Addressing the dichotomy of fishing and climate in fishery management with the FishClim model

Managing fish stocks is incredibly complex due to the influence of various intrinsic and extrinsic factors, including fishing and climate-induced environmental change (CIEC). Stock collapses can result from overexploitation or climate-driven alterations in fish distribution and abundance. While many studies have investigated the interplay between fishing and environmental factors, the precise, time-varying contributions of each remain poorly understood, hindering effective fisheries management. The North Sea cod, *Gadus morhua*, provides a key case study, as its decline has sparked debate regarding the relative contributions of overfishing and CIEC. Existing studies have jointly examined these influences, but haven't precisely quantified their effects. Current management practices largely ignore the potential impact of CIEC, despite the growing influence of anthropogenic climate change on marine ecosystems. This research aims to address this gap by developing and applying a new model, FishClim, to analyze the interaction between fishing and CIEC on North Sea cod stocks, both historically and in future projections. This model quantifies the relative influence of fishing and CIEC, providing crucial insights for developing better, sustainable long-term fish stock management strategies. The improved understanding of this interplay is crucial because anthropogenic climate change is expected to drastically increase its impacts on marine ecosystems in the coming decades.

Several studies have investigated the combined impacts of climate change and fishing on cod populations. Engelhard et al. (2014) examined the influence of both drivers on the spatial distribution of cod in the North Sea over the past century, demonstrating that warming caused a northward and deeper shift while fishing depleted stocks off the coasts of England and Scotland. In the Baltic Sea, Eero et al. (2011) analyzed the relative influence of CIEC, predation, eutrophication, and exploitation on cod biomass throughout the 20th century. They found that nutrient availability and mammal predation were the main drivers in the early 20th century, followed by fishing in the 1940s, and eutrophication playing a role in the 1980s. Their study quantified these influences for 1980-1984, showing a 13%, 43%, and 52% contribution from eutrophication, climate, and fishing, respectively. Other research, including studies by Beaugrand and Kirby (2010) and Möllmann et al. (2021), highlight the complex interactions between these factors and the urgent need for a model that integrates both fishing and climate effects for more accurate predictions and management strategies. This work acknowledges the limitations of previous attempts in accurately assessing these combined impacts and aims to offer a more robust solution using FishClim.

The FishClim model estimates cod population size (standardized Spawning Stock Biomass, or dSSB) based on three factors: population growth rate (*r*), fishing intensity (*α*), and maximum standardized SSB (mdSSB) attainable given the environmental conditions. The mdSSB is determined solely by CIEC, while fishing intensity reflects the impact of fishing effort. The model is applied to the North East Atlantic, focusing on the North Sea cod stock, using data from various sources. Data includes sea surface temperature (SST) from the COBE SST2 dataset (1850-2019), bathymetry from GEBCO, and daily chlorophyll-a concentration from the GlobColour project (1997-2019). Biological data, including cod recruitment at age 1, spawning stock biomass (SSB), and fishing effort (F) from 1963 to 2019, were obtained from ICES. A plankton index of larval cod survival, updated from Beaugrand et al. (2003), based on Continuous Plankton Recorder (CPR) data, was also used. Climate projections for SST and chlorophyll-a were obtained from CMIP6, using Shared Socioeconomic Pathways (SSPs) 245 and 585. The FishClim model uses an empirical niche model, integrating temperature, bathymetry, and chlorophyll-a concentration (duration and concentration) to estimate mdSSB. Spatial patterns in mdSSB were modeled using a combination of Gaussian and trapezoidal functions to represent thermal and bathymetric niches, respectively. The trophic niche was modeled using a rectangular function that considers chlorophyll-a concentration above a certain threshold over a 15-day period. The model combines these niches using a multiplicative approach. The model then incorporates fishing intensity, initially derived from ICES SSB data, to reconstruct long-term changes in dSSB. Cluster analysis was performed to identify key time periods, and a Jackknife procedure was used to quantify the influence of fishing and CIEC. The model was then forced with CMIP6 outputs to assess future mdSSB under different climate scenarios. Analyses included the estimation of the years to cod extirpation and pooled standardized catch in 2100 under various combinations of climate scenarios and management approaches (constant versus adjusted fishing intensity using the mean sustainable yield approach). A sensitivity index was developed to assess the combined influence of fishing intensity and CIEC on dSSB.

The FishClim model demonstrated that fishing and CIEC have nearly equal influence on the North Sea cod stock's long-term fluctuations. Over the period 1963-2019, fishing intensity contributed about 55% to changes in SSB, while CIEC contributed approximately 45%. However, this overall equality masks important temporal variations in their respective influence. For example, during the Gadoid Outburst (approximately 1963-1983), both drivers contributed almost equally. In contrast, from the end of the 1980s to 2007, fishing and CIEC acted synergistically, leading to a pronounced stock decline. From 2008 onward, reduced fishing effort led to a SSB increase despite continued adverse environmental conditions, suggesting that current CIEC regime strongly affects cod SSB. Future projections under climate change scenarios (SSP245 and SSP585) reveal a substantial decrease in mdSSB throughout the 21st century. The magnitude of these decreases is amplified by high levels of fishing intensity. Under the ‘fossil-fueled development’ scenario (SSP585) combined with constant fishing effort, the model predicts a full stock collapse by 2088 in some ESMs. Further, the analysis illustrates that recovering from a collapse is more difficult when the environment is less suitable. The model also demonstrates that reducing fishing effort alone will not prevent collapse when the environment becomes less suitable due to climate change. Analyses comparing constant and adjusted fishing intensity (MSY-adjusted) showed that incorporating CIEC into management strategies significantly delays cod extirpation (median delay of 3 and 25 years for SSP245 and SSP585, respectively). Failure to incorporate CIEC into management significantly reduces long-term (2020-2100) pooled standardized catch (median reduction of 9.9% and 27.1% for SSP245 and SSP585, respectively, under constant fishing).

The FishClim model offers a novel approach to quantify the combined effects of fishing and CIEC on fish stocks. Unlike previous studies, this model doesn’t simply compare the impacts of each driver independently; instead, it explicitly models their interaction, revealing a complex interplay of synergy and antagonism. The findings highlight that the long-standing debate over the relative importance of fishing and climate change is irrelevant; both are critical drivers of stock dynamics. The results emphasize the crucial role of adaptive management strategies that account for CIEC. Ignoring environmental variability in management decisions can lead to substantial negative consequences, including increased risk of stock collapse and reduced long-term yields. The model's projections emphasize the need for coordinated efforts in both fisheries management and climate change mitigation to ensure the sustainable exploitation of cod resources. The substantial inter-ESM variability in the projections highlights the importance of continued research and refinement of climate models. The model also provides insight into the challenges associated with rebuilding collapsed stocks in the face of unfavourable environmental conditions. While the model focuses on North Sea cod, its framework and approach are adaptable to other species and regions, prompting a call for broader application of this integrated modeling approach in fisheries management.

This study demonstrates the critical need to move beyond the dichotomy of fishing versus climate change in fisheries management. The FishClim model provides a powerful tool for quantifying the intertwined effects of these factors, revealing their synergistic and antagonistic interactions. The findings underscore the urgent need for adaptive management strategies that explicitly incorporate CIEC projections to mitigate the risk of stock collapses. The model's predictions highlight that mitigating climate change is essential for preventing irreversible consequences for fisheries. The study's approach can be applied to other species and regions, fostering a more integrated and effective approach to global fisheries management.

The FishClim model, while comprehensive, has certain limitations. It uses a standardized SSB, which could be scaled to actual SSB but doesn't include the size/age structure of the stock. The current model also doesn't explicitly include natural mortality, assuming it's implicitly considered within the growth rate term. Migration patterns aren't accounted for, with the assumption of limited influence at the North Sea scale. While the model uses the widely accepted BMSY approach for managing fishing intensity, other reference points could be employed. The model’s predictions rely on CMIP6 climate projections, which have inherent uncertainties and inter-ESM variability. Finally, the model focuses primarily on the interplay between fishing and CIEC, potentially overlooking other relevant factors influencing cod populations.