00630nas a2200181   4500008004100000022001300041245014500054210006900199260001600268300001400284490000800298100002200306700002200328700002100350700002100371700002000392856003600412       2019                        eng d  a0959652600aMussels or tunicates: That is the question. Evaluating efficient and sustainable resource use by low-trophic species in aquaculture settings0 aMussels or tunicates That is the question Evaluating efficient a  cJan-09-2019  a132 - 1430 v2311 aFilgueira, Ramón1 aStrople, Leah, C.1 aStrohmeier, Tore1 aRastrick, Samuel1 aStrand, Øivind  u//www.simulistics.com/node/439000937nas a2200205   4500008004100000022001400041245014800055210006900203260001600272300001600288490000800304100002200312700002200334700002300356700001900379700002200398700002900420700002300449856025900472       2018                        eng d  a0378-190900aThe effect of environmental conditions on Atlantic salmon smolts’ (Salmo salar) bioenergetic requirements and migration through an inland sea0 aeffect of environmental conditions on Atlantic salmon smolts Sal  cJan-10-2018  a1467 - 14820 v1011 aStrople, Leah, C.1 aFilgueira, Ramón1 aHatcher, Bruce, G.1 aDenny, Shelley1 aBordeleau, Xavier1 aWhoriskey, Frederick, G.1 aCrossin, Glenn, T.  uhttp://link.springer.com/10.1007/s10641-018-0792-5http://link.springer.com/content/pdf/10.1007/s10641-018-0792-5.pdfhttp://link.springer.com/article/10.1007/s10641-018-0792-5/fulltext.htmlhttp://link.springer.com/content/pdf/10.1007/s10641-018-0792-5.pdf00675nas a2200169   4500008003900000022001300039245014100052210006900193260001200262300001400274490000800288100002200296700002100318700002000339700001900359856012700378       2015                          d  a0025326X00aInforming Marine Spatial Planning (MSP) with numerical modelling: A case-study on shellfish aquaculture in Malpeque Bay (Eastern Canada)0 aInforming Marine Spatial Planning MSP with numerical modelling A  c11/2015  a200 - 2160 v1001 aFilgueira, Ramón1 aGuyondet, Thomas1 aBacher, Cédric1 aComeau, Luc, A  u//www.simulistics.com/publications/informing-marine-spatial-planning-msp-numerical-modelling-case-study-shellfish-aquacult02071nas a2200181   4500008003900000022001300039245013400052210006900186260001200255300001200267490000800279520141300287100001701700700001601717700001601733700001301749856012701762       2014                          d  a0924796300aA fully-spatial ecosystem-DEB model of oyster (Crassostrea virginica) carrying capacity in the Richibucto Estuary, Eastern Canada0 afullyspatial ecosystemDEB model of oyster Crassostrea virginica   c08/2014  a42 - 540 v1363 aThe success of shellfish aquaculture as well as its sustainability relies on adjusting the cultured biomass to local
ecosystem characteristics. Oyster filter-feeding activity can control phytoplankton concentration, reaching severe
depletion in extreme situations, which can threaten ecological sustainability. A better understanding of oyster–
phytoplankton interaction can be achieved by constructing ecosystem models. In this study, a fully-spatial hydro-
dynamic biogeochemical model has been constructed for the Richibucto Estuary in order to explore oyster carry-
ing capacity. The biogeochemical model was based on a classical nutrient–phytoplankton–zooplankton–detritus
(NPZD) approach with the addition of a Dynamic Energy Budget (DEB) model of Crassostrea virginica. Natural
variation of chlorophyll was used as a benchmark to define a sustainability threshold based on a resilience frame-
work. Scenario building was applied to explore carrying capacity of the system. However, the complex geomor-
phology of the Richibucto Estuary and the associated heterogeneity in water residence time, which is integral in
estuarine functioning, indicate that the carrying capacity assessment must be specific for each area of the system.
The model outcomes suggest that water residence time plays a key role in carrying capacity estimations through
its influence on ecological resistance.1 aFilgueira, R1 aGuyondet, T1 aComeau, L A1 aGrant, J  u//www.simulistics.com/publications/fully-spatial-ecosystem-deb-model-oyster-crassostrea-virginica-carrying-capacity-richib02509nas a2200145   4500008003900000245012100039210006900160300001400229490000700243520199900250100002202249700001502271700002002286856005702306       2014                          d00aImplementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord0 aImplementation of marine spatial planning in shellfish aquacultu  a832–8430 v243 aShellfish carrying capacity is determined by the interaction of a cultured species
with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls
the exchange of matter between farms and the adjacent areas, which in turn establishes the
nutrient supply that supports phytoplankton populations. The complexity of water circulation
makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying
capacity estimations. This detailed spatial resolution also allows for the study of processes that
depend on specific spatial arrangements, e.g., the most suitable location to place farms, which
is crucial for marine spatial planning, and consequently for decision support systems. In the
present study, a fully spatial physical-biogeochemical model has been combined with scenario
building and optimization techniques as a proof of concept of the use of ecosystem modeling
as an objective tool to inform marine spatial planning. The object of this exercise was to
generate objective knowledge based on an ecosystem approach to establish new mussel
aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best
location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer,
increasing primary production, and consequently, carrying capacity for mussel cultivation. In
addition, an optimization tool, parameter estimation (PEST), was applied to the optimal
location and mussel standing stock biomass that maximize production, according to a
preestablished carrying capacity criterion. Optimization tools allow us to make rational and
transparent decisions to solve a well-defined question, decisions that are essential for policy
makers. The outcomes of combining ecosystem models with scenario building and
optimization facilitate planning based on an ecosystem approach, highlighting the capabilities
of ecosystem modeling as a tool for marine spatial planning.1 aFilgueira, Ramón1 aGrant, Jon1 aStrand, Øivind  uhttp://www.esajournals.org/doi/pdf/10.1890/13-0479.102609nas a2200181   4500008003900000022001300039245009100052210006900143260001200212300001400224490000700238520204900245100001702294700001602311700001602327700001302343856007102356       2014                          d  a1470160X00aPhysiological indices as indicators of ecosystem status in shellfish aquaculture sites0 aPhysiological indices as indicators of ecosystem status in shell  c04/2014  a134 - 1430 v393 aThe filtration activity of cultured mussels may exert a strong control on phytoplankton populations. Given that phytoplankton constitutes the base of marine food webs, carrying capacity in shellfish aquaculture sites has been commonly studied in terms of phytoplankton depletion. However, spatial and temporal variability of phytoplankton concentration in coastal areas present a methodological constraint for using phytoplankton depletion as an indicator in monitoring programs, and necessitates intensive field campaigns. The main goal of this study is to explore the potential of different bivalve performance indices for use as alternatives to phytoplankton depletion as cost-effective indicators of carrying capacity. For that, a fully spatial hydrodynamic–biogeochemical coupled model of Tracadie Bay, an intensive mussel culture embayment located in Prince of Edward Island (Canada), has been constructed and scenario building has been used to explore the relationship between phytoplankton depletion and bivalve performance. Our underlying premise is that overstocking of bivalves leads to increased competition for food resources, i.e. phytoplankton, which may ultimately have a significant effect on bivalve growth rate and performance. Following this working hypothesis, the relationships among bay-scale phytoplankton depletion and three bivalve physiological indices, one static, condition index, and two dynamic, tissue mass and shell length growth rates, have been simulated. These three metrics present methodological advantages compared to phytoplankton depletion for incorporation into monitoring programs. Although significant correlations among phytoplankton depletion and the three physiological indices have been observed, shell length growth rate is shown as the most sensitive indicator of carrying capacity, followed by tissue mass growth rate and then by condition index. These results demonstrate the potentiality of using bivalve physiological measurements in monitoring programs as indicators of ecosystem status.1 aFilgueira, R1 aGuyondet, T1 aComeau, L A1 aGrant, J  uhttp://www.sciencedirect.com/science/article/pii/S1470160X1300496201899nas a2200157   4500008003900000245009200039210006900131260001200200300001400212520131800226100002201544700002101566700001901587700001501606856012001621       2014                          d00aStorm-induced changes in coastal geomorphology control estuarine secondary productivity0 aStorminduced changes in coastal geomorphology control estuarine   c01/2014  an/a - n/a3 aEstuarine ecosystems are highly sensitive not only to projected effects of climate change such as ocean warming, acidification, and sea-level rise but also to the incidence of nor'easter storms and hurricanes. The effects of storms and hurricanes can be extreme, with immediate impact on coastal geomorphology and water circulation, which is integral to estuarine function and consequently to provision of ecosystem services. In this article, we present the results of a natural estuarine-scale experiment on the effects of changes in coastal geomorphology on hydrodynamics and aquaculture production. A bay in Prince Edward Island, Canada, was altered when a nor'easter storm eroded a second tidal inlet through a barrier island. Previous field and modeling studies allowed a comparison of prestorm and post-storm circulation, food limitation by cultured mussels, and aquaculture harvest. Dramatic increases in mussel production occurred in the year following the opening of the new inlet. Model studies showed that post-storm circulation reduced food limitation for cultured mussels, allowing greater growth. Climate change is expected to have severe effects on the delivery of marine ecosystem services to human populations by changing the underlying physical-biological coupling inherent to their functioning.1 aFilgueira, Ramón1 aGuyondet, Thomas1 aComeau, Luc, A1 aGrant, Jon  uhttp://onlinelibrary.wiley.com/doi/10.1002/2013EF000145/abstract;jsessionid=DBD0FB7B2443BD9C9D658F85A42F41FD.f04t0401946nas a2200157   4500008003900000245011100039210006900150300001200219490000600231520143500237100001701672700001301689700001401702700001501716856005701731       2013                          d00aEcosystem modelling for ecosystem-based management of bivalve aquaculture sites in data‑poor environment0 aEcosystem modelling for ecosystembased management of bivalve aqu  a117-1330 v43 aAlthough models of carrying capacity have been around for some time, their use in aquaculture management has been limited. This is partially due to the cost involved in generating and testing the models. However, the use of more generic and flexible models could facilitate the implementation of modelling in management. We have built a generic core for coupling biogeochemical and hydrodynamic models using Simile (www.simulistics.com), a visual simulation environment software that is well-suited to accommodate fully spatial models. Specifically, Simile integrates PEST (model-independent parameter estimation, Watermark Numerical Computing, www.pesthomepage.org), an optimization tool that uses the Gauss-Marquardt-Levenberg algorithm and can be used to estimate the value of a parameter, or set of parameters, in order to minimize the discrepancies between the model results and a dataset chosen by the user. The other critical aspect of modelling exercises is the large amount of data necessary to set up, tune and groundtruth the ecosystem model. However, ecoinformatics and improvements in remote sensing procedures have facilitated acquisition of these datasets, even in data-poor environments. In this paper we describe the required datasets and stages of model development necessary to build a biogeochemical model that can be used as a decision-making tool for bivalve aquaculture management in data-poor environments.1 aFilgueira, R1 aGrant, J1 aStuart, R1 aBrown, M S  uhttp://www.int-res.com/abstracts/aei/v4/n2/p117-133/00507nas a2200145   4500008003900000245008700039210007100126300001000197490000600207100002200213700001500235700002000250700002000270856007100290       2012                          d00aA physical–biogeochemical coupling scheme for modeling marine coastal ecosystems0 aphysical–biogeochemical coupling scheme for modeling marine coas  a71-800 v71 aFilgueira, Ramón1 aGrant, Jon1 aBacher, Cédric1 aCarreau, Michel  uhttp://www.sciencedirect.com/science/article/pii/S157495411100097501466nas a2200109   4500008003900000245010000039210006900139520099100208100002101199700001501220856012101235       2009                          d00aA Box Model for Ecosystem-Level Management of Mussel Culture Carrying Capacity in a Coastal Bay0 aBox Model for EcosystemLevel Management of Mussel Culture Carryi3 a<p>The carrying capacity of shellfish aquaculture is determined by the interaction of cultured species with the ecosystem, particularly food availability to suspension feeders. A multiple box dynamic ecosystem model was constructed to examine the carrying capacity for mussel (Mytilus edulis) aquaculture in Tracadie Bay, Prince of Edward Island, Canada. Criteria for carrying capacity were based on chlorophyll concentration. The model was run in two different years (1998 and 1999) in which time series for three points inside the bay and a point outside the bay were available. This data set allows spatial validation of the ecosystem model and assessment of its sensitivity to changes in boundary conditions. The model validation process indicated that the differential equations and parameters used in the simulation provided robust prediction of the ecological dynamics within the bay. Results verified that mussel biomass exerts top-down control of phytoplankton populations.</p>1 aFilgueira, Ramon1 aGrant, Jon  u//www.simulistics.com/publications/box-model-ecosystem-level-management-mussel-culture-carrying-capacity-coastal-bay