Texas Mangrove Research Symposium

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Texas Mangrove Thursday, February 28 9:00am - 5:00pm University of Texas Marine Science Institute Research Symposium PortEstuarine Aransas, Research Texas Center, Seminar Room 750 Channel View Dr. AGENDA

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 11:15 - 11:45 Chrisheight, Wilson, and vegetation University response of Texas to the February,Marine Science 2011 freeze Institute Rhizophora mangle) trees along the coast of Texas

11:45 - 12:15 Dr.Colonization Anna Armitage, and age structure Texas A&M of red University mangrove ( – Galveston

Ecological implications of black mangrove expansion into Texas salt marshes: Comparisons among 12:15 - 1:00 CATEREDmarsh and mangroveLUNCH habitats

1:00 - 1:30 Dr. Steven Pennings, University of Houston

Ecological implications of black mangrove expansion into Texas salt marshes: Insights from a large- 1:30 - 2:00 Dr.scale Liz mangrove Smith, Internationalremoval experiment Crane Foundation

2:00 - 2:30 Dr.Habitat Rusty replacement Feagin, Texas by mangrove A&M University establishment: - College Implications Station for Whooping Crane use

Carbon Sequestration in Coastal Wetlands Historical Reconstruction of Mangrove Expansion in the Gulf of Mexico: Linking Climate Change with 2:30 - 2:45 BREAK Texas Mangrove Thursday, February 28 9:00am - 5:00pm University of Texas Marine Science Institute Research Symposium PortEstuarine Aransas, Research Texas Center, Seminar Room 750 Channel View Dr. AGENDA

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: RichardEffects of storms,Day, USGS sea-level National rise, freshwater Wetlands flow, Research and freeze. Center

KenBiogeography Krauss, ofUSGS black National mangrove Wetlands and freeze Research tolerance Center

ErikWater Yando, use characteristics University of of black Louisiana mangroves at Lafayette along the Northern Gulf Coast

The belowground implications of mangrove forest migration: Plant-soil variability across forest Mikestructural Osland, gradients USGS in National TX, LA, and Wetlands FL Research Center

4:00 - 4:30 DISCUSSIONWinter climate change and coastal wetland foundation species: Salt marshes vs. mangrove forests

4:30 - 4:45 WRAP UP AND ADJOURN

Initials Name Organization/Af�iliation Email

INVITED SPEAKERS AA Anna Armitage Texas A&M University – Galveston [email protected] RD Richard Day USGS National Wetlands Research Center [email protected] TD Tom Doyle USGS National Wetlands Research Center [email protected] RF Rusty Feagin Texas A&M University – College Station [email protected] JG James Gibeaut Texas A&M University – Corpus Christi [email protected] KK Ken Krauss USGS National Wetlands Research Center [email protected] KM Kiersten Madden Mission-Aransas National Estuarine Research [email protected] Reserve MO Mike Osland USGS National Wetlands Research Center [email protected] SP Steve Pennings University of Houston [email protected] JS John Schalles Creighton University [email protected] LS Liz Smith International Crane Foundation [email protected] TT Tom Tremblay Bureau of Economic Geology – UT Austin [email protected] EY Erik Yando University of Louisiana at Lafayette [email protected] WORKSHOP PARTICIPANTS DA Dan Alonso San Antonio Bay Partnership [email protected] KB Karen Bishop Texas Sea Grant [email protected] JB Jorge Brenner The Nature Conservancy [email protected] EB Ed Buskey Mission-Aransas NERR [email protected] RC Rhonda Cummins Texas Sea Grant [email protected] KD Kelly Darnell Univ. of Texas Marine Science Institute [email protected] ZD Zack Darnell Mission-Aransas NERR [email protected] SD Sayantani Dastidar University of Houston [email protected] MAD Mary Ann Davis The Aquarium at Rockport Harbor [email protected] ND Nicole Davis Texas State University [email protected] RD Richard Davis Texas A&M University – Corpus Christi [email protected] Sarah Douglas Univ. of Texas Marine Science Institute [email protected] CG Catalina Gempeler Univ. of Texas Marine Science Institute [email protected] HG Hongyu Guo University of Houston [email protected] BH Beau Hardegree US Fish and Wildlife Service [email protected] WH Wade Harrell US Fish and Wildlife Service [email protected] KH Kent Hicks Texas Parks and Wildlife Department [email protected] LH Lauren Hutchison Texas A&M University – Corpus Christi [email protected] CH Cammie Hyatt Mission-Aransas NERR [email protected] FK Felix Keeley City of Rockport/NERR Advisory Board [email protected] Ranjani Wasantha Texas A&M University – College Station [email protected] Kulawardhana JL Jessica Lunt Texas A&M University – Corpus Christi [email protected] SM Shanna Madsen Mission-Aransas NERR [email protected] DN Duncan Neblett Univ. of Texas Marine Science Institute DO R. Deborah Overath Texas A&M University – Corpus Christi [email protected] PR Patrick Rios City of Rockport Water Quality Committee [email protected] JR Jackie Robinson Texas Parks and Wildlife Department [email protected]

CR Carolyn Rose Mission-Aransas NERR [email protected] JS James Sanchez Texas A&M University – Corpus Christi [email protected] CPS Carlota Plantier Santos Harte Research Institute, Texas A&M [email protected] University – Corpus Christi CS Chris Shank Univ. of Texas Marine Science Institute [email protected] JT Jim Tolan Texas Parks and Wildlife Department [email protected] KT Kathryn Tunnell [email protected] HW Heather Wade Texas Sea Grant/Mission-Aransas NERR [email protected] CW Carolyn Weaver TexasTexas A&M General University Land – Of�iceGalveston [email protected] DW Dawn Whitehead US Fish and Wildlife Service [email protected] AW Ashley Whitt Texas A&M University – Galveston [email protected] LW Leslie Williams Texas Parks and Wildlife Department [email protected] DY David Yoskowitz Harte Research Institute, Texas A&M [email protected] University – Corpus Christi

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

11:45 - 12:15 Dr.Colonization Anna Armitage, and age structure Texas A&M of red University mangrove ( – Galveston

Ecological implications of black mangrove expansion into Texas salt marshes: Comparisons among 12:15 - 1:00 CATEREDmarsh and mangroveLUNCH habitats

1:00 - 1:30 Dr. Steven Pennings, University of Houston

Ecological implications of black mangrove expansion into Texas salt marshes: Insights from a large- 1:30 - 2:00 Dr.scale Liz mangrove Smith, Internationalremoval experiment Crane Foundation

2:00 - 2:30 Dr.Habitat Rusty replacement Feagin, Texas by mangrove A&M University establishment: - College Implications Station for Whooping Crane use

2:45 - 4:00 U.S. Geological Survey National Wetlands Research Center Tom Doyle, USGS National Wetlands Research Center

KenBiogeography Krauss, ofUSGS black National mangrove Wetlands and freeze Research tolerance Center

ErikWater Yando, use characteristics University of of black Louisiana mangroves at Lafayette along the Northern Gulf Coast

The belowground implications of mangrove forest migration: Plant-soil variability across forest Mikestructural Osland, gradients USGS in National TX, LA, and Wetlands FL Research Center

4:00 - 4:30 DISCUSSIONWinter climate change and coastal wetland foundation species: Salt marshes vs. mangrove forests

4:30 - 4:45 WRAP UP AND ADJOURN

Initials Name Organization/Af�iliation Email

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. toLiz get Smith a handle on if the food web will shift, and how.

: 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 Michaelregard to Osland the replacement of marshes along the salinity gradient.

: 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 TexasKiersten priority Madden sites. –

Tom Tremblay : There is a Gulf workgroup forming for mangroves would it be possible to form a Texas working group? : It might be a good idea to host a special session in conjunction with the 2014 Texas BaysRusty and Feagin Estuaries meeting.

Anna Armitage: What’s the general consensus on mangrove expansion? If we were going to restore a site, would you plant mangroves? : 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 mangroveLiz Smith: expansion. 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 Jimsoon, Gibeaut: and we may have to make some management decisions before all of those answers are known.

I want to emphasize Liz’s point about the fact that we may notSpartina 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 , 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. MoreChris researchWilson is needed on mangrove expansion in the face of sea level rise– and sedimentation.

: 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 Rustydon’t know Feagin what mangroves are, and the only ones who do are recreational users of those areas. : What about restoration managers? We are making large changes in physical arelandscape higher by– agencies completing restoration projects (mitigation banks, etc.); there is a fair Beauamount Hardegree of wetland created. It could be possible that the ecosystem services from using mangroves maybe those services make the use of mangroves a net positive. : 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’tJohn Schalles be planted in Whooping Crane habitat. - : 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?Tom Tremblay There is currently no research being done on this. : There was a previous planting effort in Bajilla Grande when it was realized that Mother Nature was spreadingSpartina mangroves better than any planting could. Maybe we don’t need to be Kierstenpromoting Madden restoration projects using mangrove, because it will happen anyhow; if we have a choice, Beaumaybe Hardegree we should plant . - Kiersten Madden:: Do restoration practitioners know this? Beau Hardegree:: There’s a recent feeling that people are using mangroves for in kind projects. Does that responsibility fall to you to make those decisions? Kiersten Madden:Resource management agencies and the Army Corps of Engineers normally make the decision. Tom Tremblay We need a representative from the Corps here. : 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 APPLYING THE NERRS APPROACH IN TEXAS National Estuarine Research Reserve System

PROTECTED PLACES

SCIENCE PEOPLE

Kiersten Madden Stewardship Coordinator Mission-Aransas National Estuarine Research Reserve

Mission-Aransas Reserve Sectors

RESEARCH STEWARDSHIP EDUCATION TRAINING The Mission-Aransas NERR brings together scientists, landowners, policy-makers, & the public to ensure that Improve Promote public Increase Increase understanding of coastal management appreciation and understanding of understanding of Texas coastal zone support for coastal ecosystems coastal ecosystems ecosystem decisions benefit flora & stewardship of by diverse by coastal decision structure and coastal resources audiences makers fauna, water quality, function and people.

Research System Wide Monitoring Program

SWMP: System 1. Abiotic Wide 2. Biotic Monitoring 3. Mapping Program 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

WHOLE PLOTS SUB-PLOTS (10 x 10 m) (1 x 1 m)

For trees with trunk diameter For trees with trunk diameter greater than 2.5 cm . . . less than 2.5 cm . . . 5 Numbered Numbered Position Mapped Position Mapped 4 Identified to Species Identified to Species DBH Total Height 3 Total Height Trunk Height Trunk Height Prop Root Height 10 m Prop Root Height 2 10 m 10 1 m

1 m 1

1 Surface Elevation Table (with marker horizons)

Mangrove Protocols

WHOLE PLOTS SUB-PLOTS (10 x 10 m) (1 x 1 m)

For trees with trunk diameter For trees with trunk diameter greater than 2.5 cm . . . less than 2.5 cm . . .

Numbered Numbered Position Mapped Position Mapped Identified to Species Identified to Species DBH Total Height Total Height Trunk Height Trunk Height Prop Root Height 10 m Prop Root Height 10 m 10 1 m

1 m 1

4 Branching Non-branching 4 4 Branching Non-Branching 3 3

No. No. Plot Plot Plot Plot No. Plot Plot 2 2 2 All Transects All All Transects All All Transects All 1 1 1

5 0 50

20 15 10 30 25 400 350 300 250 200 150 100

(cm) Height Total Average

Height (cm) Height Trunk Average

90 80 70 60 50 40 30 20 10

(cm) Height Total Average Total Height Total Height Trunk Total Height Total

15 m 15 m 15 m

4 4 4 4 4

B = B 29 B = B 44 B = B 22 NB= 6 NB= 3 3 3 3 3 3 NB= 14 Branching Branching = 17 TOTAL 43 = TOTAL TOTAL 50 = TOTAL - TOTAL = 38 38 = TOTAL TOTAL 25 = TOTAL 3 3 3 3 3

Branching Branching = 21

1 Non

5 2 2 2 2 2 2 2 2 2 2 Transect 3 Transect 4 Transect 5 Transect Transect 1 Transect 2 Transect

Transect 1 Transect 2 Transect 3 Transect 4 Transect Transect

1 1 1 1 1 1 1 1 1 1 B = B 86 B = B 80 B = B 69 NB= 7 B = B 101 NB= 63 NB= 49 NB= 67 TOTAL 149 = TOTAL TOTAL 129 = TOTAL TOTAL = 108 108 = TOTAL TOTAL 136 = TOTAL 0 0 0 0 0

80 40 80 40 80 40 80 40 80 40

0 0 0

120 120 120 120 120

25 0 90 60 30 60 0 75 50

(cm) Height (cm) Height (cm) Height (cm) Height 2 (cm) Height

40 30 20 10 120 180 120 40 30 20 10 100

Height (cm) Height (cm) Height (cm) Height (cm) Height (cm) Height

Average Total Total Average Total Average Total Average Total Average Total Average

Average Total Total Average Total Average Total Average Total Average Average Total Total Average

B = B 15 B = B 69 B = B 45 B = B 55 NB= 17 NB= 36 NB= 45 NB= 56 TOTAL 32 = TOTAL TOTAL = 90 90 = TOTAL branching branching TOTAL 105 = TOTAL TOTAL 111 = TOTAL - -

3 Branching Non Branching Non

B = B 66 B = B 44 B = B 61 B = B 67 NB= 68 NB= 45 NB= 38 NB= 116

TOTAL 89 = TOTAL TOTAL 134 = TOTAL TOTAL = 177 177 = TOTAL TOTAL 105 = TOTAL

B = B 63 B = B 65 B = B 55 B = B 23 NB= 8 NB= 81 NB= 42 NB= 179 TOTAL 31 = TOTAL TOTAL 234 = TOTAL TOTAL 144 = TOTAL TOTAL 107 = TOTAL

5 Total Height Total Trunk Height Trunk 40 Transect 1 30 20 10 GTM Reserve

Height Height (cm) 0

Trunk Height Average Trunk 1 2 3 4

40 Transect 2 30 20 10

Height Height (cm) 0 Average Trunk 1 2 3 4

40 Transect 3 30 20 10

Height Height (cm) 0 Average Trunk 1 2 3 4

40 Transect 4 30 20 10

Height Height (cm) 0 Average Trunk 1 2 3 4

40 Transect 5 30 20 10

Height Height (cm) 0 Average Trunk 1 2 3 4

GTM Reserve 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. Sentinel Sites Stewardship Coordinator Mission-Aransas NERR

361-749-3047 [email protected]

www.missionaransas.org Bench Mark with Surface Elevation Tide Gauge Geodetic Control Table (SET) (NAVD88, etc.) Observed Changes

Surface From: Montagna et al., 2011 Initial Wetland Surface Accretion

Elevation Change Upland

Subsided Wetland Surface Sea Level Rise Marker Horizon Depth of SET measurement integration 1930 1979 1995 2004 Shallow 25% 58% 39% 58% Subsidence

Deep Subsidence 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 Accretion 1979-2001 Accretion 1950s-1979 Erosion 1979-2001 Erosion 1950s-1979

0 1 2 3 4 5 Kilometers

2010

2002 Active fan Aransas Bay Spalding Cove Carlos Bay Inactive fan Mud Island Allyns Bight Mesquite Tidal delta Bay North Pass 12,000 940 786

10,000 ¯ Km Gulf of Mexico Cedar Bayou 8,000 0 1 2 3 4 5 6 7 8 9 10 Vinson Slough

Aransas Pass 11,198 10,332 Mangrove

6,000 Emergent marsh after Andrews, 1970 Area(ha) 4,000 600

2,000 500

0 400 2001-04 1979 Active fan

(ha) 300 Inactive fan 60% 58% 82% 73% 94% 90% 200 Tidal delta Mangrove +7 ha/yr Change rate 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

HyperScan-VNIR-micro (16 bit camera) Detector size: 2400 x 2400 spatial pixels Some marsh gain from uplands occurred where high marsh moved into the lower parts of HyperVision software: ENVI-IDL + flight data capture system with SSD eolian mounds. Eolian mounds are elongate sand mounds that occupy the interdistributary Spectral range: 0.4 to 0.1 μm areas of the washover fan (Andrews, 1970).

Conclusions Summary

• Salt marsh and mangroves have been increasing in • Focus on Matagorda Island and San Jose Island area since the mid-1950’s with marshes increasing at higher rates • Dynamic area affected by sea-level rise and erosion/accretion, with wetland trends similar to • Within the washover fan/tidal delta complex on San those found on much of the Lower Texas Coast Jose Island, marsh is expanding with a net loss of low marsh and a net increase of high marsh • Objective is to establish methods and protocol for automated mangrove monitoring using the • Wetland change is probably caused by relative sea hyperspectral platform level rise where low marsh is inundated and high marsh moves into flats or upland The End…?

The Order of the Straight Arrow

Season 1, episode 3

Barrier Island Environments Proposed Observatory for Understanding Coastal Wetland Change James Gibeaut Harte Research Institute for Gulf of Mexico Studies Texas A&M University – Corpus Christi

Interior upland Salt flats Algal flats

Intertidal marsh Mangroves Seagrass

Wetland Transition Model Wetland Response to Sea Level Rise

DEM Classify habitat types Habitat Future date Yes (original) according to elevation grid reached?

Adjusted Apply DEM vertical accretion adjustment

Output 1-year habitat grid Apply Shoreline Retreat loop global sea level change grid shoreline adjustment

Compute Apply local statistics of subsidence habitat status adjustment

Differential Maps subsidence Statistics grid 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 Terrestrial Lidar & Water-level loggers Microsoft Kinect sensor

Transect photography and sampling RTK transect survey & Deep set benchmark

Detection and removal of shrubs and building Airborne lidar for topographic mapping 0 0.1 0.2 0.4 km ´

http://slvg.soe.ucsc.edu/unvis.html https://www.e-education.psu.edu/

Vegetation mapping 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 Terrestrial Laser for vegetation change topographic mapping

Surface Elevation Tables (SET) for Future Exploration: low-cost lidar sensor measurement of elevation change 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 • Field deployment • power, environmental conditions • Will change signal be detectable? • mm-level • Telemetry Image credit: Greg Hauger http://www.pwrc.usgs.gov/set/theory.html 18

Marker horizons for measurement Marker horizon locations 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 Is 1963 peak present and above minimum • Gamma spectroscopy detectable activity (is it really there)? Cesium (Cs) 137 - 1963 marker horizon due to Correct peak depth for grain size influence residual atmospheric fallout prior to 1964 nuclear test ban Correct peak depth for core compaction Minimum Detectable activity

Water-level measurements Wetland Observatory Aerial multi/hyper spectral imagery, photography and Lidar

Surface Elevation Tables

Marker horizons Terrestrial Lidar & Water-level loggers Microsoft Kinect sensor

Transect photography and sampling RTK transect survey & Deep set benchmark

Wetland Change – Coastal Bend

13,647

Estuarine marsh

Tidal flat 10,000

Mangrove 2002-04 1979 1950's 8,000

6,000 ¯ 4,000 Area (ha) Area

2,000 Wetland 1950's - 1979 Distribution Km 0 2.5 5 10 2002-04

Mangrove Tidal flat Seagrass Estuarine marsh Estuarine marsh Gulf beach Flats/beaches Palustrine marsh Palustrine marsh Aquatic beds Scrub/shrub White et al., 2006 White et al., 2006 Upland

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 • Field Surveys: Anna Armitage, Wayne Carpenter, Tyler Craven, Kiersten Madden, Shanna and High Resolution Imagery to Map Madsen, Tyler Monahan, John O’Donnell, John Olley, Drew Seminara, Liz Smith

Distribution, Canopy Height, and Vegetation • AISA Eagle hyperspectral imagery and initial processing: Rick Perk, Paul Merani & Don Rundquist (CALMIT – Univ. Nebraska); Jeffrey Vincent (University of Texas – Austin) Response to the February, 2011 Freeze DREW •Field logistics, and explanations of Texas coastal ecology: Sally Morehead, Kiersten Madden, 1 2 Dennis Pridgen, Liz Smith, Wes Tunnell, John Woods, Ed Zielinski, Captain Frank John Schalles , Alissa Hart , 3 1 • Financial and logistical support: NOAA-NCCOS Environmental Cooperative Science Center, Adam Altrichter , and Eryn Carpenter Texas Parks and Wildlife, Mission-Aransas NERR, University of Texas Marine Science Institute, 1 NASA Nebraska Space Institute Creighton University, Omaha, NE 2Loyala University, Chicago, IL 3Virginia Tech, Blacksburg, VA

[email protected]

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 Spring Break Research Trip: VARI-green algorithm for estimation of canopy height • Depart Omaha early AM Sat, Mar 5 • First night lodging ~ North Texas • Arrive Port Aransas, TX in PM, Sun, Mar 6 • Follow-up field survey work in 2011 and detection of significant • Field work at Mission-Aransas NERR from mangrove freeze damage and gradient of damage 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 • January, 2013 site revisit to evaluate mangrove recovery and drop boat off, overnight stay at GB NERR above-ground regrowth patterns • Depart in AM on Sat, Mar 12 • Last night lodging ~ SE Missouri • Arrive back in Omaha in early evening on • Conclusions and next phases of our geospatial work at MANERR, Sunday, March 13 including seasonal WorldView 2 satellite imagery in 2015.

DELAWARE JULY ‘04

MARYLAND CHESAPEAKE JULY ‘05 ACE BASIN JUNE ‘03)

• SAPELO ISLAND JUNE ‘06

GRAND BAY APALACHICOLA BAY OCT ’03, MAY’09 OCT ’02, APR ‘06 MISSION-ARANSAS JUL ‘08

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 – 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 Example of flight line imagery, flown as NE / SW diagonals *Gitelson, A.A. et al., 2002. Novel Algorithms for Remote Estimation of in parallel tracks with Vegetation Fraction. Remote Sensing of Environment 80: 76-87. ~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 Green: 18 (554 nm) B Red: 31 (675 nm) NIR: 50 (856 nm)

LOCATIONS OF EIGHT MANGROVE SURVEY TRANSECTS IN REDFISH BAY SCIENTIFIC AREA (ALTRICHTER ET JULY, 2008)

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 Enlarged view of subscene, 22 plots per transect with plot locations matched 2 • 1 m plots outlined with PVC frame to respective imagery pixels • Checkerboard pattern (pixel size is 1 meter) • Nadir digital photography • 6 measures of canopy height per plot • Estimations of percent cover by plant Registration of sampling transect species and other habitat conditions 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 Mangroves pixels was approximately 78.5 cm covered • Mangroves were generally taller near larger 6.4 million m2 channels and lagoons (older specimens (= 640 ha) and/or more favorable for growth?) in Redfish Bay Freeze Damage Encountered in March, 2011 • We discovered extensive areas of mangroves killed by 2 hard freezes in early Estimated median February, 2011 canopy height • A gradient of decreasing 78.5 cm damage was documented from north to south in Redfish Bay • Damage patterns and recovery were analyzed by comparing new high resolution satellite imagery Initial histogram of Black Mangrove canopy height frequency distribution at Redfish Bay. Note: taller trees are not being properly captured in this analysis, with our 2008 baseline but median size appears realistic based on 2008 and subsequent field surveys. map and transect data

Comparison of (L) December, 2009 versus (R) November, 2011 (upper – Traylor; lower – Harbor)

MANGROVE CANOPY HEIGHTS JANUARY, 2013 140 MEAN (Standard Error)

Shellbank Island Site 120 100 DEAD CANOPY Intermediate Damage 80 LIVE CANOPY Site at Redfish Bay 60

First Survey in January, CANOPY HEIGHT (cm) 2013 – Eryn Carpenter 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) March, 2011 Examples (L) Traylor Island North VF = 0.000 2. Process through “Veg Fraction” custom (R) Harbor Island West VF = 0.648 software (Bryan Leavitt, CALMIT - Univ. of Nebraska) to identify green pixels as fraction of all pixels in the image.

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 Conclusions and Next Steps

0.7 * Most of “suitable” wetland habitat in Redfish Bay is now colonized by MEAN (Standard Error) 0.6 Black Mangrove; herbaceous vegetation cover generally less than 5% or non-existent 0.5 * Median canopy height of mangroves estimated at 78.5 cm; our technique 0.4 and VARI-green algorithm is underestimating the rather limited but 0.3 important occurrence of taller plants (esp above ~ 1.8 m)

0.2 * The Coastal Bend Black Mangroves appear to be quite “hardy”, and are recovering rapidly in areas of severe damage in 2011 freeze event

VEGETATION FRACTION VEGETATION 0.1 0 * 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 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” Recruitment Year Population - 4 propagules were planted in UTMSI WEC 18 120

16 100 - Plantings included sun and shade plots 14 80 12

- After two years, the total node number was 10 60

8 quantified for each plant 40

6 Total Population

Number of Individuals 20 - The node production rate (4.08 ± 0.74 nodes 4

-1 2 year ) was used to extrapolate tree age 2 0 r = 0.94 Annual growth rate = 0.31 0 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 0 2 4 6 8 10 12 14 16 * Error becomes larger as you extrapolate further in time Extrapolated Settlement Year Time (years)

*Mean node production = 4.08 ± 0.74 nodes year -1 (n = 4)

Plantsystematics.org Why the recent plant explosion? Mangrove Growth: Juvenile Reserves

18 Plantsystematics.org 16

12 Duke and Pinzon M. 1992 10 n = 30 - 92 10 8 1 Year

6 Reproductive

Number of Individuals Cohort 4 8

0 6 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Extrapolated Settlement Year

4 14 *colors denote separate locations

12 Internodal Extension (cm) 2

8 0 0 2 4 6 8 10 12 6 Node Number

4 Number of (Self) Recruits

0 Reserves likely supplement plant growth during initial year of establishment 2004 2005 2006 2007 2008 2009 2010 2011 Extrapolated Year Mangrove Growth: Annual Patterns Mangrove Growth: Rate and Maximum

10 12 *colors denote individual trees 300

10 8 250

8 200 6

6 150 4

4 100 Tree Height (cm)

Internode Extension (cm) 2 Internode Extension (cm) 2 50 r2 = 0.85

0 0 0 Growth Rate = 14 cm yr-1

2000 2002 2004 2006 2008 2010 2012 2000 2002 2004 2006 2008 2010 2012 0 2 4 6 8 10 12 14 16 Extrapolated Year Extrapolated Year Mean Extrapolated Age

Although mangroves exhibit indeterminate growth, red mangroves in TX have a pronounced Red mangroves typically achieve site-specific maximum canopy heights (TX < 3m). annual signal that is subject to perturbation.

How cold is too cold? Documented Mangrove Facilitation

Infrequent freezing temperatures are likely limiting 6 Peterson and Bell (2012) 4 the maximum canopy height of red mangroves.

-2

-4

-6

Minimum Temperature (C) -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 Questions? 3. Nutrient Cycling a. No soil aeration! b. OM likely different

4. Fauna a. Canopy b. intertidal structure

Marsh  Mangrove Ecological implications of black mangrove expansion

into Texas salt marshes:

Comparisons among marsh and mangrove habitats

• 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 Atmospheric CO2 2University of Houston 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? - Landsat TM 5 images from 1990 and 2010 - Used Artificial Neural  One perspective: Use of remote sensing to identify Networks to classify 10 land “hot spots” of expansion over the last 20 years cover types (courtesy W. Highfield, TAMUG) Specifically targeted black mangrove (Avicennia germinans) and salt marsh (various species) coverage

Has vegetation changed? Yes!

Mangroves expanded by 74% Marshes decreased by 24% Mangrove increase Marsh decrease • Mangroves increased by 74% • Salt marshes decreased by 24% • 2 16 km increase • 77.8 km2 decrease • Mostly conversion from: • Mostly converted to: – Upland pasture – indicates upland – Upland pasture migration of salt marsh? – Water – submergence – Salt marsh – Other wetland – Other wetland – Bare – Water – probably salt marsh at low

tide in 1990 Only 7.7% of the salt marsh loss Mangrove expansion occurred in was due to mangrove expansion areas of marsh or upland Mangrove area small relative to

marshes Marsh loss largely due to habitat loss

Questions Approach • Study sites in “hot  Mangroves are increasing, marshes are decreasing spot” of expansion, Port Aransas vicinity • What are the species- and process-level implications of – 3 marsh Marsh sites these vegetation shifts? – 4 mangrove- • Are there ecological differences between marsh and dominated (mix) mangrove habitats? 1. Comparisons among stands of marshes and

mangroves Mangrove sites 2. Experimental mangrove removal/marsh revegetation Advantage: Communities established

Disadvantage: Spatial separation Approach Edaphic characteristics: grain size

• Transects along elevation gradient perpendicular to shoreline • Mangrove sites sandier – Used relative elevation as a covariate  Located on barrier island – Marshes had slightly higher elevation at upper end • No elevation change • 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 Mangrove-mix

Edaphic characteristics: sediment CNP Edaphic characteristics: elevation gradient

• Soil P higher in marsh sites • Soil moisture decreased at higher elevations – No significant elevation pattern – No vegetation type effect • C and N higher in marsh sites, but not significantly • Other soil characters that varied only with elevation: • Nutrient availability may be linked to sediment and/or – Soil salinity (↑) vegetation type – Redox (↑) • Nitrogen competition Mangrove-mix between Avicennia Mangrove -mix and Spartina – pH not (McKee & Rooth 2008) affected by – P competition? elevation or – Analyses of leaf vegetation tissue ongoing type – Concurrent enrichment experiments

Vegetation characteristics: Richness Vegetation characteristics: Composition

• Species richness similar Low elevation • Species composition distinct at low elevation No habitat type effect Group average Resemblance: S17 Bray Curtis similarity 50 No elevation gradient 50

60 Mangrove-mix 70 70

Similarity

Similarity 80 80

90 90

100100

Mix (S1) Mix (S4) Mix (S2) Mix (S3) Mix Marsh (S6) Marsh (S4) Marsh (S5)

Marsh 7 Marsh 5 Marsh 6 Marsh Samples Mangrove 1 Mangrove 4 Mangrove 2 Mangrove 3 Mangrove Vegetation characteristics: Composition Nekton composition

High elevation  Abundance and richness similar • Species composition heterogeneousGroup average at high elevation  Composition different… …May be linked to seagrass density Resemblance: S17 Bray Curtis similarity 0 0

20 20 Marsh Mangrove-Mix Fish 40 40 Crabs Shrimp Similarity 60 Similarity 60 Isopods 80 80 Gammarids Gastropods 100100

Bivalves Mix (S3) Mix (S2) Mix (S1) Mix (S4) Mix Marsh (S6) Marsh (S7) Marsh (S5)

Marsh 6 Marsh 7 Marsh Samples 5 Marsh Mangrove 3 Mangrove 2 Mangrove 1 Mangrove 4 Mangrove

Nekton characteristics Summary

Community composition not linked to vegetation type • Edaphic characteristics: Further suggests links to seagrass density – Few differences definitively linked to vegetation type

Resemblance: S17 Bray Curtis similarity – Some elevation patterns 2D Stress: 0 Site Type S6 Mix • Vegetation: Marsh Marsh Mangrove-Mix – Richness similar, composition different , especially at low What does elevation vegetation type – mean for food Ongoing studies: Linked to processes such as accretion, webs? nutrient storage? • Nekton: S7 Isotope analyses S1 – Richness and abundance similar, composition different S2 S4 are ongoing S3 – Linked to seagrass?

S5 – Ongoing studies: trophic relationships

Next steps Acknowledgements • Still many questions left to be answered! Funded by Texas Sea  More sites, wider spatial array Grant (NOAA) Seasonal measurements: plant and fishery productivity More process- and ecosystem-level measurements Integrate with experimental approach

Ecological implications of black mangrove expansion into Mangroves are expanding Texas salt marshes: Insights from a large-scale mangrove removal experiment 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

Natural versus manipulative experiments Plot 10 Plot 9 Plot 8 • Natural-large spatial and temporal scale • Experimental-better control of confounding Plot 7 Plot 6 variables 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).

100 Avicennia germinans 100 Salicornia virginica 100 Borrichia frutescens

80 80 80

60 60 60

40 40 40

20 20 20 0 0 0 30 Batis maritima 20 Salicornia virginica 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 25 100 Mangrove Pneumatophore 100 Spartina alterniflora 100 Bare Ground 15 80 80 80 20 60 60 60 15 10 40 40 40 20 20 20 10 0 0 0 5 Percentage cover (%) 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 5

100 Batis maritima 100 Sesuvium maritimum Percentage cover (%) 0 0 80 80 Before After Before After 60 60

40 40 20 20 Changes in percentage cover for Batis maritima and Salicornia virginica before 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 (in May 2012) and after (in November 2012) mangrove tree clearing in plot 2 Plot (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

3.5 R2=0.73 One-way ANOVA P=0.26 P<0.01 3.0 1.5 2.5

2.0 1.0

1.5

0.5 1.0 Average wind speed (m/s) 0.5 Daily average wind speed (m/s)

0.0 0.0 0 11 22 33 44 55 66 77 88 100 0 10 20 30 40 50 60 70 80 90 100 Plots referred by aimed mangrove cover (%) Mangrove cover (%) Daily average wind speed across plots before mangrove tree clearing (June 5-July5, 2012). Average wind speed across plots after mangrove tree clearing Data are means ±SE. Analyses only included wind data with wind directions from channel (September 10-November 10, 2012). Analyses only included wind data into each plots. with wind directions from channel into each plots.

2.0 2.0

1.8 2 P= 0.70 1.8 R =0.73 P<0.01 1.6 1.6

1.4 1.4

1.2 1.2

1.0

SD of wind speed (m/s) wind of SD 1.0

0.8 SD of wind speed (m/s) 0.8 0.6 0 10 20 30 40 50 60 70 80 90 100 0.6 0 10 20 30 40 50 60 70 80 90 100 Plots referred by aimed mangrove cover (%) Mangrove cover (%) Standard deviation (SD) of wind speed across plots before mangrove Standard deviation (SD) of wind speed across plots after mangrove tree tree clearing (June 5-July 5, 2012). Analyses only included wind data clearing (September 10-November 10, 2012). Analyses only included with wind directions from channel into each plots. wind data with wind directions from channel into each plots.

36 35 34

C) One-way ANOVA P=0.84 34 One-way ANOVA P=0.37 o C)

o 32 33 30 32 28 31

30 26

29 24 at 1m aboveground 28 22 at 1m aboveground

27 20 Daily average air temperature ( 26 Daily average air temperature ( 18 25 0 11 22 33 44 55 66 77 88 100 0 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 Daily average air temperature at 1m aboveground across plots after mangrove before mangrove tree clearing (June 5-July5, 2012). Data are tree clearing (September 10-November 10, 2012). Data are means ±SE. means ±SE. 5.4 5.4 5.2 P=0.17 5.2 5.0 C) C) C) 5.0 o 4.8 o 4.6 4.8 4.4 4.6

4.2 4.4 4.0 4.2 3.8 2 4.0 R =0.56 at 1m aboveground at 1m 3.6 P=0.01 at 1m aboveground 3.4 3.8 SD of air temperature ( air temperature of SD

3.2 SD of air temperature ( 3.6 3.0 0 10 20 30 40 50 60 70 80 90 100 3.4 0 10 20 30 40 50 60 70 80 90 100 Aimed mangrove cover (%) Mangrove cover (%)

Standard deviation (SD) of air temperature at 1m aboveground across plots Standard deviation (SD) of air temperature at 1m aboveground across plots before mangrove tree clearing (June 5-July 5, 2012). after mangrove tree clearing (September 10-November 10, 2012).

95 95

One-way ANOVA P=0.86 90 One-way ANOVA P=0.13 90 85

85 80

80 75

70 75 at 1m aboveground at 1m aboveground 65

70 60 Daily average air relative humidity (%) Daily average air relative (%) Daily humidity 65 55 0 11 22 33 44 55 66 77 88 100 0 11 22 33 44 55 66 77 88 100 Plots referred by aimed mangrove cover (%) Mangrove cover (%)

Daily average air relative humidity at 1m aboveground across plots after mangrove Daily average air relative humidity at 1m aboveground across plots before tree clearing (September 10-November 10, 2012). Data are means ±SE. mangrove tree clearing (June 5-July5, 2012). Data are means ±SE.

16 16 P=0.38 15 15

14 14

13 13

12 12 R2=0.53 at 1m aboveground P=0.02 11 at 1m aboveground

SD of air relative humidity SD (%) 11

10 SD of air relative humidity (%) 0 10 20 30 40 50 60 70 80 90 100 10 Aimed mangrove cover (%) 0 10 20 30 40 50 60 70 80 90 100 Mangrove cover (%)

Standard deviation (SD) of air relative humidity at 1m aboveground across Standard deviation (SD) of air relative humidity at 1m aboveground across plots before mangrove tree clearing (June 5-July 5, 2012). plots after mangrove tree clearing (September 10-November 10, 2012). Future work Next 2 years Conclusions (so far) Continue plant and climate measurements

Next 3-5 years: Marsh vegetation increasing where mangroves removed Soil salinity

Wave environment Mangrove density has strong effects on microclimate at 1m. Vegetation Reduces wind Arthropods Reduces wind SD Benthic macrofauna Increases temperature SD Nekton Increases humidity SD Birds

Appears to be a threshold between 22 and 33 percent cover Long-term:

Soils Not much happening with soil temperature so far. Carbon cycle

Soil infauna We hypothesize that effects on temperature and humidity may vary seasonally. Collaborators welcome!

“Habitat Replacement by Mangrove Establishment: Implications for Whooping Crane use”

Whooping Crane Annual Cycle Whooping Crane Ecological Requirements in Wintering Range APR

ARRIVAL ARRIVAL WBNP AT

WBNP ANWR

JAN Juveniles, Juveniles, JUL Subadults, Subadults, Adults Adults ATANWR ARRIVAL

OCT

Whooping Crane Territories Primary Food Items 1 Family

• Blue Crab ~ 300 acres • (200-500) Wolfberry Fruits • Clams, Snails, Shrimp Defended • Acorns, Snakes, Lizards, Insects, Small Rodents ADULT

JUVENILE Aransas National Wildlife Refuge Blackjack Peninsula Coastal Habitat Availability HABITATS

TERRITORY

Oak Woodland Fresh Coastal Shallow Coastal Marsh Prairie Flat Marsh Bay BLUE F CRAB O WATER O WOLF- BERRY Elevation: 0-9 ft D Tidal Range: 1-2 ft FRUIT R R ACORN CLAM CLAM E S SNAIL O O SHRIMP SHRIMP Oak Woodland Coastal U LIZARD Fresh Shallow Coastal Prairie R SNAKE Marsh Flat Marsh Bay C INSECT E S SMALL RODENT

Land Use/Land Cover Employing the Conservation Design Approach on Sea-Level Rise Impacts on Coastal Avian Oak Woodland Coastal Fresh Shallow Coastal Habitats along the Central Texas Coast Prairie Marsh Flat Marsh Bay

LEGEND Woodlands Fresh Marsh Coastal Prairie Shallow Flat Coastal Marsh Bay

Funded by the Landscape LAND USE/LAND COVER MAP Conservation Cooperative International Crane Foundation

San Antonio Gulf Coast Bird Observatory Bay Woodlands Harte Research Institute for Gulf of Mexico Shrubland Studies – TAMU-CC Rangeland Cropland Fresh Marsh Conrad Blucher Institute – TAMU-CC Copano Floodplain Bay Coastal Flats Coastal Marsh The Nature Conservancy of Texas Oyster Reef Aransas Seagrass Bay Mangrove Mission-Aransas National Estuarine Research Developed Reserve - UTMSI Data Source: FWS (Stehn & Prieto 2010) Whooping Crane Territories 1950 Whooping Crane Territories 1961

Woodlands Woodlands Rangeland Rangeland Coastal Flat Coastal Flat Coastal Marsh Coastal Marsh Mangrove San Antonio Mangrove San Antonio Seagrass Bay Seagrass Bay

31 Individuals 36 Individuals Copano Copano 7 Territories 9 Territories Bay Bay

Aransas Gulf of Mexico Aransas Gulf of Mexico Bay Bay

Data Source: FWS (Stehn & Prieto 2010) Data Source: FWS (Stehn & Prieto 2010)

Whooping Crane Territories 1971 Whooping Crane Territories 1979

Woodlands Woodlands Rangeland Rangeland Coastal Flat Coastal Flat Coastal Marsh Coastal Marsh Mangrove San Antonio Mangrove San Antonio Seagrass Seagrass Split Bay Bay Territory

Split Split Territory Territory

Split Territory 59 Individuals 76 Individuals Copano Copano 17 Territories 18 Territories Bay Bay

Aransas Gulf of Mexico Aransas Gulf of Mexico Bay Bay

Data Source: FWS (Stehn & Prieto 2010) Data Source: FWS (Stehn & Prieto 2010)

Whooping Crane Territories 1985 Whooping Crane Territories 1990

Woodlands Woodlands Rangeland Rangeland Coastal Flat Coastal Flat Coastal Marsh Coastal Marsh Mangrove San Antonio Mangrove San Antonio Seagrass Bay Seagrass Bay Split Territory Split Split Split Territory Territory Territory

Split Split Territory Territories 84 Individuals 146 Individuals Copano Copano 28 Territories 37 Territories Bay Bay

Aransas Gulf of Mexico Aransas Gulf of Mexico Bay Bay

Data Source: FWS (Stehn & Prieto 2010) Data Source: FWS (Stehn & Prieto 2010) Whooping Crane Territories 2000 Whooping Crane Territories 2006

Woodlands Woodlands Rangeland Rangeland Coastal Flat Coastal Flat Coastal Marsh Coastal Marsh Mangrove Split Mangrove Split San Antonio Territories San Antonio Territories Seagrass Bay Seagrass Bay Split Territory

Split 180 Individuals Territory 237 Individuals Copano Copano 57 Territories 66 Territories Bay Bay

Aransas Gulf of Mexico Aransas Gulf of Mexico Bay Bay

Data Source: FWS (Stehn & Prieto 2010) Data Source: FWS (Stehn & Prieto 2010)

Mangrove Establishment Mangrove Establishmentt Implications for Whooping Crane Conservation – Indicator species: sensitive to • Habitat conversion from marsh to environmental changes mangrove reduces habitat availability – Increasing temperature – Decreasing freeze event frequency • Whooping cranes cannot walk through – Decreasing dissolved oxygen in water mangroves to forage – Sensitive to sea-level changes • Predators may have an advantage within

mangrove/upland areas

Montagna et al. 2011 Coastal Impacts in The Impact of Global Warming on Texas

TOP 2008 Natural Color 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 Color Infrared Tx Ecological Systems Database

Tidal Flat Reg. Flooded Brack./Salt Marsh Grassland Mangrove Shrubland

National Wetland Inventory Tx Benthic Habitat Database

Tidal Flat Reg. Flooded Brack./Salt Marsh Reg. Flooded Brack./Salt Marsh Seagrass Seagrass Mangrove Shrubland Mangrove Shrubland

Whooping Crane Territories 2006 Long Island: 2006 Territories Woodlands Rangeland Coastal Flat Coastal Marsh Mangrove Split San Antonio Territories Seagrass Bay

MANGROVE

Split Territory 237 Individuals Copano 66 Territories Bay

Aransas Gulf of Mexico Bay

Data Source: FWS (Stehn & Prieto 2010) Long Island: 2001-2010 Pts Long Island: 2006 Territories

MANGROVE

Long Island: TESD Long Island: NWI

Tidal Flat Tidal Flat Irreg. Flooded Brack./Salt Marsh Irreg. Flooded Brack./Salt Marsh Reg. Flooded Brack./Salt Marsh Reg. Flooded Brack./Salt Marsh Mangrove Shrubland Mangrove Shrubland

LAND USE/LAND COVER MAP Long Island: Tx Benthic Atlas

San Antonio Bay

Woodlands Shrubland Rangeland Cropland Fresh Marsh Copano Floodplain Bay Coastal Flats Coastal Marsh Oyster Reef Aransas Seagrass Reg. Flooded Brack./Salt Marsh Seagrass Bay Mangrove Mangrove Shrubland Developed

Data Source: FWS (Stehn & Prieto 2010) Whooping Crane Territories 2006 Whooping Crane Recovery Goals Woodlands (Downlist Criteria) Rangeland Coastal Flat Coastal Marsh Mangrove Split San Antonio Territories Seagrass Bay • 1000 individuals • 250 nesting pairs

Split • 10 years Territory ~ 30 lost of the Copano Bay 66 Territories • 250 winter territories @ 500 ac

Aransas Gulf of Mexico each = 125,000 ac Bay

Data Source: FWS (Stehn & Prieto 2010)

Future Whooping Crane Expansion

Lavaca-Lower Colorado Basin Matagorda Bay System

Future Whooping Crane Expansion

Brazos Basin Brazos Basin Central Coast System Central Coast System Suitability, acres Suitability, acres

116,893.02 600000 120000 500,013.96 500000 100000 400000 80000 67,491.79 250,059.60 244,515.34 58,020.25 300000 60000 200000 119,344.88

40000 25,965.79 100000 0 20000 Not Marginal Suitable Highly Suitable Suitable 0 Not Suitable Marginal Suitable Highly Suitable Texas Coast Salt and Texas Coast Salt and Brackish Marsh, Brackish Marsh, regularly flooded, regularly flooded, irregularly flooded irregularly flooded Open Water Open Water

Lumb, Gibeaut, Smith in prep Lumb, Gibeaut, Smith in prep

Conservation Questions Effects of plants as

• Does habitat conversion = essential habitat • Sediments modifiers lost? – light, temperature, chemistry regulators of benthic • Is loss primarily related to habitat structure habitats changes? • Food source – Fresh and detrital organic matter • Are primary food resources impacted? • Structural support • How will sea level rise affect habitat type and – Nursery habitat, coastal stabilization, run-off filtration extent?

• Where will Whooping Crane expansion occur? Literature Summary by (Alfaro 2010)

Habitat Conversion Trend

• Flats > Marshes • Marshes > Mangroves • Upland > Marsh/Mangrove?

• Drivers – Relative sea level rise – Lack of sediment supply – Temperature shifts – Freshwater inflows Friess et al. 2011

Coastal Habitat Availability Temporal-Spatial Scales

Elevation: 0-9 ft Tidal Range: 1-2 ft

Oak Woodland Coastal Fresh Shallow Mangroves Prairie Marsh Flat Bay

? Day et al. 2008

Thank You! 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 PLEASE CONTACT: Liz Smith, Whooping Crane Conservation Biologist availability for conservation prioritization International Crane Foundation Texas Office, 361-543-0303

Liz Smith, Whooping Crane Conservation Biologist International Crane Foundation Texas Office, 361-543-0303 This presentation dedicated to Dave Smith 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 Dept. Oceanography, Texas A&M University 2 Institute for Geophysics, University of Texas at Austin 3 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 1. Can we determine when mangroves historically colonized a site?

• Coring (sectioning, bulk density) • Sediment accumulation rates (radionuclides) • Elemental analysis (TOC, TN, δ13C, δ15N) • Biomarkers (lignin phenol metrics) • Aerial image interpretation

C3 plants (like woody mangroves) = -35 to -20 (-28 = A. germinans) C3 plants (like woody mangroves) = -35 to -20 (-28 = A. germinans) C4 plants (like herbaceous marsh) = -19 to -9 (-13 = S. alterniflora) 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) Plant sources of lignin

Λ6 = vanillyl + syringyl phenols C/V= cinnamyl/vanillyl Λ8 = vanillyl + syringyl + cinnamyl phenols S/V = syringyl/vanillyl

• TOC and C:N ratio increased around 1960s

• The most obvious differences in TOC are • Biomarkers also record changes around 1960s between the two sites

• Aerial images show changes around 1960s • For biomarkers and isotopic composition, there are no big differences between mangroves and marsh core locations

2. Is there a difference in the carbon Indices of lignin decay Ad/Al = vanillic acid:vanillin sequestration rate between A. germinans P/(V+S) = p-hydroxyl/(vanillyl+syringyl) and S. alterniflora, at a common site?

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