Elevation use over time
Changes in elevation were
analysed by applying a “segmented” (or “broken-line”) regression
model with record elevation as a response, and the year as a predictor.
We obtained the best-fit breakpoint value with the davies.testfunction of the ’segmented’ library in R (Muggeo 2003). Additional
break-points were tested by applying the davies.test to each time
frame previously detected. Linear regressions were performed on the two
obtained intervals (namely to the left and to right of the breakpoint
value), a t-test was applied to compare the two regression slopes. For
these analyses, we included observations older than 1949 in order to
include data evenly distributed over time. Only for B. konradinia different analysis was used: as the few records are unevenly
distributed over time, we grouped them in three ranges:“1960s” from
1961-1963, “1980s-1990s” from 1984 to 1998, “2010s-2020” from 2011
to 2020. To calculate the uphill shift, we considered the difference in
25% quantile elevation values of the oldest 40 observations in the
recent and the older time group, although we calculated the differences
also with other quantiles too for comparison.