2.4 Importance of variables
To analyze the relative
importance of environmental variables in explaining sea snakes’
distributions, we first classified the variables into ten groups based
on their identity. For example, the group “Temperature (Tem)” included
seven variables that represent the median of the mean, maximum and
minimum values of the sea surface and benthic temperature (Table 1).
We used two measures to assess the relative importance of environmental
variables: the percentage of contribution (PC) and the permutation of
importance (PI) estimated by MaxEnt. PC measures the gain of a model
built with a single specific variable divided by the total gain of a
model built with all the variables. PI is obtained from randomizing the
values of each variable so that this variable is not informative and
then measures the resulting drop in the area under the curve (Phillips
2011). To identify the consistency or variability in our results, we
performed this procedure at three levels: “lineage”, when we analyzed
the variables for all species independently of subfamily; “subfamily”,
where we divided the results into the Hydrophiinae and Laticaudinae
subfamilies; and “genus”, where we repeated the same analysis for each
of the six genera. We performed this analysis at both resolutions (5 and
10 arc-minutes).
We also separated the identity variables into two groups (high relative
importance and low relative importance) based on their relative
importance using the natural Jenks thresholds calculated with thegetJenksBreaks function of the “BAMMtools” package (Rabosky et
al. 2014).
To determine if the results depended on spatial resolution, we evaluated
the consistency of the importance of each variable between the two
spatial resolutions for the two MaxEnt metrics (PC and PI) through a
non-parametric Mann-Whitney-Wilcoxon test through thewilxicon.test function in “stats” package (R Core Team, 2013).
Overall, our approach allowed us to identify the most important
environmental variables driving the distributions of sea snakes and to
assess the consistency of these results across different metrics of
importance, taxonomic levels and spatial resolutions.