Transcript "The Butterfish Smackdown”: Steps toward an operational seascape ecology supporting ecosystem management

"The Butterfish Smackdown”:
Steps toward an operational seascape
ecology supporting ecosystem
management
John Manderson, NOAA Fisheries
Josh Kohut, Rutgers University
Chris Roebuck, FV Karen Elizabeth
Greg DiDomenico, Garden State Seafood
John Hoey, NEFSC Cooperative Research
6th World Fisheries Congress
Edinburgh, Scotland, May 2012
How to build a regional scale seascape ecology
supporting ecosystem management?
Cape
Cod
Science must be broad in extent
Ocean Habitat is not just the seabed
Get motion & variability of fluid
into habitat definitions
Regional Ocean Observing
Systems
Measure properties & motions at
scales to capture regional ocean
physics- & therefore fluid
New
York
Mid
Atlantic Bight
US
NW
Atlantic
Cape Hatteras
Data & Models Integrated in Ocean Observing Systems
Data:
Satellites
HF radar
Gliders
Buoys
Ensemble of Oceanographic Assimilation Models
ROMS
HOPS
Current approach: statistical species distribution models
NOAA US Fishery Data
Spatial grain = 11km
Ocean
observations
+
Regional
seabed data
Statistical
“niche” models
(e.g. GAM, GLM, MAXENT)
Regional
Habitat
Projection
(Hypothesis)
Model habitats of ecosystem “keystone” species
Mid-Atlantic Bight US Ecosystem model - EMAX
Butterfish
&
Long fin inshore squid
Resilience of keystone populations
~> ecosystem resilience
From Link et al.
2008
HF radar data
Response models
Upwelling
Divergence index
Downwelling
Satellite data
Downwelling
Upwelling
Frontal index
But are models
accurate & useful?
Distance: Far
Strength: Weak
Close
Strong
Biomass index NEFSC fall survey
Estimated biomass from stock assessment
Sometimes a management problem finds you
Can
we
address
the
issue
with
Butterfish by-catch mortality cap
regional
habitat
models?
in long finscale
inshore
squid fishery
Enlist experts from fishery in model refinement
Ask fisherman about the fish
Hypothesis:
Combining fishermen & scientists’ knowledge within
an Operational Ocean Observing system should:
(1) Increase chances models capture space-time
scales of important behaviors & processes
(2) Enable adaptive decision making at space-time
scales matching those of ecosystem
Butterfish Habitat Modeling Workshops
Fishermen, habitat ecologists & oceanographers
Ocean habitat variables associated with high butterfish biomass
Scientists &
fisherman
Scientists
Bottom
Temperature
Index of
upwelling
Solar
elevation
Day length
Surface
fronts
Bottom
complexity
Bottom
depth
Mixed layer
depth
+
Fisherman
Sediment
grain size
Lunar Phase
Chlorophyll
Base model
Scientists &
fisherman
Bad
Bottom
Temperature
NULL
Ship
Solar
elevation
Bottom
complexity
Day length
Better
Bottom
temperature
Bottom
complexity
Surface
fronts
Mixed layer
depth
Bottom
depth
Variable selection
Criterion
(AIC)
Solar
elevation
Day length
MLD
Fronts
Best
Resid. Depth
Variables
Bad
Butterfish “Smackdown”
Base model
Better
Best
Variables
Bad
Butterfish “Smackdown”
Scientist’s model
Base model
Better
“Upwelling”
Best
Bad
Butterfish “Smackdown”
Fisherman’s model
Base model
Better
“Upwelling”
Best
Lunar
phase
Sediment
Chlorophyll
Butterfish Habitat Model 2.0
Combined fisherman & scientist model
NULL
Ship
Bottom
temperature
Bottom
complexity
Solar
elevation
“Upwelling”
Hours of daylight
Sediment grain size
Can we operationalize a habitat model
&
collaboratively field evaluate using
“now casts”?
Inputs to operational butterfish habitat model “now casts”
Depth
Day Length
Solar Elevation
Modified Butterfish 2.0 to accept near-real time IOOS surface observations
Satellites
8-Day
Sea Surface Temp
Satellites
8-Day
Frontal Index
HF radar
32-Day
Divergence Trend
Test of prototype operational habitat model
Model “now cast” based
on IOOS observations
Atlantis/
Veatch
Wilmington
Norfolk
Canyons
along
shelf break
Focus group
Fisherman: “You modeled our vessel tracks”!
Scientists: “No, No. We modeled the fish”
Catch data
&
analysis
F/V Karen Elizabeth
Design of 7 day adaptive & cooperative survey
3 canyon areas
Atlantis/Veatch
Wilmington
Norfolk
Regional
hotspots
x
Night
Daylight
x
Model “now casts”
Bad Habitat
pixel
Good Habitat
pixel
Diel vertical
migration
Fisherman “now cast”
Good habitat
Temperature
Rhode Island
New
Jersey
Atlantis/
Veatch
Wilmington
December 10 - 17, 2011
200 km
Norfolk
North
Carolina
What did we learn?
• Spatial resolution of model ~ 40 km (meso-scale)
– Nyquist frequency: 2 x interstation distance
What did we learn?
• Spatial resolution of model ~ 40 km (meso-scale)
– Nyquist frequency: 2 x interstation distance
• Animals respond to fine scale habitat processes nested
within coarser meso-scale processes. e.g.:
– Thermal gradients
– Predators, prey, production dynamics
What did we learn?
• Spatial resolution of model ~ 40 km (meso-scale)
– Nyquist frequency: 2 x interstation distance
• Animals & respond to fine scale habitat variation
nested within meso-scale variation. e.g.:
– Thermal gradients
– Predators & prey
• Animals occupy areas un- or under sampled in
assessment surveys. Some are important habitats.
– Shallow near-shore in summer-early fall
– Continental slope during late winter-early spring
What did we learn?
• Spatial resolution of model ~ 40 km (meso-scale)
– Nyquist frequency: 2 x interstation distance
• Animals & respond to fine scale habitat variation
nested within meso-scale variation. e.g.:
– Thermal gradients
– Predators & prey
• Animals occupy areas un- or under sampled in
assessment surveys. Some are important habitats.
– Shallow near-shore in summer-early fall
– Continental slope during late winter-early spring
Management Application
Butterfish Habitat Model 3.0
Butterfish Biomass
Fall survey 1980 - 2010
Fish use shallow
near-shore in summer
(un)dersampled in surveys
&
Migrate offshore with changes
temperature & photoperiod
in the Fall
Preliminary analysis
Butterfish thermal habitat
as defined by SST
Not
Preferred
Preferred
Preliminary analysis
SST
When do autumn near shore temperatures fall
below preferred range?
D<20m
(5 day moving average SST)
Day of the year
Changes
in climate affect seasonal habitat dynamics:
Southern New England
Mid Atlantic
Timing
ofBay
a migratory trigger?
Hudson
to Buzzards
Hatteras to Hudson River
Day y-1
Day y-1
Year
Preliminary analysis
Timing of assessment surveys
Bottom Depths
90% Observations
14 - 240 meters
Preliminary analysis
Fall survey index of Butterfish Biomass
Possible Sources of Variation
Seasonal habitat dynamics
Survey period
Actual Population size
Prototype Butterfish Habitat Model 3.0
Couple to bottom temperature hind casts from PO models
Night
Day
Prototype Butterfish Habitat Model 3.0
Couple to bottom temperature hind casts from PO models
- Has seasonal habitat dynamics changed with climate change?
Night
Day
Prototype Butterfish Habitat Model 3.0
Couple to bottom temperature hind casts from PO models
- Has seasonal habitat dynamics changed with climate change?
- Does this confound survey based estimates of population trends?
Night
Day
Prototype Butterfish Habitat Model 3.0
Couple to bottom temperature hind casts from PO models
- Has seasonal habitat dynamics changed with climate change?
- Does this confound survey based estimates of population trends?
- Use habitat model to calibrate indices for changes?
Night
Day
Couple ecological models to PO model “now casts” for
supplemental habitat based assessments
of keystone species & processes
Scale of knowledge of seascape in space
Collaboration with Fishing Industry
within an Operational Ocean Observing system
= improved science & a lot less acrimony
Ecosystem
Scientists
Mechanistic
ecosystem
process scales
Oceanographers &
Habitat Ecologists
Fishermen
Scale of knowledge of seascape in time
Median R Predictions vs. Observations (95% CL)
Butterfish habitat model 2.0
(resolution~40 km (22 nm)
Backward stepwise CV (N iterations=999)
Bottom
temperature
Bottom
Complexity
Solar
elevation
Fronts
Upwelling
Sediment
grain size
Ship
Number of variables in model
Preliminary analysis
Coastal SSTs
Depths 0-20M
http://www.ncdc.noaa.gov/oa/climate/research/sst/griddata.php
Integrated Ecosystem Assessment
Recreation
Food web & other interactions
Energy
Fishing
Human ecology
+
“Wild” ecology
Biophysical
interactions