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Articles by Link JS
Evaluating use of seabird data, identifying entry points, and building bridges to inform US fisheries management
Ecosystem-based fisheries management (EBFM) focuses on marine ecosystems and ecological interactions, such as predator–prey interactions, rather than just the population biology of target fisheries taxa (Pikitch et al. 2004). In recent decades, fisheries management agencies across the globe have been shifting to this approach to better understand the impacts of ecosystem dynamics on managed species (Fulton et al. 2019, Townsend et al. 2019; Rodriguez-Perez et al. 2023).
Laying the foundation for ecosystem-based fisheries management in the Eastern Ionian demersal fishery
Fisheries management involves trade-offs among several and potentially conflicting objectives; single stock sustainability, economic viability, social welfare, and ecosystem health. Management traditionally focused on single-stock sustainability and economic objectives. However, in a mixed fishery, interdependencies often make it unfeasible to achieve maximum sustainable yield (MSY) for all target species simultaneously.
Ecosystem modeling in the Northeastern United States: a comment on Sivel et al
It was with great interest that I [and many other ecosystem modelers and scientists in the Northeast US (NEUS), NOAA Fisheries, and NOAA] anticipated reading Sivel et al. (2025). I appreciate the expression of different perspectives, coupled with debate and examination of science to advance the discipline and the application of its knowledge.
Opportunities and barriers identified during the co-creation of a sustainability index for small-scale fisheries
Sustainability in fisheries aims to ensure that fish populations are harvested at a rate that allows them to replenish, while maintaining the ecological balance and supporting the socio-economic well-being of fishing communities (Hilborn et al. 2004, FAO 2020). This approach recognizes that fisheries are not just about extracting resources but about maintaining a delicate balance between ecological integrity, economic viability, and social equity now and in the future (Worm et al. 2009, FAO 2015).
Applying a joint-species spatio-temporal model to guide the reduction of bycatch in longline fisheries with a case study on swordfish in the Southwestern Pacific Ocean
Longline fisheries targeting tunas are major commercial operations for many regions and countries (Ward and Elscot 2000, Ward and Myers 2005). However, these fisheries also result in the incidental capture of other pelagic migratory species, including swordfish (SWO), marlins, and sharks, which can have substantial ecological and economic impacts.
An ecosystem-based management strategy evaluation of harvest control rules for Norwegian spring-spawning herring (Clupea harengus L.)
Management Strategy Evaluation (MSE) is essential for supporting the management of living marine resources. While MSEs can fall into different categories (ICES 2020, Walter et al. 2023), fundamentally, the process uses simulations from an operating model (OM) to evaluate and communicate the trade-offs in performance among candidate management strategies against management objectives (Punt et al. 2016). Some areas of the world have a history of using MSE.
An analysis of stakeholders’ vision of the future of coastal fisheries in Germany
Global coastal ecosystems are expected to change considerably in the coming decades due to climate change and increasing anthropogenic pressures (Cheung et al. 2016, Moll et al. 2024). In present times, the oceans are highly affected by human influence (Halpern et al. 2008).
Looking back in awe: spectacular advances in the marine biodiversity toolbox to support sustainable oceans
When ICES editor Howard Browman, an old friend from McGill graduate school days, invited me to write a Food for Thought piece, it challenged me to ask how I got here and what I have learned that I would like to share. “Looking Back in Awe” refers to how we operated at the beginning of my career and how far technology has advanced (Table 1). Some of the ways we worked back then bring a smile to my face.
Seal-fishery interactions in the Falkland Islands-operational and environmental factors drive resource competition
Interactions between marine mammals and commercial fisheries are a key threat to marine mammal populations worldwide. The incidental capture and entanglement of marine mammals during commercial fishing operations is regarded as a significant cause of mortality in global marine ecosystems (Avila et al. 2018, Nelms et al. 2021). Various marine mammal populations have experienced dramatic declines as a result of sustained interactions and competition with fisheries (Nelms et al. 2021, Jog et al. 2022).
Community structure and environmental drivers of offshore hard-bottom reef fishes in the northern Gulf of Mexico
Characterizing the community structure of marine fishes and their relationships to potential environmental drivers is important for understanding ecological processes in marine environments and for advancing ecosystem-based fisheries management (Mangel and Levin 2005, Fogarty 2014, Tam et al. 2017).
Disentangling bottom-up and top-down controls on fish consumption of key prey in the Northeast US Shelf ecosystem
Efforts to develop and operationalize ecosystem approaches to fisheries management (EAFM) for living marine resources have been driven in large part by a renewed appreciation for the role that trophodynamics and biophysical forcing play in governing the dynamics of exploited taxa (Gaichas et al. 2012, Link and Marshak 2022).
Adding the risk of stock collapse over time to stock assessments and harvest allocation decisions
Technical measures are used to manage many fisheries to address sustainability policy objectives (Belschner et al. 2019). The use of technical measures such as harvest controls, gear selectivity specifications, area, and seasonal closures are used to control fishing effort to a level that is expected to maintain fish stocks while reducing by-catch of nontargets species and impacts on marine ecosystems (Suuronen and Sardà 2007, Cadrin and Pastoors 2008, Kraak 2023).
Even low levels of cannibalism can bias population estimates for Pacific hake
There is an increasing need for holistic models of marine systems to support management strategies that adapt to changing ocean conditions. Re-examining data inputs and model assumptions can improve implementation and our understanding of the ecosystem (Link et al. 2020, Karp et al. 2023).
Density-dependent habitat selection and warming determine the spatial distribution of haddock (Melanogrammus aeglefinus) on Georges Bank
Marine fish distribution is influenced by a variety of factors, such as habitat quality, environmental conditions, and biological interactions (Pinsky et al. 2013, Wang et al. 2020, Von Leesen et al. 2022). In an ever-changing environment, detecting shifts in the spatial distribution of marine fish and understanding the relative importance of climate change and biotic factors impacting fish distributions can improve fisheries management (Link et al. 2011, Klein et al. 2017, Bahri et al. 2021).
Facilitating an ecosystem approach through open data and information packaging
An ecosystem approach (EA) to marine management considers environmental, ecological, and socio-economic factors in decision-making processes (Long et al. 2015, Langlet and Rayfuse 2019, O'Higgins et al. 2020). The implementation of this approach is linked to a growing demand for increasingly diverse information about marine ecosystems, with a corresponding increase in data volumes and complexity (Reichman et al. 2011, Addison et al. 2018).
Ecological indicators to monitor offshore wind interactions with fisheries resources
Offshore wind development (OWD) is a central component of society’s approach to generating renewable energy as it moves toward reducing its reliance on fossil fuels to combat global climate change. Currently, the USA is on track to develop 30 GW of offshore wind energy capacity by 2030 and an additional 15 GW by 2035 (DOI 2022).
Multispecies population-scale emergence of climate change signals in an ocean warming hotspot
The Northeast Shelf of the USA is characterized by strong seasonal cycles and interannual variability in oceanographic conditions that drive nutrient availability and energy flows through the ecosystem (Parr 1933, Pershing and Stamieszkin 2020). This ecoregion has historically been renowned for its productive fisheries, with the challenges of overfishing dominating management concerns in the region (Rosenberg et al. 2006).
An Eulerian perspective on habitat models of striped bass occurrence in an offshore wind development area
Globally, offshore wind energy development is increasing in both scale and pace. In particular, vast regions of the US Atlantic shelf slated for offshore wind farms (OWFs) overlap broadly with known migration corridors of fishes, marine mammals, and birds (Gulka and Jenkins 2020). As of December 2020, 16 sites amounting to 7051 km2 along the US Mid-Atlantic Bight (MAB) have been leased for future construction (Fig. 1; Bureau of Ocean Energy Management, 2022).
Simultaneous Bayesian estimation of size-specific catchability and size spectrum parameters from trawl data
Effective ecosystem-based management of marine populations and communities requires monitoring tools capable of detecting effects of multiple interacting drivers, both ecological and anthropogenic (Tam et al. 2017). The size spectrum of an assemblage is the relationship between the abundance of organisms to their body size, such that smaller, lower-trophic-level organisms will be more abundant than larger ones (Sheldon and Parsons 1967, Rice and Gislason 1996).
Modelling perspective on the climate footprint in south east Australian marine waters and its fisheries
Climate change has had a significant impact on distribution and abundance of 81% of marine species globally (Poloczanska et al. 2014). It affects primary productivity and alters marine habitats through changes in ocean circulation, stratification, and oxygen concentration (Manabe et al. 1993, Keeling et al. 2010, Bopp et al. 2013).
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