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Indicator: number of new introductions of alien species per year in Belgium #17
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I’ve added column “species” to dataframe. It’s likely we will also rename some of the columns. |
Yes, @peterdesmet for sure! Tomorrow I am "blocked" for preparing the hackathon. |
Column names updated (and few others added) in "data output" table of #17 (comment) |
with respect to the requeste facet_subplots (aka Breakdowns). Not all are possible yet, we can trakc the progress here:
With respect to
For the source checklist, a line based breakdown was requested by @timadriaens ; is this of any value?
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Similar to #20 , the facet graphs underneath are included as well as part of the functionality; e.g. for |
@Yasmine-Verzelen and @SanderDevisscher: my workflow .Rmd has passed internal reviews and it is now merged in master.
Unfortunately you cannot do this via GitHub Desktop. So, the most important stuff is the fact that the database is now 100% tidy! That means that you are now able to make facet_subplots for native range breakdown as well 👍. You can start by importing the new version of file |
Hi, where do I find the latest graphs based on the unified checklist including all the breakdowns, need them for a chapter in the Living Planet Report Belgium @damianooldoni ? |
@timadriaens : I will rerun the checklist indicators pipelines and push to master: as written via Hangout I plan it to do on June 24th (25th as backup if unexpected errors occur). |
By the way, this issue should be closed as this indicator is now working and it is updated on master. |
Description
Temporal trends in first record rates of alien species (number of first records per year/per x year interval) for alien species (based on Seebens et al. 2017). This indicator provides information on the number of new introductions in time, for instance the rate of increase of alien species introductions and the accumulation rate of alien species (Rabitsch et al. 2016). The information will be updated and refined as the checklist is further supplemented.
Data needs
Data output
The data retrieved by GBIF would be organized in a (tidy) data.frame
This data should be already filtered as explained in #21 .
This data output will serve as input for the plots based on group_by-like pipes, e.g.
It is suggested to write these series of
group_by()
in a function for plotting because of the high number of combinations of information.See issue #18 about temporal information (
first_observed
andlast_observed
) in checklists.The text was updated successfully, but these errors were encountered: