Tracking the global footprint of fisheries

By D. Kroodsma, Juan Mayorga, Timothy Hochberg, Nathan A. Miller, K. Boerder, F. Ferretti, A. Wilson, Bjorn Bergman, T. White, B. Block and 4 more. Science, 2018

919 citations recorded by the source corpus.

Subfields: Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/4a75f9406b2bc407ededf651d75a052c1122d7fc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. R. Phillips
2. J. Croxall
3. A. G. Wood
4. R. R. Warner
5. C. Small
6. M. Jacox
7. Daniel M. Palacios
8. D. Marshall

In Global and Planetary Change

1. R. Phillips
2. R. R. Warner
3. M. Jacox
4. Daniel M. Palacios
5. D. Marshall
6. E. Hazen
7. Michael Bode
8. J. Croxall

Citations in the corpus

• Underestimating the benefits of marine protected areas for the replenishment of fished populations (2019, background): “Intense debate about the sustainability of wild fisheries continues, but improving their sustainability is a common goal (Pauly et al. 2002; Kroodsma et al. 2018).”
• A comprehensive large‐scale assessment of fisheries bycatch risk to threatened seabird populations (2019, background): “Given the vast geographical distribution of global fisheries (Kroodsma et al., 2018), bycatch reduction requires management efforts that are well targeted in space and time.”
• Species diversity, taxonomy and distribution of Chondrichthyes in the Mediterranean and Black Sea (2020, background): “The Mediterranean Sea is one of the most exploited ocean sectors on the planet (Colloca et al. 2017b; Fortibuoni et al. 2017; Kroodsma et al. 2018; Corrales et al. 2019; Giménez et al. 2020).”
• Dynamic ensemble models to predict distributions and anthropogenic risk exposure for highly mobile species (2019, background): “Daily distributions of whale habitat suitability could be combined with vessel movement data derived from shipboard monitoring systems (e.g., AIS; Kroodsma et al., 2018) to re‐ fine strike risk and evaluate alternative management options.”
• Applications for deep learning in ecology (2018, background): “Recently, deep neural networks mapped the footprint of fisheries using tracking informa‐ tion from industrial fishing vessels (Kroodsma et al., 2018).”