03 Lyche Solheim Lake Assessment
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Conference, date, place
Lakes assessment:suitability of BQEs along gradients of
eutrophication and hydromorphological pressures
Anne Lyche Solheim, NIVAPhytoplankton experts: Laurence Carvalho2, Geoff Phillips3, Ute Mischke4, GiuseppeMorabito5, Gbor Borics6, Birger Skjelbred1, Marko Jrvinen7, Stina Drakare8, Tiina Noges9,Peeter Noges9, Stephen Thackeray2, Claire McDonald2, Christophe Laplace-Treyture18,
Macrophyte experts: Agnieszka Kolada10, Martin Sndergaard11, Nigel Wilby12, SeppoHellsten7, Bernard Dudley2, Fraucke Ecke8, Marit Mjelde1, Vincent Bertrin18
Macroinvertebrate experts: Martin Pusch4, Ralph Clarke13, Ken Irvine14,15, Angelo
Solimini16, Jukka Aroviita7, Oliver Miler4, Elaine McGoff8, Jrgen Bhmer17,
Fish experts: Erik Jeppesen11, Torben L. Lauridsen11, Christine Argillier18, StephaniePedron18,20, Simon Causs18, Murielle Gevrey18, Sandra Brucet19, Kerstin Holmgren8,
Matthias Emmrich4, Thomas Mehner4, Julien De Bortoli18, Ian Winfield2, Pietro Volta5, AtleRustadbakken1, Martti Rask21,
Cross-BQE Statisticians: Jannicke Moe1 , Mike Dunbar2
Generalists and coordinators: Sandra Poikane19 , Christian Feld22, Daniel Hering22
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WISER final conference, 25-26 Jan 2012, Tallin, Estonia
Outline
Objectives
Datasets and methodology Main results for each BQE Cross BQE comparisons Key messages and recommendations Future challenges
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WISER final conference, 25-26 Jan 2012, Tallin, Estonia
Objectives for WISER work on Lakes
identify and develop suitable biological indicators /metrics for assessing status of European lakes
according to WFD requirements
propose common metrics sensitive to eutrophicationand hydro-morphological pressures, to support theWFD intercalibration process
quantify uncertainty for each biological qualityelement as a basis for recommendations on WFDmonitoring design
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Datasetsbiggest in Europe and the world?
Existing data from 21 countries
with harmonised taxonomy
New data from 26-51 lakes25 lakes sampled for all BQEs in 2009
(and 2010)
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
BQE # Water-bodies
Phytoplankton 6 927*
Macrophytes 1 575
Macroinvertebrates 227
Fish
Abio&cpressuredata
forallwaterbodies
1 632
*taxonomic data available from ca. 1500 water bodies
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Methodology
Metric development/testing:
Statistical data analyses
Multivariate methods(CCA & others)
Univariate regressions(linear & non-linear)
Uncertainty analyses:
Sampling of each BQE accordingto standardised methodology
Statistically stratified samplingdesign used for all BQEs
Using WISERBUGS software toquantify uncertainty components
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Phytoplankton main results and impacts
Results
New common metricdeveloped for taxonomic
composition: Phytoplankton
Trophic Index (PTI)
New bloom metric developed:Cyanobacteria biovolume
Low spatial uncertainty,temporal uncertainty more
important
Impacts
PTI metric used in IC in CentralBaltic and Northern GIGs
Cyanobacteria biovolume adoptedas national metric by several
countries (Spain,Italy, Norway,UK) Both metrics can be used together
with chlorophyll a for whole BQEassessment and to set more WFD
compliant nutrient targets
Uncertainty results can be used toimprove the design of WFD
monitoring programmes, esp.
concerning sampling frequency
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Phytoplankton Taxonomic composition metric:
Phytoplankton trophic index (PTI)
PTI scores had a significant typespecific relationship with phosphorusthat was linear in the range of 2
100 gP L-1. The lack of response of the phytoplankton
community > 100 gP L-1 highlights the
importance of reducing lake P
concentrations to below this level.
Low alkalinity lakes (red) had lowerPTI scores than high alkalinity lakes
(green) at the same level ofphosphorus.
Eutrophic taxa are less dominant in lowalkalinty lakes than in high alkalinity lakesat same TP level
For more info, see poster by G. PhillipsWISER final conference, 25-26 Jan 2012, Tallin, Estonia
L N2 b L N 2 a L N 1 L CB 1 L C B2C ar te ri a - 0, 48 0 10 4S S S VS VSS po nd yl os i um - 0, 48 0 6 43 S S S VS VS
C h ry s oc h ro m u li n a - 0 ,4 7 2 2 2 2S S S VS VS
C hr ys oc oc cu s - 0, 46 8 2 6 S S S V S VS
R ha bd od er ma - 0, 44 8 6 00 S S S V S VS
Q ua dr ig ul a - 0, 43 6 1 07 7S S S VS VSOo cystis -0,405 68 S S S VS VS
R ad io cy st is - 0, 33 1 8 3T S S VS VS
Eunotia -0,318 2 57 T S S VS VS
Synura -0,316 18 T S S V S VS
Pinnula ri a -0,290 322 T S S VS VS
S ph ae ro c ys t is - 0, 27 7 7 99 T S S S VSAsterionella -0,227 775 T S S S VS
C yc lo te ll a - 0, 20 9 3 9T S S S VS
P un ct ic ul at a - 0, 16 3 4 86 T S S S VS
C hl am yd oc ap sa - 0, 13 9 1 10 1 T S S S V S
P er id in iu m - 0, 12 5 2 5 0T S S S VSM ou ge ot ia - 0, 11 2 3 53 T S S S VS
Ankyra -0,071 167 T T S S VS
G on yo st om um - 0, 06 9 8 7T T S S VS
Peridini opsis -0,057 46 T T S S S
Xanthid ium -0,055 123 T T S S S
R ap hi do ce li s 0 ,0 08 5 6T T S S SW or on ic hi ni a 0 ,0 43 4 21 T T S S S
F ra gi la ri a 0 ,3 17 1 47 T T T S S
C ya no di ct yo n 0 ,3 18 2 0T T T S S
Katodinium 0,343 50 T T T S S
Cym bell a 0,353 82 T T T S SC er at iu m 0 ,5 83 1 05 VT T T T S
Navicu la 0,687 98 VT VT T T T
Eudorina 0,694 64 VT VT T T T
P la nc to ne ma 0 ,7 30 6 16 V T VT T T T
Closteri um 0,732 44 VT VT T T T
P la nk t os ph a er ia 0 ,7 55 2 1 VT VT T T TAnabaena 0,984 26 VT V T VT T T
Volvox 1,032 4 1VT V T VT T T
Go le nk in ia 1 ,0 53 8 5VT V T VT T T
Treuba ri a 1,054 27 VT VT VT T T
C oe la st ru m 1 ,0 78 1 58 V T VT V T T T
Diatoma 1,082 41 VT V T VT T TLyngbya 1,345 25 VT VT VT VT T
C hl or el la 1 ,3 73 4 50 VT VT VT VT T
P la nk to th ri x 1 ,4 16 3 21 V T VT V T V T V T
S te ph an od is cu s 1 ,4 27 1 1 V T V T V T V T V T
Ulothrix 1,430 1 90 V T V T V T V T VTL im no th ri x 1 ,4 41 6 1V T V T V T V T VT
P se ud a na ba en a 1 ,5 70 1 69 V T V T V T V T VT
O sc il la to ri a 1 ,5 75 1 3V T V T V T V T VT
Aphanizomenon 1,595 58 VT VT VT VT VTN it zs ch ia 1 ,6 74 2 1 V T V T VT VT VT
Melo sira 1,711 1 0 V T V T V T V T VTG ol en k in io ps i s 1 ,7 52 1 43 V T V T V T V T VT
P an do ri na 1 ,7 63 2 7V T V T V T V T VT
M ic ro cy st is 1 ,7 88 5 6 V T VT V T V T VT
Phacus 1,912 15 VT VT VT VT VT
Euglena 2,095 51 V T V T V T V T VT
C y li n dr o sp e r mo p s is 2 , 12 1 2 4 V T V T V T V T VT
PTI
Optima Nrecords
LakeType
Genus
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Phytoplankton bloom intensity metric:
Cyanobacteria biovolume
Cyanobacterial blooms aresevere in enriched lakes
across Europe
Risk of exceedance of WHO healthalert threshold (biovolume 2mm3 L-1)
10% exceedance at 20 g L-1 TP 30% exceedance at 40 g L-1 TP
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Metric scores vary largely between lakes - significantlyrelated to eutrophication pressure for IC recommended
metrics (chla, PTI, cyanobacteria)
Within-lake sampling- and analytical variability areminor for integrated samples in euphotic pelagic zone
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
Metric Country Waterbody Station Sample Analyst Error
(sub-
sample)
Total
within
Total
between
Optimal predictor
Chlorophylla 0 0.96 0.01 0.01 - 0.02 0.04 0.96 TP, depth, latitude
PTI 0 0.88
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Macrophytes main results and impacts
Results
Common metrics suitable foreutrophication are: Taxonomic composition metrics:
ICM and Ellenberg index
Abundance proxy metrics: max.colonisation depth and % cover Metric suitable for
hydromorphological pressure:
The macrophyte water levelfluctuation index (FI, NO)
Uncertainty: largest variability foundbetween stations within a lake
Impacts
The ICM has been used forintercalibration in Northern and
Central Baltic GIG
The abundance metrics arepromising, but need furtherimprovement in field methodology
The Water level fluctuation indexis a promising tool to set true
biological boundaries for good
ecological potential for heavilymodified water bodies
to reduce uncertainty in ecologicalstatus assessment formacrophytes, several stations or
increased station area should besampledWISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Eutrophication metrics for macrophytes
taxonomic composition
Intercalibra&onCommonMetricforlakemacrophytes(ICM),calculatedusing
averageofunweightedspeciesscores
(scaling110)basedonarithme&cmean
TPinlakes(leE)wheretheyoccur
LogTP (ug/L)
ICM
BE
EE
FI
IE
LT
LV
NL
NO
PL
RO
SE
UK
0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,50
1
2
3
4
5
6
7
8
9
10
LogTP (ug/L)
Ellen
berg
Index
0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,50
1
2
3
4
5
6
7
8
9
ICM r2 = 0.52
Ellenberg r2 = 0.47
llenbergNindex,calculatedusing
averageofunweightedspeciesscores
(scaling110),andexpertbased
indicatorvalues(speciesscores)
Bothmetrics,butesp.llenbergindexhave
lessresponsetoTPwhenTPis>100g/l
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Eutrophication metrics for macrophytes
abundance proxy: Cmax and % cover
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
Maximum colonisation depth is apromising abundance metric for
macrophytes : Log Cmax = 0.84 0.17*log TP (0.17) -0.27*log
Colour (0.21) + 0.19*log Z_max (0.07),
% cover shows a decrease atincreasing nutrient concentrations
r2=0.45, N= 233
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Macrophytes Water Level Fluctuation index
WLc correlated very well withwinter drawdown in storagereservoirs in Northern countries
Aquatic macrophytes in Finnish, Swedish and Norwegianlakes sensitive and tolerant to water level regulation
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Macrophytes uncertainty
Spatial variability is high,but can be reduced byincreasing the number of
stations and transects
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Macroinvertebrates main results and impacts
Results:
A new multimetric index isdeveloped for HyMo pressure: The littoral macroinvertebrate
shore-line modification index (LIM)
Macroinvertebrates in thelittoral zone are less suited
than the botanical BQEs to
detect eutrophication pressure
Spatial variability is high,requiring sampling many
replicates for each level of
pressure
Impacts:
A new assessment tool formorphological alterations of the
shores of natural lakes is now
applied in Germany and can be
applied in other countries
Eutrophication pressure is notspecifically assessed with littoral
macroinvertebrates
To reduce uncertainty asampling protocol is
recommended
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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2.Addi&onalquan&ta&vees&ma&onusing
theLakeHabitatSurveyprotocol
High alterationReferenceIntermediate
alteration
Es#ma#onofstresslevel1.samplingsitesgroupedinto3levelsofmorphological
altera&on
Rowan, J.S. 2008. Lake Habitat Survey in the United Kingdom. Field survey guidance manual. Version4. Dundee, The Scotland and Northern Ireland forum for environmental research (SNIFFER) & Scottish
Natural Heritage (SNH)
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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basedonsamplesfrom51lakes
-compositesampling(LIMCO)and
-habitat-specificsampling(LIMHA)
Differen&a&onofmul&metricwasdone
dependingonregionduetobiogeogr.
MMI Spearmans
Rho
Region Metrics
LIMCO 0.700.490,440.47
DE+DK
ItalySE+FIIE+UK
MEAN of (Gath&Coll%AC + MargalefDiv + Chiro%AC +No.EPTCBOtaxa)MEAN of (rK-relation + MargalefDiv + Odon% + no.ETOtaxa)MEAN of (Lithal%AC + no.famil + Crusta%AC + no.Odontaxa)MEAN of (GathColl% + MargalefDiv + Dipt%AC + no.ETOtaxa)
LIMHA 0.720.400,440.71
DE+DK
Italy
SE+FI
IE+UK
STONES: MEAN of (Gath&Coll%AC + MargalefDiv + Coleopt%AC +No.EPTCBOtaxa)SAND: MEAN of (%TypePsa + ShanWienDiv + Oligo%AC + EPTtaxa%)MACROPHYTES: MEAN of (Predat% + Evenness + Coleopt%AC +
EPTCBOtaxa%)STONES: MEAN of (SwimmDiv%AC + ShanWienDiv + no.famil +EPTCBOtaxa%)
Li7oralInvertebrateMul#metric(LIM)forshorelinemodifica#ons
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Littora
lInverte
bra
teM
ultime
tricIndex
base
do
ncompos
itesa
mp
les
(LIMCO
)
Pressure-response-rela#onshipsofassessmenttool
Li7oralInvertebrateMul#metricIndexbasedoncompositesamples(LIMCO)
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Further improvement
Merging data from all four regions together Finding the overall best single metrics to be
combined to a multimetric applicable for
larger parts of Europe
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Fish main results and impacts
Results: Impacts: Fish seem less suited than otherBQEs to detect single pressures at
the pan-European scale, but canbe used regionally
Hydroacoustics provide cost-effective assessment of fishabundance
Fish species can be goodindicators of climate change
A multimetric Fish index respondingto eutrophication is developed,
consisting of:
CPUE, BPUE, OMNI Response to pressure is less good
than the botanical BQEs
Hydroacoustic method is promisingto assess fish abundance
No relationship found between fishand HyMo pressure
Large intra-lake variability betweendepth strata means many nets per
lake (or precise hydroacoustics) Fish species are sensitive to
increased temperature with warmwater species increasing and cold
water species decreasingWISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Fish metric response to eutrophication
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
r = -0,5
% of non-natural land cover in the catchment
Fishind
ex
ALCBECMEDNO
0.0
0.2
0.4
0.6
0.8
1.0
0 10 20 30 40 50 60 70 80 90
Mu
ltime
tricindex
(CP
UE
,BPUE
,OMNI)E
QR
R2 = 0.25
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Main trends in fish response to eutrophication and climate
DENSITY & BIOMASS EutrophicWarm
Lowland lakes
Oligotrophic
Cold
High altitude lakes
RICHNESS & DIVERSITYLarge lakes
Warm
Small lakes
Cold
BODY SIZEHigh altitude lakes
Low seasonality
Lowland lakes
High seasonality
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Fish in lakes and Hydromorphology
Seemingly no relationship between fish community descriptors andhydromorphological alterations. Why?
Fish are not sensitive or they have a high resilience ? Fish are moving Impacts of these pressures is obscured by the effect ofbiological
interactions?
Results are limited to a certain degree of pressure intensity? New analyses focusing on fish sampled by gill nets in the littoral
zone may reveal impacts
HyMo pressure should be better characterised
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Cross BQE comparisons:
Sensitivity to human pressures
BQE Pressure
Best common metrics R2 Rho
Phytoplankton Eutrophication (TP) Chlorophyll a
PTI (tax. comp.)
0.63
0.67
Macrophytes Eutrophication (TP) ICM (tax.comp) 0.52
HyMo (water level fluct.) WLi (tax. Comp) (NO+FI) 0.77
Benthic fauna
(littoral)
Eutrophication (TP) MMI 0.40
HyMo (shore modifications) MMI (LIMCO) (DE+DK)MMI (LIMHA) (DE+DK)
0.70
0.72
Fish Eutrophication (non-naturalland cover)
MMI (CPUE, BPUE, OMNI) 0.25
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Cross BQE comparisons:
Variability based on the field sampling
BQE Major variance component Overall natural +methodological
variability
Phytoplankton Temporal (seasonal) Small (~90%)
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
*Large within lake variability for fish is less important, as data from all gill nets andall depth strata are merged when analysing fish response to pressure
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Other evidence supporting WISER
results on sensitivity and uncertainty
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
The WISER common metric results
are supported by a comparison of
93 national lake assessment
methods (Brucet , Birk et al.)showing that correlation
coefficients are higher and less
variable for phytoplankton and
macrophytes than for
macroinvertebrates and fish.
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Key messages for lake assessment
Phytoplankton and macrophytes arerecommended for assessing
eutrophication pressure. Good common
metrics developed in WISER and used forintercalibration can be used also as
national metrics
Littoral BQEs are well suited forassessing HyMo pressures: metrics are
available for macrophytes response towater level fluctuations, and benthic
invertebrates response to morphological
shore-line degradation.
Fish show less clear signals to individualpressures at the European scale, but maybe good indicators at the regional scale.Fish are also good indicators of climate
change: warm water species are
increasing, cold water species decreasing
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
Phyto-plankton
Macrophytes
Fish
Lake
BiologicalQuality
brates
Benthicinverte
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Recommendations for lake monitoring
Phytoplankton monitoring should have sufficientfrequency (monthly) to reduce the temporal variability
Monitoring of littoral BQEs: macrophytes and benthicinvertebrates should have several stations andreplicates for each station
Fish monitoring must include all depth strata withmany gill nets (or whole-lake hydroacoustics)
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
For all BQEs:
Uncertainty can be further reduced by ensuring effectiveand consistent training in sampling and species
identification across Europe
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Future challenges Linking ecological status in lakes to
ecosystem services
Metrics, reference values and classboundaries should take account of climate
change
Functional metrics across BQEs are neededto improve whole lake assessment, including
top-down control and trophic interactions
Better metrics for Eastern Continental andMediterranean regions needed
More metrics needed for reservoirs (HMWBs)
WISER final conference, 25-26 Jan 2012, Tallin, Estonia
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Thanks for your attention
WISER final conference, 25-26 Jan 2012, Tallin, Estonia