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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)
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1
Predicting suitable habitat for the European lobster (Homarus gammarus), on the Basque
continental shelf (Bay of Biscay), using Ecological-Niche Factor Analysis
Ibon Galparsoro
EURO-BASIN Training Workshop on
Introduction to statistical modelling tools,
for habitat models development
AZTI-Tecnalia; Marine Research Division [email protected]
Pasaia
26-28 October 2011 Introduction to Statistical Modelling Tools for Habitat Models Development, 26-28th Oct 2011 EURO-BASIN, www.euro-basin.eu
© AZTI-Tecnalia 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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! (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.
Objetives
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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
Study area and lobster sampling estrategy
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SeaBat 7125 and SeaBat 8125 MBES
1 m resolution seafloor DEM
Multibeam echosounder data
Seafloor morphologic feature extract ion 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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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
Wave flux over the seafloor
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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’
σG
µG
Frequency
Altitude
σG
µG
σGσG
µGµG
Frequency
Altitude
GlobalSpecies
σS
µS
GlobalSpecies
σS
GlobalSpeciesGlobalSpecies
σSσS
µS
G
SG mmMδ96.1
〉−〈=
S
GS∂
∂=
Ecological-Niche Factor Analysis and habitat suitability map production
Marginality (M) represents the ecological distance
between the species optimum and the mean habitat
within the reference area
Multi-scale analysis
Specialisation (S) is defined as the ratio of the
standard deviation of the global distribution ( ), to
that of the focal species ( )
G∂
S∂
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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
Results
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Best results were obtained the
maximum resolution analysis
Results
Scale (pixel) Marginality Specialisation
3x3 0.983 2.418 9x9 1.196 2.138
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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Environmental variables
Overall area Presence areas
Maximum Minimum Mean Standard Deviation Maximum Minimum Mean Standard
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
Results
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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Results
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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.
Discusion
© AZTI-Tecnalia 13
This study was funded by the Basque government: Department of Environment and Regional Planning Department of Agriculture, Fishing and Alimentation
© AZTI-Tecnalia 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
© AZTI-Tecnalia 15
Zostera noltii Hornem., 1832: Widely distributed within the intertidal zones of the northeast Atlantic
Vermaat et al., 1993; Phillippart et al.; 1995; Auby and Labourg, 1996; Laborda et al., 1997; Milchakova et al., 1999; Pérez Llorens, 2004
INTRODUCTION
Cantabrian Sea
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Habitats Directive (92/43/EEC)
Fitoplancton Macroalgas
Bentos
Peces
Factores fisico-químicos (agua)
Water Framework Directive (2000/60/EC)
INTRODUCTION
Garmendia et al., 2008
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Global Warming
Mean Sea-Level Rise
49 cm at the end of 21st Century
(Chust et al., 2010 ECSS 87:113-124)
INTRODUCTION
Year1940 1960 1980 2000 2020 2040 2060 2080 2100
Sea
leve
l ris
e (c
m)
-20
0
20
40
60
St. Jean de Luz Santander Bilbao SRES A2 + MinMelt SRES A1B + MaxMelt
+49 cm
+29 cm
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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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BioMapper (Hirzel et al. 2002)
MATERIAL AND METHODS
Marginality (0-1)
Distribution of focal species Distribution of any EGV
Specialization
Ecological Niche Factor Analysis
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Habitat Suitability
Map
Ecological Niche Factor Analysis
Presence data
Ecogeographical variables
Sediment characteristics
LiDAR derived topographic height
Ocean currents
MATERIAL AND METHODS
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• Marginality 1.004: Z. noltii’s habitat differs from the mean environmental conditions over the study area
• Specialization 6.209:
restrictive in the range of conditions which it dwells. Narrow ecological niche
• Cross-Validation 0.95 ± 0.15
RESULTS
Main EGV determining species presence: 1. Mean grain size 2. Redox potencial 3. Sediment selection 4. Slope 5. Velocity of flood tide 6. % of gravel Topographic characteristic high importance
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RESULTS Actual HSM SLR Scenario HSM
Habitat Suitability: 0-33 à 33-67 à 67-100à
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RESULTS
Surface percentage modification for Habitat Suitability (HS) areas:
82.48%
17.52%
93.16%
6.84% Present SLR scenario
HS<50
HS>50 HS>50
HS<50
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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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• 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.
FUTURE PERSPECTIVES
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Thank you very much for your attention! Merci beaucoup!
This research has been supported by:
Introduction to Statistical Modelling Tools for Habitat Models Development, 26-28th Oct 2011 EURO-BASIN, www.euro-basin.eu