Jiří Jarkovský - Masarykova univerzita · 2010-04-27 · Computational biology: Environmental data analysis & modeling © RECETOX & IBA, MU Life is risk Evaluation of environmental

© RECETOX & IBA, Masaryk University

Environmental data analysis & modeling: environmental and

human risks

Environmental data analysis & modeling: environmental and

human risks

JiJiřříí

JarkovskýJarkovský

INVESTICE DO ROZVOJE VZDĚLÁVÁNÍ

Computational biology: Environmental data analysis & modeling © RECETOX & IBA, MU

Life and environmentLife and environment

Mutual interaction of life and environment

How does it work ?


Life is riskLife is risk

Evaluation of environmental and human risk


What are we doing and howWhat are we doing and how

Evaluation of environmental and human risks

Many fields of research for computational biologists

Analysis and modeling of environmental data

Statistics

Deterministic modelling

Data mining

GIS

Environmental informatics for data storage, processing, visualization and communication


EcoRA: Ecological risk assessment as covering concept for

environmental data analysis & modeling


ECORA AND ITS ECORA AND ITS BASIC BASIC COMPONENTSCOMPONENTS

Management


EcologicalEcological risk risk assessmentassessment ((EcoRAEcoRA): ): keykey methodicalmethodical stepssteps

Risk characterization

Interpretation & Management

Multicomponentexposure

assessmentBiological

effectsassessment

Problem

formulation Hazard identification

COMMUNICATION OF RESULTSCOMMUNICATION OF RESULTS

COLLECTION COLLECTION & &

PROCESSING PROCESSING OF DATAOF DATA

VALIDATION VALIDATION OF RESULTSOF RESULTS


Data analysis and iData analysis and informaticsnformatics: : indispensableindispensable part part ofof eacheach methodicalmethodical step step

RISK CHARACTERIZATION

CONCEPTUAL MODEL & SCENARIO

EXPOSURE ASSESSMENT

BIOLOGICAL EFFECTS

Bio-testsBioindicators Biomonitoring

Expert judgement

Sampling Modelling

Biota

Prospective evaluation

Problem definition Hazard identification

Uncertainty analysis

Data gathering Data aggregation

Information services

Model of area of interest

Experimental design

Data processing Modelling

Multivariate analyses

Benchmarking Probability estimation

Optimization &

Processing in information

systems &

CommunicationActual / urgent situation

Retrospective problem


ProblemProblem definitiondefinition == complex information complex information survesurveyy

EXPOSURE

COMPARTMENTS ACCORDING TO POTENTIAL RISK

Environmental characteristics

Source

of contamination

Compounds of

interest

Pilot

(screening) test

Development of exact Development of exact situation plan situation plan inteinteggrates rates also exposure assessment also exposure assessment ((at least at screening levelat least at screening level))


Assessment scenario and basic principle: Assessment scenario and basic principle: „„Where is the problemWhere is the problem““

Stre

ssor

(s)

Scenario is in direct relation to estimated (predicted) exposure pathways: all further analyses follow from this starting point

Primary exposure

Secondary exposure

Time

Air

Soil

Sedi

men

tW

ater

Air

Soil

Sedi

men

tW

ater

Further tests

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EndpointEndpoint selectionselection mustmust followfollow strictstrict rulesrules

Ecological relevance

Susceptibility to

exposure

Reprezentativeness

Environmental &

societal importa

nce

Unambiguous definition

Accessibility

for measurement

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Stressor

• Population• Sub-cell systems

• Cell systems

• Tissue

tests

• Organisms • Ecosystems

• Communities

Bio-tests Bio-indication

EndpointEndpoint selectionselection: : therethere are are twotwo basic basic strategiesstrategies

?

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Endpoint selection: there are two basic strategiesEndpoint selection: there are two basic strategies

Evaluation of real ecosystems

Assessm

ent on

model system

s

Risk characterization

Problem formulation

Mechanisms of effects Standardized approach

Spec

ifici

ty

Reprezentativeness

Ecosystem-related interpretation

Model systems, biomarkers /BIO-TESTS/

Monitoring of real ecosystems

/BIOINDICATION/

Biological examination provides always stochastic („uncertain“) data

Both approaches must be combined in optimal way

The analyses are basically multivariate


Analog modelling for Analog modelling for ecologicalecological risk risk assessmentassessment

A) Calibration data set B) Environmental gradient

Contaminated sites

Reference (clean) sites

X1 X2

X3

...... Xp X1 X2

X3

...... Xp

X1 X2

X3

...... Xp

New problem

Searching for similarities

X1 X2

X3

...... Xp

New problem Searching

for similarities

Gradient calibration

Increasing contamination

Increasing

disturbance

RISK ASSESSMENT SCENARIORISK ASSESSMENT SCENARIO




Stochastic processing of data: key methodical toolStochastic processing of data: key methodical tool

Stochastic

model evaluation

Concentration of stressorMATC

X ?

MATCX ?

Prob

abili

ty d

ensi

ty fu

nctio

n

Distribution 1: Concentration of stressor in environmentDistribution 2: Concentration of stressor in relation to effectsGiven probability of significant negative influence (events)Maximum accepted toxicant concentration (threshold)

In final risk characterization are chemical and biological data evaluated in direct contrast

Dichotomous

evaluation

HQ = AEC

TEC

Hazard quotient

Actual environmental concentration

= Toxicological effect concentration


There are many demands on information service There are many demands on information service from from EcoRAEcoRA

COMMUNICATION OF RESULTSCOMMUNICATION OF RESULTS

DATA INFORMATION COMMUNICATION

„„INFLUENTIAL FACTORINFLUENTIAL FACTOR““ „„EXPOSUREEXPOSURE““ „„RECEPTORRECEPTOR““

TARGET

Public

Experts

Managers

CHARACTERIZED CHARACTERIZED RISKRISK

ExactExact methodologymethodology

Significant & Significant & verified resultsverified results

Minimized Minimized uncertaintiesuncertainties

Quantified Quantified riskrisk Cost Cost

analysesanalyses

Clear Clear conclusionsconclusions

Value Value communicationcommunication

EffectivenessEffectiveness


ECORA AND ITS ECORA AND ITS BASIC BASIC COMPONENTSCOMPONENTS

Management

DatabasesGIS

Statistics & modeling

Data mining


Data mining

GISInformation systems and

portals


Data mining


Key topics of our research


What are we doing?What are we doing?

Distribution and concentration levels of harmful chemicalsBiodiversity of organisms and their relation to environmentHuman risk assessment

Environmental data analysis and modelingVisualization and communication of environmental data

In environmental matricesSoilSedimentsWaterAir

Many open fields of research


SoilSoil

Databases of soil contaminationConcentration levels of harmful chemicals

Spatial modeling and prediction

Input for complex models

Open areas for spatial modeling and complex model development


WaterWater

National database of monitoring and biomonitoring of surface waters

Evaluation of ecological status of rivers (based on biodiversity and community composition)

Intercalibration of biomonitoring results among European countries

Spatial modeling in river networks

Time series analysis

Priority compounds

Ecological state

Macrophytes

Fytobenthos

Benthic macroinvertebrates

Fishes

Supporting parameters

Hydromorphology

Chemical and physics parameters

Mul

timet

ricev

alua

tion

Norms

5 levels

2 levels

Specific pollutants

Open areas for spatial modeling, intercalibration and time series analysis


AirAir

Monitoring of harmful chemicals in air as input for status assessment and modeling

Trajectories

Identification of pollution sources

Input for complex modeling

Open areas for pollution source identification


Biodiversity in contemporary biology Biodiversity in contemporary biology and environmental sciencesand environmental sciences

Biodiversity is one of the leading concepts in biology, that

is defined at many levels

…

GenesIndividualsPopulations

SpeciesCommunitiesEcosystems

… and

very

suitable

for bioindication

Effects

of

chronic

exposureImpact

of

low

dose

exposures

Impact

on relationships

in communities

Effects

made

in past

Biodiversity bears

very

useful

and

lasting

information, even when

„short-term“

methods

fail

(biotests, chemical

analyses)


Cell

Organism

Community

BiodiversityBiodiversity as as endend--point in point in environmentalenvironmental studiesstudies

Population

Biodiversity

is

one

ofthe

most complex

measures

/“integrating

endpoint“/

Time fluctuations

Space

heterogeneity

Natural

stress factors

Open areas for methodological development and application for biomonitoring data


GISGIS

GIS technology is increasingly being used in the EcoRA process

Manipulation, analysis, and graphic presentation of the risk data can be done within a GIS system

As this data contains an associated information on the location, their spatial interrelationships can be determined

Risk can be identified by scientists using GIS to analyze field survey data, satellite image, aerial photos...

GIS is a suitable tool for each phase of the EcoRA process

Geographic

Information

System

(GIS) in the EcoRA

process


Visualization and communication of environmental dataVisualization and communication of environmental data

The results of environmental data analysis have to be communicated to public and/or other scientists

Open areas for development of information systems and environmental portals.


Complex environmental modelingComplex environmental modeling

Data from various matrices and monitoring approaches can be combined in complex models of environmental status and pollution distribution.

Open areas for methodological work and complex models development.


Rozvoj studijního oboru „Matematická

biologie“

PřF MU Brno je finančně

podporován prostředky projektu

ESF č. CZ.1.07/2.2.00/07.0318 „Víceoborová inovace studia matematická

biologie“

a státním rozpočtem České

republiky

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Jiří Jarkovský - Masarykova univerzita · 2010-04-27 · Computational biology: Environmental data analysis & modeling © RECETOX & IBA, MU Life is risk Evaluation of environmental