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 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 P. oceanica (coarse sediment and strong currents) is “ideal” for fish farming since: n it allows rapid dispersion of solute wastes n minimal accumulation of particulates and n excellent 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 biomass due to increased phytoplankton biomass due to increased suspended particulates due to increased suspended particulates by favouring the growth of epiphytes on Posidonia leaves by favouring the growth of epiphytes on Posidonia leaves competition with fast growing macroalgae competition with fast growing macroalgae accumulation of OM in the sediments accumulation of OM in the sediments increasing NH 4 and H 2 S in the sediments increasing NH 4 and H 2 S in the sediments
Posidonia: 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 Report 2005, unpublished data
MedVeg fluxes measured with sediment traps Sounion Flux P=0.10*x Alicante Flux P=0.26*x MedVeg Report 2005, unpublished data
MedVeg Report 2005, unpublished data **** ** *** * **** Control site * signif different from control site
MedVeg Bioassays - Ulva Control site * signif different from control site MedVeg Report 2005, unpublished data ****** ****
MedVeg: Posidonia mortalities with distance MedVeg Report 2005, unpublished data
MedVeg: Posidonia mortalities with sedimentation rate MedVeg Report 2005, unpublished data Mortality increases rapidly beyond the sedimentation rate of 6g m -2 d -1
MedVeg: Posidonia density & cover MedVeg Report 2005, unpublished data Decrease close to the farms
MedVeg: Posidonia biomass MedVeg Report 2005, unpublished data 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 Ζ shoot biomass, expressed as the average dry weight of at least ten replicates shoots Physiological descriptors Ζ total phosphorus content in different tissues, specifically young leaves and rhizomes, expressed as % of dry weight. Ζ total non-structural carbohydrates reserves in rhizomes, expressed as % of dry weight Ζ elemental sulphur content (as μmol per g dry weight) in roots.
MedVeg descriptors/indicators: At population level Ζ 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 Ζ epiphyte biomass, expressed as the dry weigh of epiphytes in relation of the size of the shoots. Ζ 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 models Karakassis et al. (2005) Sci Mar vol 69
Land-based tanks inputoutput 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
Nutrient dynamics Fish size: 1gr Significant difference and Diel pattern in discharge 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 Significant difference and Diel pattern in discharge Tsapakis, Pitta, Karakassis (2006) Aquat. Liv. Resour vol 19
N & P mass balance: % losses over feed input PO 4 (%) (%) AverageAverage NH 4 (%) (%)PON(%)PON(%) Fish Size (gr) (gr) Fine particulate material settling at very slow rates and over larger distance from the discharge points Tsapakis, 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
Grazing experiment in Crete using dialysis chambers >500 Distance (m) filtered Chlorella unfiltered Chl 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 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 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 s Farm Production
Effects on Landings: MAFA analysis AB 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 changes Ithaki Sounion TOC (%) TON (%) Eh (mV) current Cephalonia Karakassis et al. (2000) ICES J mar sci 57
Meta-analysis of benthic effects Kalantzi & Karakassis (2006) Mar. Pollut. Bull vol 52
Meta-analysis of benthic effects Kalantzi & Karakassis (2006) Mar. Pollut. Bull vol. 52
Meta-analysis of benthic effects
Sediment profiling imagery (SPI): an «inverted periscope» mirror glass camera
SPI images beneath fish farms Bg CH4 or H 2 S UF FS FS BLT BLT BT Source: Karakassis, Tsapakis, Smith, Rumohr. (2002) Mar Ecol Prog Ser, 227
Multivariate analysis of SPI data Source: Karakassis, Tsapakis, Smith, Rumohr. (2002) Mar Ecol Prog Ser 227 FebruaryJulyOctober Euclidean distance Comparisons between multivariate patterns fauna SPI
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 -> MERAMOD A tool for prediction of benthic degradation High correlation between predicted and observed sedimentation High correlation between predicted sedimentation and macrofaunal diversity 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 * for trout cage farming in Sweden by Holby & Hall (1991) and by Hall et al. (1992) MEPS * for trout cage farming in Sweden by Holby & Hall (1991) and by Hall et al. (1992) MEPS
effects on benthos 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 stress
Biotic 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) The value of BC is then calculated for every sample based on the % of each group on total macrofaunal abundance. (0 x G I ) + (1.5 x G II ) + (3 x G III ) + (4.5 x G IV ) + (6 x G V ) 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. n 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 Borja et al (2000) Mar Pollut Bull –1114. classification In terms of pollution BCDominant groupBenthic community health Non polluted0.0
BENTIX 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) 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. n Rosenberg R, Blomqvist M, Nilsson HC, Cederwall H, Dimming A (2004) Marine Pollution Bulletin 30 (7), 470 –474
Calculation of ES disturbed undisturbed 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). Mar Pollut. Bull. 30:470 –474
Calculation of ES for various species Low values: tolerant species, High values: sensitive species Χαμηλές τιμές: ανθεκτικά είδη, Υψηλές τιμές: ευαίσθητα είδη 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
After calculating ES for each species, BQI is calculated for each sample: BQI= x ES x 10 log(S+1) Benthic quality index (BQI) n Σ i=1 ( ) )( AiAiAiAi tot A
BQI and sediment condition Rosenberg R, et al. (2004). Mar Pollut. Bull. 30:470 –474 SPI images Condition in relation to Pearson & Rosenberg 1978 Thresholds 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 Values at 0.5 mm Values at 1.0 mm Highly correlated y=1.0*x Good news !
season index Spearman rank correlation 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?
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 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
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) Βάθος (m) depth % ιλύος αργίλου (% silt-clay) Παραγωγή (τόνοι/έτος) Production (tn/year)
Αριθμός ειδών (species number) # species Παραγωγή (τόνοι/έτος) Production (tn/year) Minimum=5spp Minimum=32spp
Μέσος αριθμός ειδών (average species number) Average # species Απόσταση Distance
Δείκτης Shannon (Shannon index) H’ (bits) Παραγωγή (τόνοι/έτος) Production (tn/year)
Δείκτης Shannon (Shannon index) H’ (bits) Απόσταση Distance
Δείκτης Bentix (BENTIX index) Bentix index Παραγωγή (τόνοι/έτος) Production (tn/year) Poor- bad
Δείκτης AMBI (AMBI index) AMBI index Παραγωγή (τόνοι/έτος) Production (tn/year) Poor-bad
Δείκτης AMBI σε όλα τα δείγματα (AMBI index, all samples & stations) AMBI categories (%) Απόσταση (m) Distance
Δείκτης Shannon σε όλα τα δείγματα (H’ index, all samples & stations) Shannon categories (%) Απόσταση (m) Distance
Δείκτης BENTIX σε όλα τα δείγματα (BENTIX index, all samples & stations) BENTIX categories (%) Απόσταση (m) Distance