Health prediction for king salmon via evolutionary machine learning with genetic programming.

King (Chinook) salmon is the only salmon species farmed in Aotearoa New Zealand and accounts for over half of the world's production of king salmon. Determining the health status of king salmon effectively is important for farming. However, it is a challenging task due to the complex biotic and abiotic factors that influence health.

Mapping drivers of change for biodiversity risk assessment to target conservation actions: Human frequentation in protected areas.

Mapping the drivers of change that pose negative pressures or threats to biodiversity can help to identify where biodiversity is most threatened and can be used to determine priority sites to target conservation actions. Overlapping drivers of change maps with distribution maps of sensitive species provides valuable information to identify where and when it would be better to target actions to minimize the risk. The overall aim of this study was to develop a methodology for the integration of risk mapping associated with high human frequentation to guide conservation actions in two case study: the Kentish plover () and Posidonia meadows (), both sensitive to human frequentation.

Harnessing environmental DNA to reveal biogeographical patterns of non-indigenous species for improved co-governance of the marine environment in Aotearoa New Zealand.

Aotearoa New Zealand's Northern region is a major gateway for the incursion and establishment of non-indigenous species (NIS) populations due to high numbers of recreational and commercial vessels. This region also holds a unique marine ecosystem, home to many taonga (treasured) species of cultural and economic importance. Regular surveillance, eradication plans and public information sharing are undertaken by local communities and governmental organizations to protect these ecosystems from the impact of NIS.

Prediction of Feed Efficiency and Performance-Based Traits in Fish via Integration of Multiple Omics and Clinical Covariates.

Fish aquaculture is a rapidly expanding global industry, set to support growing demands for sources of marine protein. Enhancing feed efficiency (FE) in farmed fish is required to reduce production costs and improve sector sustainability. Recognising that organisms are complex systems whose emerging phenotypes are the product of multiple interacting molecular processes, systems-based approaches are expected to deliver new biological insights into FE and growth performance.

Net overboard: Comparing marine eDNA sampling methodologies at sea to unravel marine biodiversity.

Environmental DNA (eDNA) analyses are powerful for describing marine biodiversity but must be optimized for their effective use in routine monitoring. To maximize eDNA detection probabilities of sparsely distributed populations, water samples are usually concentrated from larger volumes and filtered using fine-pore membranes, often a significant cost-time bottleneck in the workflow. This study aimed to streamline eDNA sampling by investigating plankton net versus bucket sampling, direct versus sequential filtration including self-preserving filters.