A new multi-object tracking pipeline based on computer vision techniques for mussel farms.

Mussel farming is a thriving industry in New Zealand and is crucial to local communities. Currently, farmers keep track of their mussel floats by taking regular boat trips to the farm. This is a labour-intensive assignment.

A new artificial intelligent approach to buoy detection for mussel farming.

Aquaculture is an important industry in New Zealand (NZ). Mussel farmers often manually check the state of the buoys that are required to support the crop, which is labour-intensive. Artificial intelligence (AI) can provide automatic and intelligent solutions to many problems but has seldom been applied to mussel farming.

A dynamic ocean management tool to reduce bycatch and support sustainable fisheries.

Seafood is an essential source of protein for more than 3 billion people worldwide, yet bycatch of threatened species in capture fisheries remains a major impediment to fisheries sustainability. Management measures designed to reduce bycatch often result in significant economic losses and even fisheries closures. Static spatial management approaches can also be rendered ineffective by environmental variability and climate change, as productive habitats shift and introduce new interactions between human activities and protected species.

Characterizing habitat suitability for a central-place forager in a dynamic marine environment.

Characterizing habitat suitability for a marine predator requires an understanding of the environmental heterogeneity and variability over the range in which a population moves during a particular life cycle. Female California sea lions () are central-place foragers and are particularly constrained while provisioning their young. During this time, habitat selection is a function of prey availability and proximity to the rookery, which has important implications for reproductive and population success.

Fit to predict? Eco-informatics for predicting the catchability of a pelagic fish in near real time.

The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing eco-informatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting.