References
Amante, C. & Eakins, B. (2009). ETOPO1 1 arc-minute global relief
model: procedures, data sources and analysis .
Amoroso, R.O., Pitcher, C.R., Rijnsdorp, A.D., McConnaughey, R.A.,
Parma, A.M., Suuronen, P., et al. (2018). Bottom trawl fishing
footprints on the world’s continental shelves. Proc. Natl. Acad.
Sci. , 115, E10275–E10282.
Andersen, K.H. (2019). Fish ecology, evolution, and exploitation .
Princeton University Press.
Battista, W., Kelly, R.P., Erickson, A. & Fujita, R. (2018). Fisheries
Governance Affecting Conservation Outcomes in the United States and
European Union. Coast. Manag. , 46, 388–452.
Beukhof, E., Dencker, T.S., Palomares, M.L.D. & Maureaud, A. (2019). A
trait collection of marine fish species from North Atlantic and
Northeast Pacific continental shelf seas.
Brander, K.M. (2007). Global fish production and climate change.Proc. Natl. Acad. Sci. , 104, 19709–19714.
Brown, J.H., Gillooly, J.F., Allen, A.P., Savage, V.M. & West, G.B.
(2004). Toward a metabolic theory of ecology. Ecology , 85,
1771–1789.
Carl, G. & Kühn, I. (2010). A wavelet-based extension of generalized
linear models to remove the effect of spatial autocorrelation.Geogr. Anal. , 42, 323–337.
Carl, G., Levin, S.C. & Kühn, I. (2018). spind: an R Package to Account
for Spatial Autocorrelation in the Analysis of Lattice Data.Biodivers. Data J. , 6, e20760.
Cheung, W.W.L., Sarmiento, J.L., Dunne, J., Frölicher, T.L., Lam,
V.W.Y., Deng Palomares, M.L., et al. (2013). Shrinking of fishes
exacerbates impacts of global ocean changes on marine ecosystems.Nat. Clim. Chang. , 3, 254–258.
Couce, E., Schratzberger, M. & Engelhard, G.H. (2020). Reconstructing
three decades of total international trawling effort in the North Sea.Earth Syst. Sci. Data , 12, 373–386.
van Denderen, D., Gislason, H., van den Heuvel, J. & Andersen, K.H.
(2020). Global analysis of fish growth rates shows weaker responses to
temperature than metabolic predictions. Glob. Ecol. Biogeogr. ,
29, 2203–2213.
van Denderen, P.D., Lindegren, M., MacKenzie, B.R., Watson, R.A. &
Andersen, K.H. (2018). Global patterns in marine predatory fish.Nat. Ecol. Evol. , 2, 65–70.
van Denderen, P.D., Petrik, C.M., Stock, C.A. & Andersen, K.H. (2021).
Emergent global biogeography of marine fish food webs. Glob. Ecol.
Biogeogr. , 30, 1822–1834.
Eddy, T.D., Bernhardt, J.R., Blanchard, J.L., Cheung, W.W.L., Colléter,
M., du Pontavice, H., et al. (2021). Energy flow through marine
ecosystems: confronting transfer efficiency. Trends Ecol. Evol. ,
36, 76–86.
Frainer, A., Primicerio, R., Kortsch, S., Aune, M., Dolgov, A. V,
Fossheim, M., et al. (2017). Climate-driven changes in functional
biogeography of Arctic marine fish communities. Proc. Natl. Acad.
Sci. , 114, 12202 LP – 12207.
Free, C.M., Thorson, J.T., Pinsky, M.L., Oken, K.L., Wiedenmann, J. &
Jensen, O.P. (2019). Impacts of historical warming on marine fisheries
production. Science (80-. ). , 363, 979–983.
Friedland, K.D., Langan, J.A., Large, S.I., Selden, R.L., Link, J.S.,
Watson, R.A., et al. (2020). Changes in higher trophic level
productivity, diversity and niche space in a rapidly warming continental
shelf ecosystem. Sci. Total Environ. , 704, 135270.
Friedland, K.D., Stock, C., Drinkwater, K.F., Link, J.S., Leaf, R.T.,
Shank, B. V, et al. (2012). Pathways between primary production
and fisheries yields of Large Marine Ecosystems. PLoS One , 7,
e28945.
Froese, R. & Pauly, D. (2018). FishBase World Wide Web electronic
publication. www.fishbase.org, version (10/2018).www.fishbase.org .
Gillooly, J.F., Brown, J.H., West, G.B., Savage, V.M. & Charnov, E.L.
(2001). Effects of size and temperature on metabolic rate. Science
(80-. ). , 293, 2248–2251.
Gislason, H., Collie, J., MacKenzie, B.R., Nielsen, A., Borges, M. de
F., Bottari, T., et al. (2020). Species richness in North
Atlantic fish: Process concealed by pattern. Glob. Ecol.
Biogeogr. , 29, 842–856.
Grace, J.B. (2006). Structural equation modeling and natural
systems . Cambridge University Press, Cambridge, UK.
Guiet, J., Galbraith, E.D., Bianchi, D. & Cheung, W.W.L. (2020).
Bioenergetic influence on the historical development and decline of
industrial fisheries. ICES J. Mar. Sci. , 77, 1854–1863.
Hamon, K.G., Kreiss, C.M., Pinnegar, J.K., Bartelings, H., Batsleer, J.,
Catalán, I.A., et al. (2021). Future socio-political scenarios
for aquatic resources in Europe: an operationalized framework for marine
fisheries projections. Front. Mar. Sci.
Hatton, I.A., Heneghan, R.F., Bar-On, Y.M. & Galbraith, E.D. (2022).
The global ocean size spectrum from bacteria to whales. Sci.
Adv. , 7, eabh3732.
Kwiatkowski, L., Torres, O., Bopp, L., Aumont, O., Chamberlain, M.,
Christian, J.R., et al. (2020). Twenty-first century ocean
warming, acidification, deoxygenation, and upper-ocean nutrient and
primary production decline from CMIP6 model projections.Biogeosciences , 17, 3439–3470.
Laufkötter, C., John, J.G., Stock, C.A. & Dunne, J.P. (2017).
Temperature and oxygen dependence of the remineralization of organic
matter. Global Biogeochem. Cycles , 31, 1038–1050.
Link, J., Overholtz, W., O’Reilly, J., Green, J., Dow, D., Palka, D.,et al. (2008). The Northeast US continental shelf Energy Modeling
and Analysis exercise (EMAX): Ecological network model development and
basic ecosystem metrics. J. Mar. Syst. , 74, 453–474.
Lotze, H.K., Tittensor, D.P., Bryndum-Buchholz, A., Eddy, T.D., Cheung,
W.W.L., Galbraith, E.D., et al. (2019). Global ensemble
projections reveal trophic amplification of ocean biomass declines with
climate change. Proc. Natl. Acad. Sci. , 116, 12907–12912.
Maureaud, A., Hodapp, D., van Denderen, P.D., Hillebrand, H., Gislason,
H., Spaanheden Dencker, T., et al. (2019).
Biodiversity–ecosystem functioning relationships in fish communities:
biomass is related to evenness and the environment, not to species
richness. Proc. R. Soc. B Biol. Sci. , 286, 20191189.
Myers, R.A. & Worm, B. (2003). Rapid worldwide depletion of predatory
fish communities. Nature , 423, 280–283.
O’Connor, M.I., Piehler, M.F., Leech, D.M., Anton, A. & Bruno, J.F.
(2009). Warming and resource availability shift food web structure and
metabolism. PLOS Biol. , 7, e1000178.
Pauly, D. & Christensen, V. (1995). Primary production required to
sustain global fisheries. Nature , 374, 255.
Petrik, C.M., Stock, C.A., Andersen, K.H., van Denderen, P.D. & Watson,
J.R. (2019). Bottom-up drivers of global patterns of demersal, forage,
and pelagic fishes. Prog. Oceanogr. , 176, 102124.
Petrik, C.M., Stock, C.A., Andersen, K.H., van Denderen, P.D. & Watson,
J.R. (2020). Large pelagic fish are most sensitive to climate change
despite pelagification of ocean food webs. Front. Mar. Sci. , 7,
588482.
Pinsky, M.L., Worm, B., Fogarty, M.J., Sarmiento, J.L. & Levin, S.A.
(2013). Marine taxa track local climate velocities. Science (80-.
). , 341, 1239–1242.
Pomeroy, L.R. & Deibel, D.O.N. (1986). Temperature regulation of
bacterial activity during the spring bloom in Newfoundland coastal
waters. Science (80-. ). , 233, 359–361.
du Pontavice, H., Gascuel, D., Reygondeau, G., Stock, C. & Cheung,
W.W.L. (2021). Climate-induced decrease in biomass flow in marine food
webs may severely affect predators and ecosystem production. Glob.
Chang. Biol. , 27, 2608–2622.
Rall, B.C., Brose, U., Hartvig, M., Kalinkat, G., Schwarzmüller, F.,
Vucic-Pestic, O., et al. (2012). Universal temperature and
body-mass scaling of feeding rates. Philos. Trans. R. Soc. B Biol.
Sci. , 367, 2923 LP – 2934.
Ricard, D., Minto, C., Jensen, O.P. & Baum, J.K. (2012). Examining the
knowledge base and status of commercially exploited marine species with
the RAM Legacy Stock Assessment Database. Fish Fish. , 13,
380–398.
Rice, J. & Gislason, H. (1996). Patterns of change in the size spectra
of numbers and diversity of the North Sea fish assemblage, as reflected
in surveys and models. ICES J. Mar. Sci. , 53, 1214–1225.
Rosseel, Y. (2012). Lavaan: An R Package for structural equation
modeling. J. Stat. Softw. , 48, 1–36.
Silsbe, G.M., Behrenfeld, M.J., Halsey, K.H., Milligan, A.J. &
Westberry, T.K. (2016). The CAFE model: A net production model for
global ocean phytoplankton. Global Biogeochem. Cycles , 30,
1756–1777.
Stock, C.A., Dunne, J.P. & John, J.G. (2014). Global-scale carbon and
energy flows through the marine planktonic food web: an analysis with a
coupled physical–biological model. Prog. Oceanogr. , 120, 1–28.
Stock, C.A., John, J.G., Rykaczewski, R.R., Asch, R.G., Cheung, W.W.L.,
Dunne, J.P., et al. (2017). Reconciling fisheries catch and ocean
productivity. Proc. Natl. Acad. Sci. , 114, E1441–E1449.
Tittensor, D.P., Novaglio, C., Harrison, C.S., Heneghan, R.F., Barrier,
N., Bianchi, D., et al. (2021). Next-generation ensemble
projections reveal higher climate risks for marine ecosystems.Nat. Clim. Chang. , 11, 973–981.
Vucic-Pestic, O., Ehnes, R.B., Rall, B.C. & Brose, U. (2011). Warming
up the system: higher predator feeding rates but lower energetic
efficiencies. Glob. Chang. Biol. , 17, 1301–1310.
Walker, N.D., Maxwell, D.L., Le Quesne, W.J.F. & Jennings, S. (2017).
Estimating efficiency of survey and commercial trawl gears from
comparisons of catch-ratios. ICES J. Mar. Sci. , 74, 1448–1457.
Watson, R.A. (2017). A database of global marine commercial,
small-scale, illegal and unreported fisheries catch 1950–2014.Sci. data , 4, 170039.
Wei, C.-L., Rowe, G.T., Escobar-Briones, E., Boetius, A., Soltwedel, T.,
Caley, M.J., et al. (2011). Global patterns and predictions of
seafloor biomass using random forests. PLoS One , 5, e15323.
Windle, M.J.S., Rose, G.A., Devillers, R. & Fortin, M.-J. (2010).
Exploring spatial non-stationarity of fisheries survey data using
geographically weighted regression (GWR): an example from the Northwest
Atlantic. ICES J. Mar. Sci. , 67, 145–154.