Demography with drones: detecting growth and survival of shrubs with unoccupied aerial systems

Author:

Olsoy Peter J.1ORCID,Zaiats Andrii2,Delparte Donna M.3,Germino Matthew J.4ORCID,Richardson Bryce A.5,Roser Anna V.2,Forbey Jennifer S.2,Cattau Megan E.6,Caughlin T. Trevor2

Affiliation:

1. USDA Agricultural Research Service 67826‐A Hwy 205 Burns OR 97720 U.S.A.

2. Department of Biological Sciences Boise State University 1910 W University Dr Boise ID 83725 U.S.A.

3. Department of Geosciences Idaho State University 921 S 8th Ave Pocatello ID 83209 U.S.A.

4. U.S. Geological Survey Forest and Rangeland Ecosystem Science Center 230 N Collins Rd Boise 83702 ID U.S.A.

5. USDA Forest Service Forest Sciences Laboratory 1221 S Main St Moscow ID 83843 U.S.A.

6. Human‐Environment Systems Boise State University 1910 W University Dr Boise ID 83725 U.S.A.

Abstract

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.

Funder

National Science Foundation

Publisher

Wiley

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