Spatial data reporting, assembly, and analysis: adjusted a link/organisation name+acronym
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**fish catch reporting for the purpose of stock assessment by the New South Wales Department of Primary Industries/Fisheries New South Wales in Australia; examples:<ref name=”Hall_2020″>Hall, K.C. (2020). [https://www.dpi.nsw.gov.au/__data/assets/pdf_file/0008/1222568/NSW-Stock-Assessment-Report-Bluespotted-Flathead-2019.pdf Stock assessment report 2019 – Ocean Trawl Fishery – Bluespotted Flathead (Platycephalus caeruleopunctatus)]. NSW Department of Primary Industries, Coffs Harbour, 67 pp.</ref><ref name=”Chick_2021″>Chick, R.C. (2021). [https://www.dpi.nsw.gov.au/__data/assets/pdf_file/0011/1294760/stock-status-summary-2020-21-nipper-v2.pdf NSW Stock Status Summary 2020/21 – Estuary General Fishery (Hand Gathering) – Ghost Nipper (Trypaea austaliensis)]. Fisheries NSW, Port Stephens Fisheries Institute. 12 pp.</ref>
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**fish catch reporting for the purpose of stock assessment by the New South Wales Department of Primary Industries/Fisheries New South Wales in Australia; examples:<ref name=”Hall_2020″>Hall, K.C. (2020). [https://www.dpi.nsw.gov.au/__data/assets/pdf_file/0008/1222568/NSW-Stock-Assessment-Report-Bluespotted-Flathead-2019.pdf Stock assessment report 2019 – Ocean Trawl Fishery – Bluespotted Flathead (Platycephalus caeruleopunctatus)]. NSW Department of Primary Industries, Coffs Harbour, 67 pp.</ref><ref name=”Chick_2021″>Chick, R.C. (2021). [https://www.dpi.nsw.gov.au/__data/assets/pdf_file/0011/1294760/stock-status-summary-2020-21-nipper-v2.pdf NSW Stock Status Summary 2020/21 – Estuary General Fishery (Hand Gathering) – Ghost Nipper (Trypaea austaliensis)]. Fisheries NSW, Port Stephens Fisheries Institute. 12 pp.</ref>
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*”’0.05×0.05 degree squares:”’
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*”’0.05×0.05 degree squares:”’
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**VMS (vessel monitoring systems) data and fishing logbook data for [[International Council for the Exploration of the Sea
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**VMS (vessel monitoring systems) data and fishing logbook data for [[International Council for the Exploration of the Sea]] (ICES) and others,<ref name = “ICES_2019” /><ref name = “Schulte_et_al_2020″>{{Cite journal |last1=Schulte |first1=K. F. |last2=Siegel |first2=V. |last3=Hufnagl |first3=M. |last4=Schulze |first4=M. |last5=Temming |first5=A. |year=2020 |title=Spatial and temporal distribution patterns of brown shrimp (”Crangon crangon”) derived from commercial logbook, landings, and vessel monitoring data |journal=ICES Journal of Marine Science |volume=77 |issue=3 |pages=1017–1032 |doi=10.1093/icesjms/fsaa021|doi-access=free }}</ref> as also implemented in the ICES “FishFrame” regional database<ref name = “Hintzen_et_al_2012″>{{Cite journal |last1=Hintzen |first1=Niels T. |last2=Bastardie |first2=Francois |last3=Beare |first3=Doug |last4=Piet |first4=Gerjan J. |last5=Ulrich |first5=Clara |last6=Deporte |first6=Nicolas |last7=Egekvist |first7=Josefine |last8=Degel |first8=Henrik |year=2012 |title=VMStools: Open-source software for the processing, analysis and visualisation of fisheries logbook and VMS data |journal=Fisheries Research |volume=115-116 |pages=31–43 |doi=10.1016/j.fishres.2011.11.007|url=https://backend.orbit.dtu.dk/ws/files/56377631/Hinzen.pdf }}</ref><ref>Beare, D.J., ”et al”. (2011). “Development of tools for logbook and VMS data analysis: Studies for carrying out the common fisheries policy (No MARE/2008/10 Lot 2)”. IMARES Wageningen UR, Report no. C019/11, 94 pp. Available at https://storage.googleapis.com/google-code-archive-downloads/v2/code.google.com/vmstools/C019.11_VMS_tools-DB-FinalVersion.pdf</ref>
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**identification of vulnerable marine ecosystems (VMEs) in the North-East Atlantic for the EU-funded Horizon 2020 ATLAS Project.<ref name = “Morato_et_al_2018″>{{Cite journal |last1=Morato |first1=Telmo |last2=Pham |first2=Christopher K. |last3=Pinto |first3=Carlos |last4=Golding |first4=Neil |last5=Ardron |first5=Jeff A. |last6=Muñoz |first6=Pablo Durán |last7=Neat|first7=Francis |year=2018 |title=A multi criteria assessment method for identifying vulnerable marine ecosystems in the North-East Atlantic |journal=Frontiers in Marine Science |volume=5 |pages=460 |doi=10.3389/fmars.2018.00460|doi-access=free }}</ref> According to Turner ”et al.”, 2021, “ATLAS partners helped develop a data aggregation approach, the VME Index, to help identify areas where vulnerable marine ecosystems are known or are likely to occur. The VME Index is a single metric based on a multi-criteria assessment method that combines VME indicator records within a C-square (i.e., a spatial unit used by ICES: 0.05 x 0.05 degree grid, equivalent to approximately 15 km² at 60°N latitude) based on the abundance/presence of VME indicator taxa and how reliable the underlying data are. … ICES has been using the VME Index since 2018 to provide advice concerning the protection of vulnerable marine ecosystems.”<ref name = “Turner_et_al_2021”>{{Cite journal |last1=Turner |first1=Phillip J. |last2=Gianni |first2=Matthew |last3=Kenchington |first3=Ellen |last4=Valanko |first4=Sebastian |last5=Johnson |first5=David E. |year=2021 |title=New scientific information can help to inform the evaluation of EU deep-sea fisheries regulations |journal=The International Journal of Marine and Coastal Law |volume=36 |pages=627-646 |doi=10.1163/15718085-bja10074}}</ref>
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**identification of vulnerable marine ecosystems (VMEs) in the North-East Atlantic for the EU-funded Horizon 2020 ATLAS Project.<ref name = “Morato_et_al_2018″>{{Cite journal |last1=Morato |first1=Telmo |last2=Pham |first2=Christopher K. |last3=Pinto |first3=Carlos |last4=Golding |first4=Neil |last5=Ardron |first5=Jeff A. |last6=Muñoz |first6=Pablo Durán |last7=Neat|first7=Francis |year=2018 |title=A multi criteria assessment method for identifying vulnerable marine ecosystems in the North-East Atlantic |journal=Frontiers in Marine Science |volume=5 |pages=460 |doi=10.3389/fmars.2018.00460|doi-access=free }}</ref> According to Turner ”et al.”, 2021, “ATLAS partners helped develop a data aggregation approach, the VME Index, to help identify areas where vulnerable marine ecosystems are known or are likely to occur. The VME Index is a single metric based on a multi-criteria assessment method that combines VME indicator records within a C-square (i.e., a spatial unit used by ICES: 0.05 x 0.05 degree grid, equivalent to approximately 15 km² at 60°N latitude) based on the abundance/presence of VME indicator taxa and how reliable the underlying data are. … ICES has been using the VME Index since 2018 to provide advice concerning the protection of vulnerable marine ecosystems.”<ref name = “Turner_et_al_2021”>{{Cite journal |last1=Turner |first1=Phillip J. |last2=Gianni |first2=Matthew |last3=Kenchington |first3=Ellen |last4=Valanko |first4=Sebastian |last5=Johnson |first5=David E. |year=2021 |title=New scientific information can help to inform the evaluation of EU deep-sea fisheries regulations |journal=The International Journal of Marine and Coastal Law |volume=36 |pages=627-646 |doi=10.1163/15718085-bja10074}}</ref>
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**a 2019 ICES Report “Working Group on Spatial Fisheries Data (WGSFD)” contains a number of example maps plotted using 0.05×0.05 degree c-squares, and also a discussion of whether or not a move towards 0.01×0.01 degree square reporting would be beneficial (higher spatial data resolution) or detrimental (increased number of squares with no content)<ref name = “ICES_2019b”>{{Cite journal |last1=ICES |first1= |year=2019 |title=Working Group on Spatial Fisheries Data (WGSFD) |journal=ICES Scientific Reports |volume=1 |issue=52 |pages=1–144 |doi=10.17895/ices.pub.5648|doi-access=free }}</ref>
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**a 2019 ICES Report “Working Group on Spatial Fisheries Data (WGSFD)” contains a number of example maps plotted using 0.05×0.05 degree c-squares, and also a discussion of whether or not a move towards 0.01×0.01 degree square reporting would be beneficial (higher spatial data resolution) or detrimental (increased number of squares with no content)<ref name = “ICES_2019b”>{{Cite journal |last1=ICES |first1= |year=2019 |title=Working Group on Spatial Fisheries Data (WGSFD) |journal=ICES Scientific Reports |volume=1 |issue=52 |pages=1–144 |doi=10.17895/ices.pub.5648|doi-access=free }}</ref>
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