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Dust events originate from multiple sources in arid and semi-arid regions, making it difficult to quantify source contributions. Dust geochemical/mineralogical composition, if the sources are sufficiently distinct, can be used to quantify the contributions from different sources. To test the viability of using geochemical and mineralogical measurements to separate dust-emitting sites, we used dust samples collected between 2018 and 2020 from ten National Wind Erosion Research Network (NWERN) sites that are representative of western United States (US) dust sources. Dust composition varied seasonally at many of the sites, but within-site variability was smaller than across-site variability, indicating that the geochemical signatures are robust over time. It was not possible to separate all the sites using commonly applied principal component analysis (PCA) and cluster analysis because of overlap in dust geochemistry. However, a linear discriminant analysis (LDA) successfully separated all sites based on their geochemistry, suggesting that LDA may prove useful for separating dust sources that cannot be separated using PCA or other methods. Further, an LDA based on mineralogical data separated most sites using only a limited number of mineral phases that were readily explained by the local geologic setting. Taken together, the geochemical and mineralogical measurements generated distinct signatures of dust emissions across NWERN sites. If expanded to include a broader range of sites across the western US, a library of geochemical and mineralogical data may serve as a basis to track and quantify dust contributions from these sources. 

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.