Closed lizzieinvancouver closed 5 months ago
I started looking at this and put some plots here https://github.com/lizzieinvancouver/grephon/tree/main/figures via this commit. I didn't spot any clear patterns across species but let me know if you have ideas for other plots to make!
@AileneKane will add plots that 1) break up the species by continent; 2) add a plot that shows results within paper (not studies); and 3) ask Freddie about indeterminate vs determinate growth for each species.
@AileneKane will add plots that 1) break up the species by continent; 2) add a plot that shows results within paper (not studies); and 3) ask Freddie about indeterminate vs determinate growth for each species.
I am still waiting for some library loans from some old literature that might be helpful for that...just so you know...
@AileneKane I am working on integrating your species cleaning code and getting these warnings:
> #Pull out the species and genera to do answer the questions
> spd2<-spd %>%
+ separate(species_list,c("sp1","sp2","sp3","sp4","sp5","sp6","sp7","sp8","sp9","sp10"),", ")
Warning message:
Expected 10 pieces. Missing pieces filled with `NA` in 47 rows [3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 28, ...].
> gen1<-spd2 %>%
+ separate(sp1,c("gen1","spe1")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 2 rows [46, 47].
> gen2<-gen1 %>%
+ separate(sp2,c("gen2","spe2")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 2 rows [46, 47].
> gen3<-gen2 %>%
+ separate(sp3,c("gen3","spe3")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 2 rows [46, 47].
> gen4<-gen3 %>%
+ separate(sp4,c("gen4","spe4")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 2 rows [46, 47].
> gen5<-gen4 %>%
+ separate(sp5,c("gen5","spe5")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 2 rows [46, 47].
> gen6<-gen5 %>%
+ separate(sp6,c("gen6","spe6")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 2 rows [46, 47].
> gen7<-gen6 %>%
+ separate(sp7,c("gen7","spe7")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 2 rows [46, 47].
> gen8<-gen7 %>%
+ separate(sp8,c("gen8","spe8")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 1 rows [47].
> gen9<-gen8 %>%
+ separate(sp9,c("gen9","spe9")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 1 rows [47].
> gen10<-gen9 %>%
+ separate(sp10,c("gen10","spe10")," ")
Warning message:
Expected 2 pieces. Missing pieces filled with `NA` in 1 rows [47].
Were you getting these?
Also, you don't need:
library(dplyr)
library(tidyr)
When you have already loaded tidyverse, as tidyverse loads all those packages and more.
@lizzieinvancouver yes, I got those warnings- they can be ignored. Feel free top modify the code as you like!
@AileneKane Great! Your plotting code is now analyses/plotspecies.R
@AileneKane Could you work on finalizing this figure for submission? It's currently figure 2 in the supp.
@AileneKane I am planning to use your species figure in the supp. Can you check it is updated and add italics to species names? Thank you!
@lizzieinvancouver Apologies for my delay! I have updated and italicized the names! Please let me know if there are other tweaks I should make.
@AileneKane Thank you! As I working on the caption, I realized that I do not understand why there is both not tested
and not mentioned
as it looks like not mentioned
is what we entered. I think it must relate to this line:
spd1_long$authorsthink_evidence_gsxgrowth[is.na(spd1_long$authorsthink_evidence_gsxgrowth)]<-"not tested"
#what does NA mean? that either GSL or growth were not tested, i think
So I think if we overwrite the not mentioned
as not tested
(as not tested
is what we use in the heatmaps), but I wanted to check with you. Also @cchambe12 can you confirm how you got not tested
to make sure our code is consistent!
@lizzieinvancouver @AileneKane Hi both! For the Figure 3 heatmap, we used "Not measured" for any studies that only measured a growth metric or a phenology metric but did not measure both. It essentially replaces any NAs. I can easily change the language to be consistent with this species figure though!
@lizzieinvancouver and @cchambe12 I can overwrite "not tested" with "not mentioned" as I think the difference between the two is subtle and not really important for the figure. My understanding is that "not mentioned" was listed in our table when the authors could have tested for the relationships but did not (i.e., when they had growing season start ad end or GSL). "NA" (which I replaced with "not tested") appears when there was one or more of the growing season start/end/length metrics missing. I will remove "not tested" and replace with "not mentioned" to be consistent
@lizzieinvancouver and @cchambe12 I can overwrite "not tested" with "not mentioned" as I think the difference between the two is subtle and not really important for the figure. My understanding is that "not mentioned" was listed in our table when the authors could have tested for the relationships but did not (i.e., when they had growing season start ad end or GSL). "NA" (which I replaced with "not tested") appears when there was one or more of the growing season start/end/length metrics missing. I will remove "not tested" and replace with "not mentioned" to be consistent
@AileneKane Many thanks! I think not tested
might be best as we have not tested
and not measured
so far in the manuscript figures and I would be happy to not add another term.
@AileneKane Could you update the code and figure?
@lizzieinvancouver i believe this is now done! Please let me know if any additional changes should be made!
@AileneKane Looks good to me, thank you!
Make a script to pull out all the species from the species columns and check for any trends in any/all of the following:
i) How diverse or not the species studied to date are.
ii) Which species are studied more than others?
iii) Which species show trends versus which do not?
iv) Any useful ways to categorize species (Grime CSR, functional type, freeze tolerance, shade tolerance) etc..