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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 igalparsoro@azti.es

Pasaia

26-28 October 2011 Introduction to Statistical Modelling Tools for Habitat Models Development, 26-28th Oct 2011 EURO-BASIN, www.euro-basin.eu

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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

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This study was funded by the Basque government: Department of Environment and Regional Planning Department of Agriculture, Fishing and Alimentation

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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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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