Statistické hodnocení biodiverzity
Case study I: EcoRA
Jiří Jarkovský
Biodiversity and its
informative value in evaluation
of localities under
anthropogenic stress
Dušek L. , Jarkovský J. , Zahrádková S. , Brabec K. ,
Hodovský J. , Gelnar M. , Anděl P
Biodiversity as end-point of ecological studies
Biodiversity is one of
the most complex measures
/“integrating endpoint“/
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Community
Population
Organism
Natural stress
factors
Cell
Time fluctuations
Space heterogeneity
Are we able to analyse and communicate biodiversity ?
As aesthetic nature
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As parametrically standardized end-point
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Species-abundance profile
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No of individuals
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4
1
2
3
Model level
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Species abundance
profile
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Informative level
2
1
4
5
6
7
8
9
3
10 11 12 13
Species rank
Niche-oriented
modelling
Diversity indices
Descriptive level
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Indicative species
Species richness
Dominance
No. of individuals
Stress influence and diversity structure of biological communities
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1
2 3 4
5 6
7 8 9 10 11 12 13
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3
4
5
5
6
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Species rank
1 2 3 4 5 6 7 8 9 10 11 12 13
1 2 3 4 5 6 7 8 9 10 11 12 13
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2
3
4
5
6
7
8
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Species abundance profiles description – many
indices measuring different aspects of community
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AIMS OF THE STUDY
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Biodiversity is frequently reported as too heterogeneous and complex
measure for exact risk assessment studies
Analyses of the whole communities are
rather inconclusive due to heterogeneous
structure
Community
?
Are we able to find sufficiently sensitive
parts (BIOINDICATIVE COMPONENTS) in
different biological communities ?
Population
Are we able to statistically analyse
biodiversity of such relatively small
samples ?
Methodology
•
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Stratification of communities
– problem: strongly decreases sample size
• Analysis of species abundance profile
– stochastic Q statistic
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10
20
0
10
30
0
20
10
0
Q statistic
• measure of species abundace profile slope
• related to conventional diversity indices
(Shannon etc.)
• produce distribution –> statistical analysis
EXAMPLE I. Multicellular parasites of fresh water fish
(case studies on chub (Leuciscus cephalus L.)
Water exposed community at
the top of trophic chain
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Biodiversity
evaluation
Very complex taxonomic
structure
Community of practical
importance
Ecosystem – relevant
interpretation
Ectoparasites
Water exposed
community
Endoparasites
Gelnar et al., Parasitologia, 1997
Dušek et al, Int. J. Parasitol., 1998
EXAMPLE I. Comparative study of two and five Morava river sites
Morava river catchment area
(tributary of Danube)
Area - 24109,6 km2,
length - 353,1 km
Chemical
industry
Power plants
Agglomeration,
industry
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EXAMPLE I. Chub parasites : comparative study of two and five
Morava river sites
Two sites: A: Control
B: Organic pollution
A
B
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Five differently polluted sites I - V Heavy
metals + POPs
EXAMPLE I. Comparison of two sites under anthropogenic
stress (A: control; B: polluted)
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Community
Endoparasites
Ectoparasites
MONOGENEA
Other
species
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GUILDS
GENERA
Gyrodactylus
Dactylogyrus
Paradiplozoon
Gills, Fins Skin
Life strategy
GENERALIST
SPECIALIST
Q statistics
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12
8
p = 0.185
4
0
A
B
EXAMPLE I. Comparison of two sites under anthropogenic
stress (A: control; B: polluted)
Interpretation of biodiversity data
?
Fish
STRESS
?
Parasites
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EXAMPLE I. Comparison of two sites A - B
MONOGENEA
GUILDS
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p = 0.785
Gills, Fins Skin
GENERA
Life strategy (generalist vs. specialist): Q
Gyrodactylus
Dactylogyrus
Paradiplozoon
p = 0.412
Generalists
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p < 0.01
20
16
9
12
6
8
3
0
Specialists
4
A
B
0
A
B
EXAMPLE I. Comparison of two sites A - B
Specialists
Control site (A)
Generalists
Polluted site (B)
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EXAMPLE I. Large scale study on sites I-V: life strategy of
parasites as an important statifying factor (1997)
The whole community
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16
16
12
8
4
0
Generalists
p = 0.682
I
II III IV V
p < 0.010
Specialists
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12
12
8
8
4
4
0
I
II III IV V
0
I
II III IV V
INCREASED ANTHROPOGENIC LOAD I = II < III < IV << V
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EXAMPLE II. Lichen community under imission load
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Air exposed relatively
sensitive community
Limited in sample size and
in species richness
Bio-indication with already
standardized methodology
Ecosystem – relevant
interretation
Biodiversity
evaluation
Air exposed
community
EXAMPLE II. Lichen community under imission load
(150 sites, 32 species)
Acid imissions, dust,
NOx, As, Fe, Mn
SO2
A large scale survey of 150 sites
Four imission load categories
Load I. Low (< 50 mg SO2 / m3)
Load II. Medium (50 - 70 mg SO2 / m3)
Load III. Increased (70 - 100 mg SO2 / m3)
Class IV. Heavy
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EXAMPLE II. Community of lichen (150 site, 32 species)
Community
12.0
9.0
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Q statistic
*
(p = 0.041)
Morphology
Crustose, foliose,
fruticose
6.0
*
3.0
Substrate
Fraxinus, Tilia, Quercus,
Acer, Aesculus
0.0
I
II
III IV
Niche preference
Eutrophic conditions
Non-eutrophic conditions
INCREASING IMISSION LOAD
EXAMPLE II. Community of lichen (150 site, 32 species)
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The whole community
12.0
9.0
Q statistic
*
p = 0.682
*
3.0
I
Non-eutrophic
conditions
(p = 0.041)
12.0
6.0
0.0
Eutrophic conditions
II III IV
p = 0.785
12.0
9.0
9.0
6.0
6.0
3.0
3.0
0.0
I
II
III
IV
0.0
p < 0.010
I
INCREASING IMISSION LOAD I < II < III < IV
II
III IV
Conclusions I
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Prospective
Retrospectiv
e
BIOINDICATION OF
STRESS
?
- ecologically relevant interpretation
- indication of complex changes
- sensitive, early warning
- indicator with long-term memory
IN REAL ECOSYSTEMS
- ecosystem health
- ecosystem stability
Conclusions II
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Community must be stratified
in order to reach environmentally reasonable units
(sensitivity, mechanisms of influence, exposure pathways)
Stratification
criteria
Taxonomy
Niche type
Evolution
Trophic level
Substrate/food
Metabolism
Physiology
Reproduction
Life cycle
Morphology
Growth rate
Size
BIOINDICATIVE COMPONENTS ARE NECESSARY FOR EFFECTIVE
MONITORING PLANS OR ECOLOGICAL RISK ASSESSMENT STUDIES
Conclusions III
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•
•
•
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Measure of diversity could be computed and statistically analyzed
These measures could be related to anthropogenic load of ecosystems
and thus utilized in risk assessment
General pattern of diversity measures under stress conditions is similar
even in communities of very different organisms
Accuracy of analysis is improved when meaningful subsets of whole
community are used; definition of relevant groups is crucial for utilization
of biodiversity data in risk assessment
Diversity measures are parameterized and suitable for risk and
environmental quality assessment, i.e. also for
macrozoobenthos data.
Acknowledgements
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•
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Milan Gelnar (fish parasites)
Petr Anděl (lichen)
Miroslav Machala (environmental data)
•
Ivan Holoubek
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