Transcript Spatial database model of ichthyofauna bioindicators of

Spatial database model of ichthyofauna
bioindicators of coastal environment
Jorge Brenner and José A. Jiménez
Coastal Zone Management Group
Universitat Politècnica de Catalunya
Ocean Biodiversity Informatics Conference
Hamburg, Germany
December 1, 2004
Contents
• Objectives and motivation
• Case of study
• Conceptual approach
• Data model
•Pre-implementation
OBI, Hamburg, Dec. 1, 2004
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Objectives
At this moment:
To develop an ichthyofauna
indicator spatial data model
Is fish diversity a good/useful
indicator of the coastal environment?
In a broader scope:
To develop an indicator framework for assessing the
environmental condition of the Calatonian coast.
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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
Local issues:
• Several legal motivations (EU Water Dir., 2006)
• Other community based bioindicators
• Address coastal resources state
• Mitigate human competition for coastal
resources
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Science based CZ/Ocean Management
Reseach motivation
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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
Ebro River
delta
Mediterranean Sea
Continental shelf
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Conceptual approach
System’s
condition
Ecological resilience
B. Desired/sustainable state
Probability of accomplish
depends on system’s
stability, given by:
• Structure
• Function
A. Unknown transitional state
- Multiscale – accross scales OBI, Hamburg, Dec. 1, 2004
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Functional diversity
Functions
Fish biodiversity
Fish functional
diversity
Diversity
groups
Ecosystem
resilience
Response
- Diversity (interaction) buffer variability OBI, Hamburg, Dec. 1, 2004
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The functional model
Structure
template
Taxa
occurrence
1
.
.
.
N
Resilience
algorithm
Output
Criteria
Resilience
Link
Criteria
Response
Memory
GIS
sub-models
Fish
Community unit (1 . . . N)
Input
Functional
diversity
groups
• Marine communities
• Pressure – impacts
• Vulnerability
- Ecological resilience: distribution of functional groups at accross scales OBI, Hamburg, Dec. 1, 2004
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The data model: general
Core groups
Specific
Dependent
General
System modules
Objectives
Management
tools
Fish diversity
Indicator (s):
Bio-physical
Socio-economic
• Condition
• Management
Independent
Independent
External: Data + Applications
Metadata
G I S
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The data model: conceptual
Spatial domain
structured
Spatial relationships
Resilience assessment
Community
*
*
Fish diversity
1..*
Functional
group
Vulnerability
Impact
EO
1..*
Pressure
1..*
Ecological
Taxonomic
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Database implementation
Fish species:
CBR-CSIC + literature + Fishbase:
265 species in 93 families
46 species with some degree of concern (30 families)
93 maximum EO in sample point
2598 total EOs in analysis area
2542
Eos
Spp
850
480
1904-1980
158
105
164
1981-1990
1991-1995
1996-2000
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Species – environment
Analysis:
A. Mantel’s simple correlation between spp EOs and
Independent variables.
Conceptual models (131 spp @ 999 permutations):
A)
B)
C)
Pressure indexes
Bio-physico-chemical parameters
Hybrid model
•
0.174
p=0.001
M = Indexes -> Parameters
-0.0713
p=0.015
species
0.079
p=0.004
B. RDA analysis with automatic selection
among “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 YOU
Jorge Brenner
+34-934017392
[email protected]
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Structure template
• Swimming mode
Trophic level (1 … N)
LINK
• 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
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• Local
• Frequent
* Group of parameters
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Pressure - impact model
Land originated P- I:
Indicator
Pressure attributes
Impact
factor
Industry
Nuclear plant / other
1-1000 m
Possible impact species:
Possible impact area:
66.7 % spp (177)
32.8 % EOs (854)
54.5 % SCS (6)
10.7 % hexagons (331)
Land
EOs
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
0
1
2-3
4 - 21
23 - 37
39 - 93
CUP 2001
Ports
Waste discharge tubes
Tourism
Aquaculture
Industry
Water properties
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