Spatial database model of ichthyofauna bioindicators of coastal

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Spatial database model of ichthyofauna bioindicators of coastal environment Jorge Brenner and José A.

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 OBI, Hamburg, Dec. 1, 2004

Contents • Objectives and motivation • Case of study • Conceptual approach • Data

Contents • Objectives and motivation • Case of study • Conceptual approach • Data model • Pre-implementation OBI, Hamburg, Dec. 1, 2004 2

Objectives At this moment: To develop an ichthyofauna indicator spatial data model Is fish

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. OBI, Hamburg, Dec. 1, 2004 3

Develop a bioindicator framework for: • Envision the complexity • Understand the role of

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 OBI, Hamburg, Dec. 1, 2004 Science based CZ/Ocean Management Reseach motivation 4

Study area Catalonian coastal area: • 848 km long coastline • 44 % of

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 OBI, Hamburg, Dec. 1, 2004 5

Conceptual approach System’s condition Ecological resilience B. Desired/sustainable state Probability of accomplish depends on

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 6

Functional diversity Functions Fish biodiversity k Lin Diversity groups y or em M Fish

Functional diversity Functions Fish biodiversity k Lin Diversity groups y or em M Fish functional diversity Ecosystem resilience Response - Diversity (interaction) buffer variability OBI, Hamburg, Dec. 1, 2004 7

The functional model Structure template Taxa occurrence 1. . . N Resilience algorithm Output

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 8

The data model: general Core groups Specific Dependent General System modules Objectives Management tools

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 External: Data + Applications Metadata G I S OBI, Hamburg, Dec. 1, 2004 9

The data model: conceptual Spatial domain structured Spatial relationships Resilience assessment Community * *

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 OBI, Hamburg, Dec. 1, 2004 10

Database implementation Fish species: CBR-CSIC + literature + Fishbase: 265 species in 93 families

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 OBI, Hamburg, Dec. 1, 2004 11

Species – environment Analysis: A. Mantel’s simple correlation between spp EOs and Independent variables.

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: NO 3 -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) OBI, Hamburg, Dec. 1, 2004 12

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

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 OBI, Hamburg, Dec. 1, 2004 13

On going work • Improve the coastal/marine biophysical model in order to develop species

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 OBI, Hamburg, Dec. 1, 2004 14

Thanks for their support to: – Marine Engineering Lab (LIM) – UPC – Fishbase

Thanks for their support to: – Marine Engineering Lab (LIM) – UPC – Fishbase Project (www. fishbase. org) – Agencia Catalana de l’Aigua (DMAi. H) - Gen. Cat THANK YOU Jorge Brenner +34 -934017392 jorge. [email protected] edu OBI, Hamburg, Dec. 1, 2004 15

Structure template Trophic level (1 … N) • Swimming mode LINK • Max weigth

Structure template Trophic level (1 … N) • Swimming mode 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 OBI, Hamburg, Dec. 1, 2004 • Local • Frequent * Group of parameters 16

Pressure - impact model Land originated P- I: Indicator Pressure attributes Impact factor Industry

Pressure - impact model Land originated P- I: 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 Possible impact species: Possible impact area: 66. 7 % spp (177) 32. 8 % EOs (854) 54. 5 % SCS (6) 10. 7 % hexagons (331) OBI, Hamburg, Dec. 1, 2004 17