TY - JOUR
T1 - Adding perspectives to
T2 - “Global trends in carbon dioxide (CO2) emissions from fuel combustion in marine fisheries from 1950 - 2016"
AU - Ziegler, Friederike
AU - Eigaard, Ole Ritzau
AU - Parker, Robert W.R.
AU - Tyedmers, Peter H.
AU - Hognes, Erik Skontorp
AU - Jafarzadeh, Sepideh
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/9
Y1 - 2019/9
N2 - A contribution in this issue, Greer et al. (2019), models carbon dioxide emissions from fuel combustion in global fisheries. This is done based on a method using data on fishing effort, presenting results for two sectors: small-scale and industrial fisheries. The selection of these sectors is not motivated in relation to studying fuel use, and it is well-documented that other factors more accurately predict fuel use of fisheries and would constitute a more useful basis for defining sub-sectors, when the goal of the study is to investigate fuel use. Weakly grounded assumptions made in the translation of fishing effort into carbon dioxide emissions (e.g. the engine run time per fishing day for each sector) systematically bias results towards overestimating fuel use of “industrial” vessels, underestimating that of “small-scale”. A sensitivity analysis should have been a minimum requirement for publication. To illustrate how the approach used by Greer et al. (2019) systematically misrepresents the fuel use and emissions of the two sectors, the model is applied to Australian and New Zealand rock lobster trap fisheries and compared to observed fuel use. It is demonstrated how the approach underestimates emissions of small-scale fisheries, while overestimating emissions of industrial fisheries. As global fisheries are dominated by industrial fisheries, the aggregate emission estimate is likely considerably overestimated. Effort-based approaches can be valuable to model fuel use of fisheries in data-poor situations, but should be seen as complementary to estimates based on direct data, which they can also help to validate. Whenever used, they should be based on transparent, science-based data and assumptions.
AB - A contribution in this issue, Greer et al. (2019), models carbon dioxide emissions from fuel combustion in global fisheries. This is done based on a method using data on fishing effort, presenting results for two sectors: small-scale and industrial fisheries. The selection of these sectors is not motivated in relation to studying fuel use, and it is well-documented that other factors more accurately predict fuel use of fisheries and would constitute a more useful basis for defining sub-sectors, when the goal of the study is to investigate fuel use. Weakly grounded assumptions made in the translation of fishing effort into carbon dioxide emissions (e.g. the engine run time per fishing day for each sector) systematically bias results towards overestimating fuel use of “industrial” vessels, underestimating that of “small-scale”. A sensitivity analysis should have been a minimum requirement for publication. To illustrate how the approach used by Greer et al. (2019) systematically misrepresents the fuel use and emissions of the two sectors, the model is applied to Australian and New Zealand rock lobster trap fisheries and compared to observed fuel use. It is demonstrated how the approach underestimates emissions of small-scale fisheries, while overestimating emissions of industrial fisheries. As global fisheries are dominated by industrial fisheries, the aggregate emission estimate is likely considerably overestimated. Effort-based approaches can be valuable to model fuel use of fisheries in data-poor situations, but should be seen as complementary to estimates based on direct data, which they can also help to validate. Whenever used, they should be based on transparent, science-based data and assumptions.
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U2 - 10.1016/j.marpol.2019.03.001
DO - 10.1016/j.marpol.2019.03.001
M3 - Article
AN - SCOPUS:85070112108
SN - 0308-597X
VL - 107
JO - Marine Policy
JF - Marine Policy
M1 - 103488
ER -