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Mapping foodscapes and sagebrush morphotypes with unmanned aerial systems for multiple herbivores

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Abstract

Context

The amount and composition of phytochemicals in forage plants influences habitat quality for wild herbivores. However, evaluating forage quality at fine resolutions across broad spatial extents (i.e., foodscapes) is challenging. Unmanned aerial systems (UAS) provide an avenue for bridging this gap in spatial scale.

Objectives

We evaluated the potential for UAS technology to accurately predict nutritional quality of sagebrush (Artemisia spp.) across landscapes. We mapped seasonal forage quality across two sites in Idaho, USA, with different mixtures of species but similar structural morphotypes of sagebrush.

Methods

We classified the sagebrush at both study sites using structural features of shrubs with object-based image analysis and machine learning and linked this classification to field measurements of phytochemicals to interpolate a foodscape for each phytochemical with regression kriging. We compared fine-scale landscape patterns of phytochemicals between sites and seasons.

Results

Classification accuracy for morphotypes was high at both study sites (81–87%). Forage quality was highly variable both within and among sagebrush morphotypes. Coumarins were the most accurately mapped (r2 = 0.57–0.81), whereas monoterpenes were the most variable and least explained. Patches with higher crude protein were larger and more connected in summer than in winter.

Conclusions

UAS allowed for a rapid collection of imagery for mapping foodscapes based on the phytochemical composition of sagebrush at fine scales but relatively broad extents. However, results suggest that a more advanced sensor (e.g., hyperspectral camera) is needed to map mixed species of sagebrush or to directly measure forage quality.

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Acknowledgements

This research was funded by the National Science Foundation (DEB-1146368 to LAS, DEB-1146194, IOS-1258217, OIA-1826801 and OIA-1757324 to JSF, and DEB-1146166 to JLR); USDA National Institute of Food and Agriculture (Hatch Project 1005876 to LAS). Washington State University; Boise State University; and the University of Idaho. Special thanks to the University of Florida Unmanned Aircraft Systems Research Program, and Empire Unmanned for collection of UAS data; and to C. Merriman, C. Milling, M. Camp, M. Crowell, and many undergraduate students for assistance with field data collection and chemical analyses.

Funding

This study was funded by the National Science Foundation (DEB-1146368 to LAS, DEB-1146194, IOS-1258217, OIA-1826801 and OIA-1757324 to JSF, and DEB-1146166 to JLR) and USDA National Institute of Food and Agriculture (Hatch Project 1005876 to LAS).

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Authors and Affiliations

  1. School of the Environment, Washington State University, Pullman, WA, 99164, USA

    Peter J. Olsoy, Lisa A. Shipley & Daniel H. Thornton

  2. Department of Biological Sciences, Boise State University, Boise, ID, 83725, USA

    Jennifer S. Forbey, Brecken C. Robb & Jordan D. Nobler

  3. Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID, 83844, USA

    Janet L. Rachlow

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  1. Peter J. Olsoy
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  2. Jennifer S. Forbey
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Correspondence to Peter J. Olsoy.

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Olsoy, P.J., Forbey, J.S., Shipley, L.A. et al. Mapping foodscapes and sagebrush morphotypes with unmanned aerial systems for multiple herbivores. Landscape Ecol 35, 921–936 (2020). https://doi.org/10.1007/s10980-020-00990-1

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