Download Vladimir Kostylev - Gulf of Maine Council

Habitat template approach to
benthic habitat mapping
Vladimir Kostylev
Natural Resources Canada
Bedford Institute of Oceanography
Pluto didn't make the cut
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•
•
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The International Astronomical Union, a worldwide society of
astronomers from 75 countries voted on the final proposal after
more than a week of heated debates over the standards in properly
classifying celestial bodies into different categories.
The new guidelines — introduced in Prague in August 2006 after a
week of debate by the 2,500 astronomers at the organization's
conference — define what is a planet and what is not.
Pluto didn't make the cut.
The "New Definition" explicitly says that "a planet is a celestial body
that is in orbit around the sun, has sufficient mass for self-gravity to
overcome rigid body forces so that it assumes an almost round
shape, and has cleared the neighborhood around its orbit."
“Astronomers have been working without a solid definition of a
planet since the days of Copernicus. The new definition fills
that void.”
Habitat classification
• “It should be understood that we are not
referring to here to the realities or limits of
these subdivisions or the problems of
zonation on the shore, but to the manner
in which the terms have been applied”.
– Joel Hedgpeth (1957)
In: National Research Council (U.S.). Committee on a Treatise on Marine Ecology and
Paleoecology.
What are habitats?
• For mapping purposes, habitats are
defined as spatially recognizable areas
where the physical, chemical and
biological environment is distinctly
different from surrounding areas.
• The degree of similarity is defined
ecologically.
Which characteristics should
habitat maps have?
• Should be based on repeatable methodology
– Assumptions, techniques are explicit
• Should have low uncertainty
– data, positional, taxonomic, statistical, boundary, drill-down
• Should reflect temporal continuity of the environment
– They will not be repeated often
• Should be useful four understanding of ecosystem
processes
– Responses of ecosystems to management actions
• Should reflect and predict emergent properties
– Summaries instead of compilations
• Should be useful to managers
– (like navigation charts to sailors, not too complex)
www.resortmaps.com
Thick sand
Thin sand
Thin mud
Video + acoustic -
Armoured sand
Armoured mud
Video + grab -
Thick mud
Acoutics- bio +
Till
Bedrock
Classification- bio +
Seabed surface
?
Remote sensing
(acoustic) data
Physical samples
(groundtruthing)
?
Texture, stratigraphy, etc.
Interpretation of
Morphology
Hardness
?
Roughness
?
Surficial geology map/
Substrate map
Assumptions on
animal-sediment
?
coupling
?
Benthic habitat map
Which paths should be tested?
Benthic
distributions
Benthic populations
Benthic
distribution
data
Benthic habitat map
Seabed surface
Physical
sediment
samples
Benthic populations
Benthic
distribution
data
Assumptions on
animal-sediment
coupling
Benthic habitat map
Seabed surface
Remote sensing
(acoustic) data
Interpretation of seabed
Morphology,
Processes etc.
Assumptions on
animal-sediment
coupling
Benthic habitat map
Seabed surface
Remote sensing
(acoustic) data
Physical samples
(groundtruthing)
Texture, stratigraphy, etc.
Interpretation of
Morphology
Hardness
Roughness
Surficial geology map/
Substrate map
Assumptions on
animal-sediment
coupling
Benthic habitat map
A – series map of German Bank surficial geology
B. Todd 2008
Three paths
• The path from remote sensing to habitat is
lacking groundtruthing information,
• The path from geological samples to habitat
map lacks coverage and definition of
boundaries,
• The path from benthic community samples to
habitat map is as problematic as creating
geological maps from grab samples alone
without acoustic information which provides
spatial context.
Seabed surface
Benthic populations
?
Remote sensing
(acoustic) data
Physical samples
(groundtruthing)
?
Texture, stratigraphy, etc.
Interpretation of
Morphology
Hardness
?
Roughness
?
Surficial geology map/
Substrate map
+ Other
important
environmental
factors
Assumptions on
animal-habitat
?
coupling
?
Benthic habitat map
Benthic
distribution
data
Animal-sediment coupling
assumptions
• The classical marine ecology assumption that similar
groups of species occur on similar substrates (Thorson
1957)
– Species diversity is shown a significant function of sediment
particle size diversity
– Composition of sediment communities can be influenced by
sediment particle size
• Effects of sediment grain size on benthos produced
contradictory results (e.g. Snelgrove and Butman 1994)
• Arbitrary subdivisions between different classes in
geological classifications do not need to be meaningful
to benthic fauna.
• Effects of geomorphological features on benthos are
usually induced from ordination techniques and not
followed by hypothesis testing
• Processes had not been considered
Saint John harbor
Sable Island Gully
Browns Bank
Assumptions implicit to habitat
maps
•
•
Assumption that geological boundaries are accurate and meaningful
Assumption that species are habitat specialists (as the opposite to
generalists)
– Some animals have well-defined functional association with the
sediment type (sand lance), sessile animals attaching to sediment.
•
•
•
•
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Assumption that animals have 0m home range
Relative homogeneity of other important variables (oceanography)
Assumption of temporal stability of patterns
Assumption of causal relationship
Empirical data problem: If in a field study we find a relationship
between a particular type of sediment and a particular species, does
it mean that
– 1 this will work in unsampled areas,
– 2 this will work in other years/seasons
– 3 the studied species or assemblages will always be found where this
particular sediment type exists.
1000
EROSION
current speed (cm/sec)
100
10
TRANSPORTATION
hydraulically rough
1
DEPOSITION
0.1
hydraulically smooth
0.01
0.001
0.0001
CLAY
SILT
SAND
0.001
0.01
0.1
1
Particle size (mm)
GRAVEL
10
100
1000
Fishery and regulatory priorities
Fishery:
• Get higher catches
• Decrease fishing effort
and cost
• Make fishery sustainable
= make profits
sustainable
Governments:
• Preserve rare species
and exploited stocks
• Preserve habitats
(vulnerable, sensitive,
unique) and ecosystems
• Preserve biodiversity
Both sides require:
Knowledge of habitat properties and distribution
Knowledge of life history traits and habitat association
of species
•Putting demographic r-K
theory in habitat context
•“Energy allocation” and
“adaptive strategy”
•Determined by genetical
and environmental
constraints which result
in trade-offs in life history
traits
•Physiological adaptation
•Ontogenetic processes
•Reproduction and
somatic growth
•Behaviour (predator
avoidance and migration)
•Applies to species and
communities
The Blender habitat model
reproduction
growth
biomass
stress
energy
removal
What these habitats do to the species occupying them?
POPULATION RECOVERY FROM IMPACT
Fast
Slow
Low
Migration high
Offspring medium
large
Longevity medium
Tolerance high
R
Migration high
Offspring many small
Longevity small
Tolerance low
Risk of habitat
destruction
High
K
rK
Migration low
Offspring few and
large
Longevity great
Tolerance high
Migration low
Offspring medium
and small
Longevity medium
Tolerance low
Scope for Growth
Disturbance
A
Biotic interactions
Fish
Winemiller 1995
Size at
maturity
Maximum
size
Growth rate
Fecundity
Max age
Egg size
Parental
investment
J.R.KING &G.A.MCFARLANE 2003
Disturbance
We define disturbance as the ratio of the
characteristic friction velocity to the critical shear
stress required for initiation of sediment movement
(1) high resolution
bathymetry of the region
(the analysis grid),
(2) 42 year hindcast of the
wave height and period
data,
(3) near-bottom tidal
current extracted from
models;
(4) grain size estimates
Disturbance
0
Kostylev and Hannah 2007
1
Scope for growth
Reflects energy available for growth
and reproduction of a species after
accounting for energy spent adapting
to the environment.
Fuzzy index
SfG = (Fa + Tm – Ta – Ti + O)/5
Fa = C – S
Scope for Growth
1
Kostylev and Hannah 2007
Similarity in template values %
100
95
90
85
80
75
Similarity in species %
60
40
20
0
70
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
Distance (m)
Figure 4. Comparison of the relationship of Bray-Curtis similarity in species composition with
distance between samples and with similarity in habitat template values. The closer two samples
are within the habitat template the more likely they are to have similar faunas, while their spatial
proximity is a poor predictor. Similarity in species composition is spline interpolated, red - high,
green - low.
D is tu r b a n c e
Gorgonians
Arctica
Brachiopoda
Cucumaria
Filograna
Flabellum
Lobster
Modiolus
Placopecten
Potamilla
Sand dollar
Snow crab
Mactromeris
Sponges
Kostylev and Hannah 2007
Scope for growth
?
Disturbance
Scope for growth
ir sk
Risk map (O’Boyle, Kostylev, et al 2006)
150 km
Kostylev and Hannah 2007
A.
Adversity
B.
Disturbance
Edward Gregr, 2006. Digital data for the benthic classification of British Columbia offshore waters.
Technical Report.
C. Habitat Template
D=disturbed
S=stable
A=adverse
B=benign
D.
Habitat Template
With Winter Flounder
Noji, T.T., Fromm, S., Fromm, S., Vitaliano, J. and Smith, K. 2008. Habitat Suitability Modeling
using the Kostylev Approach as an Indicator of Distribution of Benthic Invertebrates. In
ICES Annual Science Conference. International Council for the Exploration of the Sea,
Halifax, Nova Scotia, Canada, p. 5
K. Smith. 2005. A benthic habitat model for the Gulf of Maine.
Scope for Growth
Disturbance
r
Beaufort Sea
(climate change)
Kostylev et al. in prep.
Scope for Growth
Scotian Shelf
(fishery)
1000 km
This work is possible because of help,
advice, encouragement and hard work
provided by:
Brian Todd, Charles Hannah, Bob O’Boyle, John Shaw, Dick
Pickrill, Steve Blasco, Russ Parrott, Angus Robertson, Kevin
MacKillop, Walli Rainey, Kim Conway, Gordon Fader, Don
Gordon, Brian Petrie, Victor Soukhovtsev, Igor Yashayayev,
Colin Dickson, Bob Courtney, Gary Grant, Phil Oregan and
many others.