Spatial database model of ichthyofauna bioindicators of coastal environment

Jorge Brenner and José A. JiménezCoastal Zone Management Group

Universitat Politècnica de Catalunya

Ocean Biodiversity Informatics Conference

Hamburg, Germany

December 1, 2004

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Contents

• Objectives and motivation

• Case of study

• Conceptual approach

• Data model

•Pre-implementation

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Objectives

To develop an ichthyofaunaindicator spatial data model

To develop an indicator framework for assessing theenvironmental condition of the Calatonian coast.

At this moment:

In a broader scope:

Is fish diversity a good/usefulindicator of the coastal environment?

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Reseach motivation

Develop a bioindicator framework for:• Envision the complexity• Understand the role of biodiversity function• Assess the system ecological condition• Identify conservation priorities• Develop a monitoring/management tool

Sci

ence

bas

ed C

Z/O

cean

Man

agem

ent

Sci

ence

bas

ed C

Z/O

cean

Man

agem

ent

Local issues:• Several legal motivations (EU Water Dir., 2006)• Other community based bioindicators• Address coastal resources state• Mitigate human competition for coastalresources

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Study area

Catalonian coastal area: • 848 km long coastline• 44 % of total population (2.8 mill.) living in the coastal municipalities• One of the largest ports in the Mediterranean• A global tourist coastal destination

Catalonia

Continental shelf

Mediterranean SeaEbro Riverdelta

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Conceptual approach

System’scondition

B. Desired/sustainable state

A. Unknown transitional state

Probability of accomplish depends on system’s stability, given by:

• Structure• Function

- Multiscale – accross scales -

Eco

log

ical

res

ilie

nce

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Functional diversity

ResponseLi

nk

Mem

ory

Diversitygroups

Fish functionaldiversity

Ecosystemresilience

Fish biodiversity

- Diversity (interaction) buffer variability -- Diversity (interaction) buffer variability -

Functions

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The functional model

- Ecological resilience: distribution of functional groups at accross scales -- Ecological resilience: distribution of functional groups at accross scales -

Link

Response

Memory

Criteria Criteria Resilience

Functionaldiversitygroups

Co

mm

un

ity

un

it (

Co

mm

un

ity

un

it (

1 .

. .

N)

1 .

. .

N)

Taxaoccurrence

1...N

OutputInput Structuretemplate

Resiliencealgorithm

GIS

sub

-mo

del

s

Fis

h

• Marine communities• Pressure – impacts• Vulnerability

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The data model: generalS

y s

t e

m

m o

d u

l e

sS

y s

t e

m

m o

d u

l e

s

Independent

Gen

eral

Spe

cific

Dependent

Independent

Fish diversityBio-physical

Socio-economic

M e t a d a t a

Objectives Core groupsManagement

tools

Indicator (s):

• Condition

• Management

Data + ApplicationsExternal:

G I S

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The data model: conceptualS

p a

t i

a l

r

e l

a t

i o

n s

h i

p s

S p

a t

i a

l

r e

l a

t i

o n

s h

i p

s

ImpactVulnerability

Community

Functionalgroup

1..*Pressure

EO

TaxonomicEcological

1..*

*

*

1..*Fish diversityFish diversity

Resilience assessmentResilience assessment Spatial domainstructured

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Database implementation

480

850

2542

158 105 164

1904-1980 1981-1990 1991-1995 1996-2000

Eos

Spp

Fish species:

CBR-CSIC + literature + Fishbase:

265 species in 93 families46 species with some degree of concern (30 families)93 maximum EO in sample point2598 total EOs in analysis area

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Species – environment

Analysis:

A. Mantel’s simple correlation between spp EOs andIndependent variables.

Conceptual models (131 spp @ 999 permutations):

A) Pressure indexesB) Bio-physico-chemical parametersC) Hybrid model

0.174 p=0.001

M = Indexes -> Parameters species

0.079p=0.004

-0.0713p=0.015

B. RDA analysis with automatic selectionamong “all parameters:” 15 % of variance.

Examples of species found related to:

NO3-M:•Cetorhinus maximus (Cetorhinidae; very low)•Syngnathus phlegon (Syngnathidae; medium)•Helicolenus d. Dactylopterus (Sebastidae; ?)•Alosa fallax nilotica (Clupeidae; medium)

FC-M:•Chelidonichthys lucernus (Triglidae; low)•Callionymus risso (Callionymidae; high)•Scomber japonicus (Scombridae; medium)•Spondyliosoma cantharus (Sparidae; medium)•Polyacanthonotus rissoanu (Notacanthidae; ?)•Pomatoschistus microps (Gobiidae; high)

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Final ideas

• Structure controlled fish species can represent specific functional groups at macroecology level

• Ecological resilience can be a reasonable proxy of the ecological condition at multiple scales of the marine environment

• The design (model) of species behaviours is directly influenced by data depth, breath and quality and determines the implementation of the data conceptual model

• Species presence only data relation to environmental factors and coastal originated human impacts is scale dependent of the biophysical model

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On going work

• Improve the coastal/marine biophysical model in order to develop species distribution models

• Identify the functional research clusters based on specific structural criteria

• Assess the coastal/marine probable resilience at community level

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Thanks for their support to:

– Marine Engineering Lab (LIM) – UPC– Fishbase Project (www.fishbase.org)– Agencia Catalana de l’Aigua (DMAiH) - GenCat

THANK YOUTHANK YOU

Jorge Brenner

+34-934017392

jorge.brenner@upc.edu

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Structure template

Tro

ph

ic le

vel

(1

… N

) LINK

• Swimming mode

• Max weigth• TL• Depth range• Environment

MEMORY

• Reproduction type *• Growth *• Swimming mode• Feeding habit• TL

RESPONSE

• Reproduction type *• Growth *• Feeding habit• Depth range

Occurrence type

* Group of parameters

• Local• Frequent

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Pressure - impact model

Land originated P- I: Possible impact area:

32.8 % EOs (854)

10.7 % hexagons (331)

Possible impact species:

66.7 % spp (177)

54.5 % SCS (6)

Water pro pertiesIndus tryAquacultureTourismWaste discharge tubesP ortsCU P 2001

EOs012 - 34 - 2123 - 3739 - 93

Land

Indicator Pressure attributes Impact factor

Industry Nuclear plant / other 1-1000 m

Aquaculture Surface / type / organism / intensity

1000 m

Coastal Tourism

Beach length >= 100 m / high use / urban

Beach length

Submarine waste outfalls

Diameter / long / category / status

Outfall length

Ports Type / surface class 2000 m

Coastal Urban

Pressure

Municipal urban surface / municipality

coastal length

Coastal length