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License: MIT License
Code for: Habitat edges affect tree diversity more than biomass regeneration in a wet neotropical secondary forest
License: MIT License
wanting to try using 'tidyr::nest()' to run a basic linear
regression for all collected variables, but table structure
from 'rstatix::get_summary_stats()' is different (maybe already
a bit nested). solving this would really shorten the data
exploration phase, since the regression models would all
have the same independent variable--distance to forest.
potentially efficient!
try summarizing
discrete distance
levels, since study
only analyzes 1
gradient at 1 study
site
choice of diversity metric from issue 6 still open, but for later. for now, re-model stats for non-normal
variables, and maybe integrate into big results table skeleton, if possible.
polish/adapt intro frmo previous Word verson.
with draft dispersal categories, run dispersal
analysis for fig3
make histograms of size metrics
(DAP, height, biomass) to
supplement later diversity
metrics, which use instead species
frequencies to get entropy
basing choice on higher R2...or AIC?
maybe it will bring out
other variables as
predictors? but may explain
opposite relationship
between richness and
diversity.
map and mutate biomass data models and graphs. try to
select out timber sp onto graph.
general improvement/work
organize current code into new file structure advised by Pat Schloss, remembering that the main notebook file is for discussion and presentation of most updated figures and numbers, and use separate files/scripts for each analysis--exploratory, or for each individual figure.
stat plus graph
while centers are needed for their own stats, for plots, add
variance to plot, maybe by plotting as stat_summary() instead of
direct calculated ceters from full tbl (i.e. $varData1).
find out which
species cause the
diffs in
community/diversity
try nlme to reduce "2" system
based on poly
try making beta diversity among plots in addition or instead of ordination in fig2, suggested by Schloss
Riffomonas CC204.
start making new figs from updated plan in Results section.
incorporate tidymodel::
skeleton into stat
pipeline?
extracting pvals from nested summary tbls in col of main
stat tbl, then adding final col to eval it, per measured
var
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