Predicting aquaculture-derived benthic organic enrichment: Model validation

Jusup, Marko; Klanjšček, Jasminka; Petricioli, Donat; Legović, Tarzan

doi:10.1016/j.ecolmodel.2009.06.033

Cited by 24 publications

(27 citation statements)

References 28 publications

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“…Plotting predicted values on the x-axis is widely accepted, as model predictions are more under the control of the modeller and may be deemed to contain less error than observations from an irregular sampling regime (Sokal & Rohlf 1995). A Student's t-test was undertaken for R 2 , β 0 , β 1 (α = 0.05, df = n − 2) to test if R 2 , β 0 and β 1 were significantly different from 1, 0 and 1, respectively (Mesple et al 1996, Jusup et al 2009). Following the termino logy given in Jusup et al (2009) (after Tett 2007, models were classified as follows: Excellent, the slope and intercept are not significantly different from 1 and 0, respectively, and R 2 is sig nificantly greater than 0; Good, either the slope is significantly different from 1 or the intercept is sig nificantly different from 0, and R 2 is significantly greater than 0; Fair, the slope is significantly different from 1 and the intercept is significantly different from 0, and R 2 is significantly greater than 0; Poor, the variance ex plained (R 2 ) is not significantly different from 0.…”

Section: Mass Balance Checks and Statistical Testing Of Model Performmentioning

confidence: 99%

“…Waste deposition models that predict flux of waste material at the seabed are relatively common (Hevia et al 1996, Silvert & Sowles 1996, Silvert & Cromey 2001, Cromey & Black 2005, Jusup et al 2009, Symonds 2011, but very few models relate flux to a benthic effect. Aquaculture impact models that link the physics (flux) to a benthic effect (biological) and/or include a biochemical component are useful for planning and regulation of aquaculture sites, as measurement of benthic community structure is a well-established method of assessing the effect of mariculture discharges (Brown et al 1987, Findlay & Watling 1997, Pearson & Black 2001, Brooks & Mahnken 2003, Pereira et al 2004, Borja et al 2009).…”

Section: Introductionmentioning

confidence: 99%

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MERAMOD: predicting the deposition and benthic impact of aquaculture in the eastern Mediterranean Sea

Cromey¹,

Thetmeyer²,

Lampadariou³

et al. 2012

Aquacult. Environ. Interact.

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A model composed of coupled particle tracking and benthic response modules was developed for predicting waste solids flux and benthic impacts of gilthead sea bream Sparus aurata L. and sea bass Dicentrarchus labrax L. aquaculture. The model was tested at 6 sites with different hydrodynamics, bathymetries and biomasses in the Aegean and Ionian seas, eastern Mediterranean Sea, and sediment trap flux and benthic impact indicators were observed. Seven sediment trap validation studies were conducted that varied in design with traps deployed either on the seabed, attached to nets or suspended in the water column. Model predictions of flux to traps spaced 5 m apart up to 50 m from the cages over a 13 d period were significant (R 2 = 0.61, n = 57, p ≤ 0.05). However, the model could not predict adequately the flux to traps spaced 2 m apart in the high-flux zone underneath cages where variability between trap observations was high. In this high-flux zone underneath cages, the averaged model flux predictions resulted in a performance of ± 49%. Statistically significant relationships were established at 4 sites between modelled flux and either benthic fauna impact indicator species (S), abundance (A), A/S ratio, Shannon-Wiener index or biomass fractionation index (BFI), (R 2 = 0.82, 0.60, 0.57, 0.67 and 0.48, respectively; n = 24, p ≤ 0.05). Two other sites, which did not exhibit an abundance peak in enriched zones, did not fit these relationships. Using relative abundance of taxonomic groups, a modelled flux of 4.1 g m −2 d −1 was determined to be a useful boundary; on either side of this boundary, clear trends occurred in pollutant tolerant and intolerant species.

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Section: Mass Balance Checks and Statistical Testing Of Model Performmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MERAMOD: predicting the deposition and benthic impact of aquaculture in the eastern Mediterranean Sea

Cromey¹,

Thetmeyer²,

Lampadariou³

et al. 2012

Aquacult. Environ. Interact.

View full text Add to dashboard Cite

show abstract

“…The second was carried out between 11 and 13 September 2015, at the very beginning of the annual mussel rearing cycle. Three PVC (polyvinyl chloride) sediment traps were deployed at each station, with a cylindrical shape, an aspect ratio of 5 : 1, and a collecting area of 0.0095 m 2 each (Cromey et al, 2002;Jusup et al, 2009). In the first experiment (Fig.…”

Section: Sediment Traps Measurementsmentioning

confidence: 99%

Modelling biogeochemical processes in sediments from the north-western Adriatic Sea: response to enhanced particulate organic carbon fluxes

et al. 2018

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Abstract. This work presents the result of a study carried out in the north-western Adriatic Sea, by combining two different types of biogeochemical models with field sampling efforts. A longline mussel farm was taken as a local source of perturbation to the natural particulate organic carbon (POC) downward flux. This flux was first quantified by means of a pelagic model of POC deposition coupled to sediment trap data, and its effects on sediment bioirrigation capacity and organic matter (OM) degradation pathways were investigated constraining an early diagenesis model by using original data collected in sediment porewater. The measurements were performed at stations located inside and outside the area affected by mussel farm deposition. Model-predicted POC fluxes showed marked spatial and temporal variability, which was mostly associated with the dynamics of the farming cycle. Sediment trap data at the two sampled stations (inside and outside of the mussel farm) showed average POC background flux of 20.0-24.2 mmol C m −2 d −1 . The difference of organic carbon (OC) fluxes between the two stations was in agreement with model results, ranging between 3.3 and 14.2 mmol C m −2 d −1 , and was primarily associated with mussel physiological conditions. Although restricted, these changes in POC fluxes induced visible effects on sediment biogeochemistry. Observed oxygen microprofiles presented a 50 % decrease in oxygen penetration depth (from 2.3 to 1.4 mm), accompanied by an increase in the O 2 influx at the station below the mussel farm (19-31 versus 10-12 mmol O 2 m −2 d −1 ) characterised by higher POC flux. Dissolved inorganic carbon (DIC) and NH + 4 concentrations showed similar behaviour, with a more evident effect of bioirrigation underneath the farm. This was confirmed through constraining the early diagenesis model, of which calibration leads to an estimation of enhanced and shallower bioirrigation underneath the farm: bioirrigation rates of 40 yr −1 and irrigation depth of 15 cm were estimated inside the shellfish deposition footprint versus 20 yr −1 and 20 cm outside. These findings were confirmed by independent data on macrofauna composition collected at the study site. Early diagenesis model results indicated a larger organic matter mineralisation below the mussel farm (11.1 versus 18.7 mmol m −2 d −1 ), characterised by similar proportions between oxic and anoxic degradation rates at the two stations, with an increase in the absolute values of oxygen consumed by OM degradation and reduced substances re-oxidation underneath the mussel farm.

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“…Similar models were tested in the Ligurian Sea (Doglioli et al, 2004), the Adriatic Sea (Jusup et al, 2009), and the North Aegean Sea (Petihakis et al, 2014). Doglioli et al (2004) nested a Lagrangian particle model within a numerical hydrodynamic model, and estimated the regional dispersion patterns of different inorganic and organic nutrients, fecal matter and feed wastes.…”

Section: Introductionmentioning

confidence: 99%

“…A similar scenario was examined by Lee et al (2003), who approached nutrient concentration from tidal flushing with Lagrangian methodology and using numerical tracer experiments. Tracking of particulate matter, especially organic carbon, from fish farms and its effect on sediment and benthos has been examined by several authors (e.g., Cromey et al, 2002;Jusup et al, 2009;Brigolin et al, 2014). An example of such a study concerns the application of a Lagrangian model for simulating the deposition of feces and uneaten feed FIGURE 1 | Site selection of fish farms tested within model domain.…”

Section: Introductionmentioning

confidence: 99%

A Quantitative Management Tool Reflecting Impact of Nutrient Enrichment from Mariculture in the Levantine Basin

2017

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Mariculture production has increased significantly in recent years due to global rise in human population. However, in addition to providing food, fish farms are also a source of nutrients and antibiotics to the water column. Here, we model the nutrient changes originating from fish cages in the Eastern Mediterranean by utilizing a Lagrangian modeling approach that followed trajectories of the water parcels. The effects of farm size and the farm's distance from the shoreline were included in the model, and biological uptake and sinking of nutrients were incorporated into the analysis. By using computation of back-trajectories examining the origin of the water arriving at strategically important shoreline areas, such as desalination plants, we were able to identify which of the proposed farm locations might be potentially harmful. The results suggest that remotely-located, smaller and spatially distant farms are more preferable to limit the nutrient effects resulting from mariculture activity.

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Predicting aquaculture-derived benthic organic enrichment: Model validation

Cited by 24 publications

References 28 publications

MERAMOD: predicting the deposition and benthic impact of aquaculture in the eastern Mediterranean Sea

MERAMOD: predicting the deposition and benthic impact of aquaculture in the eastern Mediterranean Sea

Modelling biogeochemical processes in sediments from the north-western Adriatic Sea: response to enhanced particulate organic carbon fluxes

A Quantitative Management Tool Reflecting Impact of Nutrient Enrichment from Mariculture in the Levantine Basin

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