Key lecture for the EURO-BASIN Training Workshop on Introduction to Statistical Modelling for Habitat Model Development, 26-28 Oct, AZTI-Tecnalia, Pasaia, Spain (www.euro-basin.eu)

1. EURO-BASIN Training Workshop on
Introduction to statistical modelling tools,
for habitat models development
Predicting suitable habitat for the European
lobster (Homarus gammarus), on the Basque
continental shelf (Bay of Biscay), using
Ecological-Niche Factor Analysis
Ibon Galparsoro
AZTI-Tecnalia; Marine Research Division
igalparsoro@azti.es
Pasaia 1
26-28 October 2011
EURO-BASIN, www.euro-basin.eu Introduction to Statistical Modelling Tools for Habitat Models Development, 26-28th Oct 2011

2. Background
In the Basque Country, a marine habitat mapping programme started in 2004
Determine habitat suitability for some key species
Although this fishery is limited, its socio-economic importance in some ports is
very high
However, there is a lack of information on the H. gammarus fishery and on the
official registration of catches, leading to an underestimate of the population size
This makes it difficult to understand the stock and its management to maintain a
sustainable fishery.
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3. Objetives
! (i) the identification of seafloor morphological characteristics,
together with wave energy conditions, that determine the
presence of European lobster (Homarus gammarus);
! (ii) to habitat suitability model for the lobster, using ENFA.
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4. Study area and lobster sampling
estrategy
7th June and 10th August, 2007
Total of 17 lobster pot lines were laid
Each line was 650 m long, including 60 pots
The initial, middle (or bearing change) and final
positions
Pots were deployed in the afternoon and recovered
in the morning
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5. Multibeam echosounder data
SeaBat 7125 and SeaBat 8125 MBES
1 m resolution seafloor DEM
Seafloor morphologic feature extraction
multiscale analysis (15mX15m; 45mX45m;
135mX135m)
Bathymetry
Slope
Aspect
Curvature (planimetric and profile)
Benthic Positon Index (Broad and Fine Scale)
Rugosity
Distance to rock
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6. Wave flux over the seafloor
Most representative wave characteristics were
obtained from databases
Coastal hydrodynamic numerical modelling
software (SMC)
Waves were propagated up to the coast
Mean wave flux, per metre of fetch over the first
metre above the seafloor was calculated
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7. Ecological-Niche Factor Analysis and habitat
suitability map production
The ENFA approach (Hirzel et al., (2002)) computes suitability functions by comparing the
species distribution in the eco-geographical variables space, with that of the whole set of
cells
It does not require ‘absence data’
Marginality (M) represents the ecological distance
Frequency
Global 〈 m − mS 〉
Species M= G between the species optimum and the mean habitat
1.96δ G
within the reference area
σG
Specialisation (S) is defined as the ratio of the
∂
σS S= G standard deviation of the global distribution ( ∂G ), to
µG
∂S
µS Altitude that of the focal species (∂S )
Multi-scale analysis
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8. Results
92 lobsters were caught, in 17 pot
line deployments (average= 5.3)
The pot were located on the lowest
part of a steep slope, at the
boundary with the sandy bottom
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9. Results
Scale (pixel) Marginality Specialisation
3x3 0.983 2.418
Best results were obtained the
9x9 1.196 2.138
maximum resolution analysis
27x27 1.514 2.261
Multiscale 1.861 1.618
The cross-validation of the model quality,
predicted to expected ratio for the overall
curve, resulted in a Boyce Index of 0.98 ± 0.06
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10. Results
Environmental
Overall area Presence areas
variables
Standard Standard
Maximum Minimum Mean Deviation
Maximum Minimum Mean Deviation
Euclidean distance to rock (m) 3950 0 597 243 158 0 30 44
Broad sacale Benthic Position
Index
28 -17 0.5 2.71 9 -7 -1.1 2.9
Slope (º) 65 0 3 3.94 44 0 6 6
Wave flux (kWhm-1) 12 0 0.2 0.37 0.63 0.09 0.3 0.09
Bathymetry (m, below Chart
Datum)
-88 -1 -47 19.6 -47 -30 -37 4.14
These results indicate:
1. Lobster habitat differs considerably from the mean
environmental conditions over the study area
2. It is restrictive in the range of conditions in which it
dwells
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11. Results
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12. Discusion
Results are comparable to those obtained for other lobster species in terms of
the seafloor morphological characteristics that best explain the presence of the
lobster.
Wilson et al., 2007, identified multi-scale ENFA approach as providing better
results than the one-scale analysis.
This observation suggests that bottom topography is important
Special care should be taken in the representativeness of the lobster sampling
Future work will focus upon the realisation of specific surveys, with random
sampling, in order to quantify statistically the reliability of the lobster
distribution model.
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13. This study was funded by the Basque government:
Department of Environment and Regional Planning
Department of Agriculture, Fishing and Alimentation
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14. Predicting suitable habitat for Zostera noltii in
the Oka estuary (Basque Country) and its
modification under mean sea-level rise scenario
Mireia Valle, Ángel Borja, Ibon Galparsoro,
Joxe M. Garmendia and Guillem Chust
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15. INTRODUCTION
Zostera noltii Hornem., 1832:
Widely distributed within the
intertidal zones of the
northeast Atlantic
Cantabrian Sea
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Vermaat et al., 1993; Phillippart et al.; 1995; Auby and Labourg, 1996; Laborda et al., 1997; Milchakova et al., 1999; Pérez Llorens, 2004

16. INTRODUCTION
Habitats Directive (92/43/EEC)
Water Framework Directive (2000/60/EC)
Fitoplancton Macroalgas
Bentos
Factores fisico-químicos (agua)
Garmendia et al., 2008
Peces
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17. INTRODUCTION
Global Warming
Mean Sea-Level Rise
60
St. Jean de Luz +49 cm
49 cm at the end of 21st 40
Santander
Bilbao
Sea level rise (cm)
Century
SRES A2 + MinMelt
SRES A1B + MaxMelt +29 cm
20
(Chust et al., 2010 ECSS 87:113-124)
0
-20
1940 1960 1980 2000 2020 2040 2060 2080 2100
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17

18. OBJECTIVES
1. Determine the main
environmental variables
explaining Zostera noltii
distribution, within the Oka
estuary
2. Evaluate the modification
of the present suitable
habitats under the
mentioned sea-level rise
scenario
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19. MATERIAL AND METHODS
Marginality
(0-1)
Ecological Niche
Factor Analysis
Specialization
BioMapper
(Hirzel et al. 2002)
Distribution of focal species Distribution of any EGV
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20. MATERIAL AND METHODS
Ecogeographical variables
Habitat
Sediment characteristics Suitability
Map
Ocean currents
Ecological
LiDAR derived Niche
topographic height Factor
Analysis
Presence data
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21. RESULTS
• Marginality 1.004:
Z. noltii’s habitat differs from Main EGV determining
the mean environmental species presence:
conditions over the study area
1. Mean grain size
• Specialization 6.209: 2. Redox potencial
restrictive in the range of 3. Sediment selection
conditions which it dwells.
Narrow ecological niche 4. Slope
5. Velocity of flood tide
• Cross-Validation
0.95 ± 0.15 6. % of gravel
Topographic
characteristic high
importance
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22. RESULTS
Actual HSM SLR Scenario HSM
Habitat
Suitability:
0-33 à
33-67 à
67-100à
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23. RESULTS
Surface percentage modification for Habitat Suitability (HS) areas:
Present SLR scenario
17.52% 6.84%
HS>50 HS>50
HS<50 HS<50
82.48% 93.16%
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24. DISCUSION AND PERPECTIVES
• Applicability of the method à
van der Heide et al., 2009; Fonseca and Kenoworthy, 1987;
Cabaço et al. 2009
• Rising sea level may adversely impact Z. noltii meadows. HS
under the SLR scenario show the vulnerability of this species,
which highlights the importance of the recovery tasks in the
remainders estuaries where the species is not present.
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25. FUTURE PERSPECTIVES
• Validation of the model à Bidasoa and Lea estuaries à
improvement of the accuracy of the model.
• SLR scenario à take into account changes in current patterns à
erode seagrass beds and create new areas for seagrass
colonization à increase the suitable areas for focal species.
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26. This research has been supported by:
Thank you very much for your attention!
Merci beaucoup!
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EURO-BASIN, www.euro-basin.eu Introduction to Statistical Modelling Tools for Habitat Models Development, 26-28th Oct 2011