Clustering of disaggregated fisheries data reveals functional longline fleets across the Pacific

Dynamic human, oceanographic, and ecological factors mediate transboundary fishery overlap across the Pacific high seas

“…The longline fleets (which are the focus of this analysis) are depicted in solid colors. Their approximate fishing areas were determined by the methodology described by Frawley et al (2022), which considered AIS observations between 2017–2019. Major surface fishing fleets interacting with North Pacific albacore (not explicitly modeled in this study) are depicted in dashed colors.…”

“…As many coastal fish stocks have declined due to overfishing and habitat degradation, pelagic species are an increasingly important source of livelihoods and revenue (Bell et al, 2018), particularly across Pacific Island Countries and Territories where tuna fishing and processing industries may represent a substantial proportion of the total gross domestic product. Despite their economic and cultural importance, considerable uncertainty persists regarding the distribution and biology of many pelagic fish species, including the nature and extent to which they interact with different fishing fleets and gear types (Frawley et al, 2022), and the degree to which such patterns and processes are impacted by environmental variability. Indeed, there is growing concern that climate‐driven changes in the distribution and abundance of pelagic organisms may disrupt sustainable resource management and negatively impact developing ocean economies (Bell et al, 2021; Pinsky et al, 2018).…”

“…Here, we use the North Pacific albacore ( Thunnus alalunga , Scombridae), one of the only Pacific tuna stocks primarily targeted by longline fishing gear that is not listed as overfished or experiencing overfishing (ISSF, 2022), as a test case to examine how seasonal and interannual oceanographic variability mediate overlap between different longline fishing fleets, gear types and albacore life history stages. Building on previous work describing the global environmental niche of pelagic longline fishing vessels (Frawley et al, 2022; Ortuño Crespo et al, 2018) and the habitat associations (Lee et al, 2020; Muhling et al, 2019) and migratory strategies (Childers et al, 2011; Muhling et al, 2022) of the North Pacific albacore, we (1) identify and describe the spatial and environmental drivers influencing the distribution of different fishing fleets and albacore life stages; (2) quantify changes in spatial niche overlap between each fishing fleet and albacore life stage within and between years; and (3) explore how spatial overlap and fishery interactions may be mediated by different configurations of longline fishing gear. While previous research has identified static areas of overlap between different species and gear types (Guy et al, 2013; White et al, 2019), our analysis highlights the utility of dynamic models to identify underlying social–ecological processes and obtain mechanistic insight.…”

Mesoscale eddies modulate the dynamics of human fishing activities in the global midlatitude ocean

“…AIS-based global fishing activity datasets have prompted an increasing number of studies to clarify the variation pattern of fishing activity and its drivers (Crespo et al, 2018;Frawley et al, 2022;Guiet et al, 2019;Hintzen et al, 2021;Kroodsma et al, 2018;Welch et al, 2022). Previous research shows that the global patterns of fishing activities present a strong response to cultural and political factors (e.g., holidays and closures), while the effects of short-term economic and environmental variation are ambiguous in terms of temporal variation (Kroodsma et al, 2018).…”

“…Based on convolutional neural networks, navigation information every few seconds, such as the identity, position, speed, and turning angle of each ship from an automatic identification system (AIS), has been successfully applied to classify the gear type of fishing vessels and quantify their fishing activity (Kroodsma et al, 2018). AIS‐based global fishing activity datasets have prompted an increasing number of studies to clarify the variation pattern of fishing activity and its drivers (Crespo et al, 2018; Frawley et al, 2022; Guiet et al, 2019; Hintzen et al, 2021; Kroodsma et al, 2018; Welch et al, 2022). Previous research shows that the global patterns of fishing activities present a strong response to cultural and political factors (e.g., holidays and closures), while the effects of short‐term economic and environmental variation are ambiguous in terms of temporal variation (Kroodsma et al, 2018).…”