fws.gov
Kent.hicks@tpwd.state.tx.us
Lauren.hutchison@tamucc.edu
Cammie.hyatt@utexas.edu
F_keeley@yahoo.com
Wasanthkula@yahoo.com
jlunt@tamucc.edu
Shanna.l.madsen@gmail.com
Deborah.overath@tamucc.edu
Prios1001@sbcglobal.net
Jackie.robinson@tpwd.state.tx.us
CR
JS
CPS
CS
JT
KT
HW
CW
DW
AW
LW
DY
Carolyn Rose
James Sanchez
Carlota Plantier Santos
Chris Shank
Jim Tolan
Kathryn Tunnell
Heather Wade
Carolyn Weaver
Dawn Whitehead
Ashley Whitt
Leslie Williams
David Yoskowitz
Mission-Aransas NERR
Texas A&M University – Corpus Christi
Harte Research Institute, Texas A&M
University – Corpus Christi
Univ. of Texas Marine Science Institute
Texas Parks and Wildlife Department
Texas General Land Of�ice
Texas Sea Grant/Mission-Aransas NERR
Texas A&M University – Galveston
US Fish and Wildlife Service
Texas A&M University – Galveston
Texas Parks and Wildlife Department
Harte Research Institute, Texas A&M
University – Corpus Christi
Carolyn.rose@utexas.edu
James.sanchz5484@sbcglobal.net
Carlota.santos@tamucc.edu
cshank@utexas.edu
James.tolan@tpwd.state.tx.us
Kathryn.tunnell@glo.texas.gov
hbwade@tamu.edu
caweaver@tamug.edu
Dawn_Whitehead@fws.gov
whitta@tamug.edu
Leslie.williams@tpwd.state.tx.us
David.yoskowitz@tamucc.edu
Discussion Notes
Liz Smith: Mangrove research needs to concentrate on �inding funding that will allow for more
information on the types of species that will be impacted by the conversion of salt marsh to
mangrove structure; speci�ically, we need to �igure out what will happen with snails, crabs, �ish, etc.
to get a handle on if the food web will shift, and how.
Liz Smith: Research into the potential impact of mangrove establishment higher in the estuary,
given that we will have diminishing freshwater in�lows (due to climate change, water use, etc.). We
already have a narrow band of intermediate marsh, and a lower brackish area. If we lose that, will
we have mangroves all the way into the delta? We need to look at the diversity of the system with
regard to the replacement of marshes along the salinity gradient.
Michael Osland: We have a proposal into the Climate Science Center to quantify the relationship
between precipitation and temperature on a gradient from the Florida/Alabama border to Mexico.
At Liz’s suggestion, we will look into making the Mission-Aransas and San Antonio bay systems
Texas priority sites.
Kiersten Madden: There is a Gulf workgroup forming for mangroves – would it be possible to form
a Texas working group?
Tom Tremblay: It might be a good idea to host a special session in conjunction with the 2014 Texas
Bays and Estuaries meeting.
Rusty Feagin: What’s the general consensus on mangrove expansion? If we were going to restore a
site, would you plant mangroves?
Anna Armitage: We can’t answer that question yet, because we don’t know enough about the
implications, costs, and what you gain or lose when you use mangroves in restoration projects. This
is a broad area for future research – understanding how to manage these resources in response to
mangrove expansion.
Liz Smith: I don’t think that we should take mangroves out of the equation if we don’t have a good
understanding of the impacts yet. We also shouldn’t be putting these opinions into our research
designs. The public may have one opinion regarding mangrove expansion, but we don’t know, and
mangrove expansion may be something that we cannot change at all. With regard to whooping
cranes, we want to know quantitatively and scienti�ically what the answer is. However, we need it
soon, and we may have to make some management decisions before all of those answers are known.
Jim Gibeaut: I want to emphasize Liz’s point about the fact that we may not be able to stop
mangrove expansion. There are some good points to mangrove expansion: based on data from
Rusty and others, the sedimentation rate from mangroves is higher than Spartina, and therefore
they should be able to keep up with sea level rise better than marshes. Given the future rates for sea
level rise, it might be a question of whether we have any kind of vegetation habitat rather than
simply open water. Having mangroves in the mix might maintain that intertidal vegetation habitat.
More research is needed on mangrove expansion in the face of sea level rise and sedimentation.
Chris Wilson: People don’t necessarily see mangroves as a positive thing – they see mangroves as
an invasive species. The ecotone is changing, and mangroves don’t directly cause the loss of salt
marsh.
Lauren Hutchison: We’ve conducted focus groups and based on those preliminary results, people
don’t know what mangroves are, and the only ones who do are recreational users of those areas.
Rusty Feagin: What about restoration managers? We are making large changes in physical
landscape by agencies completing restoration projects (mitigation banks, etc.); there is a fair
amount of wetland created. It could be possible that the ecosystem services from using mangroves
are higher – maybe those services make the use of mangroves a net positive.
Beau Hardegree: That might be the case, but we shouldn’t be too hasty and put mangroves in all of
our restoration projects. In the past, when mitigation occurs we haven’t used mangroves because
mitigation is usually completed in perpetuity – mangroves freeze. New research is showing that
mangroves don’t freeze and die off completely as previously thought, so we are looking at mangrove
restoration as an option. However, we need to think about where we’re placing them – maybe they
shouldn’t be planted in Whooping Crane habitat.
John Schalles: No one has brought this up yet, but does the expansion of mangroves present issues
for human health and an increase of vector-borne diseases? Are there any implications for avian
health? There is currently no research being done on this.
Tom Tremblay: There was a previous planting effort in Bajilla Grande when it was realized that
Mother Nature was spreading mangroves better than any planting could. Maybe we don’t need to be
promoting restoration projects using mangrove, because it will happen anyhow; if we have a choice,
maybe we should plant Spartina.
Kiersten Madden: Do restoration practitioners know this?
Beau Hardegree: There’s a recent feeling that people are using mangroves for in-kind projects.
Kiersten Madden: Does that responsibility fall to you to make those decisions?
Beau Hardegree: Resource management agencies and the Army Corps of Engineers normally make
the decision.
Kiersten Madden: We need a representative from the Corps here.
Tom Tremblay: Future research might look into morphology classi�ications (clumps, singular,
linear formations along inlets) to determine if certain forms are less intrusive than others. We are
also currently focusing a lot on Harbor Island, which could possibly be a unique case because of its
origin as a relic-ed tidal fan delta, which is unusual for the proliferation of mangroves. There are
other forms of expansion (linear, etc.) found elsewhere. We need more research in general, not just
here in Harbor Island.
Monitoring Mangroves
National Estuarine Research Reserve System
A P P LY I N G T H E N E R R S A P P R O A C H I N T E X A S
PROTECTED
PLACES
SCIENCE
PEOPLE
Kiersten Madden
Stewardship Coordinator
Mission-Aransas National Estuarine Research Reserve
Mission-Aransas Reserve
The Mission-Aransas
NERR brings together
scientists, landowners,
policy-makers, & the
public to ensure that
coastal management
decisions benefit flora &
fauna, water quality,
and people.
Research
System
Wide
Monitoring
Program
Sectors
RESEARCH
STEWARDSHIP
EDUCATION
TRAINING
Improve
understanding of
Texas coastal zone
ecosystem
structure and
function
Promote public
appreciation and
support for
stewardship of
coastal resources
Increase
understanding of
coastal ecosystems
by diverse
audiences
Increase
understanding of
coastal ecosystems
by coastal decision
makers
System Wide Monitoring Program
SWMP:
1. Abiotic
2. Biotic
3. Mapping
Standardized Protocols
Vegetation Monitoring Protocol
The NERRS monitoring protocol for vegetation communities
is designed to:
1. Quantify vegetation patterns and their change over space and time;
2. Be consistent with other monitoring protocols used nationally and worldwide;
3. Be consistently used over a wide range of estuarine sites and habitats, and for
a variety of reserve specific purposes;
4. Be used as a foundation for quantifying relationships among the various
edaphic factors and the processes that are regulating the patterns of
distribution and abundance in these communities;
5. Provide detailed information that can be used to support comprehensive
remotely sensed mapping of vegetation communities and other NERRS System
Wide Monitoring Program data collection, as well as NERRS/NOAA education,
stewardship and restoration efforts.
Mangrove Protocols
Sampling Site
For trees with trunk diameter
greater than 2.5 cm . . .
For trees with trunk diameter
less than 2.5 cm . . .
Numbered
Position Mapped
Identified to Species
DBH
Total Height
Trunk Height
Prop Root Height
Numbered
Position Mapped
Identified to Species
Total Height
Trunk Height
Prop Root Height
5
4
3
10 m
2
10 m
1m
Surface Elevation Table
(with marker horizons)
1
Mangrove Protocols
WHOLE PLOTS
(10 x 10 m)
SUB-PLOTS
(1 x 1 m)
For trees with trunk diameter
greater than 2.5 cm . . .
For trees with trunk diameter
less than 2.5 cm . . .
Numbered
Position Mapped
Identified to Species
DBH
Total Height
Trunk Height
Prop Root Height
Numbered
Position Mapped
Identified to Species
Total Height
Trunk Height
Prop Root Height
10 m
10 m
1m
1m
SUB-PLOTS
(1 x 1 m)
1m
WHOLE PLOTS
(10 x 10 m)
5
4
1
2
3
Total Height
B = 61
NB = 116
TOTAL = 177
Branching = 21
Non-Branching = 17
TOTAL = 38
B = 101
NB = 7
TOTAL = 108
B = 45
NB = 45
TOTAL = 90
15 m
B = 55
NB = 179
TOTAL = 234
All Transects
400
Branching
350
B = 29
NB = 14
TOTAL = 43
B = 80
NB = 49
TOTAL = 129
B = 15
NB = 17
TOTAL = 32
15 m
B = 44
NB = 45
TOTAL = 89
B = 44
NB = 6
TOTAL = 50
B = 86
NB = 63
TOTAL = 149
B = 69
NB = 36
TOTAL = 105
15 m
B = 65
NB = 42
TOTAL = 107
B = 66
NB = 68
TOTAL = 134
Average Total Height (cm)
Non-Branching
B = 63
NB = 81
TOTAL = 144
300
250
200
150
100
50
0
1
B = 23
NB = 8
TOTAL = 31
B = 67
NB = 38
TOTAL = 105
2
3
4
Plot No.
B = 22
NB = 3
TOTAL = 25
B = 69
NB = 67
TOTAL = 136
B = 55
NB = 56
TOTAL = 111
Average Total
Height (cm)
Transect 1
Trunk Height
40
30
20
10
0
Total Height
1
2
3
4
Non-branching
All Transects
100
75
50
25
0
1
2
3
Average Total
Height (cm)
40
30
20
10
0
1
2
3
4
Average Total
Height (cm)
Transect 4
120
90
60
30
0
1
2
3
4
70
60
50
40
30
20
10
0
1
180
3
0
1
Average Total
Height (cm)
2
3
4
Transect 1
80
Trunk Height
40
0
1
Average Total
Height (cm)
120
2
3
4
Transect 2
All Transects
80
40
30
0
1
Average Total
Height (cm)
120
2
3
4
Transect 3
80
40
0
1
120
Average Total
Height (cm)
4
Plot No.
60
120
2
3
4
Transect 4
80
40
25
20
15
10
5
0
1
120
Average Total
Height (cm)
Non-branching
2
120
Average Trunk Height (cm)
Average Total
Height (cm)
Transect 5
Branching
Non-branching
80
4
Transect 3
Total Height
Branching
90
Average Total Height (cm)
Branching
Average Total
Height (cm)
Transect 2
2
3
4
0
1
Transect 5
2
3
Plot No.
80
40
0
1
2
3
4
4
Trunk Height
Average Trunk
Height (cm)
40
Transect 1
30
GTM Reserve
20
10
0
1
2
Average Trunk
Height (cm)
40
Average Trunk
Height (cm)
Average Trunk
Height (cm)
3
4
3
4
3
4
3
4
Transect 2
20
10
0
1
2
Transect 3
30
20
10
0
1
40
2
Transect 4
30
20
10
0
1
2
40
Average Trunk
Height (cm)
4
30
40
GTM Reserve
3
Transect 5
30
20
10
0
1
2
What’s the best approach?
Is annual monitoring sufficient?
Do we need to be monitoring this many “individuals”?
Is the GTM approach better suited for this type of mangrove
habitat?
Kiersten Madden, Ph.D.
Stewardship Coordinator
Mission-Aransas NERR
361-749-3047
kiersten.madden@utexas.edu
www.missionaransas.org
Sentinel Sites
Tide Gauge
Bench Mark with
Geodetic Control
(NAVD88, etc.)
Surface Elevation
Table (SET)
Surface
Accretion
From: Montagna et al., 2011
Initial Wetland Surface
Elevation
Change
Sea Level Rise
Observed Changes
Upland
Marker
Horizon
Subsided Wetland Surface
Depth of SET
measurement
integration
Shallow
Subsidence
Deep Subsidence
1930
25%
1979
58%
1995
39%
2004
58%
Baseline Mapping for Mangrove Monitoring in the Coastal Bend,
Texas Gulf Coast
Thomas A. Tremblay
Bureau of Economic Geology, UT
Amy L. Neuenschwander
Applied Research Laboratories, UT
Daniel Gao
Texas General Land Office
2010
2001
Ac cretion 1979-2001
Ac cretion 1950s -1979
Erosion 1979-2001
Erosion 1950s -197 9
0
1
2
3
4
5 Kilo meters
2010
2002
Active fan
Aransas Bay
Inactive fan
Carlos
Bay
Mesquite
Bay
Allyns Bight
Tidal delta
12,000
Spalding Cove
Mud Island
North Pass
940
786
10,000
¯
Area (ha)
8,000
11,198
10,332
6,000
Mangrove
Aransas Pass
0
1
2
3
4
5
6
7
8
9
Km
10
Gulf of Mexico
Vinson Slough
Emergent marsh
Cedar Bayou
after Andrews, 1970
600
4,000
500
2,000
0
400
2001-04
Active fan
1979
(ha) 300
82%
Mangrove
+7 ha/yr
Change rate
73% 94%
Inactive fan
60% 58%
90%
200
Tidal delta
100
Emergent marsh
+38 ha/yr
0
1979
2002-04
Salt marsh in fan/delta complex (% low marsh)
Range: 350 to 2500 nm
Spectral resolution: 3 nm @ 700
Sampling interval: 1.4 nm @ 350 – 1000 nm
Speed: 0.2 seconds/ spectrum
Some marsh gain from uplands occurred where high marsh moved into the lower parts of
eolian mounds. Eolian mounds are elongate sand mounds that occupy the interdistributary
areas of the washover fan (Andrews, 1970).
Conclusions
• Salt marsh and mangroves have been increasing in
area since the mid-1950’s with marshes increasing at
higher rates
• Within the washover fan/tidal delta complex on San
Jose Island, marsh is expanding with a net loss of low
marsh and a net increase of high marsh
• Wetland change is probably caused by relative sea
level rise where low marsh is inundated and high
marsh moves into flats or upland
HyperScan-VNIR-micro (16 bit camera)
Detector size: 2400 x 2400 spatial pixels
HyperVision software: ENVI-IDL + flight data capture system with SSD
Spectral range: 0.4 to 0.1 μm
Summary
• Focus on Matagorda Island and San Jose Island
• Dynamic area affected by sea-level rise and
erosion/accretion, with wetland trends similar to
those found on much of the Lower Texas Coast
• Objective is to establish methods and protocol for
automated mangrove monitoring using the
hyperspectral platform
The End…?
The Order of the Straight Arrow
Season 1, episode 3
Proposed Observatory for
Understanding Coastal Wetland
Change
Barrier Island Environments
James Gibeaut
Harte Research Institute for Gulf of Mexico Studies
Texas A&M University – Corpus Christi
Classify habitat types
according to elevation
Habitat
grid
Salt flats
Algal flats
Intertidal marsh
Mangroves
Seagrass
Wetland Response to Sea Level Rise
Wetland Transition Model
DEM
(original)
Interior upland
Future date
reached?
Yes
No
Adjusted
DEM
Shoreline
change grid
Retreat
shoreline
Apply
vertical accretion
adjustment
1-year
loop
Apply local
subsidence
adjustment
Differential
subsidence
grid
Apply
global sea level
adjustment
Output
habitat grid
Compute
statistics of
habitat status
Maps
Statistics
Graphs
Topographic relationship of habitat types
Processes Affecting Marsh Elevation
Wetland Observatory
Aerial multi/hyper
spectral imagery,
photography and Lidar
Surface Elevation Tables
Marker horizons
Observatory
Water-level loggers
Transect photography
and sampling
Airborne lidar for topographic mapping
Terrestrial Lidar &
Microsoft Kinect sensor
RTK transect survey &
Deep set benchmark
Detection and removal of shrubs and building
0.1 0.2
0.2
00 0.1
0.4 km
km
0.4
´
http://slvg.soe.ucsc.edu/unvis.html
Vegetation mapping
https://www.e-education.psu.edu/
Elevation control: deep set benchmarks
• Aerial photography
• Multi/hyperspectral
Image credit: Greg Hauger
Real-time Kinematic Surveys
Record vegetation height and type
Transect monitoring of wetland
vegetation change
Transect monitoring of wetland
vegetation change
Surface Elevation Tables (SET) for
measurement of elevation change
Terrestrial Laser for
topographic mapping
Future Exploration: low-cost lidar sensor
Microsoft Kinect
•
•
•
•
IR projector & camera for depth map
30 cm to 15 m range
Spatial resolution ~7 mm at 5 m
Cheap < $150; open source tools
Potential Metrics
• Micro-topography time series
• mount along transect
• Water inundation
• Near-IR & RGB camera
Challenges
•
•
•
http://www.pwrc.usgs.gov/set/theory.html
Field deployment
• power, environmental conditions
Will change signal be detectable?
• mm-level
Telemetry
Image credit: Greg Hauger
18
Marker horizon locations
Marker horizons for measurement
of sedimentation rates
http://www.pwrc.usgs.gov/set/theory.html
http://www.pwrc.usgs.gov/set/theory.html
Total of 168 Marker Horizons
Coring for accretion
measurements
Accretion Rate Calculation
137Cs activity
• Field Methods
• Coring & compaction
• GPS observations
• Lab Methods
• Grain size analysis
• Bulk density
• Gamma spectroscopy
Cesium (Cs) 137
- 1963 marker horizon due to
residual atmospheric fallout
prior to 1964 nuclear test ban
Is 1963 peak present and above minimum
detectable activity (is it really there)?
Correct peak depth for grain size influence
Correct peak depth for core compaction
Minimum
Detectable
activity
21
Water-level measurements
Wetland Observatory
Aerial multi/hyper
spectral imagery,
photography and Lidar
Surface Elevation Tables
Marker horizons
Water-level loggers
Transect photography
and sampling
Terrestrial Lidar &
Microsoft Kinect sensor
RTK transect survey &
Deep set benchmark
Wetland Change – Coastal Bend
13,647
Estuarine marsh
Tidal flat
10,000
Mangrove
2002-04
1979
1950's
Area (ha)
8,000
¯
4,000
2,000
Flats/beaches
h
be
ac
h
m
ar
s
ulf
19
5
19 0 's
79
20
02
-04
G
Tid
al
fla
t
Pa
lu
st
ri n
e
Estuarine marsh
Se
ag
ra
ss
m
ar
sh
Km
10
M
an
gr
ov
e
0 2.5 5
Es
tu
ar
in
e
Wetland
Distribution
6,000
Palustrine marsh
Aquatic beds
Scrub/shrub
Upland
White et al., 2006
White et al., 2006
0m
+0.46m
+0.87m
Relative Sea-level Rise
Mustang
Island
Inundation
by Year
2100
Based on
IPCC (2007) sea-level
rise projections plus
local land subsidence
estimate
$
modified from Paine et al., 2004
Interior upland
Salt flats
Algal flats
Intertidal marsh
Mangroves
Seagrass
Source: Gibeaut et al., (2009)
Accretion Rate Calculation
137Cs activity
Is 1963 peak present and above minimum detectable
activity (is it really there)?
Correct peak depth for grain size influence
Correct peak depth for core compaction
Minimum
Detectable
activity
The Mangroves of Redfish Bay: Field Surveys
and High Resolution Imagery to Map
Distribution, Canopy Height, and Vegetation
Response to the February, 2011 Freeze
John Schalles1, Alissa Hart2,
Adam Altrichter3, and Eryn Carpenter1
1Creighton University, Omaha, NE
2Loyala University, Chicago, IL
3Virginia Tech, Blacksburg, VA
• Field Surveys: Anna Armitage, Wayne Carpenter, Tyler Craven, Kiersten Madden, Shanna
Madsen, Tyler Monahan, John O’Donnell, John Olley, Drew Seminara, Liz Smith
• AISA Eagle hyperspectral imagery and initial processing: Rick Perk, Paul Merani & Don
Rundquist (CALMIT – Univ. Nebraska); Jeffrey Vincent (University of Texas – Austin)
DREW
•Field logistics, and explanations of Texas coastal ecology: Sally Morehead, Kiersten Madden,
Dennis Pridgen, Liz Smith, Wes Tunnell, John Woods, Ed Zielinski, Captain Frank
• Financial and logistical support: NOAA-NCCOS Environmental Cooperative Science Center,
Texas Parks and Wildlife, Mission-Aransas NERR, University of Texas Marine Science Institute,
NASA Nebraska Space Institute
JohnSchalles@creighton.edu
Outline for My Presentation
• Airborne Imaging Campaign at Mission-Aransas NERR in 2008
with CALMIT-University of Nebraska AISA-Eagle Sensor
• Mapping products for research and management at MANERR
and imagery processing work-flow
• Field Survey Methodologies – transect approach used in July, 2008
• Delineation of Black Mangrove stands in Redfish Bay, and
VARI-green algorithm for estimation of canopy height
Spring Break Research Trip:
• Depart Omaha early AM Sat, Mar 5
• First night lodging ~ North Texas
• Arrive Port Aransas, TX in PM, Sun, Mar 6
• Field work at Mission-Aransas NERR from
Mon, Mar 7 to Thurs, Mar 10 and housing
(tentative) at U.T Marine Inst. apartment
• Drive to Grand Bay, MS on Fri, Mar 11
drop boat off, overnight stay at GB NERR
• Depart in AM on Sat, Mar 12
• Last night lodging ~ SE Missouri
• Arrive back in Omaha in early evening on
Sunday, March 13
• Follow-up field survey work in 2011 and detection of significant
mangrove freeze damage and gradient of damage
• January, 2013 site revisit to evaluate mangrove recovery and
above-ground regrowth patterns
• Conclusions and next phases of our geospatial work at MANERR,
including seasonal WorldView 2 satellite imagery in 2015.
DELAWARE
JULY ‘04
MARYLAND
CHESAPEAKE
JULY ‘05
ACE BASIN
JUNE ‘03)
•
MISSION-ARANSAS
JUL ‘08
SAPELO ISLAND
JUNE ‘06
GRAND BAY
APALACHICOLA BAY
OCT ’03, MAY’09
OCT ’02, APR ‘06
ECSC PARTNER SCHOOLS JOINED WITH SEVEN NOAA-NERR SITES
FOR EIGHT HYPERSPECTRAL IMAGERY ACQUISITIONS WITH THE
UNIVERSITY OF NEBRASKA’S AISA EAGLE INSTRUMENT
AISA – Eagle Flight Line Mosaic
Aransas NWR and inshore waters
October, 2008
CALMIT-University of Nebraska
Creighton Geospatial Analysis Lab
Schalles & Hladik, 2012, Israel Journal Plant
Science: VIS and IR Spectroscopy in Plant Science
Black Mangrove (Avicennia germinans) Image versus In-Situ Endmembers
Colonizing Along ICWW
From: Technical Progress Report on Mission-Aransas National Estuarine
Research Reserve AISA+ Image Acquisition and Analysis. Jeffrey S. Vincent,
Ph.D., Bureau of Economic Geology, University of Texas at Austin. May, 2009
In-Situ (narrow IFOV of
leaves)
Image Spectra
Imagery Acquisition
• In October, 2008, 1m hyperspectral images were
obtained with an AISA Eagle at MANERR
• These images were then processed using ENVI
software
Example of flight line imagery,
flown as NE / SW diagonals
in parallel tracks with
~30% overlap (imagery
acquired in late October, 2008)
Gitelson, Kaufman, Stark, & Rundquist. 2002. Novel algorithms
for remote estimation of vegetation fraction. Remote Sensing of
the Environment 80: 76-87.
1. NDVI: (RNIR - Rred) / (RNIR+Rred)
2. Green VARI: (Rgreen - Rred) / (Rgreen + Rred - Rblue)
3. NIR / GRN: (RNIR) / (Rgreen - 1)
NIR
AISA Bands
Blue: 8 (463 nm)
R
G
B
Green: 18 (554 nm)
Red: 31 (675 nm)
NIR: 50 (856 nm)
LOCATIONS OF EIGHT
MANGROVE SURVEY
TRANSECTS IN
REDFISH BAY
SCIENTIFIC AREA
(ALTRICHTER ET
JULY, 2008)
– Masking: all non-mangrove components were
masked out
– The Gvari Vegetation Index was applied to assess
plant density/canopy height, using Band Math in
ENVI:
GVI = (Green – Red) / ((Green + Red) – Blue)*
– Color Density Slicing used to display different size
classes
*Gitelson, A.A. et al., 2002. Novel Algorithms for Remote Estimation of
Vegetation Fraction. Remote Sensing of Environment 80: 76-87.
2008 Transect Survey: Transect 6 – Traylor Island
Survey transects & AISA imagery
Subscene from
fllight line 2
with overlay of
transect location
• 8 transects: 2 x 22 m
22 plots per transect
• 1 m2 plots outlined with PVC frame
• Checkerboard pattern
• Nadir digital photography
• 6 measures of canopy height per plot
• Estimations of percent cover by plant
species and other habitat conditions
Enlarged view of subscene,
with plot locations matched
to respective imagery pixels
(pixel size is 1 meter)
Registration of sampling transect
and AISA flight line subscene
Redfish Bay Subscenes
• Gvari Index was the best predictor of canopy
height (R2 = 0.583)
• Median canopy height for all mangrove
pixels was approximately 78.5 cm
• Mangroves were generally taller near larger
channels and lagoons (older specimens
and/or more favorable for growth?)
Mangroves
covered
6.4 million m2
(= 640 ha)
in Redfish Bay
Freeze Damage Encountered in March, 2011
Estimated median
canopy height
78.5 cm
Initial histogram of Black Mangrove canopy height frequency distribution at
Redfish Bay. Note: taller trees are not being properly captured in this analysis,
but median size appears realistic based on 2008 and subsequent field surveys.
• We discovered extensive
areas of mangroves killed
by 2 hard freezes in early
February, 2011
• A gradient of decreasing
damage was documented
from north to south in
Redfish Bay
• Damage patterns and
recovery were analyzed by
comparing new high
resolution satellite imagery
with our 2008 baseline
map and transect data
Comparison of (L) December, 2009
versus (R) November, 2011
(upper – Traylor; lower – Harbor)
Shellbank Island Site
Intermediate Damage
Site at Redfish Bay
First Survey in January,
2013 – Eryn Carpenter
CANOPY HEIGHT (cm)
140
MANGROVE CANOPY HEIGHTS
JANUARY, 2013
MEAN (Standard Error)
120
100
DEAD CANOPY
80
LIVE CANOPY
60
40
20
0
TRANSECT
Example of Vegetation Fraction Calculation
1. Load field digital photograph (shown
here is frame DSC00069 taken by Eryn
Carpenter at Traylor Island North;
Transect 1 – Plot 19, Canopy Heights:
85 cm – dead, 57 cm – live)
(27o 57’ 14.094” N, 97o 4’ 24.930” W)
2. Process through “Veg Fraction” custom
software (Bryan Leavitt, CALMIT - Univ.
of Nebraska) to identify green pixels as
fraction of all pixels in the image.
March, 2011 Examples
(L) Traylor Island North VF = 0.000
(R) Harbor Island West VF = 0.648
3. In this case, the fraction was 0.450
(45.0% of 262,144 pixels; range across
all calculations for 7 transects in January,
2013 was 0.069 – 0.758)
MANGROVE VEGETATION FRACTION
JANUARY, 2013
VEGETATION FRACTION
0.7
0.6
Conclusions and Next Steps
* Most of “suitable” wetland habitat in Redfish Bay is now colonized by
Black Mangrove; herbaceous vegetation cover generally less than 5%
or non-existent
MEAN (Standard Error)
0.5
* Median canopy height of mangroves estimated at 78.5 cm; our technique
and VARI-green algorithm is underestimating the rather limited but
important occurrence of taller plants (esp above ~ 1.8 m)
0.4
0.3
* The Coastal Bend Black Mangroves appear to be quite “hardy”, and are
recovering rapidly in areas of severe damage in 2011 freeze event
0.2
0.1
* In 2015, the NOAA-ECSC and MANERR plan to acquire 3 sets of World
View 2 imagery in winter, early, and late growing seasons (2 m pixels,
8 bands – very useful for detailed spatial mapping at substantially lower
0
cost than our AISA-Eagle system)
TRANSECT
Back to Our Mother Ship (March, 2011)
The colonization and age structure of red mangrove
(Rhizophora mangle) trees along the coast of Texas
Worldwide Mangrove Distributions
Christopher Wilson, Kimberly Jackson and Kenneth Dunton
Most recent northern limit described for Rhizophora mangle (29° 42.94’ N) by Zomlefer et al. (2006).
Harbor Island, Texas lies at 27° 51.48’ N!
How is this plant boundary enforced?
Frozen Mangrove = Dead Mangrove
Wikipedia.org
Stuart et al. (2006)
Red Mangroves in Texas
Red Mangroves in Texas
Continuous account in Texas since 1980’s:
- Sherrod et al. 1986*
- Tunnell 2002
- Montagna et al. 2007
- Montagna et al. 2011 (Pictures)
Sherrod et al., 1986
Methods: Survey Location
Methods: Aging Mangroves
Duke and Pinzon M. 1992
Calculating Node Production Rate
Survey Results: Demographics
“Plant and Wait”
Population
Recruitment Year
- 4 propagules were planted in UTMSI WEC
120
18
16
- Plantings included sun and shade plots
- The node production rate (4.08 ± 0.74 nodes
year -1 ) was used to extrapolate tree age
14
80
12
Total Population
Number of Individuals
- After two years, the total node number was
quantified for each plant
100
10
8
6
60
40
20
4
r2 = 0.94
0
2
Annual growth rate = 0.31
0
1992
* Error becomes larger as you extrapolate further in time
1994
1996
1998
2000
2002
2004
2006
2008
2010
0
2012
2
4
6
8
10
12
14
16
Time (years)
Extrapolated Settlement Year
*Mean node production = 4.08 ± 0.74 nodes year -1 (n = 4)
Plantsystematics.org
Why the recent plant explosion?
18
Mangrove Growth: Juvenile Reserves
Plantsystematics.org
16
12
Duke and Pinzon M. 1992
10
n = 30 - 92
10
8
Reproductive
Cohort
6
4
0
1992
1994
1996
1998
2000
1 Year
8
2
2002
2004
2006
2008
2010
2012
Extrapolated Settlement Year
14
*colors denote separate locations
12
Internodal Extension (cm)
Number of Individuals
14
6
4
Number of (Self) Recruits
2
10
8
0
0
2
4
6
8
10
6
Node Number
4
2
0
2004
Reserves likely supplement plant growth during initial year of establishment
2005
2006
2007
2008
Extrapolated Year
2009
2010
2011
12
Mangrove Growth: Rate and Maximum
Mangrove Growth: Annual Patterns
10
12
*colors denote individual trees
300
10
250
6
4
2
8
Tree Height (cm)
Internode Extension (cm)
Internode Extension (cm)
8
6
4
2
0
2000
2004
2006
2008
2010
Extrapolated Year
2012
2000
2004
2006
2008
2010
2012
Although mangroves exhibit indeterminate growth, red mangroves in TX have a pronounced
annual signal that is subject to perturbation.
How cold is too cold?
Infrequent freezing temperatures are likely limiting
the maximum canopy height of red mangroves.
Minimum Temperature (C)
4
100
r2 = 0.85
Growth Rate = 14 cm yr-1
0
2002
Extrapolated Year
6
150
50
0
2002
200
0
2
4
6
8
10
12
14
16
Mean Extrapolated Age
Red mangroves typically achieve site-specific maximum canopy heights (TX < 3m).
Documented Mangrove Facilitation
Peterson and Bell (2012)
2
0
-2
-4
-6
-8
-10
-12
1985
1990
1995
2000
2005
2010
Year
New Hypothesis Alert : Black mangrove trees
facilitate the expansion of red mangrove trees
through insulation.
Freeze index = -Ʃ [Freezing Temperature (˚C)] x [Duration of Temperature (hours)]
How did R. mangle get here?
How did R. mangle get here?
 Propagules are positively buoyant
 Prevailing SW winds in spring and
summer
Harbor Island Population
 Numerous eddies spinning off of
loop current
 Harbor Island is easy target
Nearest Donor Population
(La Pesca, Mexico)
Sherrod et al. (1986)
Future Directions in Research
1. Persistence and Reproduction
a. How cold is too cold?
b. Quality and quantity of propagules
2. Trajectory of population
a. Carrying capacity TBD
b. Reproduction vs. immigration
c. Potential to serve as a source population
3. Nutrient Cycling
a. No soil aeration!
b. OM likely different
4. Fauna
a. Canopy
b. intertidal structure
Questions?
Ecological implications of black mangrove expansion
into Texas salt marshes:
Comparisons among marsh and mangrove habitats
Marsh  Mangrove
• Gulf of Mexico coastal wetlands are transitional between
marshes and mangroves
• Mangrove expansion rate may be accelerating
Temperature (Osland et al. 2013)
Sea level rise (Doyle et al. 2010)
Anna R. Armitage1, Steven Pennings2, Carolyn Weaver1, Ashley
Whitt1, Hongyu Guo2, Zoe Hughes2, Sayatanii Dastidar2
1Texas
A&M University at Galveston
of Houston
2University
Atmospheric CO2
Herbivory
Other stressors
Habitat change in Texas: One perspective
• Has vegetation composition in Texas coastal wetlands
changed?
– Where?
– By how much?
– On what time scale?
 One perspective: Use of remote sensing to identify
“hot spots” of expansion over the last 20 years
(courtesy W. Highfield, TAMUG)
Has vegetation changed?
Yes!
Mangroves expanded by 74%
Marshes decreased by 24%
- Landsat TM 5 images from
1990 and 2010
- Used Artificial Neural
Networks to classify 10 land
cover types
Specifically targeted black
mangrove (Avicennia
germinans) and salt marsh
(various species) coverage
Mangrove increase
• Mangroves increased by 74%
• 16 km2 increase
• Mostly conversion from:
– Upland pasture – indicates upland
migration of salt marsh?
– Salt marsh
– Other wetland
– Water – probably salt marsh at low
tide in 1990
Mangrove expansion occurred in
areas of marsh or upland
Marsh decrease
• Salt marshes decreased by 24%
• 77.8 km2 decrease
• Mostly converted to:
– Upland pasture
– Water – submergence
– Other wetland
– Bare
Only 7.7% of the salt marsh loss
was due to mangrove expansion
Mangrove area small relative to
marshes
Marsh loss largely due to habitat
loss
Questions
 Mangroves are increasing, marshes are decreasing
• What are the species- and process-level implications of
these vegetation shifts?
• Are there ecological differences between marsh and
mangrove habitats?
1. Comparisons among stands of marshes and
mangroves
2. Experimental mangrove removal/marsh
revegetation
Approach
• Study sites in “hot
spot” of expansion,
Port Aransas vicinity
– 3 marsh
– 4 mangrovedominated (mix)
Marsh sites
Mangrove sites
Advantage: Communities established
Disadvantage: Spatial separation
Approach
Edaphic characteristics: grain size
• Transects along elevation gradient perpendicular to shoreline
– Used relative elevation as a covariate
– Marshes had slightly higher elevation at upper end
• Sampled edaphic, vegetation, and nekton characters in Sept. 2012
– 5 evenly spaced stations:
• Soil: moisture, salinity, CNP, pH, mV
– Plant presence/absence every 10 m
– Nekton in seine nets
at water’s edge
• Pit traps
• Light traps
Edaphic characteristics: sediment CNP
Mangrove-mix
Edaphic characteristics: elevation gradient
• Soil moisture decreased at higher elevations
– No vegetation type effect
• Other soil characters that varied only with elevation:
– Soil salinity (↑)
– Redox (↑)
Mangrove-mix
Mangrove-mix
– pH not
affected by
elevation or
vegetation
type
(McKee & Rooth 2008)
– P competition?
– Analyses of leaf
tissue ongoing
– Concurrent
enrichment
experiments
Vegetation characteristics: Richness
• Species richness similar
No habitat type effect
No elevation gradient
Vegetation characteristics: Composition
Low elevation
• Species composition distinct at low elevation
Group average
Resemblance: S17 Bray Curtis similarity
50
50
6060
7070
Similarity
8080
Mix (S3)
Mangrove
3
Mangrove
2
Mix (S2)
Samples
Mangrove
4
Mix (S4)
Mix (S1)
Mangrove
1
Marsh (S5)
Marsh
6
100
100
Marsh
5
Marsh (S4)
9090
Marsh (S6)
Marsh
7
Mangrove-mix
Similarity
• Soil P higher in marsh sites
– No significant elevation pattern
• C and N higher in marsh sites, but not significantly
• Nutrient availability may be linked to sediment and/or
vegetation type
• Nitrogen competition
between Avicennia
and Spartina
• Mangrove sites sandier
 Located on barrier island
• No elevation change
Vegetation characteristics: Composition
High elevation
Nekton composition
• Species composition heterogeneous
at high elevation
Group average
Resemblance: S17 Bray Curtis similarity
0
0
Marsh
20 20
Mangrove-Mix
Fish
Crabs
Shrimp
Isopods
Gammarids
Gastropods
Bivalves
40 40
Similarity
Similarity
 Abundance and richness similar
 Composition different… …May be linked to seagrass density
60 60
Mangrove
4
Mix (S4)
Mix (S1)
Mangrove
1
Samples
Mix (S2)
Mangrove
2
Marsh
5
Marsh (S5)
Marsh (S7)
Marsh
7
Marsh (S6)
Marsh
6
100
100
Mix (S3)
Mangrove
3
80 80
Nekton characteristics
Summary
Community composition not linked to vegetation type
Further suggests links to seagrass density
Resemblance: S17 Bray Curtis similarity
What does
vegetation type
mean for food
webs?
Isotope analyses
are ongoing
Marsh
Mangrove-Mix
2D Stress: 0
S6
Mix
Marsh
S7
S1
Site Type
S2
S4
S3
S5
Next steps
• Still many questions left to be answered!
More sites, wider spatial array
Seasonal measurements: plant and fishery productivity
More process- and ecosystem-level measurements
Integrate with experimental approach
• Edaphic characteristics:
– Few differences definitively linked to vegetation type
– Some elevation patterns
• Vegetation:
– Richness similar, composition different , especially at low
elevation
– Ongoing studies: Linked to processes such as accretion,
nutrient storage?
• Nekton:
– Richness and abundance similar, composition different
– Linked to seagrass?
– Ongoing studies: trophic relationships
Acknowledgements
Funded by Texas Sea
Grant (NOAA)
Ecological implications of black mangrove expansion into
Texas salt marshes:
Insights from a large-scale mangrove removal
experiment
Mangroves are expanding
Steven Pennings, Hongyu Guo, Anna
Armitage, Zoe Hughes, Carolyn Weaver,
Sayatani Dastidar
University of Houston
Texas A&M University, Galveston
Thank You Texas Sea Grant!
Osland et al. 2013 GCB
Osland et al. 2013 GCB
Plot 10
Natural versus manipulative experiments
Plot 9
Plot 8
• Natural-large spatial and temporal scale
• Experimental-better control of confounding
variables
Plot 7
Plot 6
Plot 5
Plot 4
Plot 3
Plot 2
Plot 1
3/6/2013
Plot-1
Plot-2
Plot-3
Plot-4
Plot-5
Plot-6
Plot-7
Plot-8
Plot-9
Plot-10
33%M
0%M
66%M
100%M
77%M
22%M
55%M
44%M
11%M
88%M
Block 1
Block 2
Block 3
Layout of the 24 x 42 m experimental plots on Harbor Island in
Port Aransas. Cleared over summer of 2012. M: mangrove cover
A
B
C
Selected experimental plots after mangrove clearing. A: Plot 2 (0% mangrove
cover); B: Plot 9 (11% mangrove cover) C: Plot 8 (44% mangrove cover).
Avicennia germinans
100
100
80
80
60
60
60
40
40
20
100
20
0
Mangrove Pneumatophore
0
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
100
Spartina alterniflora
1 2 3 4 5 6 7 8 9 10
100
80
80
80
60
60
60
40
40
40
20
20
20
0
0
Batis maritima
100
80
80
60
60
40
40
20
Bare Ground
0
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
100
Borrichia frutescens
40
20
0
Percentage cover (%)
Salicornia virginica
80
1 2 3 4 5 6 7 8 9 10
Sesuvium maritimum
0
1 2 3 4 5 6 7 8 9 10
30
Batis maritima
1 2 3 4 5 6 7 8 9 10
Plot
20
Salicornia virginica
25
15
20
15
10
10
5
5
0
0
Before
20
0
Percentage cover (%)
100
After
Before
After
Changes in percentage cover for Batis maritima and Salicornia virginica before
(in May 2012) and after (in November 2012) mangrove tree clearing in plot 2
(0% mangrove cover plot; cleared in July 2012). Data are means + SE.
Plant percentage cover (by species) in the experimental plots before the mangrove
clearing. Data shown are averages of the 84 1×1m quadrats in each plot
Before (2012) data for
soil water content
porewater salinity
organic content
After data to be collected summer 2013
4.0
2.0
Average wind speed (m/s)
Daily average wind speed (m/s)
3.5
One-way ANOVA P=0.26
1.5
1.0
0.5
R2=0.73
P<0.01
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0.0
0
11
22
33
44
55
66
77
88
0
100
10
20
30
Daily average wind speed across plots before mangrove tree clearing (June 5-July5, 2012).
Data are means ±SE. Analyses only included wind data with wind directions from channel
into each plots.
50
60
70
80
90
100
Average wind speed across plots after mangrove tree clearing
(September 10-November 10, 2012). Analyses only included wind data
with wind directions from channel into each plots.
2.0
2.0
1.8
R2=0.73
P<0.01
1.8
SD of wind speed (m/s)
P= 0.70
SD of wind speed (m/s)
40
Mangrove cover (%)
Plots referred by aimed mangrove cover (%)
1.6
1.4
1.2
1.0
1.6
1.4
1.2
1.0
0.8
0.8
0.6
0
10
20
30
40
50
60
70
80
90
100
0.6
0
Plots referred by aimed mangrove cover (%)
10
20
30
40
50
60
70
80
90
100
Mangrove cover (%)
Standard deviation (SD) of wind speed across plots before mangrove
tree clearing (June 5-July 5, 2012). Analyses only included wind data
with wind directions from channel into each plots.
Standard deviation (SD) of wind speed across plots after mangrove tree
clearing (September 10-November 10, 2012). Analyses only included
wind data with wind directions from channel into each plots.
Daily average air temperature (oC)
at 1m aboveground
One-way ANOVA P=0.37
34
33
32
31
30
29
28
27
26
Daily average air temperature (oC)
at 1m aboveground
36
35
34
One-way ANOVA P=0.84
32
30
28
26
24
22
20
18
0
25
0
11
22
33
44
55
66
77
88
100
11
22
33
44
55
66
77
88
100
Mangrove cover (%)
Plots referred by aimed mangrove cover (%)
Daily average air temperature at 1m aboveground across plots
before mangrove tree clearing (June 5-July5, 2012). Data are
means ±SE.
Daily average air temperature at 1m aboveground across plots after mangrove
tree clearing (September 10-November 10, 2012). Data are means ±SE.
5.4
5.4
5.2
P=0.17
SD of air temperature (oC)
at 1m aboveground
SD of air temperature (oC)
at 1m aboveground
5.2
5.0
4.8
4.6
4.4
4.2
4.0
3.8
3.6
3.4
3.2
5.0
4.8
4.6
4.4
4.2
R2=0.56
P=0.01
4.0
3.8
3.6
3.0
0
10
20
30
40
50
60
70
80
90
100
3.4
0
Aimed mangrove cover (%)
10
20
30
40
50
60
70
80
90
100
Mangrove cover (%)
Standard deviation (SD) of air temperature at 1m aboveground across plots
before mangrove tree clearing (June 5-July 5, 2012).
Standard deviation (SD) of air temperature at 1m aboveground across plots
after mangrove tree clearing (September 10-November 10, 2012).
95
Daily average air relative humidity (%)
at 1m aboveground
Daily average air relative humidity (%)
at 1m aboveground
95
One-way ANOVA P=0.86
90
85
80
75
70
65
One-way ANOVA P=0.13
90
85
80
75
70
65
60
55
0
11
22
33
44
55
66
77
88
100
0
11
22
Plots referred by aimed mangrove cover (%)
Daily average air relative humidity at 1m aboveground across plots before
mangrove tree clearing (June 5-July5, 2012). Data are means ±SE.
44
55
66
77
88
100
Daily average air relative humidity at 1m aboveground across plots after mangrove
tree clearing (September 10-November 10, 2012). Data are means ±SE.
16
16
P=0.38
SD of air relative humidity (%)
at 1m aboveground
SD of air relative humidity (%)
at 1m aboveground
33
Mangrove cover (%)
15
14
13
12
11
10
0
10
20
30
40
50
60
70
80
90
100
Aimed mangrove cover (%)
15
14
13
R2=0.53
P=0.02
12
11
10
0
10
20
30
40
50
60
70
80
90
100
Mangrove cover (%)
Standard deviation (SD) of air relative humidity at 1m aboveground across
plots before mangrove tree clearing (June 5-July 5, 2012).
Standard deviation (SD) of air relative humidity at 1m aboveground across
plots after mangrove tree clearing (September 10-November 10, 2012).
Future work
Conclusions (so far)
Marsh vegetation increasing where mangroves removed
Mangrove density has strong effects on microclimate at 1m.
Reduces wind
Reduces wind SD
Increases temperature SD
Increases humidity SD
Appears to be a threshold between 22 and 33 percent cover
Not much happening with soil temperature so far.
We hypothesize that effects on temperature and humidity
may vary seasonally.
Next 2 years
Continue plant and climate measurements
Next 3-5 years:
Soil salinity
Wave environment
Vegetation
Arthropods
Benthic macrofauna
Nekton
Birds
Long-term:
Soils
Carbon cycle
Soil infauna
Collaborators welcome!
“Habitat Replacement by Mangrove
Establishment: Implications for
Whooping Crane use”
Whooping Crane Annual Cycle
WBNP
Juveniles,
Subadults,
Adults
ANWR
Juveniles,
Subadults,
Adults
JUL
JAN
ARRIVAL
AT WBNP
APR
Whooping Crane Ecological
Requirements in Wintering Range
ARRIVAL
AT ANWR
OCT
Primary Food Items
Whooping Crane Territories
1 Family
•
•
•
•
Blue Crab
Wolfberry Fruits
Clams, Snails, Shrimp
Acorns, Snakes, Lizards,
Insects, Small Rodents
~ 300 acres
(200-500)
Defended
ADULT
JUVENILE
Aransas National Wildlife Refuge
Blackjack Peninsula
Coastal Habitat Availability
HABITATS
TERRITORY
Oak Woodland
Elevation: 0-9 ft
Tidal Range: 1-2 ft
Oak Woodland
Fresh
Marsh
Coastal
Prairie
Shallow
Flat
Coastal
Marsh
F
F
O
O
O
O
D
D
Coastal
Prairie
Shallow
Flat
Coastal
Marsh
Bay
BLUE
CRAB
WOLFBERRY
FRUIT
WATER
R
R
E
E
S
S
O
O
U
U
R
R
C
C
E
E
S
S
Bay
Fresh
Marsh
CLAM
CLAM
ACORN
SNAIL
SHRIMP
LIZARD
SHRIMP
SNAKE
INSECT
SMALL RODENT
Land Use/Land Cover
Oak Woodland
Fresh
Marsh
Coastal
Prairie
Shallow
Flat
Coastal
Marsh
Employing the Conservation Design Approach
on Sea-Level Rise Impacts on Coastal Avian
Habitats along the Central Texas Coast
Bay
LEGEND
Woodlands
Fresh Marsh
Coastal Prairie
Shallow Flat
Coastal Marsh
Bay
Funded by the Landscape
Conservation Cooperative
LAND USE/LAND COVER MAP
International Crane Foundation
San Antonio
Bay
Gulf Coast Bird Observatory
Harte Research Institute for Gulf of Mexico
Studies – TAMU-CC
Conrad Blucher Institute – TAMU-CC
Copano
Bay
The Nature Conservancy of Texas
Mission-Aransas National Estuarine Research
Reserve - UTMSI
Aransas
Bay
Data Source: FWS (Stehn & Prieto 2010)
Woodlands
Shrubland
Rangeland
Cropland
Fresh Marsh
Floodplain
Coastal Flats
Coastal Marsh
Oyster Reef
Seagrass
Mangrove
Developed
Whooping Crane Territories 1950
Whooping Crane Territories 1961
Woodlands
Woodlands
Rangeland
Coastal Flat
Coastal Marsh
Rangeland
Coastal Flat
Coastal Marsh
Mangrove
Seagrass
Mangrove
Seagrass
San Antonio
Bay
31 Individuals
7 Territories
Copano
Bay
Data Source: FWS (Stehn & Prieto 2010)
36 Individuals
9 Territories
Copano
Bay
Gulf of Mexico
Aransas
Bay
San Antonio
Bay
Gulf of Mexico
Aransas
Bay
Data Source: FWS (Stehn & Prieto 2010)
Whooping Crane Territories 1971
Whooping Crane Territories 1979
Woodlands
Woodlands
Rangeland
Coastal Flat
Coastal Marsh
Rangeland
Coastal Flat
Coastal Marsh
Mangrove
Seagrass
Mangrove
Seagrass
San Antonio
Bay
Split
Territory
San Antonio
Bay
Split
Territory
Split
Territory
Split
Territory
59 Individuals
17 Territories
Copano
Bay
Gulf of Mexico
Aransas
Bay
Data Source: FWS (Stehn & Prieto 2010)
76 Individuals
18 Territories
Copano
Bay
Gulf of Mexico
Aransas
Bay
Data Source: FWS (Stehn & Prieto 2010)
Whooping Crane Territories 1985
Whooping Crane Territories 1990
Woodlands
Woodlands
Rangeland
Coastal Flat
Coastal Marsh
Rangeland
Coastal Flat
Coastal Marsh
Mangrove
Seagrass
Mangrove
Seagrass
San Antonio
Bay
Split
Territory
Split
Territory
Split
Territory
Split
Territory
Split
Territories
Copano
Bay
Aransas
Bay
Data Source: FWS (Stehn & Prieto 2010)
San Antonio
Bay
Split
Territory
84 Individuals
28 Territories
Gulf of Mexico
146 Individuals
37 Territories
Copano
Bay
Aransas
Bay
Data Source: FWS (Stehn & Prieto 2010)
Gulf of Mexico
Whooping Crane Territories 2000
Whooping Crane Territories 2006
Woodlands
Woodlands
Rangeland
Coastal Flat
Coastal Marsh
Rangeland
Coastal Flat
Coastal Marsh
Mangrove
Seagrass
San Antonio
Bay
Mangrove
Seagrass
Split
Territories
San Antonio
Bay
Split
Territories
Split
Territory
180 Individuals
57 Territories
Copano
Bay
Gulf of Mexico
Aransas
Bay
Data Source: FWS (Stehn & Prieto 2010)
Mangrove Establishment
Split
Territory
Copano
Bay
Aransas
Bay
237 Individuals
66 Territories
Gulf of Mexico
Data Source: FWS (Stehn & Prieto 2010)
Mangrove Establishment
t
Implications for Whooping Crane Conservation
– Indicator species: sensitive to
environmental changes
– Increasing temperature
– Decreasing freeze event frequency
– Decreasing dissolved oxygen in water
– Sensitive to sea-level changes
• Habitat conversion from marsh to
mangrove reduces habitat availability
• Whooping cranes cannot walk through
mangroves to forage
• Predators may have an advantage within
mangrove/upland areas
Montagna et al. 2011 Coastal Impacts in The Impact of Global Warming on Texas
What ICF is Doing
• Provide support letters for mangrove research
• Assist in mapping current mangrove
establishment in whooping crane winter
territory
• Assess mangrove habitat use by whooping
cranes
• Predict future mangrove expansion
TOP 2008 Natural Color
TOP 2008 Color Infrared
Tx Ecological Systems Database
Tidal Flat
Reg. Flooded Brack./Salt Marsh
Grassland
Mangrove Shrubland
National Wetland Inventory
Tidal Flat
Reg. Flooded Brack./Salt Marsh
Seagrass
Mangrove Shrubland
Tx Benthic Habitat Database
Reg. Flooded Brack./Salt Marsh
Seagrass
Mangrove Shrubland
Whooping Crane Territories 2006
Woodlands
Long Island: 2006 Territories
Rangeland
Coastal Flat
Coastal Marsh
Mangrove
Seagrass
San Antonio
Bay
Split
Territories
MANGROVE
Split
Territory
Copano
Bay
Aransas
Bay
Data Source: FWS (Stehn & Prieto 2010)
237 Individuals
66 Territories
Gulf of Mexico
Long Island: 2001-2010 Pts
Long Island: 2006 Territories
MANGROVE
Long Island: TESD
Long Island: NWI
Tidal Flat
Irreg. Flooded Brack./Salt Marsh
Reg. Flooded Brack./Salt Marsh
Mangrove Shrubland
Long Island: Tx Benthic Atlas
Tidal Flat
Irreg. Flooded Brack./Salt Marsh
Reg. Flooded Brack./Salt Marsh
Mangrove Shrubland
LAND USE/LAND COVER MAP
San Antonio
Bay
Copano
Bay
Reg. Flooded Brack./Salt Marsh
Seagrass
Mangrove Shrubland
Aransas
Bay
Data Source: FWS (Stehn & Prieto 2010)
Woodlands
Shrubland
Rangeland
Cropland
Fresh Marsh
Floodplain
Coastal Flats
Coastal Marsh
Oyster Reef
Seagrass
Mangrove
Developed
Whooping Crane Territories 2006
Whooping Crane Recovery Goals
(Downlist Criteria)
Woodlands
Rangeland
Coastal Flat
Coastal Marsh
Mangrove
Seagrass
San Antonio
Bay
Split
Territory
Copano
Bay
Aransas
Bay
Split
Territories
• 1000 individuals
• 250 nesting pairs
• 10 years
~ 30 lost of the
66 Territories
Gulf of Mexico
• 250 winter territories @ 500 ac
each = 125,000 ac
Data Source: FWS (Stehn & Prieto 2010)
Future Whooping Crane Expansion
Lavaca-Lower Colorado Basin
Matagorda Bay System
Lavaca-Lower Colorado Basin
Matagorda Bay System
Future Whooping Crane Expansion
Brazos Basin
Central Coast System
Brazos Basin
Central Coast System
Suitability, acres
Suitability, acres
116,893.02
600000
120000
400000
67,491.79
80000
300000
58,020.25
250,059.60
244,515.34
119,344.88
200000
60000
40000
500,013.96
500000
100000
100000
25,965.79
0
20000
Not
Marginal Suitable
Suitable
0
Not Suitable
Marginal
Suitable
Highly
Suitable
Highly Suitable
Texas Coast Salt and
Brackish Marsh,
regularly flooded,
irregularly flooded
Open Water
Texas Coast Salt and
Brackish Marsh,
regularly flooded,
irregularly flooded
Open Water
Lumb, Gibeaut, Smith in prep
Lumb, Gibeaut, Smith in prep
Conservation Questions
• Does habitat conversion = essential habitat
lost?
• Is loss primarily related to habitat structure
changes?
• Are primary food resources impacted?
• How will sea level rise affect habitat type and
extent?
• Where will Whooping Crane expansion occur?
Effects of plants as
• Sediments modifiers
– light, temperature, chemistry regulators of benthic
habitats
• Food source
– Fresh and detrital organic matter
• Structural support
– Nursery habitat, coastal stabilization, run-off filtration
Literature Summary by (Alfaro 2010)
Habitat Conversion Trend
• Flats > Marshes
• Marshes > Mangroves
• Upland > Marsh/Mangrove?
• Drivers
Friess et al. 2011
– Relative sea level rise
– Lack of sediment supply
– Temperature shifts
– Freshwater inflows
Coastal Habitat Availability
Temporal-Spatial Scales
Elevation: 0-9 ft
Tidal Range: 1-2 ft
Oak Woodland
Fresh
Marsh
Coastal
Prairie
Shallow
Flat
Mangroves
Bay
?
Next Steps
• Comprehensive mapping project
(multispectral, extensive groundtruthing)
• Understand mangrove establishment, ecology,
expansion rates
• Evaluate use of mangrove habitats by
Whooping Cranes, preferred prey items,
potential predators
• Predict how climate change will affect habitat
availability for conservation prioritization
Liz Smith, Whooping Crane Conservation Biologist
International Crane Foundation
Texas Office, 361-543-0303
This presentation dedicated to Dave Smith
Day et al. 2008
Thank You!
PLEASE CONTACT:
Liz Smith, Whooping Crane Conservation Biologist
International Crane Foundation
Texas Office, 361-543-0303
Historical reconstruction of
mangrove expansion:
Linkage with carbon sequestration
Bianchi, T.S.1, Allison, M.A.2, Zhao, J.1, Li, X.1, Comeaux, R.S.2,
Feagin, R.A.3, and Kulawardhana, R.W.3
1
2
3
Dept. Oceanography, Texas A&M University
Institute for Geophysics, University of Texas at Austin
Dept. Ecosystem Science & Mgmt., Texas A&M University
Questions
1. Can we determine when mangroves
historically colonized a site?
2. Is there a difference in the carbon
sequestration rate between A. germinans
and S. alterniflora, at a common site?
Methods
•
•
•
•
•
Coring (sectioning, bulk density)
Sediment accumulation rates (radionuclides)
Elemental analysis (TOC, TN, δ13C, δ15N)
Biomarkers (lignin phenol metrics)
Aerial image interpretation
1. Can we determine when mangroves
historically colonized a site?
C3 plants (like woody mangroves) = -35 to -20 (-28 = A. germinans)
C4 plants (like herbaceous marsh) = -19 to -9 (-13 = S. alterniflora)
C3 plants (like woody mangroves) = -35 to -20 (-28 = A. germinans)
C4 plants (like herbaceous marsh) = -19 to -9 (-13 = S. alterniflora)
Marsh benthic algae = -16 to -27.7
Coastal phytoplankton = -18 to -24
Lignin phenols (per 100 mg OC)
Λ6 = vanillyl + syringyl phenols
Λ8 = vanillyl + syringyl + cinnamyl phenols
Plant sources of lignin
C/V= cinnamyl/vanillyl
S/V = syringyl/vanillyl
• TOC and C:N ratio increased around 1960s
• The most obvious differences in TOC are
between the two sites
• For biomarkers and isotopic composition,
there are no big differences between
mangroves and marsh core locations
• Biomarkers also record changes around 1960s
• Aerial images show changes around 1960s
2. Is there a difference in the carbon
sequestration rate between A. germinans
and S. alterniflora, at a common site?
Indices of lignin decay
Ad/Al = vanillic acid:vanillin
P/(V+S) = p-hydroxyl/(vanillyl+syringyl)
Conclusions
• Both sites converted from unvegetated flats (likely some algal
cover) to vegetated wetland in the 1960s
• Biomarkers and mobile materials likely represent the ‘regional’
vegetation dynamics, rather than what is under a particular plant
• Lignin deposition (wood) and accretion rate increase under A.
germinans plants (compared to S. alterniflora). Lignin carbon pool
is stable, compared with other TOC components.
• Carbon sequestration rate is likely higher under A. germinans vs. S.
alterniflora, over the long-term
N