Continuing with my Climate Change in Fisheries Series (CCFS), here is my 8th on Incorporating climate scenarios in fisheries research.
For a few years now, Simon Nicol from SPC has been a reference point for all things tuna and climate change in the region. He is the tip of most of the present work in this area, and as expected, his presentation on data collection and modelling for climate scenarios was very interesting.
The subjects he covered included, among others, the importance of collecting and using climate-related data for fisheries modelling, data we aren’t yet collecting but should be, and advanced warning systems. The presenter discussed the importance of data collection in tuna fisheries management, emphasising the need for robust indicators and vulnerability analyses to prioritise areas for investment. It highlighted the need for transitioning from basin-scale to local or national-scale monitoring and improving the resolution of ocean models for more detailed economic analysis. The presentation stressed the need for proactive integration of climate impacts into tuna fisheries management; establishing baselines and understanding population structures to better manage tuna resources; and upskilling and regional autonomy.
Data collection and modelling in the context of climate change was emphasized and the importance of observations to establish baselines and quantify change was stressed as was the need for robust indicators in the areas of biology, distributions and oceanography. There is a need for vulnerability analyses to prioritise areas for investment data collection is required to identify the impacts of climate change.
The need for different types of data and information to make strategic decisions and forecasts for the upcoming year was discussed. There is a need to transition from basin-scale to local or national-scale monitoring and to improve the resolution of ocean models for more detailed economic analysis. This underscores the importance of understanding biomass changes in specific areas. The New Zealand government is funding a project to build tools to assist our understanding of the dynamics at a EEZ scale.
Establishing baselines and understanding population structures to better manage tuna resources is required. There is also a need for upskilling scientists and managers within the region and developing regional autonomy. Furthermore, scaling up fisheries and ocean monitoring is needed. We need high-resolution models to capture finer scale processes and accurately estimate biomass within exclusive economic zones. To achieve this, we need to scale up e-reporting and identify gaps in ocean data, and find future partnerships to fill these gaps.
Ocean monitoring is required but there are challenges in obtaining precise data, particularly at lower trophic levels. There are a limited number of observation tools and is a need to balance physical parameters and biological components. There are advantages in using genomics data for modelling fish populations. Genomics can provide a cleaner data set, free from assumptions associated with standard tagging data, and can estimate absolute abundance and spawning potential.
Discussion
Data collection of meteorological data along a ships track is possible, however, acoustic data is problematic. Not all vessels are good for collecting useable acoustic data. The biggest challenge, however, is the requirement for a research permit (according to UNCLOS) to do any biological work. A discussion is therefore needed as to how this could work and how it can be permitted. This will not really be a problem if we know what it is that we wanted to do, however, it can’t be rolled out without some agreement/permitting in place.
The tuna fisheries harvest strategy process is currently under development. Within this framework, some of the biological variability is captured by the biological data going into the model. If that underlying biology changes then the model will need to be updated. If that change is extreme, then this may need to take place through the exceptional circumstance clause. At the time the change is noticed a decision needs to be made as to whether it is “normal” and/or consistent between consecutive years; or an outlier; or a change in state that is becoming commonplace. If that variable is influential within the model, then a model change may be required. Forecasting tuna distribution and size can be predicted by looking at the past data to predict the future conditions, and then modelling what that change may look like in the future.
Models currently are large in the scale concerning the area that they can evaluate and a downscaling exercise is underway. The time frame for starting a downscaling exercise of the oceanographic models is known. Models that are being optimised for the best fit for the downscaling to EEZ scale to evaluate impacts will be completed within 6-12 months. For the wider climate models, a 4-5 year time horizon is required if we use an ensemble approach for the 4 tuna models at a 1-degree resolution.
SPC is closer to developing models based on genetics and close kin scalers of abundance. It is estimated that for albacore, reliable results will be available in 12 months and calibrated epigenetics for all four tunas is expected by August 2024. But skipjack is problematic as the computing power is too restrictive currently, the population is too big and this work may take another 5-6 years to be able to develop a fully realised model.