Drone imagery protocols to map vegetation are transferable between dryland sites across an elevational gradient

Authors: ROSER, ANNA - Boise State University; ENTERKINE, JOSH - Boise State University; REQUENA-MULLOR, JUAN - University Of Michigan; GLENN, NANCY - Boise State University; Boehm, Alex; DE GRAAFF, MARIE-ANNE - Boise State University; Clark, Pat; Pierson Jr, Frederick; CAUGHLIN, TREVOR - Boise State University

Submitted to: Ecosphere
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/11/2022
Publication Date: 12/28/2022
Citation: Roser, A., Enterkine, J., Requena-Mullor, J., Glenn, N.F., Boehm, A.R., de Graaff, M., Clark, P., Pierson Jr, F.B., Caughlin, T. 2022. Drone imagery protocols to map vegetation are transferable between dryland sites across an elevational gradient. Ecosphere. 13(12). Article e4330. https://doi.org/10.1002/ecs2.4330.
DOI: https://doi.org/10.1002/ecs2.4330

Interpretive Summary: In this study of dryland ecosystems, we investigated whether the same UAS flight protocols were transferable along an elevational and precipitation gradient. We assessed the accuracy of classified PFT and estimated fractional photosynthetic cover maps. The same UAS flight protocols were transferable across the landscape gradient for the accuracy of the maps. In contrast, the correlation between the field data and UAS imagery was inconsistent between sites. For maps of PFTs, sites with small forbs and grass and a high amount of bare ground likely required pixel resolution of less than 1cm to achieve stronger agreement with field data. As a result, it may be necessary to alter UAS data collection protocols based on the structural and compositional differences in vegetation in some ecosystems. UAS imagery can be used to model fractional photosynthetic cover at fine spatial scale resolution, with coverage and sampling density that greatly exceeds field data, a key advantage in ecosystems where individual plant cover varies at scales far below the scale of widely used satellite platforms. Lastly, linking the PFT imagery with fractional photosynthetic cover imagery allowed us to estimate the variation of contributions of plant functional types to fractional photosynthetic cover at peak biomass. Altogether, our results speak to the great promise of UAS for spatially extensive, continuous measurements of fine-scale variation in ecosystem structure. The time is right to implement UAS as a standard tool for long-term monitoring.

Technical Abstract: The structure and composition of plant communities in drylands are highly variable across scales, from microsites to landscapes. Fine spatial resolution field surveys of dryland plants are essential to unravel the impact of climate change; however, traditional field-data collection is challenging considering sampling efforts and costs. Unoccupied Aerial Systems (UAS) can alleviate this challenge by providing standardized measurements of plant community attributes with high resolution. However, given widespread heterogeneity in plant communities in drylands, and especially across environmental gradients, the transferability of UAS flight protocols is unclear. Plant functional types (PFTs) are a classification scheme that aggregates the diversity of plant structure and function. We mapped and modeled PFTs and fractional photosynthetic cover with the same UAS flight protocol across three dryland communities, differentiated by a landscape-scale gradient of elevation and precipitation. We compared the accuracy of the UAS products between the three dryland sites. We found classifications of plant cover and modeled photosynthetic cover had high accuracies and strong agreement with field data at higher elevations with denser vegetation. The lowest site, with more bare ground, had the least agreement with the field data. Notably, shrub cover was well predicted across the gradient. UAS surveys captured the heterogeneity of plant cover among sites and presented options to measure leaf-level composition and structure at landscape levels. Our results demonstrate some PFTs can readily be detected across sites using the same UAS flight protocols, while others may require site-specific flight protocols for best accuracy. As UAS are increasingly used to monitor dryland vegetation, developing protocols that maximize information and efficiency is a research and management priority.