Influence of mussel aquaculture on nitrogen dynamics in a nutrient enriched coastal embayment

Cranford, Peter J.; Strain, Peter M.; Dowd, Michael K.; Hargrave, B. T.; Grant, Jonathan; Archambault, Marie-Claude

doi:10.3354/meps06997

Cited by 112 publications

(98 citation statements)

References 30 publications

(43 reference statements)

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“…Biogeochemical models for Japanese coastal waters have also been developed (Hata et al 2004;Sohma et al 2001Sohma et al , 2004Sohma et al , 2008. Of note, the BHI concept proposed by Hori (2008) focused more on the spatial heterogeneity of habitats within a coastal area, which is different from numerical studies of biogeochemical/material cycles at larger scales, often considering areas with a homogeneous benthic habitat (Cranford et al 2007;Lacroix et al 2007;Nobre et al 2010;Xu and Hood 2006).…”

Section: Concepts Coupling the Four Featuresmentioning

confidence: 99%

Modeling the coastal ecosystem complex: present situation and challenges

et al. 2018

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To enhance numerical modeling of the coastal ecosystem complex (CEC), we reviewed the CEC and related concepts along with the current coastal ecosystem model framework in this study. We identified two model implementation paths from the initial objectives to numerical models: specific model building, and the use of existing model frameworks. As the CEC is still at the conceptual stage, both paths are possible. Four important ecological features of CEC modeling (population connectivity, habitat heterogeneity, ontogeny of organisms, and trophic interactions) were also identified. Models for population connectivity, species distributions, life histories, and food webs were categorized using these features. We found that some previously established concepts (between-habitat interactions, coastal ecosystem mosaic, and seascape nursery) overlap with the CEC concept. Several existing integrated model frameworks were reviewed, focusing on their potential to simulate CEC processes. Building specific models for the CEC at the current conceptual stage will be challenging, and modification of existing models will be needed if they are to be used for CEC modeling. Habitat function, ontogenetic development in early life stages, and recruitment variability are important factors when modifying existing models for the development of CEC models. Although model complexity should become high to reproduce observed ecoclogical processes, an intermediate level of model ccomplexity is feasible to decrease parameter uncertainty in models for fisheries management.

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Section: Concepts Coupling the Four Featuresmentioning

confidence: 99%

Modeling the coastal ecosystem complex: present situation and challenges

et al. 2018

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“…Modeling is also among the few tools capable of assessing aquaculture sustainability while also considering the cumulative effects of additional human activities (e.g. eutrophication, climate change) and resident and invasive suspension-feeding species (Cranford et al 2007, Ferreira et al 2008. In summary, it is possible to utilize models to:…”

Section: Role Of Modeling In Bivalve Aquaculture Managementmentioning

confidence: 99%

“…Potential effects on nutrient cycling, fluxes, and retention may also be expressed at the coastal ecosystem scale (e.g. Newell 2004, Nizzoli et al 2006, Cranford 2007 such that the boundary of the aquaculture system to be managed must include both benthic and pelagic components and extend beyond the footprint of the farm.…”

Section: Ecosystem Interactions With Bivalve Aquaculturementioning

confidence: 99%

“…Grant et al (2008) used a fully-coupled biological−physical−chemical model to demonstrate that suspended mussel culture may, under certain conditions, exert a controlling effect on the concentration and distribution of phytoplankton and other suspended particles. Similarly, Cranford et al (2007) utilized a nitrogen budget and box model to demonstrate how a suspended mussel culture activity controlled nutrient dynamics at the coastal ecosystem scale.…”

Section: Role Of Modeling In Bivalve Aquaculture Managementmentioning

confidence: 99%

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An ecosystem-based approach and management framework for the integrated evaluation of bivalve aquaculture impacts

Cranford¹,

Kamermans²,

Krause³

et al. 2012

Aquacult. Environ. Interact.

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An ecosystem-based approach to bivalve aquaculture management is a strategy for the integration of aquaculture within the wider ecosystem, including human aspects, in such a way that it promotes sustainable development, equity, and resilience of ecosystems. Given the linkage between social and ecological systems, marine regulators require an ecosystem-based decision framework that structures and integrates the relationships between these systems and facilitates communication of aquaculture-environment interactions and policy-related developments and decisions. The Drivers-Pressures-State Change-Impact-Response (DPSIR) management framework incorporates the connectivity between human and ecological issues and would permit available performance indicators to be identified and organized in a manner that facilitates different regulatory needs. Suitable performance indicators and modeling approaches, which are used to assess DPSIR framework components, are reviewed with a focus on the key environmental issues associated with bivalve farming. Indicator selection criteria are provided to facilitate constraining the number of indicators within the management framework. It is recommended that an ecosystem-based approach for bivalve aquaculture be based on a tiered indicator monitoring system that is structured on the principle that increased environmental risk requires increased monitoring effort. More than 1 threshold for each indicator would permit implementation of predetermined impact prevention and mitigation measures prior to reaching an unacceptable ecological state. We provide an example of a tiered monitoring program that would communicate knowledge to decision-makers on ecosystem State Change and Impact components of the DPSIR framework.KEY WORDS: Bivalve aquaculture management · Ecosystem-based approach · DPSIR framework · Indicators · Thresholds · Benthic effects · Pelagic effects · Social-ecological systems Resale or republication not permitted without written consent of the publisher

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“…However, the production of faeces and pseudofaeces (excess particles rejected by palps before ingestion) leads to a net transfer of organic matter from the water column to the surface sediment (Tenore and Dunstan, 1973;Cranford et al, 2007). This process is expected to locally affect sediment biogeochemistry, benthicpelagic coupling, and benthic community functioning.…”

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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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Influence of mussel aquaculture on nitrogen dynamics in a nutrient enriched coastal embayment

Cited by 112 publications

References 30 publications

Modeling the coastal ecosystem complex: present situation and challenges

Modeling the coastal ecosystem complex: present situation and challenges

An ecosystem-based approach and management framework for the integrated evaluation of bivalve aquaculture impacts

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

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