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What Do We Know? • Keys…

− Stony benthic cover declined by 40% from 1996 – 2009 (Ruzicka et al. 2013).

− Potential Driving Factor? Stress due to extreme cold & warm water temperatures

− Stony coral communities in patch reefs remained relatively constant after the 1998 El Niño (Ruzicka et al. 2013).

− Patch reefs exposed to moderate SST Carysfort - Images from Gene Shinn - USGS Photo Gallery variability exhibited the highest % live coral cover (Soto et al. 2011).

Objective

To test if the differences in stony coral diversity on Florida Keys reefs were correlated with habitats or SST variability from 1996 - 2010.

Methods: Evaluation & Monitoring Program (CREMP)

% coral cover 43 DRY TORTUGAS UPPER KEYS

MIDDLE KEYS LOWER KEYS

36 CREMP STATIONS (Patch Reefs (11), Offshore Shallow (12), Offshore Deep (13)) Methods: Sea Surface Temperature (SST)

• Annual SST variance were derived from weekly means.

• Categories for SST variability (variance):

• Low (<7.0°C2) • Intermediate (7.0 - 10.9°C2) • High (≥11.0°C2)

Advanced Very High Resolution Radiometer (AVHRR) SST data Vega-Rodriguez M et al. (2015) Results

1

I 0.5 palmata

I

s i Millepora complanata

x Multivariate Statistics

A

l

a Acropora c

i n

o Pseudodiploriarevealed clivosa cervicornisthat stonycomplex

n

a C

0 Porites astreoides Madracis auretenra

h t i coral diversity varied

w labyrinthiformis

Agaricia lamarcki n

o Siderastrea radians i

t

a l

e significantly with r

r o C -0.5 Pseudodiploriahabitats strigosa natansStephanocoenia intercepta cavernosa Canonical Analysis of Principal Coordinates (CAP) -1 0.6 -1 -0.5 0 0.5 1

Correlation with Canonical Axis I

) %

0.4

7

6 .

9 0.2

4

(

I Boulder-type coral speciesPatch (e.g. Montastraea cavernosa & Siderastrea siderea) were characteristic of I

0

s i x patch reefs whereasOffshore branching Shallow-type (e.g. Acropora palmata) was more representative of

A -0.2

l

a Offshore Deep c

i -0.4 offshore shallow reefs.

n

o n

a -0.6 C -0.8

-1 -0.5 0 0.5 1 Canonical Axis I (50.33 %) Results: Vega-Rodriguez M et al. (2015) CAP ordination plot

1

Distance-based Canonical Discriminant Analysis

0.5 Oculina diffusa

I I

0.8

s

i

x

A

l Agaricia agaricites

a c

i Montastraea cavernosa

n Stony coralcomplex diversity also 0.6 o

n Stephanocoenia

a C

0 intercepta

h t i varied significantly with

) Colpophyllia natans

w

n %

o Siderastrea siderea

0.4 i

t Acropora palmata

a

7 l

e strigosa

3 SST variability

r

.

r

o 3

C Acropora Orbicella annularis complex 1

( -0.5

0.2 cervicornis Diploria labyrinthiformis

I I

Diploria clivosa

s

i x

A 0

l a

c -1

i n o -0.2 -1 -0.5 0 0.5 1

n Correlation with Canonical Axis I

a C -0.4 Similar boulder-Intermediatetype coral species SST (7.0 grouped - 10.9) towards intermediate/high SST variability whereas Low SST (< 7.0) -0.6 branching-type corals grouped towards low/intermediate SST variability High SST (> 11.0)

-1 -0.5 0 0.5 1 Canonical Axis I (86.63 %) Discussion

• Boulder-type corals more abundant in patch reefs exposed to intermediate/ high SST variability.

• Exposure to greater temperature variability could have led to thermal acclimation for corals in patch reefs rather than for those in offshore shallow or deep reefs.

Florida Bay Watch Report. Oct. 2011 The Marine Biodiversity Observation Network (MBON) integrates observations to link science & management responses across the Sanctuary What is a MBON?

• MBON focus is on biodiversity: - Change across trophic levels & habitats & time

• Quantitative assessments of organisms - (e.g. species abundance)

• Should be operational & network to broad set of stakeholders

• Connects existing databases

Biological observations: trophic-based biodiversity time series metrics PROGRAMS

SEFSC FIM - FWC GAME

FIM - FWC SEFSC CREMP Florida SE Fisheries CREST Independent Monitoring GAME

CREMP FRRP GAME CREST SFP

FWRI HAB - phytoplankton SFP CREMP and CREST – macro- Goals 7. 6. 5. 4. 3. 2. 1. OVERALL GOAL: - Link databases (e.g. State, IOOSRA’s, NODC,OBIS, Integrate, augment (bio obs.), & synthesizeIOOS useful MBON Define the minimum ofset observations required for implementing a practical, Provide Help international develop an network (GEO Leadand participate in current outreach and education Understand biodiversity Complement information information for dynamicallyupdating “Sanctuary Condition Reports” social & economic social economic & relevance ofmarine

measures existing, ongoingobservations in Sanctuaries sustained with

Develop Develop an operational

- BON MBON information )

biodiversity GenBank efforts

)

Condition Reports for the National Marine Sanctuaries

2006-2013 http://sanctuaries.noaa.gov/science/condition/

FKNMSFKNMS MBON MBON Stations: Target Stations 2015

Fowey Rocks

Molasses Reef Pulaski Tortugas Bank Shoals Crocker Reef Key West Riley’s Hump Sombrero Reef Looe Key (Deep and Shallow) Western Sambo Marine Biodiversity Observation Network (MBON)

Web-based Relational Database Independent monitoring

Coral reefs Policy Makers

Resource Managers Educators Satellite remote sensing Scientists Frank Muller Karger, Maria Vega-Rodriguez Email: [email protected], [email protected]

A Decision Support System for Ecosystem-Based Management of Tropical Coral Reef Environments

• A collaborative effort between NASA, NOAA, and USF funded by NASA and NOAA to enhance NOAA's Coral Reef Watch (CRW) Sea Surface Temperature (SST) thermal anomaly/stress products.

• Objectives of the program were:

- To assess regional thermal stress conditions that can lead to stress and bleaching in coral reefs by using spatial high-resolution (1 km) satellite data (e.g. AVHRR, MODIS, other).

Results

• H’ declined significantly for patch reefs in the UK and MK after the thermal anomalies conducive to bleaching events in 1997-1998.

• Patch reefs in the MK showed slightly less change in H’ than those in the UK despite being exposed to higher DHWs.

• Significant declines of H’Δy for 2010 were correlated with the DHWs in 2009.

Vega-Rodriguez M et al. (2015) South Florida Program cruises (R/V Walton Smith): April, June, July, September, November, January

• 10 stations for eDNA and phytoplankton • 3 stations for (64, 200 and 500 mm) • 28 stations for HPLC for validation of RS products ONMS Condition Report Questions

Water Quality 1) What is the eutrophic condition of sanctuary waters and how is it changing? 2) Do sanctuary waters pose risks to human health and how are they changing? 3) Have recent changes in climate altered water conditions and how are they changing? 4) Are other stressors, individually or in combination, affecting water quality, and how are they changing?

Habitat Quality 5) What is the integrity of major habitat types and how are they changing? 6) What are the contaminant concentrations in sanctuary habitats and how are they changing?

Living Resources 7) What is the status of keystone and foundation species and how is it changing? 8) What is the status of other focal species and how is it changing? 9) What is the status of non-indigenous species and how is it changing? 10) What is the status of biodiversity and how is it changing?

Maritime Archaeological Resources 11) What is the archaeological integrity of known maritime archaeological resources and how is it changing? 12) Do known maritime archaeological resources pose an environmental hazard and how is this threat changing?

Human Dimensions 13) What are the levels of human activities that may adversely influence water quality and how are they changing 14) What are the levels of human activities that may adversely influence habitats and how are they changing? 15) What are the levels of human activities that may adversely influence living resources and how are they changing? 16) What are the levels of human activities that may adversely influence maritime archaeological resources and how are they changing 17) What are the states of influential human drivers and how are they changing? Seascape assessments: climatological and time series analyses

Weekly, monthly, and annual seascapes constructed using MODIS chl-a, SST, and PAR at 4-km resolution

Sanctuary boundary CREMP DATA

Ruzicka et al. 2009