Transcript MISIS cruise Intercalibration Exercise BENTHOS

“General Note as regards the Methodology of macrozoobenthos
accountability and application of the integrated assessment of the state
of the macrozoobenthos for marine environment’s quality
determination (calculation methods, quality assessment scales)
(Общие замечания к методике количественного учета
макрозоообентоса и использование интегральной оценки
состояния макрозообентоса для определения качества морской
среды (методика расчета, шкалы оценки качества)”
Adrian Teacă
National Institute of Research-development of Marine Geology and Geoecology GeoEcoMar
YOUR ATTENTION PLEASE!
It aims to be an
interactive presentation
Scope of the presentation:
 To show the assessment methodologies, in terms of methods, instruments and
samples processing necessary to conduct a macrobenthos monitoring programme
 To bring into attention the methodologies employed by MSFD for benthos monitoring
At the end of the presentation, the course participants should:
 Have sufficient understanding of the main methodologies utilized within the
macrozoobenthos monitoring programmes;
 Be able to apply the knowledge regarding the sampling protocol and MSFD
requirements to design the macrozoobenthos monitoring program;
 Be able to draw up a common protocol for macrozoobenthos sampling and analysis.
To achieve GES, cooperation between all Black Sea riparian
countries is a must
A key requirement of the MSFD is that Member States
work together to implement each stage of the Directive
in a coherent and coordinated way, in order to ensure
comparability across Europe.
Cooperation between EU countries Romania and Bulgaria - should be
extended to non-EU member state
Certain progress has been made by the Black Sea Commission, however, further
efforts to improve coordination between EU-member and non-member states are
required.
Major discrepancies between BS Coastal States are related to:
 Differences in available research infrastructure between BS Coastal States
 Lack of a common implementation strategy (e. g. a wide variety of indicator
types for the same ecosystem component)
 The degree of risk and uncertainty that each authority is prepared to accept
 The interpretation of the term ‘good status’
Necessary Steps for elaboration of monitoring program
for D1 & D6, according to MSFD
Define the priority habitats
Identification of GES for each habitat
Set the environmental targets
Monitoring parameters
Monitoring methods
National classification of water habitats identification according to
MSFD requirements
• RO-TT03 – the marine waters situated in the northern
part, under the direct influence of the Danube River,
bounded by the seasonal average of salinity up to 8.0
PSU, the annual average up to 14.5 PSU. The
hydrological stations corresponding with the depth
down to 20m depth, from the mouth of the Danube
into the Black Sea (Chilia, Sulina and St. George)
towards south to Portita;
•
•
•
•
RO-CT01 – the marine waters from the central to the southern
area, from Portita down to Vama Veche), the corresponding
hydrological stations down to 20m depth. The characteristic
salinity for this perimeter is associated with the seasonal
average of 8 – 16 PSU or the annual average up to 16 PSU;
RO-MT01 – delimited territorial seawater by the seasonal and
annual average salinity of 16 – 17PSU for the inner shelf
hydrological stations with the depth between 20 to 50m;
RO-MT02 – the outer shelf marine area (50-100m)
corresponding to a average seasonal and annual salinity about
17 – 17.5 PSU;
RO-MT03 – offshore waters specific salinity corresponding
with the seasonal and annual average more than 17.5 PSU,
related with the maximum depth more than 100m.
Common indicators (RO-BG) – Results Project: Technical and
administrative support for the joint implementation of the Marine Strategy
Framework Directive (MSFD) in Bulgaria and Romania
Descriptor
MSFD (2010/477/EU)
Criterion Indicator
D1 - Habitat 1.1
D6
Indicator
Common parameter (Green: agreed by BG & RO; Orange: potential agreement, to be
further discussed)
1.2
1.3
1.4
1.1.1
1.1.2
1.1.3
1.2.1
1.3.1
1.4.1
Distributional range (species)
Distributional pattern (species)
Area covered
Population abundance and/or biomass
Population demographics
Distributional range (habitat)
1.5
1.4.2
1.5.1
Distributional pattern (habitat)
Habitat area
1.6
1.5.2
1.6.1
Habitat volume
Condition of typical species/ communities Species length of Mytilus galloprovinicialis (mm)
Spatial distribution/extent of pressure
Relevant biogenic substrate
Extent of seabed affected
Species present. Presence of Zostera noltei, Cystoseira barbata, Phyllophora crispa, Ophelia
Presence sensitive/ tolerant species
bicornis
Multi-metric indexes
Multimetric indices (EEI, AMBI, M-AMBI)
Proportion macrobenthos
Size spectrum of benthic community
6.1
6.2
6.1.1
6.1.2
6.2.1
6.2.2
6.2.3
6.2.4
Distribution area of Cystoseira barbata (km²)
Distribution area of seabed habitats (km²):
- Fine sands, Zostera noltei
- Shallow sands, Arenicola marina;
- Sands, Donax trunculus;
- Midlittoral sands, Donacilla cornea;
- Midlittoral rocks, Corallina cornea;
- Infralittroral rock, Cystoseira barbata;
- Infralittoral hard clay banks, Pholas dactylus
- Mytilus galloprovincialis biogenic reefs;
- Circalitoral rock, Mytilus galloprovincialis;
Habitat area (Spread, distribution) (km²) of the following habitats: midilittoral rocks;
midlittoral sands; infralittoral hard clay banks
Criteria/Indicator
(2010/477/EU)
1.1.1 Distributional range
GES and Target
Monitoring parameters
Maintain or increase the distribution range (and pattern within the latter) of the typical zoobenthos and phytobenthos species in the
MSFD predominant habitat types, relevant habitats under the Habitats directive and the associated national biotopes, according to
1.1.2 Distributional pattern the Bulgarian report under Art. 10 of the MSFD
benthic communities sampling
(Todorova V. and Konsulova T.,
2005. Gray, J.,S., Mcintyre, A.,D.,
and Štirn, J., 1992)
1.1.3 Area covered by the
species
E.g.: Donacilla cornea (MSFD: Midilittoral sediments. Habitats Directive: 1140; National biotope: Coarse and medium mediolittoral
sands, exposed to wave action with Donacilla cornea and Ophelia bicornis)
Monitoring method
Distribution range of Donacilla
cornea
Cystoseira barbata and Cystoseira crinita (MSFD: Shallow rocks and biogenic reefs. Habitats Directive: 1170; National biotope:
Infralittoral seabed with perennial associations of Cystoseira spp.).
Distribution range of
Cystoseira barbata and
Cystoseira crinita
1.2.1 Population
Maintain the abundance and biomass of the typical zoobenthos and phytobenthos species by preventing the deterioration of
Community composition and
abundance and/or biomass marine environment resulting from sealing, nutrient enrichment , smothering, abrasion and extraction of living or non-living
abundance (no indv. and.
resources according to the threshold values specified in the Bulgarian Art. 10 MSFD Report
biomass)
2
2
Abundance (Donacilla cornea) > 4500 ind./m ; Biomass (Donacilla cornea) > 2500 g/m (Table I.2.5 of the Bulgarian MSFD Art. 10
abundance (individuals /m2);
report)(MSFD: Mediolittoral sediments. Habitats Directive: 1140; National biotope: Coarse and medium mediolittoral sands, exposed biomass (g/m2 ) - Donacilla
to wave action with Donacilla cornea and Ophelia bicornis)
cornea
1.3.1 Population
demographic
characteristics
Maintain the population demographic characteristics of the benthic habitat defining species according to the threshold values
defined in Bulgarian MSFD Art. 10 report
Length (Donacilla cornea) > 16 cm (MSFD: Mediolittoral sediments. Habitats Directive: 1140; National biotope: Coarse and medium
mediolittoral sands, exposed to wave action with Donacilla cornea and Ophelia bicornis)
1.4.1 Distributional range
(habitat)
The current distribution and distributional range of benthic habitats
Maintaining existence of the three grasslands of Zostera noltei
1.5.1 Habitat area
The area of the Natura 2000 habitats
Maintaining surface of the habitat 1110-1 Fine sands, clean or slightly muddy, with Zostera noltei meadows: The area occupied by
habitat ≥ 2,43 ha
ha or km2
Maintaining good status of Mytilus galloprovincialis population:
The median size of specimens by Mytilus galloprovincialis (shell length) ≥ 50 mm SL
Mytilus galloprovincialis,
length (mm), weight (g/m2)
1.6.1 Condition of typical
species/ communities
benthic communities sampling
(Todorova V. and Konsulova T.,
2005. Gray, J.,S., Mcintyre, A.,D.,
and Štirn, J., 1992)
length - Donacilla cornea
benthic communities sampling
(Todorova V. and Konsulova T.,
2005. Gray, J.,S., Mcintyre, A.,D.,
and Štirn, J., 1992)
fine sand, Zostera noltei
side scan sonar; benthic
communities sampling (Todorova
V. and Konsulova T., 2005. Gray,
J.,S., Mcintyre, A.,D., and Štirn, J.,
1992)
side scan sonar; benthic
communities sampling (Todorova
V. and Konsulova T., 2005. Gray,
J.,S., Mcintyre, A.,D., and Štirn, J.,
1992)
Criteria/Indicator (2010/477/EU)
6.1.1 Type, abundance, biomass and extent of
relevant biogenic substrate
6.2.1 Presence of particularly sensitive species
and / or tolerant species
GES and Target
Spatial distribution/extent of pressure
Monitoring parameters
1) Distribution & extent of
physical loss from human
activities
2) Distribution, extent &
frequency of physical
disturbance
Distribution in space & time,
frequency
Distribution in space and
time of relevant activities
Maintain the presence of the particularly sensitive species in the structure of
macrozoobenthos according to the threshold values in the Bulgarian and
Romanian MSFD Article 10 report.
Lepidochitona caprearum, Lepidochitona cinerea, Acanthochitona
species presence
fascicularis, Gibbula divaricata, Eriphia verrucosa, Pilumnus hirtellus,
Pachygrapsus marmoratus, Xantho poressa, Pisidia longicornis, Clibanarius
erythropus, Palaemon adspersus, Palaemon elegans, Hippolyte leptocerus,
Athanas nitescens (MSFD: Shallow rocks and biogenic reefs; Habitats
Directive: 1170; National biotope: infralittoral rocks encrusted with black
mussels Mytilus galloprovincialis and Mytilaster lineatus).
6.2.2 Multimetric indices for assessment of
Multimetric indices show good status of stated communities according to
benthic community condition and functionality, as the stated (and approved) treshold values:
well as species diversity and richness report
opportunistic species / species sensitive
Maintaining good status of communities with Cystoseira barbata: Cystoseira
EEI
barbata: Index values EEI > 0.
Maintaining good status of communities with Modiolula phaseolina:
S, H', AMBI, M-AMBI
Modiolula phaseolina: Indices values: M-AMBI ≥ 0,55; AMBI ≤ 3,3
Monitoring
method
Lateral sonar
scanning, geological
sampling
MONITORING DEFFINITION, TYPES AND SCOPES
MONITORING - an intermittent (regular or irregular) series of observations in time, carried out to
show the extent of compliance with a formulated standard or degree of deviation from an
expected norm (Hellawell, 1991 modified by Brown, 2000).
It defines the state desired in terms of objectives or targets
SURVEILLANCE - repeated survey using a standard methodology undertaken to
provide a series of observations over time.
Surveillance can yield valuable information on trends in the state of
environment,
but does not by itself establish whether objectives or standards have been met.
MONITORING STRATEGY
A strategy is defined as an elaborate and systematic plan of action designed to achieve a
particular goal.
 What and how is to be determined (measured)?
• The range of spatial and temporal (e.g., season, month) scales relevant for the species, assemblage or process
under consideration should be accounted
• Thus, the spatial replication is a mandatory component of any benthic study
• The above planning issues are relevant for determining the parameters measured (diversity, abundance,
biomass, age/size of populations, sexual maturity, distribution pattern etc.)
 Where ? (geographic coordinates, type of habitat, substrate etc.)
• The establishing of true “relationship” of one community to ecological factors (habitat engineering species) is
capital, and the sampling strategy should be based largely on good knowledge of the natural history of the species
• In case that a priori information is not available, a range of sampling units should be employed before the
sampling strategy is set.
 Time and frequency
• It depends of monitoring goal (changes of communities over time period, response to impact etc.)
 Information on the final use of data, including data analysis, statistical calculations, and evaluation
Why to use macrozoobenthos in marine
monitoring programmes?
Majority of species are:
- Sedentary/vagile
- Their natural distributions usually show good relationships with their
sedimentary habitat and depth.
- Their responses to environmental change can easily be measured.
Response of benthic communities to ecological
disturbances over time
The state of any benthic community represents the “mirror” of ecological changes
along the time, reflected in the “inventory” of the biota quality and quantity.
Phyllophora field on the Ukrainian continental shelf with a “forest” of Ciona intestinalis
T. Stevens
Poseidon, 2008
Mud mussels communities on the Romanian
continental shelf with a meadow of Dipolydora
quadrilobata tubes
Modiolula communities on the Romanian
continental shelf with Ascidiella aspersa,
Mycale syrinx
R/V Poseidon 363 Cruise/2008/Photo T.Stevens
Methods for the Study of Marine Benthos
 Eleftheriou and Moore (2005), detail the current situation concerning macrofaunal sampling by trawl, sledge, corer
and other methods.
 Holme and McIntyre (1971) and Holme and McIntyre (1984). The book covers all aspects of benthic sampling and
is a core publication for all involved in seabed study.
 Todorova and Konsulova (2005). Manual for quantitative sampling and sample treatment of marine soft - bottom
macrozoobenthos
International Standard ISO/DIS 16665
 European Committee for Standardization (CEN) ISO Technical Committee 147/5 - ISO 16665: 2005
The guideline has been formulated with reference to most representative publications (e.g. Eleftheriou and Holme
1984; Rees et al., 1990; Rumohr 1999; Proudfoot et al., 2003) and coverage is therefore comprehensive.
Sampling strategy
General considerations regarding macrozoobenthos monitoring
strategy
• Establishment of the baseline community structure and the
natural variability
• Sampling habitats and sites
• Number of sampling stations
• Number of replicate samples
• Timing and temporal scales
• Establishment of reference conditions
• Selection of relevant environmental descriptors
• Adherence to standard protocols for sampling and analysis
Logistics
1. Site location
2. Sampling equipment
The positions of sampling stations should
be defined using geographic coordinates
- European Datum: ED-50;
- World Geodetic System: WGS-84
The Black Sea Integrated Monitoring and Assessment
Programme (BSIMAP) recommends to be used as a
standard macrozoobenthos sampler:
Van Veen Grab with a sampling area of 0.1 m2
+ + +
Advantages:
 an efficient sampler for the
range of soft sediments
encountered in the Black
Sea,
 reliable and simple to
operate
 widely applied, which allows
data comparison with other
marine areas.
--Disadvantages:
 The risk of losing the
sample or part of the
sample
 Sediments layer are
usually disturbed
Logistics
2. Sampling equipment
Box - corer: it is recommended mainly when undisturbed samples are
required to be taken (additional analysis can be performed; e.g., chemistry,
biochemistry etc.)
+ + +
Advantages:
 The sample comes on board
undisturbed
 The integrity of the sample is
maintained (no material looses)
 Despite of smaller sampling
area (0.07 m2) abundance of
macrobenthos is generally
higher than that of Van Veen
abundance
--Disadvantages:
 It is expensive
 The operating is difficult if
the ship is not equipped
with proper equipment
(cranes, A-frame)
 Large volume
Logistics
2. Sampling equipment
Multicorer: it is recommended mainly when undisturbed samples are
required to be taken (additional analysis can be performed; e.g., chemistry,
biochemistry etc.)
+ + +




Advantages:
Suitable for area
inaccessible for Van Veen
(deep suboxic area)
The sample comes on
board undisturbed
The integrity of the
sample is maintained (no
material looses)
Obtaining of replicates (4,
12) at one deployment
--Disadvantages:
 It is expensive
 The operating is
difficult if the ship is
not equipped with
proper equipment
(cranes, A-frame)
Ship-board techniques
1. Grab deployment
2. Washing sieving
 - If the grab is not perfectly closed (due to
pebbles, shells caught in jaws) when arrives on
deck, the sample should be discarded.
 - Water retained in the Van Veen must be also
filtrated through sieve.
 - If the sediment depth in the grab is less than
7 cm in mud or 5 cm in sand, the sample is
rejected.
 - The standard sieve for washing the samples is
metallic (stainless steel, brass or bronze) and has a
mesh size of 0.5 mm.
 - An additional sieve with mesh size of 1 mm might be
needed. In suboxic area can be used also a 0.25 mm
sieve.
Van Veen samples from each habitat type
Box - corer samples from each habitat type
Dredge sampling
Washing table and 0.5 mm mesh size sieve
Ship-board techniques
3. Fixation
 Samples (hand-picked animals and the sieving residue)
should be fixed as soon as possible after sieving using
buffered 37 % formaldehyde (formalin).
4. Staining
 Optional according to staff preference. Rose Bengal
 (1 g/dm3 of 40% formaldehyde)
5. Labelling
 Station, sample number, replicate number and date externally and internally (if necessary)
Laboratory processing
1. Sorting and taxonomic identification
2. Abundance determination
 - The basic premise of all macrobenthic sample analyses in the
 - Taxa that are not sampled quantitatively or that
are not truly indicative of sediment conditions
shall not be quantified but their presence should
be noted.
 - Broken animals shall only be counted as
individuals by their heads (e.g. polychaetes) or
hinges of bivalves with adhering pieces of tissue.
laboratory is that all specimens extracted from the samples are
to be identified to the lowest possible taxonomic level and
counted.
 - In order to overcome taxonomic discrepancies due to usage
of synonymous names common nomenclature shall be used
according to the European/World Register of Marine Species
(ERMS/WoRMS) available on
http://www.marbef.org/data/ermssearch.php.
 This will facilitate comparison of data not only within the Black
Sea region but also with other European seas.
 - A taxonomic reference collection should also be available for
training and verification purposes.
3. Biomass determination
 - wet weight - mandatory (specimens with
calcareous parts will be weighted integrally)
 - dry weight - optional
 - ash-free dry weight (optional): most appropriate
measure of living biological matter(no inorganic
material and water);can be estimated by applying
conversion factors obtained from the literature,
backed up by local calibration where necessary.
 - standard data report sheets (EurOBIS data format)
4. Data reporting
Label
rightsHolder
scientificNameAuthorship
Scientific NameID
basisOfRecord
bibliographicCitation
kingdom
phylum
class
subclass
order
family
genus
specificEpithet
identifiedBy
eventDate
fieldNumber
locationID
waterBody
country
locality
decimalLatitude
decimalLongitude
geodeticDatum
minimumDepthInMeters
maximumDepthInMeters
habitat
preparations
samplingProtocol
Data
National Research and Development Institute for Marine Geology and Geoecology -GeoEcoMar
Alitta succinea (Leuckart, 1847)
AphiaID: 234850
HumanObservation
Teaca A., Begun T., (2015). Macrozoobenthos – DG Env MISIS, R/V Akademic Cruises 2013. National Research and
Development Institute for Marine Geology and Geoecology - GeoEcoMar Database.
Animalia
Annelida
Polychaeta
Errantia
Phyllodocida
Nereididae
Alitta
Density for square meter (ind./m2)
succinea
Teaca A.
2013-07-23
I
M01
Black Sea
Romania
Constanta
44.166667
28.783333
WGS84
33.3
33.3
sandy mud sediments
whole animal, fixed in formalin, preserved in alcohol
Van-Veen grab, sampling size - 0.1 m2. The sediment was preserved in buffered formalin 4% , then sieved through
a 1 mm and 0.5 mm mesh sieve and subsequently stored in 70% ethanol.
700
Wet weight biomass gram for square meter (g./m2)
7
Quality assurance
1. Equipment calibration
MISIS cruise Intercalibration Exercise BENTHOS
 e.g., sampling area of grab or
mesh size of sieve
 Van Veen grab of 0.14 m2 area
2. Training
 Ring tests and
intercalibration exercises on
a regional basis should be
undertaken regularly and be
obligatory for institutions
delivering data to the
BSIMAP.
2.1 Quality and quantity of the sample
Accuracy of sample sorting and
taxon identification
 This step weights most in
intercalibration exercises,
depending of expertise of
taxonomists
Quality control
Quality Control routines
 Regularly check by a second specialist of taxonomic identification and number of individuals extracted
from sample (randomly subsamples) as well as the correctness of wet biomass determination
 A simple method for checking the similarity between the results obtained is by using the Bray-Curtis
Similarity Index (BCSI), which should give a value higher or equal of 90%. Data flags are applied as
follows:
100 % BCSI:
95 <100 % BCSI:
90-95 % BCSI:
85-90 % BCSI:
<85 % BCSI:
Excellent
Good
Acceptable
Poor – remedial actions suggested
Fail - remedial actions required
MISIS cruise Intercalibration Exercise
BENTHOS
MISIS cruise Intercalibration Exercise BENTHOS
The scheme of the number of species found at stations M10 and M18 by
different institutes, the share of the number of species (%) and their
distribution according to the institutes (A: SNU-FF, B: GeoEcoMar, C: NIMRD).
M10
M10
M18
identified by all
three institutes
identified by
one institute
identified by
two institutes
M18
The intercalibration exercise revealed differences in the taxonomic
skills of the participants that call for further training and more frequent
intercallibration campaigns.
MISIS cruise Intercalibration Exercise
BENTHOS
MISIS : Statistical calculations were run on raw data under two titles as Z-Score calculation and Similarity/Dissimilarity analysis
Z-Score – Inadequate for Exercise Benthos
Qualitative cluster dendogram obtained by the
samplings of the institutes for station M10 (A: SNU-FF,
B: GeoEcoMar, C: NIMRD).
Similarity/Dissimilarity analysis - Adequate
Similarity and dissimilarities calculated as a result of the
SIMPER analysis
Analysis Groups
Group I
Average Similarity
66.22
Average Dissimilarity
-
Group II
46.47
-
Group III
26.63
-
Group I&II
-
75.72
Group I&III
-
90.45
Group II&III
-
81.44
MISIS cruise Intercalibration
Exercise BENTHOS
Quantitative cluster dendogram obtained by the
samplings of the institutes for station M10 (A: SNU-FF,
B: GeoEcoMar, C: NIMRD).
Similarity and dissimilarities calculated as a result of the
SIMPER analysis
Analysis Groups
Average Similarity
Average Dissimilarity
Group I
64,19
-
Group II
50,29
-
Group III
40,83
-
Group I&II
-
81,28
Group I&III
-
90,42
Group II&III
-
82,79
MISIS cruise Intercalibration Exercise BENTHOS
- CONCLUSIONS
Dissimilarities observed between results obtained by the teams who analysed the samples are due to:
 The natural variability of species distribution in their habitats
 The sampling design (the repetitive cast of VanVeen in the same place affected the species composition, so that
each sample collected had different number of species (different qualitative composition) and number of
individuals (quantitative composition) from each species (especially for those species that have small
populations).
 Samples' processing on board (washing, sieving, preserving and staining); however, these aspects can be in very
small measure claimed for the differences observed.
 The samples' lab processing (experts work).
 However, the results can be considered only satisfactory from the point of comparability since in both stations
analyzed (M10 and M18) there were found significant dissimilarities (> 50%) between the results provided by the
three teams (SNUFF, GeoEcoMar, NIRD Antipa)
The SIMPER analysis of similarities and dissimilarities within the groups (replicates) and between groups
(institutes) concerning the abundance, presence/absence and biomass parameters of benthic populations has
been proved an appropriate statistical method to envince the gaps and plusses regarding the intercalibration
exercise, that could be useful for Black Sea regional monitoring programme design.
Benthic habitats – WFD and MSFD
Broad spatial knowledge of the habitats and associated biological communities
overlapped with human uses is essential
 The assessment of the condition of benthic habitats is one of the evaluation
criteria both in the WFD (as biological quality element) as in the MSFD descriptors
(D1 - biodiversity & D6 - sea floor integrity).
An assessment procedure for determining the condition of softsediment benthic habitats requires the following aspects:
• habitat assignation of the samples (habitat approach),
• reference or target conditions for the benthic parameters,
• the selection of indicator tools to assess the relative quality status
(indicator approach).
HABITATS vs. BIOCOENOSIS
Harmonization of bionomic classification
The main benthic assemblages in the
NW Black Sea
The main benthic habitats (biological zonation according
to EUNIS categories, adapted to Black Sea) (EUSeaMap Seabed habitats lot output, http://www.emodnetseabedhabitats.eu/)
Harmonization of bionomic classification
E.g., Sublittoral = infralittoral + circalittoral
Periazoic = suboxic
Biodiversity
Components
Benthic
(former seabed)
habitats
Biodiversity habitat groups
List of Black Sea broad scale habitats
Littoral rock and biogenic reef
Littoral sediment
Infralittoral rock and biogenic
reef
Infralittoral coarse sediment
Infralittoral sand
Infralittoral mud
Infralittoral mixed sediment
Circalittoral rock and biogenic
reef
Circalittoral coarse sediment
Biodiversity (D1) indicators and criteria (at habitat
Circalittoral sand
level) of the MSFD assessment have to be assessed
Circalittoral mud
for each representative habitat selected (EUNIS level
Circalittoral mixed sediment
4/5); and then all representative habitat assessments
Upper bathyal rock and biogenic
have to be aggregated under each of the habitat
reef
groups (assessment units) as a minimum
Upper bathyal sediment
Lower bathyal rock and biogenic
requirement.
reef
Lower bathyal sediment
Abyssal rock and biogenic reef
Abyssal sediment
Revised list of biodiversity components and groups
Pelagic (former Coastal
(former predominant) for habitats, as minimum
water column) Shelf
requirement for MSFD reporting.
habitats
Oceanic
Further improvement is
needed!
Correspondence between biodiversity habitats
groups (minimum requirements) and proposed
EUNIS 2015 typology.
Red lines delineate revised benthic habitats
groups (minimum requirement for MSFD
reporting) and their allocation to the new
EUNIS classification level 2 (2015 EEA proposal);
Black lines delineate further optional
subdivision of these habitats groups, reflecting
previously used classification in EUNIS, and
(sub)regional specificities.
*Includes soft rock - marls, clays-, artificial hard substrata
Thresholds for each habitat and region (ongoing in
RO & BG)
MISIS cruise: STATE OF THE ENVIRONMENT OF THE
BLACK SEA – Biodiversity assessment - BENTHOS
• Romanian transect, Constanta-East;
• Bulgarian transect - Galata transect (Varna);
• Turkish transect (Igneada).
Stations: 13
Samples: 47
The distribution of samples on depth
intervals were as follows:
• 20 - 30 m: 2 stations;
• 31 - 50 m: 3 stations;
• 51 - 100 m: 6 stations;
• >100 m: 2 stations (M05 and M15).
Description of Benthic habitats
Descriptor 1
1.4. Habitat distribution – requires large spatial coverage of sampling
1.6. Habitat condition
1.6.1 Species state and communities - diversity, abundance, biomass
Descriptor 6
6.2 Condition of benthic community
6.2.2 Multi-metric indexes assessing benthic community condition and
Functionality - (Shannon, AMBI, M-AMBI)
Description of Benthic habitats in the framework MISIS
- to assess the ecological state of benthic habitats, which were classified after EUNIS;
Based on samples analysis five benthic habitats have been found in the study area:
1. Moderately exposed lower infralittoral sand with Chamelea gallina and Lucinella divaricata,
2. Shallow circalittoral mud with Abra, Spisula, Pitar, Cardiidae, Nephtys, etc,
3. Shallow circalittoral with Mytilus galloprovincialis beds on mud and sandy mud,
4. Deep circalittoral mud with Terebellides stroemii,
5. Deep circalittoral shelly mud with Modiolula phaseolina.
the EUNIS classification is still in its infancy in the Black Sea
Description of Benthic habitats in the framework MISIS
Circalittoral shelly muds
with Modiolula phaseolina
Mytilus galloprovincialis beds on
mud and sandy mud
Upper circalittoral mud with Abra,
Spisula, Pitar, Cardiidae, Nephtys
Similarity
Bray Curtis similarity analysis on the
presence/absence data
Samples
Application of Macrobenthic Indicators in
Assesssing the Ecological Quality Status
PEARSON & ROSENBERG
(1978) MODEL
Peak of opportunistic species
Richness
Biomass
Abundance
+
ORGANIC MATTER ENRICHMENT
-
• Initial State = Normal zone
• Rich biocenosis in individuals and species
• Many species exclusive from the biocenosis, linked to
grain-size
• High diversity
• Slight unbalance = Ecotone I = Disequilibrium zone
• Exclusive species decrease in number and abundance
• Tolerant species proliferate, pioneer species appear
• Diversity decreases
• Pronounced disequilibrium = Disequilibrium zone = Polluted
• Representative species disappear, opportunists dominate
• Diversity very low
• In extreme cases presence of 1 or 2 species
• Fauna disappears = Azoic Zone
Ecological groups (Hily, 1984; Grall and Glemarec, 1986)
 Group I: Species very sensitive to disturbance, present under unpolluted conditions
(initial state): specialist carnivores, some deposit-feeding tubicolous polychaetes.
 Group II: Species indifferent to disturbance, present in low densities, non-significant
variations with time (from initial state, to slight unbalance), suspension feeders, less
selective carnivores, scavengers.
 Group III: Species tolerant to excess organic matter enrichment. They occur under
normal conditions, but are stimulated by organic enrichment (slight unbalance
situations), surface deposit-feeding species, as tube dwelling spionids.
 Group IV: Second-order opportunistic species (slight to pronounced unbalanced
situations). Mainly small sized polychaetes: subsurface deposit-feeders, such as
cirratulids.
 Group V: First-order opportunistic species (pronounced unbalanced situations).
These are deposit-feeders, which proliferate in reduced sediments.
AMBI development
AMBI =
((0 * %GI) + (1.5 * %GII) + (3 * %GIII) + (4.5 * %GIV) + (6 * %GV))/100
1
BIOTIC COEFFICIENT
3
4
5
6
100
90
80
70
60
V
I
50
III
40
30
20
10
0
POLLUTION
WFD
2
AZOIC SEDIMENT
PERCENTAGE OF GROUPS
0
IV
II
0
1
UNPOLLUTED
2
3
BIOTIC INDEX
SLIGHTLY POLLUTED
4
MEANLY POLLUTED
5
6
HEAVILY
`POLLUTED
7
EXTREM.
POLLUTED
HIGH
GOOD
MODERATE
POOR
BAD
STATUS
STATUS
STATUS
STATUS
STATUS
INCREASING POLLUTION
Calculate and represent the AMBI Index
First step
• You can consult web page
(http://ambi.azti.es) and obtain
free AMBI software to calculate
and represent the index.
• This software includes the
classification of 8,000 species from
the Atlantic, Mediterranean,
Pacific, etc. (it is updated regularly).
Data format
Stations Distribution – Disturbance Classification
Ecological groups
M-AMBI
Applications
MISIS: Ecological state of macrozoobenthos after MSFD
Habitat
Moderately exposed
lower infralittoral sand
with Chamelea gallina
and Lucinella divaricata
Upper circalittoral mud
with Abra, Spisula,
Pitar, Cardiidae,
Nephtys
Mytilus
galloprovincialis beds
on mud and sandy mud
Lower circalittoral
mud with Terebelides
stroemii
Circalittoral shelly silt
with Modiolula
phaseolina
Transect
Stations
S
H'
AMBI M-AMBI
49
3.63
1.60
0.91
Good
Igneada
M18 (27m)_GEM
M18 (27m)_SINOP
46
2.49
0.07
0.87
Good
Constanta
M01 (33m)
24
2.20
4.38
0.61
Galata
M12 (23m)_GEM
37
2.75
3.51
0.68
Galata
M11 (40m)_GEM
25
2.40
4.38
0.46
Constanta
M02 (47m)
13
2.36
3.56
0.56
Constanta
M03 (54m)
18
3.07
3.42
0.71
Igneada
M17 (53m)
17
2.88
1.57
0.64
Galata
M10(76m)_GEM
23
2.43
4.23
0.49
Galata
M10(76m)_TUR
15
2.21
2.26
0.51
Galata
M10(76m)_NIMRD
18
3.10
1.93
0.74
Galata
M09(93m)_GEM
16
2.39
2.74
0.52
24
25
18
27
2.93
3.60
3.16
2.67
2.11
2.47
1.21
0.79
0.64
0.92
0.86
0.73
Igneada
Constanta
Constanta
Igneada
M16 (76m)
M04 (65m)
M05 (101m)
M15 (101m)
MSFD Ecological state
Moderate
(Not good)
Good
Moderate
(Not good)
Moderate
(Not good)
Moderate
(Not good)
Good
Moderate
(Not good)
Moderate
(Not good)
Good
Moderate
(Not good)
Good
Good
Good
Good
Advantages
(Borja, 2013. Ecological indices based on macrobenthos: the case of AMBI and M-AMBI
in assessing seafloor integrity status)
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AMBI and M-AMBI have been validated with a large set of environmental pressures and
impact sources (near 300 and 70 references, respectively).
AMBI and M-AMBI are easy to use, having freely-available software, with an updated
species list of 8,000 taxa (http://ambi.azti.es).
AMBI and M-AMBI are efficient in detecting time and spatial impact gradients.
AMBI is insensitive to seasonal variability (in absence of external impacts)
AMBI is independent from sample size
AMBI and M-AMBI have been verified in a very large number of geographical areas.
M-AMBI has been intercalibrated within the Water Framework Directive.
Disadvantages
(Borja, 2013. Ecological indices based on macrobenthos: the case of AMBI and M-AMBI in assessing seafloor integrity status)
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The robustness of AMBI is reduced with low number of taxa (1 to 3) and/or individuals (including
naturally-stressed locations).
AMBI does not work well with physical impacts: sand extraction, fish trawling, etc. (but, M-AMBI
works in some of these cases)
In order to avoid ambiguous results, calculate the AMBI values for each of the replicates, then to
derive the mean value.
Be careful with high unassigned percentage of taxa (>20%) in AMBI.
The assignation of taxa to the ecological groups, together with taxonomy problems (synonyms,
etc.) could lead to misclassification problems. The assignation requires some consensus between
the scientific community.
M-AMBI needs clear sampling protocols, since diversity and richness depend on sample size
The status assessment depends on the boundaries set in the AMBI and M-AMBI scale values.
Changing the boundaries would alter the final classification (as in other methods).
It is better to use M-AMBI with a minimum of 50 stations
Practical example
Suboxic area (130m)
Coastal area - Danube
influence (27-39m)
Ofshore area (64 -114m)
Black Sea IC exercise – Biological Quality Elements
(after Todorova et al., 2015)
Area: coastal waters - (Bulgarian and Romania)
reference sites - Krapetz, Rusalka, Northern Bulgarian coastal marine area
Methods: M-AMBI*(n) (Sigovini et al., 2013) - Combination rule of metrics - Arithmetic average of the min-max
normalized AMBI, H’, Species richness
Total number of sites - 8
In total 63 sampling dates and 33 site - years including:
- RO: 41 sampling dates from 2003-2009
- BG: 22 sampling dates from 2008, 2012-2014
- 1 – 4 sampling occasions per site-year
In total 97 taxa
Per sampling date:
- Species list
- Abundance (raw data matrix)
- AMBI
- 5 AMBI sensitivity classes
- Shannon-Wiener diversity H‘
- Taxa richness S
- M-AMBI* (n)
Boundary setting procedure in relation to the pressure
(Pressure index for the Black Sea)
The PIBS was calculated using PCA and multiple regression to define the weights of
different pressures.
PIBS integrates data for:
 Urban and Industrial area from CORINE landcover;
 Loads from point sources of biological oxygen demand, detergents, heavy metals,
phenols, suspended solids, total petroleum hydrocarbons;
 Tourism – overnights spent;
 Navigation – density of AIS positions data as an indicator for the shipping intensity.
Logarithmic relationship established between PIBS and M-AMBI*(n).
PCA of the pressures at sites
PCA analysis of the pressures
validates Krapets and Rusalka as
reference sites with the lowest level
of pressure
PIBS to M-AMBI*(n) relationship
calculated at the samples level.
PIBS to M-AMBI*(n) relationship
calculated at the year-site level
averaged data.
PIBS to M-AMBI*(n) relationship
calculated at the site level
averaged data
Description of boundary setting procedure set for the common Intercalibration type:
Step 1. Reference conditions were quantified by using the following statistic:
- the percentile 0.8 from the reference sites dataset for S, H and M-AMBI*(n);
- the percentile 0.2 from the reference sites dataset for AMBI.
AMBI = 3
H=3
S = 27 17
M-AMBI*(n) = 0.97
High/Good boundary
EQR=0.9 from reference value for each of the metrics used S, H’, AMBI and M-AMBI* (n)
Using the EQR approach the equidistant boundaries were set by dividing EQR=0.9/4
Step 2. Description of the zoobenthos biological community and a conceptual model how it changes along the pressure
gradient
Reference/High status the benthic
invertebrate community is characterised by
high species richness and diversity, high
abundance, significant proportion of
sensitive to pollution species (predators
and filter feeders), and dominance of
tolerant to organic enrichment species
(surface deposit feeders), due to naturally
mesotrophic conditions in the NorthWestern Black Sea
Good status the community is
characterised by presence of
sensitive to pollution species,
although their relative proportion
decreases. Indifferent species and
tolerant to organic enrichment
species become dominant in the
abundance structure.
Moderate status a major functional
shift in the community structure is
evident, notable by the
disappearance of the sensitive
species. The indifferent species are
still present. The tolerant species
and the opportunists become
dominant in the abundance
structure. Richness and diversity
decrease, while abundance is still
high.
At Poor status the indifferent species disappear as well. The abundance is distributed between only tolerant
and opportunistic species, the latter being dominant. Richness and diversity are low. The abundance decreases
as well.
Steps 3. PIBS to M-AMBI*(n) relationship calculated at the site level averaged data
Steps 4. Since the relationship between the M-AMBI*(n) and the pressure gradient is a continuum failed to identify
boundaries based on paired metric assessments the last option was used - dividing the continuum of metric values between
the High/Good boundary established in Step 1 and the Bad extrema (0 for S, H’, and M-AMBI *(n) and 6 for AMBI) into four
equal width classes.
Using the EQR approach the equidistant boundaries were set by dividing EQR=0.9/4.
Reference
High/Good
Good /Moderate
Moderate/Poor
Poor/Bad
EQR
1
0.9
0.68
0.45
0.23
AMBI
3
3.30
3.96
4.65
5.31
H
3.0
2.70
2.04
1.35
0.69
S
27
24
18
12
6
M-AMBI*(n)
0.97
0.87
0.66
0.44
0.22
What to do in the Joint Survey
(and/or12 month monitoring strategy in Odessa area and Zmeiniy Island):
1. To agree on the habitats which to be monitored and the criteria of selection and classification,
2. To set de indicators for environmental status assessment (e.g. Spatial distribution, Spatial pattern,
Population size),
3. For each MSFD indicator of D1 - Biodiversity linked with D4 and D6 must be found appropriate parameters
which reflect the status of habitats taking into account the targets established for the key species with
long-life span, e.g. body size of Mytilus, Chamelea or Upogebia, age structure of mollusk, etc.
4. All above mentioned are strongly linked with physical and chemical parameters (O2, TOC in sediments,
Nutrients, heavy metals, marine litter, sediment dynamics etc.) related to pressures descriptors.
5.
The number of samples and replicates (3 recommended but also depends of analyzed habitats) may
vary according to distributional pattern of engineering species: e.g. less coverage in Modiolula habitats
due to uniform distribution of it and more in spotted/aggregated community combined with remote
sensing observation (ROV) e.g. Mytilus.
6. Devices used for sampling (Van Veen grab) must be the same having standard dimensions of 0,1m2 for
all participants,
7. Use of 0,5 mm and 1 mm if it is needed, mesh size sieves to wash the sample onboard,
8. The usually parameters which are mandatory to be assessed are number of species, abundance (ind.m2) and wet weight biomass (g.m-2),
9. Taxonomical identification must be done to the lowest possible level (species) and species
nomenclature must be harmonized according to European Register of Marine Species (ERMS) or
WoRMS,
10. Statistical analyzes must be robust but to everyone understanding (such as, DAvg, BAvg, diversity index
Shannon-Wiener, species richness, frequency, dominance, ecological significance indices),
11. Assessment of habitats quality state will be done using AMBI and M-AMBI metrics, (If you use this software
please make reference to “AMBI: AZTI MARINE BIOTIC INDEX (AZTI-Tecnalia, www.azti.es)).
12. In the near future must think on boundary value for EQR between different quality status of
environment (for each region and habitat),
13. Common database monitoring sheets
Lets Get to Work