Large-scale disturbances, such as megafires, motivate restoration at equally large extents. Measuring the survival and growth of individual plants plays a key role in current efforts to monitor restoration success. However, the scale of modern restoration (e.g., >10,000 ha) challenges measurements of demographic rates with field data. In this study, we demonstrate how unoccupied aerial system (UAS) flights can provide an efficient solution to the tradeoff of precision and spatial extent in detecting demographic rates from the air. We flew two, sequential UAS flights at two sagebrush (Artemisia tridentata) common gardens to measure the survival and growth of individual plants. The accuracy of Bayesian-optimized segmentation of individual shrub canopies was high (73–95%, depending on the year and site), and remotely sensed survival estimates were within 10% of ground-truthed survival censuses. Stand age structure affected remotely sensed estimates of growth; growth was overestimated relative to field-based estimates by 57% in the first garden with older stands, but agreement was high in the second garden with younger stands. Further, younger stands (similar to those just after disturbance) with shorter, smaller plants were sometimes confused with other shrub species and bunchgrasses, demonstrating a need for integrating spectral classification approaches that are increasingly available on affordable UAS platforms. The older stand had several merged canopies, which led to an underestimation of abundance but did not bias remotely sensed survival estimates. Advances in segmentation and UAS structure from motion photogrammetry will enable demographic rate measurements at management-relevant extents.

Data Use
License:
Creative Commons Attribution 4.0 License (CC-BY 4.0)
Recommended Citation:
Olsoy PJ, Zaiats A, Delparte DM, Germino MJ, Richardson BA, Roser AV, Forbey JS, Cattau ME, Caughlin TT. 2023. Data from: Demography with drones: Detecting growth and survival of shrubs with unoccupied aerial systems [Dataset]. University of Idaho. https://doi.org/10.7923/xj7r-1d86

Funding
US National Science Foundation and Idaho EPSCoR: OIA-1757324
US National Science Foundation and Idaho EPSCoR: OIA-1826801
US National Science Foundation: BIO-2207158

Ancillary Data Sets
Olsoy P, Zaiats A, Delparte D, Roop S, Roser A, Caughlin TT. 2022. Data from: High-resolution thermal imagery reveals how interactions between crown structure and genetics shape plant temperature [Data set]. University of Idaho. https://doi.org/10.7923/B68T-2S83