Aeolian sediment transport responses to vegetation cover change: Effects of sampling error on model uncertainty

Authors: WOJCIKIEWICZ, ROBERT - New Mexico State University; WEBB, NICHOLAS - New Mexico State University; EDWARDS, BRANDON - New Mexico State University; Van Zee, Justin; Courtright, Ericha; COOPER, BRAD - New Mexico State University; HANAN, NIALL - New Mexico State University

Submitted to: Journal of Geophysical Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/17/2023
Publication Date: 12/8/2023
Citation: Wojcikiewicz, R.R., Webb, N.P., Edwards, B.L., Van Zee, J.W., Courtright, E.M., Cooper, B.F., Hanan, N.P. 2023. Aeolian sediment transport responses to vegetation cover change: Effects of sampling error on model uncertainty. Journal of Geophysical Research. 128(12). Article e2023JF007319. https://doi.org/10.1029/2023JF007319.
DOI: https://doi.org/10.1029/2023JF007319

Interpretive Summary: Studies of aeolian sediment transport are prone to sampling error, largely due to the many factors that control the transport process. However, researchers often look to simplify sample designs and monitoring methods as monitoring is time consuming and expensive. To that end, vegetative cover is an easily collected and interpreted environmental indicator that affects rates of aeolian sediment transport. However, little consideration has been given to how many samples are needed to confidently model the relationship between changes in vegetative cover and sediment transport. We investigate how changes in sample size, modeling approaches, and vegetative cover may affect inferences made about aeolian sediment transport. We show that using traditional approaches in aeolian research (using small sample sizes and relatively simple environmental data), could risk false conclusions being drawn about aeolian transport processes, even with models that appear to be accurate. If sampling doesn’t adequately describe the sediment transport ‘population’ response, variability in field measurements can be so large that it undermines our understanding of how and why aeolian sediment transport rates change over time. These findings may require a re-evaluation of typical sediment transport sampling practices.

Technical Abstract: Although it is widely known that observations of aeolian sediment transport are susceptible to large sampling errors, sample designs are frequently used that do not sufficiently reduce measurement uncertainties inherent in the study of aeolian processes. Here, we examine the influence of sample size (n) and sampling location on uncertainty in models of aeolian sediment transport responses to vegetation cover change. We compare measurements from a stratified random array of 27 horizontal sediment mass flux samplers to vegetative cover data collected at a 1 ha site over a period of 5 years. To assess the sensitivity of modeled relationships between aeolian transport and vegetative cover to sample design, we analyze statistical regressions for all possible combinations of sample size and sampler locations. We show that at least 17 randomly located sediment samplers are needed to consistently capture the sediment mass flux response to vegetative cover change. We found that multiple statistically significant models can describe the sediment flux-vegetative cover relationship when using smaller sample sizes, demonstrating the risks of inferring sediment transport response from an underpowered sample design. Across vegetative functional groups, we found that woody cover generally influenced aeolian sediment transport rates more than herbaceous cover, while model uncertainty at large sample sizes (n > 17) showed the limitation of using vegetative cover as an indicator of aeolian sediment transport. Our results suggest an evaluation of sampling practices in aeolian sediment transport studies may be needed to avoid inferential errors that are likely pervasive in this field of study.