Direct and ancillary benefits of ecosystem-based fisheries management in forage fish fisheries

Abstract

Natural resource management is evolving toward holistic, ecosystem-based approaches to decision making. The ecosystem science underpinning these approaches needs to account for the complexity of multiple interacting components within and across coupled natural-human systems. In this research, we investigate the potential economic and ecological gains from adopting ecosystem-based approaches for the sardine and anchovy fisheries off of the coast of California, USA. Research has shown that while predators in this system are likely substituting one forage species for another, the assemblage of sardine and anchovy can be a significant driver of predator populations. Currently, the harvest control rules for sardine and anchovy fisheries align more with traditional single species framework. We ask what are the economic and ecological gains when jointly determining the harvest control rules for both forage fish stocks and their predators relative to the status quo? What are the implications of synchronous and anti-synchronous environmental recruitment variation between the anchovy and sardine stocks on optimal food-web management? To investigate these questions, we develop an economic-ecological model for sardine, anchovy, a harvested predator (halibut), and an endangered predator (Brown Pelican) that includes recruitment variability over time driven by changing environmental conditions. Utilizing large-scale numerical optimal control methods, we investigate how the multiple variants of integrated management of sardine, anchovy, and halibut impact the overall economic condition of the fisheries and Brown Pelican populations over time. We find significant gains in moving to integrated catch control rules both in terms of the economic gains of the fished stocks, and in terms of the impacts on the Brown Pelican populations. We also compare the relative performance of current stylized catch control rules to optimal single species and optimal ecosystem-based fisheries management (EBFM) across ecological and economic dimensions, where the former trade-off considerable economic value for ecological goals. More generally, we demonstrate how EBFM approaches introduce and integrate additional management levers for policymakers to achieve non-fishery objectives at lowest costs to the fishing sectors.

Keywords: bioeconomics; natural resource management; optimal control; pseudo-spectral numerical techniques.

Fig. 1

Ecosystem components and set of management regimes. Plus (minus) sign indicates linkage increases (decreases) population abundance. Solid lines represent ecological interactions and dashed lines represent fishing. We consider optimal single‐species management of each fish stock, optimal two‐species combinations, and optimal food‐web management under different assumptions of recruitment variability of the forage fish. We also consider the implications of constraints on Pelican stocks on economic and ecological outcomes of the fished species under the different management regimes.

Fig. 2

Biomass over time (years) for the management regime–variability pairs. Biomass is scaled off of the initial conditions to facilitate comparisons across the panels (X(t)/X(0)). Management regime labels are found in Table 1. The top row corresponds to no variability, middle row to synchronous variability, and the bottom row to anti‐synchronous variability. The first column is anchovy, second column is sardine, and third column is halibut. The black dashed line is the population dynamics with no fishing for any species.

Fig. 3

Pelican numbers over time (years) under the management–variability pairs. Management regime labels are found in Table 1. The top row corresponds to no variability, middle row to synchronous variability, and the bottom row to anti‐synchronous variability. Pelican numbers measure percentage of the level at time 0.

Fig. 4

Long‐run Pelican numbers under the management–variability pairs. The white bars measure the increase by bringing species into the optimal management regime case relative to the case where all fisheries are open access. For example, the ecosystem‐based fisheries management model (EBFM) illustrates a 30% increase in Pelican stocks relative to the case of open access. The dark bars represent the highest possible achievement if the fisheries under management were under a fishing moratorium. For example, the dark bar in S corresponds to the case where A and H are open access and the sardine fishery is closed to fishing. The black line corresponds to the percentage gains in the long‐run average Pelican stock when all species are not fished.

Fig. 5

Sardine management (fishing mortality rates and biomass) and Pelican numbers over time. The legend is as follows: OA corresponds to open‐access, S corresponds to optimal management of sardine only, S_HS is the hockey‐stick formulation for the catch control rule, S_HCR is the harvest control rule, and A + S + H is the full‐EBFM optimal. The first column are fishing mortality rates (yr‐1), second column is scaled biomass levels (X(t)/X(0)), and the third column are Pelican numbers over time (% off of initial level). The top row is the no variability case, middle row is synchronous, and bottom row is anti‐synchronous.