limitations and solutions to the exchange of macrobenthos community data between scientists and czm...
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Limitations and solutions to the exchange ofLimitations and solutions to the exchange ofmacrobenthos community data macrobenthos community data
between scientists and CZM managersbetween scientists and CZM managersin the frame of human impact monitoring studiesin the frame of human impact monitoring studies
in SW Netherlandsin SW Netherlands
NIOO, Netherlands Institute of Ecology, Centre for Estuarine and Marine EcologyKorringaweg 7, P.O. Box 140, 4400 AC Yerseke, The Netherlands
Herman Hummel, Bart Schaub, Wil Sistermans,Mieke Rietveld, Rinus Markusse, Ko Verschuure,
Olaf van Hoesel, Tom Ysebaert, Dick van Oevelen,Peter Bot & Peter Herman
RIKZRIKZ, , the Dutch Governmental Institute of Coasts and Seathe Dutch Governmental Institute of Coasts and Sea, Den Haag, the Netherlands, Den Haag, the Netherlands
RIKZRIKZ
PresentationPresentation content: content:
1. W1. Why monitoring of macrobenthoshy monitoring of macrobenthos
2.2. PPresent-day problems regarding monitoringresent-day problems regarding monitoring
3. Problem 1: 3. Problem 1: Data stored but not analysedData stored but not analysed
6. Solution to problem 2:6. Solution to problem 2: Correspondence analysesCorrespondence analyses Adjustment of sampling strategyAdjustment of sampling strategy Example: GrevelingenExample: Grevelingen - impact abiotic factors - impact abiotic factors
4. Solution to problem 1:4. Solution to problem 1: Analyses of data - time series, ordinationAnalyses of data - time series, ordination Example: GrevelingenExample: Grevelingen - - major changesmajor changes, , not observed beforenot observed before
5. Problem 2: 5. Problem 2: Causal relationshipsCausal relationships Mismatch of data-seriesMismatch of data-series
Benthic organisms are suitable indicators for Benthic organisms are suitable indicators for changes in environmental quality, because of :changes in environmental quality, because of :- their sessile character- their sessile character- relatively long life-span- relatively long life-span
Thereby, benthic organismsThereby, benthic organisms- integrate environmental fluctuations and influences- integrate environmental fluctuations and influences- at a particular place over a relatively long time span- at a particular place over a relatively long time span
1. W1. Why monitoring of macrobenthoshy monitoring of macrobenthos
The aim of the long-term studies on benthosThe aim of the long-term studies on benthos is to obtainis to obtain insight ininsight in::- natural development of estuarine and coastal areas- natural development of estuarine and coastal areas- the anthropogenic influences in those areas- the anthropogenic influences in those areas
Such in order to help coastal managers:Such in order to help coastal managers:- saveguard natural resources- saveguard natural resources- allow optimal use of a system’s potentials- allow optimal use of a system’s potentials
1. W1. Why monitoring of macrobenthoshy monitoring of macrobenthos
As most monitoring programma’s this kind of continuous As most monitoring programma’s this kind of continuous long-term assessment (= many data) is perfect to detect:long-term assessment (= many data) is perfect to detect:- small deviations from a standard or norm- small deviations from a standard or norm- over a long-term- over a long-term- in a large area- in a large area
Year-to-year changes may not be significantYear-to-year changes may not be significant, but, butlonger series of data may reveal trendslonger series of data may reveal trends
1. W1. Why monitoring of macrobenthoshy monitoring of macrobenthos
In the Netherlands TWO major PROBLEMS arise in the In the Netherlands TWO major PROBLEMS arise in the present-day evaluation and use of the monitoring datapresent-day evaluation and use of the monitoring data
(mainly because of restricted funding).(mainly because of restricted funding).
2.2. PPresent-day problems regarding monitoringresent-day problems regarding monitoring
Basic data are stored by funding governmental agencies Basic data are stored by funding governmental agencies often often withoutwithout any further processing and any further processing and analysesanalyses..
By that the benefit of monitoring-programmes is debated:By that the benefit of monitoring-programmes is debated:- projects were costly- projects were costly- yet did not yield a proper end-product for the end-users- yet did not yield a proper end-product for the end-users(managers and the public in large) (managers and the public in large)
The The first problemfirst problem is: is:
3. Problem 1: data storage and analysis3. Problem 1: data storage and analysis
Use new techniques which allow us to analyse and visualise Use new techniques which allow us to analyse and visualise monitoring data in a limited time and at (relatively) limited costs:monitoring data in a limited time and at (relatively) limited costs:- advanced databases- advanced databases- statistical analyses (e.g. ordination, correspondence analyses)- statistical analyses (e.g. ordination, correspondence analyses)- internet communication (web-pages)- internet communication (web-pages)
Solution to problem 1: data storage and analysis
4. Solution to problem 1: data storage and analysis4. Solution to problem 1: data storage and analysis
The Grevelingen exampleThe Grevelingen example
Visualisation of a long-term (10-year) data-set showed forVisualisation of a long-term (10-year) data-set showed forthe brackish lake Grevelingenthe brackish lake Grevelingen
dramatic changes in macrobenthos species compositiondramatic changes in macrobenthos species composition--
4. Grevelingen example 1: data storage and analysis4. Grevelingen example 1: data storage and analysis
0 tot 2m diep2 tot 6m diep6 tot 45m diep
Grevelingen - Westelijk deel - plot 1Mytilus edulis
Campagnes
Naj
aar
1990
Voo
rjaar
199
1
Naj
aar
1991
Voo
rjaar
199
2
Naj
aar
1992
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199
3
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aar
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0
Dic
hth
eid
150
100
50
0
- without having been noticed before by managers.- dramatic changes in macrobenthos species composition- dramatic changes in macrobenthos species composition
0 tot 2m diep2 tot 6m diep6 tot 45m diep
Grevelingen - Westelijk deel - plot 1Cerastoderma edule
Campagnes
Naja
ar
1990
Voorja
ar
1991
Naja
ar
1991
Voorja
ar
1992
Naja
ar
1992
Voorja
ar
1993
Naja
ar
1993
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ar
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ar
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ar
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ar
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ar
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ar
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ar
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ar
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ar
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ar
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ar
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Naja
ar
1999
Bio
mas
sa m
g/m
25,000
4,500
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
0 tot 2m diep2 tot 6m diep6 tot 45m diep
Grevelingen - Westelijk deel - plot 1Hydrobia ulvae
Campagnes
Naj
aar
1990
Voo
rjaar
199
1
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aar
1991
Voo
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2
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aar
1992
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199
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rjaar
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0
Dic
hth
eid
1.500
1.000
500
0
0 tot 2m diep2 tot 6m diep6 tot 45m diep
Grevelingen - Westelijk deel - plot 1Littorina littorea
Campagnes
Naja
ar
1990
Voorjaar
1991
Naja
ar
1991
Voorjaar
1992
Naja
ar
1992
Voorjaar
1993
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ar
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ar
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ar
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ar
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ar
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ar
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ar
1999
Dic
hth
eid
35
30
25
20
15
10
5
0
0 tot 2m diep2 tot 6m diep6 tot 45m diep
Grevelingen - Westelijk deel - plot 1ACTINIARIA
Campagnes
Naja
ar
1990
Voorja
ar
1991
Naja
ar
1991
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ar
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ar
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hth
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0 tot 2m diep2 tot 6m diep6 tot 45m diep
Grevelingen - Westelijk deel - plot 1Heteromastus filiformis
Campagnes
Naja
ar
1990
Voorjaar
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Naja
ar
1991
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Naja
ar
1992
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ar
1993
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ar
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ar
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0 tot 2m diep2 tot 6m diep6 tot 45m diep
Grevelingen - Westelijk deel - plot 1Nereis succinea
Campagnes
Naj
aar
1990
Voo
rjaar
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4. Grevelingen example 1: data storage and analysis4. Grevelingen example 1: data storage and analysis
In case of “ so what ?! “ remarksIn case of “ so what ?! “ remarksit may be helpful to communicate on changes in commercial speciesit may be helpful to communicate on changes in commercial species
4. Grevelingen example 1: data storage and analysis4. Grevelingen example 1: data storage and analysis
0.1
1.0
10.0
100.0
1990 1991 1993 1994 1995 1996 1997 1998 1999 2000
Year
Nu
mb
ers
(n·m
-2)
Cerastoderma edule Mytilus edulis
Ostrea edulis Crassostrea
Next step is a statistical Next step is a statistical analysis of the data by analysis of the data by means of correspondence means of correspondence analysesanalyses
Showed influence of :Showed influence of :
- year- year- season- season- depth- depth
6-45 m 0-2 m
Spring
Autumn
4. Grevelingen example 1: data storage and analysis4. Grevelingen example 1: data storage and analysis
Next step is a statistical Next step is a statistical analysis of the data by analysis of the data by means of correspondence means of correspondence analysesanalyses
Showed influence of :Showed influence of :
- season- season- depth- depth
19901999
- year (independent of- year (independent of depth and season)depth and season)
33
11
556677
4422
88
4. Grevelingen example 1: data storage and analysis4. Grevelingen example 1: data storage and analysis
Thus a strong Thus a strong temporal evolutiontemporal evolution
4. Grevelingen example 1: data storage and analysis4. Grevelingen example 1: data storage and analysis
Our Our second problemsecond problem therefore is: therefore is:- coastal managers nowadays ask for causal relationships- coastal managers nowadays ask for causal relationships- relations to (changes in) environmental quality- relations to (changes in) environmental quality
The question arises: The question arises: What are the causes What are the causes of the changes of the changes ??
Whereas we have only information onWhereas we have only information onlarge-scale long-term processeslarge-scale long-term processes
5. Problem 2: Causal relationships5. Problem 2: Causal relationships
Solution to problem 2: causal relationshipsSolution to problem 2: causal relationships
More detailed information is needed on:More detailed information is needed on:- temporal and spatial dynamics in distribution of benthic- temporal and spatial dynamics in distribution of benthic populations (short-term / small scale)populations (short-term / small scale)- environmental variables- environmental variables
6. Solution to problem 2: causal relationships6. Solution to problem 2: causal relationships
Possible relationships, i.e. Possible relationships, i.e. causes causes for the changes in Grevelingen for the changes in Grevelingen ??
- sedimentation of organic matter and silt (esp- sedimentation of organic matter and silt (esp. . in the deeper parts)in the deeper parts) more sediment surface feeders, more wormsmore sediment surface feeders, more worms
- higher salinity, - higher salinity, disappearance of seagrass-bedsdisappearance of seagrass-beds disappearance associated faunadisappearance associated fauna
- - high concentrationhigh concentration of pollutants of pollutants decrease in numbers / biomass of sensitive speciesdecrease in numbers / biomass of sensitive species
- - lower light penetrationlower light penetration change of primary productionchange of primary production decrease of suspension feeders or grazersdecrease of suspension feeders or grazers
6. Grevelingen example 2: causal relationships6. Grevelingen example 2: causal relationships
1990-2002West
1990-2002East1982-2002
Dreischor
Benthos
environmental variables
Mismatch between benthos and environmental dataMismatch between benthos and environmental data
1972-1985data
6. Grevelingen example 2: causal relationships6. Grevelingen example 2: causal relationships
Canonical correspondentie analyse Macrobenthos Grevelingen (1990 - 2000)
As 1
As
2
Chla
O2
pH
PO4
POC
Sal
s-NO
ZS
Zicht
NH4
lTBT
Polwa
DebBr
Cre forOLIGOCap cap
Cor ins
Pol cil
Mic gryMys bid
Tha marHet fil
Exo nai
Pla tduPol lig
Pyg ele
Hyd ulv
Spi marCor gib
Sco arm
Har imb
Ner suc
Pol sp
Lep cin
Mal sp
Nep homCor bon Ner virNEMERTACTINI
Syl armNas ret
Mic mac
Har sp
Ven pulMal ful
Abr nit
Asc asp
Syl gra
Are mar
Kef cir
Cor sp
Lit lit
Pse pul
Cer sp
Ostre
Myt edu
Mya are
Ner div
Abr alb
Neo fig
Har imp
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
6. Grevelingen example 2: causal relationships6. Grevelingen example 2: causal relationships
Nereis succineaNereis succinea
Hydrobia ulvaeHydrobia ulvae
Relation with light penetration Relation with light penetration and freshwater inflow from and freshwater inflow from
polderspolders
R2 = 0.52p<0.05
0
10
20
30
40
50
60
70
0 10 20 30 40 50
Freshwater inflow(from polders: 10^6 m^3 per half-year)
Lig
ht
pen
etra
tio
n (
Sec
chi
dis
c: d
m)
20
30
40
50
60
1982 1988 1994 2000
Year
Lig
ht
pe
ne
tra
tio
n (
dm
)
6. Grevelingen example 2: causal relationships6. Grevelingen example 2: causal relationships
More freshwater from poldersMore freshwater from polders > Lower light penetration> Lower light penetration > Lower benthic> Lower benthic primary production primary production > Decrease of epiphytic grazers> Decrease of epiphytic grazers
Relation withRelation with TBT TBT
0
50
100
150
200
250
300
350
400
450
500
Jan-90
Jan-91
Jan-92
Jan-93
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
Jaar
TB
T (
ng
∙l-1
)
DN MD ZD Gem MTR (1 ng∙l-1)
6. Grevelingen example 2: causal relationships6. Grevelingen example 2: causal relationships
All these relationships need further examination and verificationAll these relationships need further examination and verification
Decrease TBTDecrease TBT
Still high Still high TBTTBT levels levels > imposex in molluscs> imposex in molluscs > decrease in numbers> decrease in numbers
ConclusionConclusion::
In addition to In addition to
a better use and co-ordination betweena better use and co-ordination betweenexisting long-term large-scale monitoring programmesexisting long-term large-scale monitoring programmes
a different type of integrated monitoring,a different type of integrated monitoring,at short-term and small-scale is desirableat short-term and small-scale is desirable
Thank youThank you