SPRAT: A Spatially-Explicit Marine Ecosystem Model Based on Population Balance Equations

TL;DR

SPRAT is a novel spatially-explicit fish stock model based on Population Balance Equations, integrating individual-level detail with PDEs, to improve ecosystem-based fisheries management and predict long-term fish stock dynamics.

Contribution

The paper introduces SPRAT, a new fish stock model combining IBMs and ADR models using PBEs, offering a more accurate and flexible tool for ecosystem modeling.

Findings

Successfully modeled the 1990s regime shift on the Scotian Shelf.

Reconciled multitrophic dynamics with environmental and fishing changes.

Provided insights into predator-prey reversal affecting cod recovery.

Abstract

To successfully manage marine fisheries using an ecosystem-based approach, long-term predictions of fish stock development considering changing environmental conditions are necessary. Such predictions can be provided by end-to-end ecosystem models, which couple existing physical and biogeochemical ocean models with newly developed spatially-explicit fish stock models. Typically, Individual-Based Models (IBMs) and models based on Advection-Diffusion-Reaction (ADR) equations are employed for the fish stock models. In this paper, we present a novel fish stock model called SPRAT for end-to\hyp{}end ecosystem modeling based on Population Balance Equations (PBEs) that combines the advantages of IBMs and ADR models while avoiding their main drawbacks. SPRAT accomplishes this by describing the modeled ecosystem processes from the perspective of individuals while still being based on partial differential equations. We apply the SPRAT model to explore a well-documented regime shift observed on the eastern Scotian Shelf in the 1990s from a cod-dominated to a herring-dominated ecosystem. Model simulations are able to reconcile the observed multitrophic dynamics with documented changes in both fishing pressure and water temperature, followed by a predator-prey reversal that may have impeded recovery of depleted cod stocks. We conclude that our model can be used to generate new hypotheses and test ideas about spatially interacting fish populations, and their joint responses to both environmental and fisheries forcing.