Effects of aquaculture on Mediterranean marine ecosystems
83
Effects of aquaculture on Mediterranean marine ecosystems I. Karakassis, D. Angel
description
Effects of aquaculture on Mediterranean marine ecosystems. I. Karakassis , D . Angel. Effects of aquaculture on marine biotic communities. (modified after Milowski 2001). Posidonia protects the seabed from errosion. Posidonia rhizomes. Plagiotropic rhizome. Orthotropic rhizome. - PowerPoint PPT Presentation
Transcript of Effects of aquaculture on Mediterranean marine ecosystems
Effects of aquaculture on Mediterranean marine ecosystemsEffects of aquaculture on Mediterranean marine ecosystems
I. Karakassis, D. Angel
Source of pressure Potential effect on biota Level scidocument
Communities affected spatialscale
type ofimpact
Estimatedrecovery of thecommunity
physical structure Direct mortality through entanglement poor Vertebrates local neg mediumBehavioral changes in coastal pelagic fish medium Vertebrates (Fish) local unid unidentifiedBehavioral changes in coastal birds andmarine mammals (e.g., avoidance)
poor Vertebrates loc/int neg unidentified
predator controlsystems
Direct mortality poor Vertebrates loc/int neg unidentified
Behavioral changes of wild fauna medium Vertebrates loc/int neg unidentified
fish escapement Disease transmission to other species poor various (probably fish) int/lar neg unidentifiedGenetic interactions with wild fish High Vertebrates (Fish) int/lar neg slowDisplacement of wild fish from naturalhabitat (e.g., through competition,predation)
poor Vertebrates (Fish) int/lar neg unidentified
release of uneaten foodand feces
Suffocation and displacement of benthicorganisms
High Macrofauna local neg slow
Loss of foraging, spawning and/or nurseryhabitat for wild species
High various local neg slow
Loss of biodiversity High Macrofauna local neg slowFragmentation of benthic habitat poor various loc/int neg slow
release of nutrients Change in water quality poor various loc/int nrg/pos rapidMortality of plankton (including fish andinvertebrate egg and larvae)
poor various local neg rapid
Increased primary productivity poor various loc/int nrg/pos rapidShift in plankton community composition poor Phytoplankton loc/int unid rapidIncrease in harmful algal blooms poor various loc/int neg rapidDecline of seagrass meadows poor-
mediummarine plants & variousindirectly
loc/int neg slow
antibiotics Tainting of wild species poor various local neg rapidChanges in benthic bacterial community poor microbes local neg unidentifiedResistant microbial strains poor various indirectly unkno
wnneg unidentified
pesticides Direct mortality and sublethal effects poor invertebrates local neg unidentifiedTainting of wild species poor various local neg unidentified
disinfectants andantifoulants
Direct mortality and sublethal effects poor invertebrates local neg unidentified
Tainting of wild species poor invertebrates loc/int neg unidentifiedChanges in physiology poor invertebrates loc/int neg unidentified
Effects of aquaculture on marine biotic communities
(modified after Milowski 2001)
Posidonia protects the seabed from errosionPosidonia protects the seabed from errosion
Posidonia rhizomesPosidonia rhizomes
Plagiotropic rhizome
Orthotropic rhizome
Posidonia: provides shelter to juvenile fish and many manire invertebrates
Posidonia: provides shelter to juvenile fish and many manire invertebrates
Spp reproducing in P. oceanica meadows
Lithignathus mormyrusSparus auratus
Oblada melanuraSapra sapra
Paracentrotus lividusSymphodus roissali
Antedon mediterraneusMurena helenaConger conger
Lichia amiaSeriola dumerili
Mullus surmuletus
Under anthropogenic pressure Posidonia meadows easily become degraded
Under anthropogenic pressure Posidonia meadows easily become degraded
… so that its past presence can only be detected by rhizomes left on the seabed
… 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
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
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
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
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
Mediterranean endemic (in need of protection under the Habitat Directive)
a nursery ground for several species provides important services for coastal marine ecosystems
(3D habitat for several invertebrate species) it stabilises the sandy beaches in the littoral zone under increasing pressure due to anthropogenic effects
(pollution, trawling, harbour constructions etc) under increasing pressure due to nutrient enrichment of the
coastal zones and flourish of fast growing macroalgae, e.g. Cladophora spp., Caulerpa sp.
Mediterranean endemic (in need of protection under the Habitat Directive)
a nursery ground for several species provides important services for coastal marine ecosystems
(3D habitat for several invertebrate species) it stabilises the sandy beaches in the littoral zone under increasing pressure due to anthropogenic effects
(pollution, trawling, harbour constructions etc) 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
The habitat of The habitat of P. oceanicaP. oceanica (coarse sediment (coarse sediment and strong currents) is “ideal” for fish farming and strong currents) is “ideal” for fish farming since:since:
it allows rapid dispersion of solute wastesit allows rapid dispersion of solute wastes minimal accumulation of particulates and minimal accumulation of particulates and excellent oxygenation of the waterexcellent oxygenation of the water
Posidonia is stressed at farming sites
However f/f causes adverse effects on Posidonia by:
reducing penetration or availability of light reducing penetration or availability of light • immediately under the cages (shadow effect)immediately under the cages (shadow effect)• due to increased phytoplankton biomassdue to increased phytoplankton biomass• due to increased suspended particulatesdue to increased suspended particulates• by favouring the growth of epiphytes on by favouring the growth of epiphytes on PosidoniaPosidonia
leavesleaves competition with fast growing macroalgae competition with fast growing macroalgae accumulation of OM in the sedimentsaccumulation of OM in the sediments increasing NHincreasing NH44 and H and H22S in the sedimentsS in the sediments
Posidonia: primary production near and far from fish farmsPosidonia: primary production near and far from fish farms
Cancemi et al. (2003) Estuar coastal shelf Sci vol56
Reference station
Farm sites
Changes in pp by an order of magnitude
MedVeg sampling sites
MedVeg: sampling design MedVeg: sampling design
MedVeg Report 2005, unpublished data
MedVeg fluxes measured with sediment traps
SounionFlux P=0.10*x-0.59
AlicanteFlux P=0.26*x-0.41
MedVeg Report 2005, unpublished data
MedVeg BioassaysMedVeg Bioassays
MedVeg BioassaysMedVeg Bioassays
MedVeg Report 2005, unpublished data
* * * * * * ** * ** * * *
Control siteControl site
* signif different from control site
MedVeg Bioassays - UlvaMedVeg Bioassays - Ulva
Control siteControl site
* signif different from control site
MedVeg Report 2005, unpublished data
* * * * * * * * * *
MedVeg: Posidonia mortalities with distance MedVeg: Posidonia mortalities with distance
MedVeg Report 2005, unpublished data
MedVeg: Posidonia mortalities with sedimentation rate MedVeg: Posidonia mortalities with sedimentation rate
MedVeg Report 2005, unpublished data
Mortality increases rapidly beyond the sedimentation rate of 6g m-2 d-1
Mortality increases rapidly beyond the sedimentation rate of 6g m-2 d-1
MedVeg: Posidonia density & cover MedVeg: Posidonia density & cover
MedVeg Report 2005, unpublished data
Decrease close to the farms
Decrease close to the farms
MedVeg: Posidonia biomassMedVeg: Posidonia biomass
MedVeg Report 2005, unpublished data
Decrease close to the farms
Decrease close to the farms
MedVeg recomendations-2
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.
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).
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
Morphometric descriptors shoot biomass, expressed as the average dry weight
of at least ten replicates shoots 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:
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 .
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... 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.
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.
Whenever a fish farm is located in the vicinity of seagrass meadows, the health of the seagrass meadow should be annually monitored.
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.
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 modelsMass balance modelsSource Species Harvested
(%)Tot wasted
(%)Dissolved
(%)N P N P N P
Hall et al., 1992 trout 28 73 50
Holby & Hall, 1991 trout 18 82 34
Gowen & Bradbury, 1987 salmon 25 75 52
Folke & Koutsky, 1989 salmonids 25 23 75 77 62 11
Ballestrazzi et al., 1994 seabass 31-34 17-29
Dosdat et al., 1996 seabass 77 43-47
Krom et al., 1985 seabream 36 29 64 71
Porter et al., 1987 seabream 30 70 60
Krom et al., 1995 seabream 25 75 60
Dosdat et al., 1996 seabream 43-55
Lanari et al., 1999 seabass 18-21 25-41 79-82 59-75
Kaushik, 1998 seabass 45-55 45-55
Kaushik, 1998 seabream 51-63 38-49
Lupatsch & Kissil, 1998 seabream 22 29 78 71 61 19
Lemarié et al., 1998 seabass 12-17 14-42 93-98 58-86 61-80 24-42
Wallin & Haakanson, 1991 various spp 21-30 15-30 70-79 70-85 49-60 16-26
Working figures max 77 82
min 49 15Karakassis et al. (2005) Sci Mar vol 69
Land-based tanksLand-based tanks
input output
Diel high frequency sampling experiments on fluxes of
Nutrients
POC
PON
Bacteria
tanks containing different fish sizes (1, 31 & 53gr)
Diel high frequency sampling experiments on fluxes of
Nutrients
POC
PON
Bacteria
tanks containing different fish sizes (1, 31 & 53gr)
Tsapakis, Pitta, Karakassis (2006) Aquat. Liv. Resour vol 19
sea bass
NH4
0.02.04.06.08.0
10.0
“M
in
out
NH4
0.02.04.06.08.0
10.0
“M
in
out
0.00.20.40.60.81.01.2
“ķ
PO4
0.00.20.40.60.81.01.2
“ķ
PO4
Nutrient dynamicsNutrient dynamics
Fish size: 1gr
Significant difference and Diel pattern in dischargeSignificant difference and Diel pattern in discharge
Tsapakis, Pitta, Karakassis (2006) Aquat. Liv. Resour vol 19
POC
0
100
200
300
400
11:3
014
:30
17:3
020
:30
23:3
02:
305:
308:
30
“g lt
-1
in
out
POC
0
100
200
300
400
11:3
014
:30
17:3
020
:30
23:3
02:
305:
308:
30
“g lt
-1
in
out
PON
0
20
40
60
11:3
014
:30
17:3
020
:30
23:3
02:
305:
308:
30
“g lt
-1
in
out
PON
0
20
40
60
11:3
014
:30
17:3
020
:30
23:3
02:
305:
308:
30
“g lt
-1
in
out
POC and PON dynamicsPOC and PON dynamics
Significant difference and Diel pattern in dischargeSignificant difference and Diel pattern in discharge
Tsapakis, Pitta, Karakassis (2006) Aquat. Liv. Resour vol 19
N & P mass balance: % losses over feed
input
N & P mass balance: % losses over feed
input
14141414
13131313
16161616
13131313
POPO4 4
(%)(%)
POPO4 4
(%)(%)
262626266666AverageAverageAverageAverage
27272727777753535353
29292929555531313131
2121212177771111
NHNH4 4
(%)(%)
NHNH4 4
(%)(%)PON PON (%)(%)
PON PON (%)(%)
Fish Size Fish Size (gr)(gr)
Fish Size Fish Size (gr)(gr)
Fine particulate material settling at very slow rates and over larger distance from the discharge points
Fine particulate material settling at very slow rates and over larger distance from the discharge pointsTsapakis, Pitta, Karakassis (2006)
Aquat. Liv. Resour vol 19
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
However However
Grazing experiment in Creteusing dialysis chambers
00 3030 8080 200200 >500>500
Distance (m)Distance (m)
00
22
44
66
88 filteredfiltered
ChlorellaChlorella
unfilteredunfiltered
Ch
l a (g
l-1)
Ch
l a (g
l-1)
Karakassis et al. (submitted)
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
Abudance
Far
Near
Stress: 0.16
Biomass
Far
Near
Stress: 0.16
Near
Far
May MayMay SeptemberSeptember
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
100
80
60
40
Sim
ilarity
Fish Abudance
L L L E E E E E E L L L C C C C C C E E E C C C L L L L L L C C C E E E
Sim
ilari
ty
Far Far FarNear Near
Fine Coarse
May MayMay SeptemberSeptemberMay MayMay SeptemberSeptemberMay MayMay SeptemberSeptemberMay MayMay SeptemberSeptember
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Mud
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
Maerl
100
80
60
40
Sim
ilarity
Fish Abudance
L L L E E E E E E L L L C C C C C C E E E C C C L L L L L L C C C E E E
Sim
ilari
ty
Far Far FarNear Near
Fine CoarseFine Coarse
Fish Abundance
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)
Fish communities
Fish Abundance
1,9
2,1
2,3
2,52,7
2,9
3,1
3,3
3,5
EN EF LN LF CN CF
May September
Means and 95.0 Percent LSD Intervals
AreaE1L2X3
log(
XW
)
1 2 38
8.3
8.6
8.9
9.2
9.5
9.8
Means and 95.0 Percent LSD Intervals
AreaE1L2X3
log(
XW
)
1 2 37.6
8
8.4
8.8
9.2
9.6
10
Fine
Coarse
May
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 LandingsChios
0
100
200
300
400
500
600
700
800
900
1000
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
Lan
din
gs
(Kg
)
0
500
1000
1500
2000
2500
3000
3500
4000
Fa
rms
Pro
du
cti
on
Landings
Farm Production
Patra
2000000
2200000
2400000
2600000
2800000
3000000
3200000
3400000
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
La
nd
ing
s (
mT
)
Chalkis
0
500
1000
1500
2000
2500
3000
3500
4000
4500
1984
1986
1988
1990
1992
1994
1996
1998
2000
Lan
din
gs
(Kg
)
0
1000
2000
3000
4000
5000
6000
7000
Fa
rms
Pro
du
cti
on
Landings
Farm Production
Kavala
4000000
4500000
5000000
5500000
6000000
6500000
7000000
7500000
8000000
8500000
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
La
nd
ing
s (
Kg
)
Alexandroupolis
1000000
1200000
1400000
1600000
1800000
2000000
2200000
2400000
2600000
2800000
3000000
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
La
nd
ing
s (
Kg
)
Chios
0
100
200
300
400
500
600
700
800
900
1000
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
Lan
din
gs
(Kg
)
0
500
1000
1500
2000
2500
3000
3500
4000
Fa
rms
Pro
du
cti
on
Landings
Farm Production
Patra
2000000
2200000
2400000
2600000
2800000
3000000
3200000
3400000
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
La
nd
ing
s (
mT
)
Chalkis
0
500
1000
1500
2000
2500
3000
3500
4000
4500
1984
1986
1988
1990
1992
1994
1996
1998
2000
Lan
din
gs
(Kg
)
0
1000
2000
3000
4000
5000
6000
7000
Fa
rms
Pro
du
cti
on
Landings
Farm Production
Kavala
4000000
4500000
5000000
5500000
6000000
6500000
7000000
7500000
8000000
8500000
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
La
nd
ing
s (
Kg
)
Alexandroupolis
1000000
1200000
1400000
1600000
1800000
2000000
2200000
2400000
2600000
2800000
3000000
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
La
nd
ing
s (
Kg
) Total LandingsTotal Landings
s Farm Productions Farm Production
Effects on Landings: MAFA analysisP
atra
Kav
ala
Ale
xand
roup
olis
Chi
osC
halk
is
1
2
Time
5 10 15
Score
s
0
0.5
A B
+(0)(0)-Chal
+(0)+-Chios
(0)(0)(0)+Alex
(0)(0)(0)+Kav
(0)(0)(0)+Patra
Fish
culture
Temp.RainFishingFleet
Landings
Explanatory VariablesResponse
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
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
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 changessediment: horizontal changes
0
1
2
3
4
contr -100 -50 -25 0 5 10 25 50 1000.0
0.1
0.2
0.3
contr -100 -50 -25 0 5 10 25 50 100
0
1
2
3
4
contr -100 -50 -25 0 5 10 25 50 1000.0
0.1
0.2
0.3
contr -100 -50 -25 0 5 10 25 50 100
0
1
2
3
4
contr -100 -50 -25 0 5 10 25 50 100
0.0
0.1
0.2
0.3
contr -100 -50 -25 0 5 10 25 50 100
April
July
Nov
Ithaki
Sounion
-150
0
150
300
450
600
contr -100 -50 -25 0 5 10 25 50 100
April July Nov.
-150
0
150
300
450
600
contr -100 -50 -25 0 5 10 25 50 100
-150
0
150
300
450
600
contr -100 -50 -25 0 5 10 25 50 100
TOC (%)TOC (%) TON (%)TON (%) Eh (mV)Eh (mV)current
current
Cephalonia
Karakassis et al. (2000) ICES J mar sci 57Karakassis et al. (2000) ICES J mar sci 57
Meta-analysis of benthic effectsMeta-analysis of benthic effectsauthors year region # ff farmed
organismdepth(m) Sediment type
Angel et al. 1995Red Sea, J ordan 1 bream-bass 15-35 fine sandKarakassis et al. 1999Mediterranean, Greece 3 bream-bass 20-40 mud, coarse sandKatavic and Antolic 1999Mediterranean, Croatia 1 bream-bass 23 sandKarakassis et al. 2000Mediterranean, Greece 3 bream-bass 20-40 mud, coarse sandMirto et al. 2000Mediterranean, Italy 1 bream-bass 10 silty sandMolina-Dominguez et al. 2001Atlantic, Spain 1 bream-bass 20 sandLa Rosa et al. 2001Mediterranean, Italy 1 bream-bass 10 silty sandYokoyama 2002Pacific, J apan 2 bream-bass 14-23 silty sandAngel and Spanier 2002Red Sea, Israel 1 bream-bass 20Belias et al. 2003Mediterranean, Greece 3 bream-bass 9-42 rocky, mudGowen et al. 1988Atlantic, Scotland 2 Salmonidae 20-25 mud, coarse (gravel)Rosenthal and Rangeley 1989Atlantic, Canada 1 Salmonidae 9 mudRitz et al. 1989Pacific, Australia 1 SalmonidaeHall et al. 1990Baltic, Sweden 1 Salmonidae 20 mudWeston 1990Pacific, USA 1 Salmonidae 16 sandKupka-Hansen et al. 1991Atlantic, Norway 1 Salmonidae 7-20 sandLauren-Maatta et al. 1991Baltic, Finland 4 Salmonidae 7-20Uotila 1991Baltic, Finland 1 Salmonidae 8Holby and Hall 1991Baltic, Sweden 1 Salmonidae 20 mudYe et al. 1991Pacific, Australia 1 Salmonidae 12 fine sandHolmer and Kristensen 1992Atlantic, Dermark 1 Salmonidae 5Hall et al. 1992Baltic, Sweden 1 Salmonidae 20 mudHargrave et al. 1993Atlantic, Canada 1 Salmonidae 13 mudHolby and Hall 1993Baltic, Sweden 1 Salmonidae 20 mudJohnsen et al. 1993Atlantic, Norway 1 Salmonidae 13-18 fine sandFindlay et al. 1995Atlantic, USA 1 Salmonidae 16 silty sandBlack et al. 1996Atlantic, Scotland 2 Salmonidae 16-33 mud, sandFindlay and Watling 1997Atlantic, USA 3 Salmonidae 11-15 silty sand, coarseHargrave et al. 1997Atlantic, Canada 1 Salmonidae 14 mudMorrisey et al. 2000Pacific, New Zealand 1 Salmonidae 26 silty sandKraufvelin et al. 2001Baltic, France 2 Salmonidae 5-25Pohle et al. 2001Atlantic, USA 3 Salmonidae 13 mudHeilskov and Holmer 2001Atlantic, Dermark 1 Salmonidae 5 mudWildish et al. 2001Atlantic, Canada 1 Salmonidae mudCromey et al. 2002Atlantic, Scotland 2 SalmonidaeKempf et al. 2002Atlantic, France 1 Salmonidae 20 silty sandWildish et al. 2003Pacific, Australia 2 Salmonidae mudNickell et al. 2003Atlantic, Scotland 1 Salmonidae 15-22 mudBrooks et al. 2003Pacific, Canada 2 Salmonidae sandPocklington et al. 1994Atlantic, Canada 4 Salmonidae mudCheshirel et al. 1996Pacific, Australia 1 Tuna
Kalantzi & Karakassis (2006) Mar. Pollut. Bull vol 52
Meta-analysis of benthic effectsMeta-analysis of benthic effectsTable 4. Results of multiple stepwise regression for all data points comprising all sediment types (*p<0,05, ** p<0,01, *** p<0,005)
Constant LNDIST Depth LatitudeNumber
of %
Variable coefficient p coefficient p coefficient p coefficient p samples variance
TOC -0,086*** -0,006*** 0,00044- 0,003*** 218 36,1LOI -0,023- -0,014*** 0,004*** 109 43,5TON -0,017*** -0,001*** 0,00015*** 0,00043*** 172 25,8EH2,4CM 118,100- 24,226*** 3,876* -3,816* 161 22,5O2BENT -30,674- -15,749*** 3,295- 79 9,5DOBOT -18,506* 0,439*** 0,475* 0,238*** 50 26,2SHANNON 3,314*** 0,233*** 0,076*** -0,068*** 161 68,6EVENNESS 15,171*** -0,163*** -0,216*** 109 26NUMSP 75,602*** 0,950*** -1,339*** 180 51,2LNABUND 13,078*** -0,067*** -0,074*** 214 6,4LNBIOM 4,412*** 0,175*** -0,060*** 123 20
Kalantzi & Karakassis (2006) Mar. Pollut. Bull vol. 52
Meta-analysis of benthic effectsMeta-analysis of benthic effectsTable 4. Results of multiple stepwise regression per sediment type (* p<0.05, ** p<0.01, *** p<0.005)
Constant LNDIST Depth Latitude Number of %variable Coeff. t p Coeff p Coeff p Coeff p samples variance
Muddysediment
TOC 0.050** -0.006*** -0.001- 0,001*** 90 27.6TON 0.010*** -0.00022*** -0.0004* 42 55.1SHANNON -0.021- 0.314*** 0,088*** 65 77.9NUMSP 20.054*** 5.514*** 22 37.2LOGABU 11.200*** -0,119- 22 12.1LOGBIOM 3.172- 0.185- -0.149** 0.078* 20 65.8
Sandysediment
TOC -0.125*** -0.004* 0.010*** 84 58.7TON 0.032*** -0.001*** 0.002*** -0.001*** 81 58.8SHANNON 4.464*** 0.386*** -0.078*** 67 49.1NUMSP 205.105*** 6.314** -11.222*** 28 54.6LOGABU 2.604- 0.287*** 0.131*** 77 21.5LOGBIOM -3.311* 0.763*** -0.287*** 0.221*** 41 67.3
Coarsesediment
TOC -0.055*** -0.002*** 0.002*** 63 78.9TON -0.042*** -0.00019*** 0.0004* 0.001*** 55 44.2SHANNON 86.015** 0.391*** -2.186* 24 46NUMSP 52.135*** 4.922- 24 10.4LOGABU -33.543- -0.501*** 0.055- 1.110- 24 71.4LOGBIOM -42.622* -0.463*** 0.041- 1.205* 24 73.6
Sediment profiling imagery (SPI): an «inverted periscope»
mirrorglass
camera
SPI images beneath fish farmsSPI images beneath fish farms
BgBgCH4 or HCH4 or H22SS
UFUF
FSFS
FSFS
BLTBLTBLTBLT
BTBT
Source: Karakassis, Tsapakis, Smith, Rumohr. (2002) Mar Ecol Prog Ser, 227Source: Karakassis, Tsapakis, Smith, Rumohr. (2002) Mar Ecol Prog Ser, 227
Multivariate analysis of SPI data
SourceSource: Karakassis, Tsapakis, Smith, Rumohr. (2002) : Karakassis, Tsapakis, Smith, Rumohr. (2002) Mar Ecol Prog SerMar Ecol Prog Ser 227 227
February JulyOctober
Euclidean distance
Oct Feb July Oct Feb July
Fauna October 1
Fauna February 0.903 1
Fauna July 0.794 0.770 1SPI October -0.927 -0.782 -0.794 1
SPI February -0.939 -0.927 -0.685 0.818 1SPI July -0.442 -0.527 -0.794 0.358 0.467 1
Comparisons Comparisons between between multivariate multivariate patternspatterns
faunafauna SPISPI
0.00
0.25
0.50
0.75
1.00
Species Genus Family Order Class Phylum
taxonomic resolution
Corers >1mmvanVeen >1mm
Corers combinedvanVeen combined
All correlation coefficient values were significant (p<0.001)
Minimizing monitoring requirements
Lampadariou, Karakassis, Pearson (2005) Mar. Pollut Bull vol 50
Modelling spatial patterns of settling
particles
DEPOMOD -> MERAMOD
Modelling spatial patterns of settling
particles
DEPOMOD -> MERAMODA tool for prediction of benthic degradationHigh correlation between predicted and observed sedimentationHigh correlation between predicted sedimentation and macrofaunal diversity
A tool for prediction of benthic degradationHigh correlation between predicted and observed sedimentationHigh correlation between predicted sedimentation and macrofaunal diversity
Cromey et al. in preparation
Sedimentation by fish farmsSedimentation by fish farms
* for trout cage farming in Swedenby Holby & Hall (1991) and by Hall et al. (1992) MEPS
* for trout cage farming in Swedenby Holby & Hall (1991) and by Hall et al. (1992) MEPS
Fish food 94-97 %
Loss of fish 1 - 4 %
Sedimentation
External food
Solute release
25-30 %
Sediment accumulation 47-54 %
benthic flux 2-4 %
50-57 %
P Juveniles 3-6 %
Harvest 17-19 %
Fish food 93-95 %
Loss of fish 2-5 %
Sedimentation
External food
Solute release 48 %
Sediment accumulation 12-20 %
benthic flux 1-3 %
23 %
N Juveniles 5-7 %
Harvest 27-28 %
effects on benthoseffects on benthos
AbundanceBiomassDiversity
Distance (temporal or spatial) from pollution source
Ecotone
transitory zone
opportunistic species peak
Azoic
zon
e
aerobic sediment
Grossly polluted
Polluted Transitory Normal
anaerobic sediment
Pearson & Rosenberg (1978)Pearson & Rosenberg (1978)
Hierarchical response to stress
Pearson & Rosenberg (1978)
Physiological reponse of the individual
Replacement by more addapted individuals from a polymorphic stock
Replacement by different species
Replacement by different genus
Replacement by different family
Replacement by different order,class, phylum
time
str
ess
Biotic coefficient (BC) - AMBIBiotic coefficient (BC) - AMBI 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)Biotic coefficient (BC)
The value of BC is then calculated for every sample based on the % of each group on total macrofaunal abundance.
(0xGI)+(1.5xGII)+(3xGIII)+(4.5xGIV)+(6xGV)BC=
100
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 BCLimits for BC
Borja et al (2000) Mar Pollut Bull 401100–1114.
classificationIn terms of pollution BC Dominant groupBenthic community health
Non polluted 0.0<BC<0.2 I normalNon polluted 0.2<BC<1.2 poor
Slightly polluted 1.2<BC<3.3 III unbalancedModerately polluted 3.3<BC<4.3 Transitional to polluted
Moderately polluted 4.3<BC<5.0 IV-V pollutedHeavily polluted 5.0<BC<5.5 Transitional to havily polluted
Heavily polluted 5.5<BC<6.0 V Heavily polluted
extremely polluted αζωική αζωική azoic
BENTIXBENTIX 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
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)Benthic quality index (BQI)
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
Calculation of ES500.05
disturbed undisturbeddisturbed undisturbed
The shaded area includes the 5% of the total abundance of the species which is related to low diversity stations
The shaded area includes the 5% of the total abundance of the species which is related to low diversity stations
Rosenberg R, et al. (2004). Rosenberg R, et al. (2004). Mar Pollut. Bull. 30:470 –474Mar Pollut. Bull. 30:470 –474
Calculation of ES500.05 for various speciesCalculation of ES500.05 for various species
Low values: tolerant species, High values: sensitive speciesΧαμηλές τιμές: ανθεκτικά είδη, Υψηλές τιμές: ευαίσθητα είδη
Low values: tolerant species, High values: sensitive speciesΧαμηλές τιμές: ανθεκτικά είδη, Υψηλές τιμές: ευαίσθητα είδηRosenberg R, et al. (2004). Mar Pollut. Bull. 30:470 –Rosenberg R, et al. (2004). Mar Pollut. Bull. 30:470 –
474474
After calculating ES500.05 for each species, BQI is
calculated for each sample:
BQI= ------ x ES500.05 x 10log(S+1)
Benthic quality index (BQI)Benthic quality index (BQI)
n
Σi=1( ))( AAii
tot Atot A
BQI and sediment conditionBQI and sediment condition
Rosenberg R, et al. (2004). Mar Pollut. Bull. 30:470 –Rosenberg R, et al. (2004). Mar Pollut. Bull. 30:470 –474474
SPI imagesSPI images
Condition in relation to Pearson & Rosenberg 1978
Condition in relation to Pearson & Rosenberg 1978
Thresholds and sediment qualityThresholds and sediment quality
Hypotheses to test
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?
Sieve size
0
1
2
3
4
5
6
7
8
0
1
2
3
4
5
6
7
0
5
10
15
20
25
30
35
0 10 20 30 40
0
2
4
6
8
60
70
80
90
100
110
D+ (0.5mm)
0
2
4
6
8
10
Values at 0.5 mm
Val
ues
at 1
.0 m
m
Highly correlated y=1.0*x
Good news !
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Shannon BQI Benthix S BC ES10 L+ D+
July-Sept (0.5mm)
July Feb (0.5mm)
season
index
Spe
arm
an r
ank
corr
elat
ion
Highly inter- correlated for most indices Relatively Good news !
Do they intercorrelate? 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 BQIES10 1H' 0.970 1DELTA 0.457 0.480 1LAMBDA -0.238 -0.287 -0.616 1AMBI -0.740 -0.764 -0.541 0.344 1BENTIX 0.739 0.735 0.431 ns -0.810 1BQI 0.891 0.918 0.517 -0.296 -0.791 0.807 1
How similar they are? Using the correlation matrix we can run an
MDS and obtain similarities among indices
D+
L+
AMBI
BENTIX
H’BQI
Stress:0.01
Do they agree in Environmental status?
bad
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
0
1
2
3
4
5
0 20 40 60 80 100
sampling station
AMBI
BQI
BENTIX
H'
poor
moderate
good
high
Are there consistently easy-to-pass and difficult ones?
Yes BENTIX and H’ tend to show more High and Good quality BQI tends to show (reveal?) more Bad and Poor conditions
0%
25%
50%
75%
100%
1.High 2.Good 3.Moderate 4. Poor 5. Bad
Environmental status
BQI
AMBI
BENTIX
H'
furthermore 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 (fish farms characteristics)
0
5
10
15
20
25
30
130 260 300 300 309 366 400 432 443 1094 1150
0
10
20
30
40
50
60
70
80
90depth silt
Βά
θος
(m)
dep
th
% ι
λύος
αργ
ίλου
(%
sil
t-cl
ay)
Παραγωγή (τόνοι/έτος)Production (tn/year)
Αριθμός ειδών (species number)
1
10
100
0 200 400 600 800 1000 1200
0m
# sp
ecie
s
Παραγωγή (τόνοι/έτος)Production (tn/year)
25m
1
10
100
1000
0 200 400 600 800 1000 1200
25m
Minimum=5spp
Minimum=32spp
Μέσος αριθμός ειδών (average species number)
Ave
rage
# s
pec
ies
Απόσταση Distance
020406080
100120140160
0m 5m 10m 25m 50m control
μέσ
ος α
ριθμ
ός ε
ιδώ
ν
Δείκτης Shannon (Shannon index)H
’ (b
its)
Παραγωγή (τόνοι/έτος)Production (tn/year)
01
2345
67
0 200 400 600 800 1000 1200
0m
01234567
0 200 400 600 800 1000 1200
25m
Δείκτης Shannon (Shannon index)
H’
(bit
s)
Απόσταση Distance
0
1
2
34
5
6
7
0m 5m 10m 25m 50m control
Δείκτης Bentix (BENTIX index)B
enti
x in
dex
Παραγωγή (τόνοι/έτος)Production (tn/year)
0
1
2
3
4
5
6
0 200 400 600 800 1000 1200
0m
0
1
2
3
4
5
6
0 200 400 600 800 1000 1200
25m
Poor-bad
Poor-bad
Δείκτης AMBI (AMBI index)A
MB
I in
dex
Παραγωγή (τόνοι/έτος)Production (tn/year)
0
1
2
3
4
5
6
7
0 200 400 600 800 1000 1200
0m
0
1
2
3
4
5
0 200 400 600 800 1000 1200
25m
Poor-bad
Poor-bad
Δείκτης AMBI σε όλα τα δείγματα (AMBI index, all samples & stations)
AM
BI
cate
gori
es (
%)
Απόσταση (m) Distance
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 25 50 ctrl
κατη
γορ
ίες
(%)
High
Good
Moderate
Poor
Bad
Δείκτης Shannon σε όλα τα δείγματα (H’ index, all samples & stations)
Sh
ann
on c
ateg
orie
s (%
)
Απόσταση (m) Distance
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 25 50 ctrl
κατη
γορ
ίες
(%)
High
Good
Moderate
Poor
Bad
Δείκτης BENTIX σε όλα τα δείγματα (BENTIX index, all samples & stations)
BE
NT
IX c
ateg
orie
s (%
)
Απόσταση (m) Distance
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 25 50 ctrl
κατη
γορ
ίες
(%)
High
Good
Moderate
Poor
Bad
Thank you
