Effects of aquaculture on
Mediterranean marine ecosystems
I. Karakassis, D. Angel
Effects of aquaculture on marine biotic communities
Source of p ressure
Potential effect on biota
phy sical structure
Direct mortality through entang lement
Behav ioral chang es in coas tal pelagic fish
Behav ioral chang es in coas tal bi rds and
marine mammals (e.g., avo idan ce)
Direct mortality
poo r
mediu m
poo r
Behav ioral chang es of wild fauna
Dis ease tran smis sion to o ther species
Genetic interaction s with wild fish
Displa cement of wild fish from na tural
hab itat (e .g., th roug h competition,
preda tion)
Suffocation and d isplacement o f benthic
organisms
Lo ss of fo raging, spawn ing and /or nu rsery
hab itat for wild species
Lo ss of biod iversity
Fragmentation of benthic hab itat
Chang e in water qua lity
Mortality o f plankto n (including fish a nd
inv ertebrate egg a nd la rva e)
Increased p rimary productivi ty
Shift in pla nkton commun ity compo sition
Increase in ha rmful algal b loom s
Decline of seagrass meadow s
mediu m
poo r
High
poo r
preda tor control
systems
fish es cap ement
release of un eaten food
and feces
release of nut rients
Level sci
do cument
Commun ities affected
spa tial
scale
typ e of
impa ct
Estimated
recovery o f the
commun ity
Vertebrates
Vertebrates (Fi sh)
Vertebrates
local
local
loc/int
neg
un id
neg
mediu m
un identified
un identified
Vertebrates
loc/int
neg
un identified
Vertebrates
va rious (probab ly fish)
Vertebrates (Fi sh)
Vertebrates (Fi sh)
loc/int
int/lar
int/lar
int/lar
neg
neg
neg
neg
un identified
un identified
slow
un identified
High
Macrofau na
local
neg
slow
High
va rious
local
neg
slow
High
poo r
poo r
poo r
Macrofau na
va rious
va rious
va rious
local
loc/int
loc/int
local
neg
neg
nrg/po s
neg
slow
slow
rap id
rap id
va rious
Phytop lank ton
va rious
marine plan ts & va rious
indi rectly
va rious
microb es
va rious indirectly
loc/int
loc/int
loc/int
loc/int
nrg/po s
un id
neg
neg
rap id
rap id
rap id
slow
neg
neg
neg
rap id
un identified
un identified
neg
neg
neg
un identified
un identified
un identified
neg
neg
un identified
un identified
poo r
poo r
poo r
poo r
poo rmediu m
poo r
poo r
poo r
an tibiotics
Ta inting of wild s pecies
Chang es in b enthic ba cterial commun ity
Res istan t microb ial strains
pesticides
Direct mortality an d sub letha l effects
Ta inting of wild s pecies
Direct mortality an d sub letha l effects
poo r
poo r
poo r
inv ertebrates
va rious
inv ertebrates
local
local
unkn o
wn
local
local
local
Ta inting of wild s pecies
Chang es in phy siology
poo r
poo r
inv ertebrates
inv ertebrates
loc/int
loc/int
disinfectan ts and
an tifou lants
(modified after Milowski 2001)
Posidonia protects the seabed
from errosion
Posidonia rhizomes
Plagiotropic rhizome
Orthotropic rhizome
Posidonia: provides shelter to
juvenile fish and many manire
invertebrates
Spp reproducing in P. oceanica meadows
Lithignathus mormyrus
Sparus auratus
Oblada melanura
Sapra sapra
Paracentrotus lividus
Symphodus roissali
Antedon mediterraneus
Murena helena
Conger conger
Lichia amia
Seriola dumerili
Mullus surmuletus
Under anthropogenic
pressure Posidonia meadows
easily become degraded
… so that its past presence
can only be detected by
rhizomes left on the seabed
High turbidity in the water
column is known to adversely
affect Posidonia
The reduced availability of
light reduces the potential
space for colonization by
Posidonia to a more and
more narrow coastal zone
During recent years it has been
reported that Posidonia oceanica faces
strong copetition by Caulepa taxifolia
C. taxifolia is an alien
species that recently
invaded W. Mediterranean.
It has no local grazers or
other means to control its
population and it excludes
P. oceanica from coastal
waters when established
there
Why Posidonia is of vital
importance
n Mediterranean endemic (in need of protection under the Habitat
Directive)
n a nursery ground for several species
n provides important services for coastal marine ecosystems (3D
habitat for several invertebrate species)
n it stabilises the sandy beaches in the littoral zone
n under increasing pressure due to anthropogenic effects (pollution,
trawling, harbour constructions etc)
n under increasing pressure due to nutrient enrichment of the coastal
zones and flourish of fast growing macroalgae, e.g. Cladophora spp.,
Caulerpa sp.
Posidonia meadows as
fish farming sites
n
n
n
The habitat of P. oceanica (coarse sediment
and strong currents) is “ideal” for fish farming
since:
it allows rapid dispersion of solute wastes
minimal accumulation of particulates and
excellent oxygenation of the water
Posidonia is stressed
at farming sites
However f/f causes adverse
effects on Posidonia by:
n reducing penetration or availability of light
•
•
•
•
immediately under the cages (shadow effect)
due to increased phytoplankton biomass
due to increased suspended particulates
by favouring the growth of epiphytes on Posidonia leaves
n competition with fast growing macroalgae
n accumulation of OM in the sediments
n increasing NH4 and H2S in the sediments
Posidonia: primary production near
and far from fish farms
Reference
station
Changes in pp by
an order of
magnitude
Farm sites
Cancemi et al. (2003) Estuar
coastal shelf Sci vol56
MedVeg sampling sites
MedVeg: sampling design
MedVeg Report 2005, unpublished data
MedVeg fluxes measured with sediment traps
Sounion
Flux P=0.10*x-0.59
MedVeg Report 2005, unpublished data
Alicante
Flux P=0.26*x-0.41
MedVeg Bioassays
MedVeg Bioassays
* * **
* * *
* * **
* * *
Control site
MedVeg Report 2005, unpublished data
* signif different from control site
MedVeg Bioassays - Ulva
**
****
*** *
Control site
MedVeg Report 2005, unpublished data
* signif different from control site
MedVeg: Posidonia mortalities with
distance
MedVeg Report 2005, unpublished data
MedVeg: Posidonia mortalities with
sedimentation rate
Mortality
increases
rapidly beyond
the
sedimentation
rate of 6g m-2 d-1
MedVeg Report 2005, unpublished data
MedVeg: Posidonia density & cover
Decrease close
to the farms
MedVeg Report 2005, unpublished data
MedVeg: Posidonia biomass
MedVeg Report 2005, unpublished data
Decrease close
to the farms
MedVeg recomendations-2
n If monitoring studies indicate a decrease in seagrass meadow extension or
shoot density, the amount of waste material (as C, N and P loads) must
decrease for a equivalent percentage until recovery of the previous
conditions. Alternatively, cages should be moved to other sites, according to
guidelines reported above.
n Concessionaires must present a plan for the monitoring of possible pressures
and damages to seagrass beds and include this in the Environmental Agenda
for certification ISO14000 and EMAS (Eco-Management and Audit Scheme).
n A suitable monitoring program must use reliable techniques and include
quality control procedures, and should be based on the rapid assessment
techniques as described below
MedVeg descriptors/indicators:
at individual plant level
n Morphometric descriptors
shoot biomass, expressed as the average dry weight of at
least ten replicates shoots
n Physiological descriptors
total phosphorus content in different tissues, specifically
young leaves and rhizomes, expressed as % of dry weight.
total non-structural carbohydrates reserves in rhizomes,
expressed as % of dry weight
elemental sulphur content (as μmol per g dry weight) in
roots.
MedVeg descriptors/indicators:
n At population level
shoot density, based in counting the number of shoots inside
patches of Posidonia oceanica and expressed as the number
of shoots per square meter .
n At community level
epiphyte biomass, expressed as the dry weigh of epiphytes in
relation of the size of the shoots.
sea-urchin density, based on counting the number of
individuals inside patches of Posidonia oceanica and
expressed as the number of individuals m-2
However...
n Our results do not mean that any fish farming activity should be banned at
distance less than 800m from any Posidonia oceanica plant in the Mediterranean.
n However, adopting this distance could be an appropriate precautionary measure in
the vicinity of important and well-developed Posidonia meadows that
environmental authorities have set as priority areas for conservation.
n Whenever a fish farm is located in the vicinity of seagrass meadows, the health of
the seagrass meadow should be annually monitored.
n Working definitions of the term "Posidonia meadow" should be harmonised among
Mediterranean countries and common standards are set regarding priorities for
conservation of such meadows.
n Otherwise, it is likely that MedVeg recommendations will be enforced differently in
different member states and other Mediterranean countries thereby resulting in
both inadequate environmental protection and in violating equal terms of
competition within aquaculture industry.
Mass balance models
Source
Species
Harvested
(%)
N
Tot wasted
(%)
P
P
73
N
Hall et al., 1992
trout
Holby & Hall, 1991
trout
Gowen & Bradbury, 1987
salmon
25
Folke & Koutsky, 1989
salmonids
25
Ballestrazzi et al., 1994
seabass
Dosdat et al., 1996
seabass
Krom et al., 1985
seabream
36
Porter et al., 1987
seabream
30
70
60
Krom et al., 1995
seabream
25
75
60
Dosdat et al., 1996
seabream
Lanari et al., 1999
seabass
Kaushik, 1998
seabass
45-55
45-55
Kaushik, 1998
seabream
51-63
38-49
Lupatsch & Kissil, 1998
seabream
Lemar ié et al., 1998
Wallin & Ha akanson, 1991
18
50
82
75
23
75
64
34
52
77
77
29
P
62
11
31-34
17-29
43-47
71
43-55
18-21
25-41
79-82
59-75
22
29
78
71
61
19
seabass
12-17
14-42
93-98
58-86
61-80
24-42
various spp
21-30
15-30
70-79
70-85
49-60
16-26
77
82
49
15
Working figures max
Karakassis et al. (2005) Sci Mar vol 69
28
N
Dissolved
(%)
min
Land-based tanks
Diel high frequency sampling experiments on fluxes of
Nutrients
input
output
POC
PON
Bacteria
tanks containing
different fish sizes
(1, 31 & 53gr)
Tsapakis, Pitta, Karakassis (2006) Aquat. Liv. Resour vol 19
sea bass
Nutrient dynamics
Fish size: 1gr
Significant difference and
Diel pattern in discharge
Tsapakis, Pitta, Karakassis (2006) Aquat. Liv. Resour vol 19
POC and PON dynamics
Significant difference and
Diel pattern in discharge
Tsapakis, Pitta, Karakassis (2006) Aquat. Liv. Resour vol 19
N & P mass balance: % losses over feed input
Fish Size
(gr)
PON
(%)
NH4
(%)
PO4
(%)
1
7
21
13
31
5
29
16
53
7
27
13
Average
6
26
14
Tsapakis, Pitta, Karakassis (2006)
Aquat. Liv. Resour vol 19
Fine particulate material settling
at very slow rates and over larger
distance from the discharge points
However
Several studies have failed to detect significant changes
in dissolved nutrients, Chl-a and POC concentrations
even at fairly short distance from the cages (Pitta et al
1998, La Rosa et al., 2002, MEDVEG unpublished data,
Soto & Norambuena 2004)
This paradox might be due to:
 The dispersive nature of the sites (nutrients are rapidly
diluted)
 Inefficient sampling (concentrations vs fluxes)
 Intensive grazing and transfer to higher trophic levels
 Combination of the above

Chl a (mg l-1)
Grazing experiment in Crete
using dialysis chambers
8
filtered
6
Chlorella
unfiltered
4
2
0
0
30
80
200
Distance (m)
Karakassis et al. (submitted)
>500
Analyses








Local Fisheries landings :time series analysis
Environmental: OC, Chla, Nutrients
Fish: Species, Abundance + Biomass per species,
diversity, biodiversity, LF, age, condition factor,
fecundity, G Index, stomachs, lipids, proteins
Mega: S, A + B per species, diversity, biodiversity
Macro: S, A, B total, diversity
Bacteria: Counts
Micro zoo + Phytoplankton: S, A, B (total), diversity
Fish spatial structure: geostatistics
Fish communities
The communities differed firstly according the
substrate and secondly according to fish-farms
presence.
The effect of fish-farm presence was mainly
quantitative
No significant differences in diversity or
biodiversity indices (taxon. distinctness etc)
Abudance
Biomass
Stress: 0.16
Stress: 0.16
Far
Near
Far
Far
Near
Near
Fish communities
 The total abundance
and biomass was higher
near to fish farms in
May – and fairly similar
in the recruitment period
in September.
 It seems that during
the recruitment period
all sites (Near and Far)
are stocked with fish
close to the carrying
capacity
Effects on Landings
Total Landings
s Farm Production
Effects on Landings: MAFA analysis
A
0 .4
B
1
2
0.5
1
2
0
Scores
Scores
Chios
0 .2
0
-0 .2
-0 .4
5
10
15
5
10
T im e
15
T im e
0.4
0.2
Scores
0 .2
Scores
Chalkis
0 .4
0
0
-0 .2
-0 .2
5
10
15
5
T im e
10
15
The correlation between the size of the fishing
fleet & the landings trend could be coincidental:
due to a clear declining trend because of a
vessel withdrawal policy
Rainfall & Temperature did not show any
correlation with the common trend (except Chios)
fish-farming production related to an increase
of local fisheries landings
T im e
Time
1
0 .4
2
Scores
Scores
Patra
0 .2
0
-0 .2
-0 .4
5
10
15
T im e
Scores
Kavala
0.2
0
Patra
-0 .2
-0 .4
5
10
15
T im e
1
Kav
0
Alex
Scores
Alexandroupolis
2
-0 .5
Chios
5
10
15
T im e
Time
Chal
Response
Explanatory Variables
Landings
Fishing
Fleet
+
+
+
-
Rain
(0)
(0)
(0)
+
(0)
Temp.
Fish
culture
(0)
(0)
(0)
(0)
(0)
(0)
(0)
(0)
+
+
AQCESS conclusions
 No change in macrofauna
 Small changes in megafaunal biomass
 Big change in fish abundance and biomass documented
through:




Before-after study: Machias et al 2004, ECSS, v. 60
Near-far study: Machias et al 2005, MEPS, v. 288
Landings: Machias et al. (2006) Aquaculture v. 261
Hydroacoustics: Giannoulaki et al. 2005, JMBA UK v. 85
 FAD effect? No, the list of species (<30 spp)
aggregating near the cages are known (Dempster et al
2002 MEPS for W. Med, Smith et al submitted from the
E. Med). Not the ones increasing in the above studies
AQCESS conclusions



Not all benthic communities respond in the
same way to disturbance
Large long living animals could be more
efficient means for monitoring subtle changes
The most possible explanation is the rapid
transfer of nutrients up the food web in a
nutrient-starving environment
sediment: horizontal changes
current
4
Eh (mV)
TON (%)
TOC (%)
Cephalonia
600
0.3
0.2
Nov.
150
0.1
1
July
300
2
0
0
4
April
450
3
0.0
contr -100 -50
Ithaki
-25
0
5
10
25
50
100
contr -100
-50
-25
0
5
10
25
50
100
0.3
-150
600
contr -100
-50
-25
0
5
10
25
50
100
contr -100
-50
-25
0
5
10
25
50
100
contr -100
-50
-25
0
5
10
25
50
100
450
3
0.2
300
2
150
0.1
1
0
0
0.0
contr -100
4
-50
-25
0
5
10
25
50
100
Sounion
contr -100
-50
-25
0
5
10
25
0.3
3
50
100
600
April
July
Nov
0.2
450
300
2
150
0.1
1
-150
0
-150
0.0
0
contr -100
-50
-25
0
5
10
25
50
100
Karakassis et al. (2000) ICES J mar sci 57
contr -100
-50
-25
0
5
10
25
50
100
Meta-analysis of benthic effects
aut ho rs
Angel et a l.
Karakassis et a l.
Katavic and Antolic
Karakassis et a l.
Mirto et al.
Molina- Dominguez et al.
La Ro sa e t al.
Yokoyama
Angel and Spanier
Belias et al.
Gowe n et al.
Rosenth al and Rangeley
Ritz et al.
Hall et al.
Weston
Kupka- Hansen et al.
Lauren- Maatta et al.
Uotila
Holby a nd Hall
Ye et al.
Holmer and Kristensen
Hall et al.
Hargrave et al.
Holby a nd Hall
Johnsen et a l.
Findlay et al.
Black et al.
Findlay and Watling
Hargrave et al.
Morrisey et al.
Kraufvelin et al.
Pohle et al.
He ilskov and Holme r
Wildish et a l.
Cromey et al.
Kempf et al.
Wildish et a l.
Nickell et al.
Brooks et al.
Pocklington et a l.
Cheshirel et al.
yea r
1995
1999
1999
2000
2000
2001
2001
2002
2002
2003
1988
1989
1989
1990
1990
1991
1991
1991
1991
1991
1992
1992
1993
1993
1993
1995
1996
1997
1997
2000
2001
2001
2001
2001
2002
2002
2003
2003
2003
1994
1996
reg ion
Red Se a, J ordan
Mediterranean, Greece
Mediterranean, Cr oatia
Mediterranean, Greece
Mediterranean, It aly
Atlantic, Spain
Mediterranean, It aly
Pacific, J apan
Red Se a, Israel
Mediterranean, Greece
Atlantic, Scotland
Atlantic, Canada
Pacific, Australia
Baltic, Swed en
Pacific, USA
Atlantic, No rway
Baltic, F inland
Baltic, F inland
Baltic, Swed en
Pacific, Australia
Atlantic, De rmark
Baltic, Swed en
Atlantic, Canada
Baltic, Swed en
Atlantic, No rway
Atlantic, USA
Atlantic, Scotland
Atlantic, USA
Atlantic, Canada
Pacific, New Zealand
Baltic, F rance
Atlantic, USA
Atlantic, De rmark
Atlantic, Canada
Atlantic, Scotland
Atlantic, France
Pacific, Australia
Atlantic, Scotland
Pacific, Ca nada
Atlantic, Canada
Pacific, Australia
# ff
1
3
1
3
1
1
1
2
1
3
2
1
1
1
1
1
4
1
1
1
1
1
1
1
1
1
2
3
1
1
2
3
1
1
2
1
2
1
2
4
1
farme d
o rganis m
de pt h
(m)
Sed ime nt ty pe
bream- bass
bream- bass
bream- bass
bream- bass
bream- bass
bream- bass
bream- bass
bream- bass
bream- bass
bream- bass
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Salmonidae
Tuna
15- 35
20- 40
23
20- 40
10
20
10
14 - 23
20
9- 42
20- 25
9
fine sand
mud, coarse sand
sand
mud, coarse sand
silty sand
sand
silty sand
silty sand
20
16
7- 20
7- 20
8
20
12
5
20
13
20
13- 18
16
16- 33
11- 15
14
26
5- 25
13
5
20
15- 22
ro cky, mud
mud, coarse ( gravel)
mud
mud
sand
sand
mud
fine sand
mud
mud
mud
fine sand
silty sand
mud, sand
silty sand, coarse
mud
silty sand
mud
mud
mud
silty sand
mud
mud
sand
mud
Kalantzi &
Karakassis (2006)
Mar. Pollut. Bull
vol 52
Meta-analysis of benthic effects
Table 4. Results of mult iple stepwise regression for all data points comp rising all sedime nt types ( *
p<0,05, ** p<0,01, *** p<0,005)
Co nstant
Variable
TOC
LOI
TON
EH2,4CM
O2BENT
DOBOT
SHANNON
EVENNESS
NUMSP
LNABUND
LNBIOM
LND IST
Dep th
coefficient p coefficient p coefficient p
- 0,086***
- 0,023- 0,017***
118,100- 30,674- 18,506*
3,314***
15,171***
75,602***
13,078***
4,412***
- 0,006***
- 0,014***
- 0,001***
24,226***
- 15,749***
0,439***
0,233***
0,175***
Latit ude
Num ber
of
%
coefficient p sam ple s varian c e
0,00044 0,00015***
3,876*
0,475*
0,076***
- 0,163***
0,950***
- 0,067***
- 0,060***
Kalantzi & Karakassis (2006) Mar. Pollut. Bull vol. 52
0,003***
0,004***
0,00043***
- 3,816*
3,2950,238***
- 0,068***
- 0,216***
- 1,339***
- 0,074***
218
109
172
161
79
50
161
109
180
214
123
36,1
43,5
25,8
22,5
9,5
26,2
68,6
26
51,2
6,4
20
Meta-analysis of benthic effects
Table 4. Results of mult iple stepwise regression per sediment ty pe (* p<0.05, ** p<0.01, *** p<0.005)
variable
Co n s ta nt
Coeff. t p
LNDIST
Coeff p
De p th
Coeff p
0.050 **
0.010 ***
- 0.021 20.054 ***
11.200 ***
3.172 -
- 0.006 ***
- 0.001 - 0.00022 ***
0,088 ***
- 0.125 ***
0.032 ***
4.464 ***
205.105 ***
2.604 - 3.311 *
- 0.004 *
- 0.001 ***
0.386 ***
6.314 **
0.287 ***
0.763 ***
- 0.055 ***
- 0.042 ***
86.015 **
52.135 ***
- 33.543 - 42 .622 *
- 0.002 ***
- 0.00019 ***
0.391 ***
4.922 - 0.501 ***
- 0.463 ***
Lat itu de
Coeff
p
Num be r o f
s ampl es
%
varianc e
90
42
65
22
22
20
27.6
55.1
77.9
37.2
12.1
65.8
84
81
67
28
77
41
58.7
58.8
49 .1
54 .6
21.5
67.3
63
55
24
24
24
24
78.9
44. 2
46
10.4
71.4
73.6
Mu dd y
se d im en t
TOC
TON
SHANNON
NUMSP
LOGA BU
LOGBIOM
0.314 ***
5.514 ***
0.185 -
- 0,119 - 0.149 **
0,001 ***
- 0.0004 *
0.078 *
S an dy
se d im en t
TOC
TON
SHANNON
NUMSP
LOGA BU
LOGBIOM
0.010 ***
0.002 ***
- 0.001 ***
- 0.078 ***
- 11.222 ***
- 0.287 ***
0.131 ***
0.221 ***
Co ar se
se d im en t
TOC
TON
SHANNON
NUMSP
LOGA BU
LOGBIOM
0.0004 *
0.002 ***
0.001 ***
- 2.186 *
0.055 0.041 -
1.110 1.205 *
Sediment profiling imagery (SPI):
an «inverted periscope»
camera
glass
mirror
SPI images beneath fish farms
UF
CH4 or H2S
Bg
FS
FS
BLT
BLT
BT
Source: Karakassis, Tsapakis, Smith, Rumohr. (2002) Mar Ecol Prog Ser, 227
Multivariate analysis of SPI data
October
February
July
Euclidean distance
fauna
Oct
Comparisons
between
multivariate
patterns
Fauna October
Fauna February
Fauna July
SPI October
SPI February
SPI July
Feb
SPI
July
Oct
Feb July
1
0.903
1
0.794 0.770
1
-0.927 -0.782 -0.794
1
-0.939 -0.927 -0.685 0.818
1
-0.442 -0.527 -0.794 0.358 0.467
Source: Karakassis, Tsapakis, Smith, Rumohr. (2002) Mar Ecol Prog Ser 227
1
Minimizing monitoring requirements
All correlation coefficient values were significant (p<0.001)
Lampadariou, Karakassis, Pearson (2005) Mar. Pollut Bull vol 50
Modelling spatial patterns of settling particles
DEPOMOD -> MERAMOD
A tool for prediction of benthic degradation
High correlation between predicted and observed
sedimentation
High correlation between predicted sedimentation and
macrofaunal diversity
Cromey et al. in preparation
Sedimentation by fish farms
Fish food
94-97 %
P
External
food
Harvest
17-19 %
Juveniles
3-6 %
Fish food
93-95 %
Loss of fish
1-4%
Solute
release
25-30 %
Sedimentation
50-57 %
benthic flux
2-4 %
Sediment accumulation
47-54 %
N
External
food
Harvest
27-28 %
Juveniles
5-7 %
Loss of fish
2-5 %
Sedimentation
23 %
benthic flux
1-3 %
Sediment accumulation
12-20 %
* for trout cage farming in Sweden
by Holby & Hall (1991) and by Hall et al. (1992) MEPS
Solute
release
48 %
Azoic zone
effects on benthos
opportunistic
species peak
transitory
zone
Ecotone
Divers ity
Biomass
Abundance
Distance (temporal or spatial) from
pollution source
anaerobic
sediment
Grossly
polluted
aerobic
sediment
Polluted
Transitory
Normal
Pearson & Rosenberg (1978)
Hierarchical response to stress
Pearson & Rosenberg (1978)
Replacement by different
order,class, phylum
stress
Replacement by different
family
Replacement by different
genus
Replacement by different
species
Replacement by more addapted individuals from
a polymorphic stock
Physiological reponse of the individual
time
Biotic coefficient (BC) - AMBI
n
The BC proposed by Borja et al (2000) distributes species
into various groups depending on their ability to tolearate
disturbence/pllution
•
Group I. Sensitive species, present only in complete
absence of pollution
•
Group II. Indifferent species always present in small
densities without significant fluctuation with time
•
Group III. Tolerant species. they may be found under natural
conditions but their population growth is stimulated under
organic enrichment
•
Group IV. Second stage opportunists. Mainly small-size
subsurface deposit feeders (e.g. Cirratulidae)
•
Group V. First stage opportunists. Deposit feeders thriving
in reduced sediments.
Biotic coefficient (BC)
n
The value of BC is then calculated for every sample based
on the % of each group on total macrofaunal abundance.
BC=
(0xGI)+(1.5xGII)+(3xGIII)+(4.5xGIV)+(6xGV)
100
n
n
n
This index is supported by a software in EXCEL (AMBI) and a data
base providing characterization of >3000 benthic species (www.azti.es)
Borja A, Franco J, Perez V (2000) A marine biotic index to establish the ecological
quality of soft-bottom benthos within European estuarine and coastal environments.
Marine Pollution Bulletin 40:1100–1114.
Muxika I, Borja A, Bonne W (2005) The suitability of the marine biotic index (AMBI)
to new impact sources along European coasts. Ecol. Indic, 5:19–31.
Limits for BC
classification
In terms of pollution
BC
Dominant group Benthic community health
Non polluted
Non polluted
0.0<BC<0.2
0.2<BC<1.2
I
normal
poor
Slightly polluted
Moderately polluted
1.2<BC<3.3
3.3<BC<4.3
III
unbalanced
Transitional to polluted
Moderately polluted
Heavily polluted
4.3<BC<5.0
5.0<BC<5.5
IV-V
Heavily polluted
extremely polluted
5.5<BC<6.0
αζωική
V
αζωική
Borja et al (2000) Mar Pollut Bull 401100–1114.
polluted
Transitional to havily polluted
Heavily polluted
azoic
BENTIX
n
n
n
n
BENTIX (Benthic index) is a variation of BC proposed by
greek scientists (Simboura &, Zenetos 2002)
The difference from BC is that BENTIX recognizes only 3
groups of species and the list of species for which there is
some characterization is not available except the first
edition in Mediterranean Marine Science.
Because BENTIX is calculated giving high scores to
intolerant species low values indicate degradation whereas
high values «pristinity»
Simboura N, Zenetos A. (2002) Benthic indicators to use in
ecological quality classification of Mediterranean soft bottom
marine ecosystems including a new Biotic index. Mediterranean
Marine Science 3:77–111.
BC and BENTIX
n
n
n
n
n
Both methods are based on subjective judjment on the ecological role
of benthic species
Their use needs communication with the authors (direct or indirect
through their web page) and up to a point confidence in their oppinion.
The role of each species and the assignment of one group is inflexible
and is given only once.
There is no agreed procedure for revising the classification of a species
in the groups of each index
The thershod values assigned are more or less arbitrary.
Benthic quality index (BQI)
n
n
n
n
n
BQI (proposed by Rosenberg et al 2004) is somehow different
than the previous indices.
Species are not divided into categories but they receive a score
depending on their disdtribution in a set of samples
The index is based on the assumption that opportunistic species
are primarily found in stations/samples with low diversity
whereas the «normal» or sensitive species in stations/samples
with increased diversity.
Therefore if the distribution of a species is determined over a
series of samples covering a wide range of diversity then the
distribution pattern will vary from species to species depending
on their sensitivity or tolerance.
Rosenberg R, Blomqvist M, Nilsson HC, Cederwall H, Dimming A (2004)
Marine Pollution Bulletin 30 (7), 470 –474
Calculation of ES500.05
The shaded area includes
the 5% of the total
abundance of the species
which is related to low
diversity stations
disturbed
undisturbed
Rosenberg R, et al. (2004).
Mar Pollut. Bull. 30:470 –474
Calculation of ES500.05 for various species
Low values: tolerant species, High values: sensitive species
Χαμηλές τιμές: ανθεκτικά είδη, Υψηλές τιμές: ευαίσθητα είδη
Rosenberg R, et al. (2004). Mar Pollut. Bull. 30:470 –474
Benthic quality index (BQI)
n
After calculating ES500.05 for each species, BQI is
calculated for each sample:
BQI=
(
n
Σ ( tot A
i=1
------Ai
x ES500.05
)
)
x 10log(S+1)
BQI and sediment condition
SPI images
Condition in relation to
Pearson & Rosenberg
1978
Thresholds and
sediment quality
Rosenberg R, et al. (2004). Mar Pollut. Bull. 30:470 –474
Hypotheses to test
n
n
n
n
n
Do all these indices describe the conditions
similarly?
Are they intercorrelated?
Do they depend on sieve size?
Do they depend on season?
Do they assign the same environmental quality to
the samples examined?
n
Highly correlated
y=1.0*x
n
Good news !
n
Values at 1.0 mm
Sieve size
Values at 0.5 mm
season
n
Highly inter- correlated for most indices
Relatively Good news !
0.9
Spearman rank correlation
n
0.8
0.7
0.6
0.5
0.4
July-Sept (0.5mm)
0.3
July Feb (0.5mm)
0.2
0.1
0.0
Shannon
BQI
Benthix
index
S
BC
ES10
L+
D+
Do they intercorrelate?
n
n
n
Highly inter- correlated (p<0.01) for most indices
Relatively Good news !
So we can chose any of them without worrying?
ES10
H'
DELTA
LAMBDA
AMBI
BENTIX
BQI
ES10
H'
1
0.970
0.457
-0.238
-0.740
0.739
0.891
1
0.480
-0.287
-0.764
0.735
0.918
DELTA+ LAMBDA+ AMBI BENTIX
1
-0.616
-0.541
0.431
0.517
1
0.344
1
ns -0.810
-0.296 -0.791
1
0.807
BQI
1
How similar they are?
n
Using the correlation matrix we can run an MDS
and obtain similarities among indices
Stress:0.01
H’
BQI
L+
D+
AMBI
BENTIX
Do they agree in Environmental status?
n
n
Well… No
In fact they reach a «consensus» in 4% of the
samples and they had 3-4 different «verdicts» in
39% of the samples
bad
poor
moderate
good
high
Are there consistently easy-to-pass
and difficult ones?
n
n
Yes BENTIX and H’ tend to show more High and Good
quality
BQI tends to show (reveal?) more Bad and Poor conditions
furthermore
n
n
The Pearson & Rosenberg model works well with
silty sediments
For coarse sediments it is possible to have a
“healthy picture” despite the fact that
environmental degradation may have severely
affected other components of the ecosystem.
Χαρακτηριστικά των
ιχθυοτροφείων στο δείγμα
30
depth
90
silt
80
Βάθος (m) depth
25
70
20
60
50
15
40
10
30
20
5
10
0
0
130
260
300
300
309
366
400
432
Παραγωγή (τόνοι/έτος)
Production (tn/year)
443
1094
1150
% ιλύος αργίλου
(% silt-clay)
(fish farms characteristics)
Αριθμός ειδών
(species number)
0m
100
# species
10
Minimum=5spp
1
0
200
400
600
800
1000
25m
1000
1200
25m
100
10
Minimum=32spp
1
0
200
400
600
800
Παραγωγή (τόνοι/έτος)
Production (tn/year)
1000
1200
Μέσος αριθμός ειδών
μέσος αριθμός ειδών
Average # species
(average species number)
160
140
120
100
80
60
40
20
0
0m
5m
10m
Απόσταση
25m
50m
Distance
control
H’ (bits)
Δείκτης Shannon
(Shannon index)
7
6
5
4
3
2
1
0
0m
0
200
400
600
800
1000
7
6
5
4
3
2
1
0
1200
25m
0
200
400
600
800
Παραγωγή (τόνοι/έτος)
Production (tn/year)
1000
1200
H’ (bits)
Δείκτης Shannon
(Shannon index)
7
6
5
4
3
2
1
0
0m
5m
10m
Απόσταση
25m
50m
Distance
control
Δείκτης Bentix
(BENTIX index)
6
0m
5
4
3
Poorbad
2
Bentix index
1
0
0
200
400
600
800
1000
1200
25m
6
5
4
3
2
1
0
Poorbad
0
200
400
600
800
Παραγωγή (τόνοι/έτος)
Production (tn/year)
1000
1200
Δείκτης AMBI
(AMBI index)
7
6
0m
5
Poor-bad
4
3
2
1
AMBI index
0
0
200
400
600
800
1000
1200
25m
5
4
3
2
1
0
0
200
400
600
800
Παραγωγή (τόνοι/έτος)
Production (tn/year)
1000
1200
Poor-bad
Δείκτης AMBI σε όλα τα δείγματα
(AMBI index, all samples & stations)
κατηγορίες (%)
AMBI categories (%)
100%
90%
80%
70%
60%
High
Good
50%
40%
30%
Moderate
20%
10%
Bad
Poor
0%
0
5
10
25
50
ctrl
Απόσταση (m) Distance
Δείκτης Shannon σε όλα τα δείγματα
(H’ index, all samples & stations)
90%
κατηγορίες (%)
Shannon categories (%)
100%
80%
70%
High
60%
50%
Good
40%
Moderate
30%
Poor
20%
Bad
10%
0%
0
5
10
25
50
ctrl
Απόσταση (m) Distance
Δείκτης BENTIX σε όλα τα δείγματα
(BENTIX index, all samples & stations)
90%
κατηγορίες (%)
BENTIX categories (%)
100%
80%
70%
High
60%
Good
50%
40%
Moderate
30%
Poor
20%
Bad
10%
0%
0
5
10
25
50
ctrl
Απόσταση (m) Distance
Thank you