Optimizing sampling across methods improves the power of ecological monitoring data

Transect-based monitoring has long been a valuable tool in ecosystem
monitoring. These transects are often used to measure multiple
ecosystem attributes. The line-point intercept (LPI), vegetation
height, and canopy gap intercept methods comprise a set of core
methods, which provide indicators of ecosystem condition. However,
users struggle to design a sampling strategy that optimizes the
ability to detect ecological change using transect-based methods. We
assessed the sensitivity of these core methods on a one-hectare plot
to transect length, number, and sampling interval to determine: 1)
minimum sampling required to describe ecosystem characteristics and
detect change for each method and 2) optimal transect length and
number for all three methods to make recommendations for future
analyses and monitoring efforts. We used data from 13 National Wind
Erosion Research Network locations spanning the western US, which
included 151 measurements over time across five biomes. We found
that longer and increased numbers of transects were more important
for reducing sampling error than increased sample intensity along
transects. For all methods and indicators across plots, three 100-m
transects reduced sampling error so that indicator estimates fall
within an 95% confidence interval of +/- 5% for canopy gap intercept
and LPI-total foliar cover, +/- 5 cm for height and +/- two species
for LPI-species counts. For the same criteria at 80% confidence
intervals, two 100-m transects are needed. Site-scale inference was
strongly affected by sample design, consequently our understanding
of ecological dynamics may be influenced by sampling decisions.