Performance measures and models for open‐water integrated multi‐trophic aquaculture

Abstract

Qualifying and quantifying nutrient flows within open‐water Integrated Multi‐Trophic Aquaculture (IMTA) systems is necessary to determine transfer efficiencies and to assess overall system performance. There are numerous empirical performance metrics, such as spatially defined growth and nutrient sequestration, which may have application. When used in combination with modelling techniques, empirical approaches can be a powerful tool for system assessment or prediction. Simple empirical growth models, such as the thermal‐growth coefficient (TGC) and scope for growth (SFG), are applicable to aquatic animals and can include nutritional mass‐balance approaches to estimate nutrient loads. Comparable empirical growth models exist for seaweeds. Mechanistic‐based dynamic growth and reproduction models, such as Dynamic Energy Budget (DEB), are more complex, but have application beyond site‐specific empirical models and can, therefore, be included into larger ecosystem models for application to IMTA. Proximity, ecological transfer efficiencies, particle dynamics, species culture ratios and the timing of multi‐species production cycles can have profound implications for IMTA effectiveness and require careful consideration for system assessment. This review provides a pragmatic evaluation of performance measures and models to assess nutrient transfer and growth in open‐water IMTA systems.

The Evolution Road of Seaweed Aquaculture: Cultivation Technologies and the Industry 4.0

“…Inflows and outflows can be easily monitored, as seawater is pumped onshore and renewed depending on the cultivar needs. In addition, nutrients can be added efficiently, and therefore the composition of the media is under tight control [ 277 , 279 ]. Nutrient inputs can be precisely arranged to maximize the production of the bioactive compounds of interest while minimizing harmful discharge to the environment [ 268 ].…”

“…More complete CFD models include populations, showing the population as an entire group or a growth of a solo specimen and after that a scale up the effects to a population, to fully understand the impact in the cultivated seaweed of all the inputted variables in the model analyzed [ 279 ]. A minor number of super-individuals, which are the model individuals where each one symbolizes several hundreds or thousands of actual individuals, could also be introduced in the model, thus gaining a grade of in-population variability (individual based models).…”

“…The usage of stochastic population models might also be a plan to decipher the deviation in progress on the individuals. The more advanced and sophisticated the model is, the further real growing data are necessary for “model training” and validation [ 279 ]. The advantage is the guarantee to have necessary data to improve the aquaculture to a next level of productivity and reduce the time in real cultivation trials.…”

Using systems thinking and open innovation to strengthen aquaculture policy for the United Nations Sustainable Development Goals

“…An example of where systems thinking is currently lacking in helping to formulate aquaculture policy (Stead, ) is the limited use and uptake of integrated multi‐trophic aquaculture (IMTA) models (Kleitou et al , ; Reid et al , ; Troell et al , ). IMTA refers to studies or farms which encompass more than one species at a time from different trophic levels and habitats.…”

Multiscale modelling of cage effects on the transport of effluents from open aquaculture systems

“…Numerical simulation models are standard and indispensable tools in studies and assessments of environmental effects and interactions of open water aquaculture systems [1,2]. Some simulation tools are, directly or indirectly, integrated in management systems [3][4][5][6].…”