# Presentation: 572525

## Integrating Satellite Data into Ecosystem-based Management of Living Marine Resources 

- Cara Wilson
- NOAA • NMFS • SWFSC
- Environmental Research Division
- Pacific Grove, CA

## Integrating Satellite Data into Ecosystem-based Management of Living Marine Resources 

- Bograd, Brodziak, Methot, Shotwell et al.
- NOAA • NMFS

## Integrating Satellite Data into Ecosystem-based Management of Living Marine Resources

**A joint NASA/NOAA workshop held at MBARI, Moss Landing, CA, May 3-5, 2006**
**Primary objective was to demonstrate the potential for satellite data to support and enhance NOAA’s Ecosystem-based Management of LMRs.**
**Representation from each of NOAA/NMFS’s six regional science centers**
**Four pilot projects were developed**

## Integrating Satellite Data into Ecosystem-based Management of Living Marine Resources

**PROJECTS **
**Using satellite data to improve short-term recruitment predictions for Georges Bank cod (*****Gadus morhua*****) and haddock (*****Melanogrammus aiglefinus*****) stocks****PI: Jon Brodziak (PIFSC)**** **
**Reducing uncertainty in Alaskan sablefish recruitment estimates****PI: Kalei Shotwell (AFSC)**** **
**Integrating environmental, fisheries, and electronic catch tag data to characterize essential turtle habitat in areas of significant bycatch ****PI: Steven Bograd (SWFSC with PIFSC & NEFSC) **
**Improving rebuilding plans for overfished west coast fish stocks through inclusion of climate information****PI: Rick Methot (NWFSC)**

**Notes:**
Presentations on three of these 4 projects were given at the Ocean Sciences meeting in Orlando in March 2008 

## What determines recruitment strength of marine fish stocks?

*Adapted from Friedland et al. 2008*

**What determines recruitment strength of marine fish stocks?**
**Early life history survival?  Spawner abundance and condition ?**

**Using Satellite Data to Improve Short-Term Recruitment Predictions**
- Jon Brodziak PIFSC

- Project: Georges Bank Cod & Haddock

## Fall Bloom Hypothesis: Food abundance enhances parental condition and reproductive output

**Fall Bloom Hypothesis: Food abundance enhances parental condition and reproductive output**

**Friedland et al. **Does the fall phytoplankton bloom control recruitment of Georges Bank haddock through parental condition? *Can. J. Fish. Aquat. Sci*., in press

**Primary Productivity Index:**
**Bottom-up forcing affects fall **
**feeding prior to spring spawning**

-  Significant positively correlated PP signal across three spatial scales: subregional, Georges Bank region (shown), and superregional
-  No signal for Cod

- Project: Georges Bank Cod & Haddock

## Work in Progress

- Is there a detectable spring bloom effect on survival ratios?
- Possibly for cod but low N
- Interannual variation in onset of spawning
- Dynamic time stratification
- Are wind stresses important relative to other effects?
- Need to access wind stress measurements
- QuikSCAT
- COADS
- Modeling environmental forcing using GAMs to discern shape of nonlinear effects
- Modifying age-structured projection model AGEPRO  to incorporate multiple environmental predictors
- Next, Pacific tunas & billfishes...

- Project: Georges Bank Cod & Haddock

## Alaskan Sablefish ProjectAuthors: S. Kalei Shotwell & Dana H. Hanselman

- Sablefish (*Anoplopoma fimbria*)
- Fast growing, wide distribution, highly valuable commercial species
- Adults generally at 200+ meters in continental slope, gullies, fjord
- Early life history (ELH) largely unknown
- Spawning at depth (400+m), larvae swim to surface, collect at shelf break
- Juveniles move nearshore to overwinter, then offshore in summer
- Reach adult habitat and recruit to fishery or survey in 4 to 5 years
- Recruitment calculated in age-structured model
- Recruitments are estimated as two year-olds
- Estimates for most recent years are highly variable with large uncertainty and excluded from model projections
- Objective
- Evaluate ELH data and explore integrating satellite derived environmental time series into the sablefish stock assessment to reduce recruitment uncertainty

- Project: Alaskan Sablefish

**Notes:**
This is the general background of the project and the basic objectives. 

## Early Life History

**1977-1986**

**1987-1996**

**1997-2006**

- Sablefish recruitment anomalies from model

- Project: Alaskan Sablefish

- Bad    Good

- Collected historical ELH survey data and compared to model recruitment
- Model recruitment estimates show high autocorrelation
- Potential decadal regimes, supported by survey data

**Notes:**
The bar graph shows the sablefish recruitment anomalies from the model estimates of recruitment. Basically purple bars are good recruitment years, red bars are poor recruitment years. The model recruitment estimates show high autocorrelation with three potential decadal regimes that are supported by the survey data (click through animation to see the maps, explanation below). When recruitment is high (purple bars) there is some interesting correspondence with small fish expanding into the Bering Sea shelf through Unimak Pass, and higher abundance west of Kodiak and in shelf gullies. The most recent regime is highly uncertain. 

The maps will show up with the animations with three clicks. First click shows 1977-1986 regime and map of historical data, Second shows 87-96, Third shows 97-06. 

Important Points: Recent model recruitment estimates are largely unknown, three potential regimes supported by survey data, when recruitment is high see expansion into Bering Sea shelf. 

FYI, in case someone wants to know. 
The maps show all the historical data we found on the early life history of sablefish, and you can see this in the different colors of dots. 
Green is the Fisheries and Oceans Coordinated Investigations (FOCI) Ichthyoplankton Database (Larvae: 1977 - Present)
White is the NMFS Trawl Survey Database (Juveniles: 1977 - Present)
Red is the Gillnet survey on the Auke Bay Labs Longline Survey (Juveniles: 1996 - 2004)
Purple is two surveys: from 1977 – 1996, the FOCI Ichthyoplankton Database (Eggs) and from 1997 – 2006, the Bering-Aleutian Salmon International Survey (BASIS) Survey Database (Juveniles: 1998 – Present). 

The pictures at the top show sablefish larvae, then pelagic juvenile, and larger juvenile that occur nearshore and are tagged in the Auke Bay Labs juvenile sablefish survey each year in southeast Alaska.  

## Next Steps:

- Identify dominant environmental mechanisms
- High spatial and temporal variability detected in the ELH surveys imply influence of physical mechanisms on sablefish recruitment
- Potential mechanisms include:
- Mesoscale eddy entrainment: variability in food availability
- Gulfwide freshwater discharge: variability in mixed layer, iron input
- Use environmental time series developed from satellite data
- AVHRR Pathfinder V5, front probability, Alaska Stream position
- Multi-mission altimetry, eddy kinetic energy, eddy position
- Coastal freshwater discharge northern Gulf of Alaska
- Incorporate into stock assessment model as time series
- Early detection of recruitment trends
- Increase efficiency in harvest decisions
- More reliable future projections

- Project: Alaskan Sablefish

**Notes:**
We are working with Ed Armstrong and Ben Holt from JPL on developing the satellite time series and derived products (e.g. front probability, stream position, eddy kinetic energy), and several physical oceanographers from University of Alaska Fairbanks on determining the potential mechanisms. We have established a contract with a stock assessment modeler to incorporate the time series into the stock assessment model and have been working with him to stabilize the model.  

## Satellite-derived SST frontal analysis for fisheries management

- Ed Armstrong1,  C. Holt2, R. Methot4,  A. Punt3, N. Mantua3 & B. Holt1

- 1 NASA JPL/ California Institute of Technology
- 2 Fisheries and Oceans Canada
- 3 University of Washington
- 4 NOAA NMFS

**Goal: Identify ****biological, chemical, ****and**** physical**** indicators of conditions in the California Current that have influences long-term trends in ****recruitment ****of west coast groundfish species**

- Project: West Coast Groundfish

## Fish species

**Black rockfish: 1985-2001**
**Lingcod N: 1985-2000**
**English Sole: 1985-2002**
**Starry Flounder N: 1985-2001**
**Cabezon N: 1985-2003**
**Cabezon S: 1985-2003**
**Lingcod S: 1985-1999**
**Starry Flounder S: 1985-2003**
**Canary Rockfish: 1985-2006**
**Sablefish: 1985-2006**
**Widow rockfish: 1985-2003**
**Chilipepper rockfish: 1985-2006**
**Pacific ocean perch (rockfish): 1985-2002**
**Commercially viable species with long life spans >50 years.****  **

- Species classified into groups with similar ecological characteristics and geographic distributions

- Project: West Coast Groundfish

## Background

- Various hypothesis on recruitment investigated
- Variability of the west coast Spring Transition (upwelling commences)
- Fine scale temporal variability of SST
- Fine scale spatial variability of SST
- Stock assessment model (NOAA Stock Synthesis II) used to generate recruitment estimates from historical observations of fish catch and surveys

- Project: West Coast Groundfish

## Spring Transition hypothesis

- Recruitment success increases when the timing of larval life stages coincides with early spring transition

- Small scale variability hypothesis

- Recruitment is affected by small scale oceanic variability
- Temperature fronts, eddies, upwelling centers add        habitat complexity and prey availability
- Goal: Use satellite SST gradients as a proxy for these

- Project: West Coast Groundfish

## Spring Transition hypothesis              Small scale variability hypothesis

**Earlier ST linked to higher recruitment, but not significant**

**Spring Transition hypothesis              Small scale variability hypothesis**

**Higher recruitment linked to higher front probability, but not significant**

- Average  frontal probability

- Log(recruitment deviations)

- Project: West Coast Groundfish

**Notes:**
No trends are significant at 5% level

## Summary

**Both the Spring Transition dates and frontal probability maps correlation to recruitment estimates were not significant at 5% level**
**But some trends were enticing, especially for nearshore spawn/settle species**
**Higher resolution SST products such 4 km Pathfinder SST could provide confirmation on possible relationships**
**Long time series is critical**
**Additional products such as sea surface height, satellite derived currents, ocean color will also be investigated**

- Project: West Coast Groundfish

## Distribution, Movements, and Behaviors of Critically Endangered Eastern Pacific Leatherback Turtles: Conservation Implications for an Imperiled Population

**Distribution, Movements, and Behaviors of Critically Endangered Eastern Pacific Leatherback Turtles: ****Conservation Implications for an Imperiled Population**

- Shillinger, Palacios, Bailey, Bograd
- Block Lab, Stanford University
- NOAA-SWFSC-ERD

- Project: Sea Turtles

## Objectives 

**Pacific Ocean  ****(-96% in 20 yrs) **
- 1980:  ~ 91,000 adult females
- 1995:  ~ 6,500 adult females
- 2000:  ~ 3,490 adult females

**Status:**** Critically Endangered**

**Objectives**** **
** **Obtain fisheries independent data
-  Horizontal and vertical movements
-  Define critical habitats and home range
-  Interannual comparisons
-  Oceanographic characterization
-  Management and conservation

**Eastern Pacific  ****(-79% in 10 yrs)**
- 1995:   4638
- 2000:   1690
- 2005:   <1000

- Project: Sea Turtles

## Internesting Movements and SST 

**Results **
** **Papagayo upwelling disrupts warm, northward Costa Rica Coastal Current (CRCC)
-  75% utilization distribution (UD): 173,313 km2
-  Dive behavior (n=10,568 profiles)
-  mean depth: 19 m (sd=13.66 m)
-  mean duration: 9.20 min (sd=5.99 min)

**Results **
** **Papagayo upwelling disrupts warm, northward Costa Rica Coastal Current (CRCC)
-  75% utilization distribution (UD): 173,313 km2
-  Dive behavior (n=10,568 profiles)
-  mean depth: 19 m (sd=13.66 m)
-  mean duration: 9.20 min (sd=5.99 min)

**2004**
- Papagayo upwelling disrupts warm CRCC
- Mean depth: 19 m
- Mean duration: 9.20 min

**Results **
** **Papagayo upwelling disrupts warm, northward Costa Rica Coastal Current (CRCC)
-  75% utilization distribution (UD): 173,313 km2
-  Dive behavior (n=10,568 profiles)
-  mean depth: 19 m (sd=13.66 m)
-  mean duration: 9.20 min (sd=5.99 min)

**Results **
** **Papagayo upwelling disrupts warm, northward Costa Rica Coastal Current (CRCC)
-  75% utilization distribution (UD): 173,313 km2
-  Dive behavior (n=10,568 profiles)
-  mean depth: 19 m (sd=13.66 m)
-  mean duration: 9.20 min (sd=5.99 min)

**2005**
- Strong Papagayo upwelling (coldest year)
- Warm (strong) CRCC
- Mean depth: 17.5 m
- Mean duration: 9.14 min

**2007**
- Weak Papagayo upwelling
- Warmest (stronger) CRCC
- Mean depth: 26.29 m
- Mean duration: 12.26 min

- Project: Sea Turtles

**Notes:**
The first row of this slide depicts internesting UD plots for each of the tagging seasons.  Core high use areas are demarcated by hot colors.  The lightest colored contour encompasses 95% of the total home range utilized by the internesting leaterbacks.
The second row of this slide depicts internesting positions from each tracking year superimposed upon the mean SST for the month of January. 
Observations:
Point out interannual variation.  Note SST and movements for each year.
Note differences in dive depth – particularly 2007.  Deep dives may be related to thermoregulatory activity or could be associated with foraging behavior along a deeper thermocline. 
Also note, turtles may have been using Santa Elena Peninsula and Gulf of Papagayo to remain in lee of CRCC and avoid risk of transport away from nesting beach – as evident in image.
Also note shallower dives during 2005 – could have been associated with foraging or themoregulatory activities in cooler surface waters around a shallower thermocline. 
Highlight importance of considering SST as an important potential predictor for turtle movement --- and implications for time-area mgmt and zoning for leatherbacks.
The tracking data indicates that the Gulf of Papagayo is a high-use area for internesting leatherbacks although internesting turtles dispersed to the north, south and west of the nesting beach. 
As previously noted, the data also support that Parque Nacional Las Baulas is appropriately sited to protect the most critical nesting habitat, however, enhanced protection of internesting leatherbacks could be achieved through:
 expansion of PNMB
 creation of new protected areas within the G of P, or 
 strategic time are closures through the breeding season (5-6 months) that consider interannual variation (and use predictive models to anticipate turtle distribution) and 
 fisheries mitigation or gear modification techniques that consider the potential presence/absences and vertical movements of leatherbacks

## Mean Kinetic Energy (cm2 s-2)

**Mean Kinetic Energy (cm****2**** s****-2****)**

**1.  Turtles must negotiate  gauntlet of zonal currents**

**2.  Turtles cluster in areas of high energy content**** **

**3.  Turtles “fan out” in areas of low energy content**** **

**4.  Turtles spend a lot of time in 5°S-35°S.****  **

**Chlorophyll (mg m****-3****)**
**10 year SeaWiFS**

**3.  Examine dive behavior**

**2.  Turtles move into zones of low phytoplankton density**

**1.  Turtles move rapidly through areas of high productivity**

**CRD (~10cm s-1)**

**NECC(~30cm s-1) **

**SEC (n) (~30cm s-1)**

**EUC (~5cm s-1)**

**SEC (s) (~15cm s-1)**

**Surface velocities cm ****s-1**

**(CHL vs. Speed linear regression: ******** = 0.964 ± 0.057, *****F*****1,9577**** = 281, *****P *****< 0.001, *****r*****2**** = 0.029)**

- Project: Sea Turtles

## Turtle Conservation within EEZ’s and on the High Seas?

- Green contour enclosing a region with lowest climatological eddy kinetic energy (>30 cm2/s2 ) in the South Pacific Gyre.

**Turtle Conservation within EEZ’s ****and on the High Seas?**

**TCA?**

**1.  South Pacific Gyre: reduced mean flow but eddy motions and eddy currents remain**

**4.   Resource-depleted females take path of least resistance, chill out, find food...**

**A “coldspot” for turtles**** **

**3. Unlike hotspots, South Pacific Gyre has low KE, fewer fronts, and low chl-a**

- Project: Sea Turtles

**Notes:**
Identified a persistent physical mechanism and feature in the spg – dispersal habitats of lbts – 
that may have the potential to be used a conservation concept/paradigm for leatherbacks on the high seas.  

Note that this contour captures a 15 yr mean in EKE – and represents the region with lowest Mean Kinetic Energy in the SPG. T
The opportunity for mgmt resides in the predictability of this region and the persistent associate of lbts with this feature.  Can envision a high-seas conservation strategy for leatherbacks that would model leatherback movements that would take into consideration the dynamics of this feature. This data could be used to develop temporal-spatial mgmt strategies for eastern Pacific leatherbacks within distant foraging habitats

## PIFSC TurtleWatch

**PIFSC TurtleWatch**

**Based on NESDIS SST (GAC 4 km 3 day average) and JPL Geostrophic Currents (9 km 7 day)**
**Provided daily by email to industry/managers and hand carried to fishers **
**Vietnamese version**
**GeoEye version **

- Project: Sea Turtles

## We’re just getting started..... 

**We’re just getting started.....**** **

## Not anymore!! 

**& **

**MISSION: IMPOSSIBLE? **

- Satellite
- data

- Not anymore!!

## Environmental Data Connector 

- Allows easy selection, and importation of any dataset served by Thredds/OPeNDAP into ArcGIS 9.2
- Developed by Applied Science Associates, Inc.
- Funded by NOAA’s Satellite R&O project
- Free distribution

- www.pfeg.noaa.gov/products/EDC

**Questions???  cara.wilson@noaa.gov**

- Provides the front-end capabilities of the EDC independent of ArcGIS
- Provides a GUI to browse THREDDS catalogs or OPENDAP directories, to subset the selected data in space and time, and to download the data as a netcdf file
- The EDC Standalone Module will work on any computer with Java 1.5

- Standalone Module

- www.pfeg.noaa.gov/products/EDC

**Questions???  cara.wilson@noaa.gov**

## Rationale  

- The continuity, global coverage, and high temporal and spatial resolution of satellite data make it an important tool for monitoring and characterizing marine ecosystems, but data have been largely inaccessible for those working with GIS tools, such as fisheries scientists and marine resource managers.

- Rationale:

- www.pfeg.noaa.gov/products/EDC

**Questions???  cara.wilson@noaa.gov**