Optimizing sampling across transect-based methods improves the power of agroecological monitoring data.

Abstract

Transect-based monitoring has long been a valuable tool in ecosystem monitoring 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 often struggle to design a sampling strategy that optimizes the ability to detect ecological change using transect-based methods. We assessed the sensitivity of each of these core methods to transect length, number, and sampling interval in 1-ha plots to determine: (1) minimum sampling required to describe ecosystem characteristics and detect change; and (2) optimal transect length and number to make recommendations for future analyses and monitoring efforts. We used data from 13 National Wind Erosion Research Network locations, including five LTAR sites, spanning the western United States, which included 151 plot sampling events over time across five biomes. We found that longer and increased replicates of transects were more important for reducing sampling error than increased sample intensity along fewer transects per plot. For all methods and indicators across biomes plots, three 100-m transects reduced sampling error such that indicator estimates fell within a 95% confidence interval of ±5% for canopy gap intercept and LPI-total foliar cover, ±5 cm for height, and ±2 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.