Abstract
The Chatham Rise is a highly productive deep-sea ecosystem that supports numerous substantial commercial fisheries, and is a likely candidate for an ecosystem based approach to fisheries management in New Zealand. We present the first end-to-end ecosystem model of the Chatham Rise, which is also to the best of our knowledge, the first end-to-end ecosystem model of any deep-sea ecosystem. We describe the process of data compilation through to model validation and analyse the importance of knowledge gaps with respect to model dynamics and results. The model produces very similar results to fisheries stock assessment models for key fisheries species, and the population dynamics and system interactions are realistic. Confidence intervals based on bootstrapping oceanographic variables are produced. The model components that have knowledge gaps and are most likely to influence model results were oceanographic variables, and the aggregate species groups ‘seabird’ and ‘cetacean other’. We recommend applications of the model, such as forecasting biomasses under various fishing regimes, include alternatives that vary these components.
Highlights
The goal of incorporating a holistic approach to understanding the system-wide repercussions of how we manage our marine resources is admirable and ambitious (Long, Charles & Stephenson, 2015; Link & Browman, 2017)
We describe the first end-to-end ecosystem model for the Chatham Rise, New Zealand
The Chatham Rise Atlantis model presented here uses the wealth of data and information available for the Chatham Rise and its fisheries, and one of the best ecosystem models for exploring ‘what-if’ type questions (Plagányi, 2007) and ecosystem-level management strategy evaluation (Fulton et al, 2014)
Summary
The goal of incorporating a holistic approach to understanding the system-wide repercussions of how we manage our marine resources is admirable and ambitious (Long, Charles & Stephenson, 2015; Link & Browman, 2017). While oceanography is not constant in our non-fishing model as it changes by year (Section: Oceanography), most of the age-structured groups should still be fairly stable This was generally the case; all biomass trajectories remained within CVs of 20% over the simulated 1900–2016 model period, except for invertebrate scavengers (commercial) and seaperch. We used simulation outputs to estimate the total effect (ε) of each species group (Eq (1)) which used the change in biomass of each group relative to the Base Model (Eq (2)). There were four species groups that stood out as having more effect than the other groups: orange roughy, hoki, pelagic fish small (primarily myctophids), and spiny dogfish These remain the top four for keystoneness, but the order changes due to the proportional biomasses (Fig. 9). Where Y is the number of years for which there are observations, Oy is the observed biomass in year y, Py is the model biomass in year y
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