knitr::opts_chunk$set(results='asis', echo=FALSE,comment=FALSE,warning=FALSE,message=FALSE) knitr::knit_hooks$set(plot = function (x, options) { float_correct <- function(f, y, opts) { if (is.null(opts$regfloat) || opts$regfloat==FALSE) paste0(f(y, opts), "\n\n\\FloatBarrier\n") else f(y, opts) } if (!is.null(options$out.width) || !is.null(options$out.height) || !is.null(options$out.extra) || options$fig.align != "default" || !is.null(options$fig.subcap)) { if (is.null(options$fig.scap)) options$fig.scap = NA return(float_correct(knitr:::hook_plot_tex, x, options)) } return(float_correct(knitr:::hook_plot_md_base, x, options)) })
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r content$text$intro_text
The combined Global Capture Production dataset contains more than 1 million records. This big data analysis looks at trends across larger areas and timeframes. It does not look at outliers or rare species but captures the trends by looking at common taxa. FAO statistical data are not collated for biodiversity studies, and we caution against comparing with other reporting frameworks.
Software The analyses used in this report can be generated using R codes. The reader can download them on faoBiofishr
Data collection [Briefly explain how the data in Global Production dataset are collected]
Data access and preparation The pre-processed data used in this circular can be downloaded as a csv file from FAO website Global Capture Production, and used in the R codes mentioned in the software sections. The pre-processing was done to facilitate the analytical steps.
Following steps were taken to filter the data:
Mammals, amphibians, and reptiles are not relevant because their records in this dataset cannot effectively reflect the impact fishing activities on aquatic environment. … and — are not available or unobtainable values. 0 means more than 0 but less than half of the unite and thus was kept. We do not expect the exclusion of these items to have a considerable impact on the overall findings. A record in the dataset is a unique combination of reported species, reporting country, year, and fishing area. Results of this report are based on calculating the number of records.
Add key findings
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```rFigure title", out.width = '100%'}
knitr::include_graphics(content$fig$com_isscaap_global)
`r content$text$com_isscaap_global` \newpage ## Commonness of Marine and anadromous vs Inland records in FishStatJ ```rFigure title", out.width = '100%'} knitr::include_graphics(content$fig$com_isscaap_area_type)
r content$text$com_isscaap_area_type
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r paste0("## ",content$title$com_isscaap_ocean)
```rFigure title", out.width = '100%'}
knitr::include_graphics(content$fig$com_isscaap_ocean)
`r content$text$com_isscaap_ocean` \newpage ## Commonness of Taxonomic Group records in FishStatJ — by FAO Fishery Areas ### Inland ```rFigure title", out.width = '100%'} knitr::include_graphics(content$fig$com_isccap_f_area_inland)
r content$text$com_isccap_f_area_inland
\newpage
```rFigure title", out.width = '100%'}
knitr::include_graphics(content$fig$com_isccap_f_area_marine)
`r content$text$com_isccap_f_area_marine` \newpage # Part 2 Biodiversity reporting development in FAO Fisheries ## Commonness among Pisces [vertebrate fish] records in FishStatJ — Global ```rFigure title", out.width = '100%'} knitr::include_graphics(content$fig$com_sp_global)
r content$text$com_sp_global
\newpage
```rFigure title", out.width = '100%'}
knitr::include_graphics(content$fig$com_sp_ocean)
`r content$text$com_sp_ocean` \newpage ## Commonness among fish records in FishStatJ — By FAO Fisheries Areas ### Inland ```rFigure title", out.width = '100%'} knitr::include_graphics(content$fig$com_sp_f_area_inland)
r content$text$com_sp_f_area_inland
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```rFigure title", out.width = '100%'}
knitr::include_graphics(content$fig$com_sp_f_area_marine)
```
r content$text$com_sp_f_area_marine
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