Abstract
Abstract. Sagebrush ecosystems (Artemisia spp.) face many threats including large wildfires and conversion to invasive annuals, and thus are the focus of intense restoration efforts across the western United States. Specific attention has been given to restoration of sagebrush systems for threatened herbivores, such as Greater Sage-Grouse (Centrocercus urophasianus) and pygmy rabbits (Brachylagus idahoensis), reliant on sagebrush as forage. Despite this, plant chemistry (e.g., crude protein, monoterpenes and phenolics) is rarely considered during reseeding efforts or when deciding which areas to conserve. Near-infrared spectroscopy (NIRS) has proven effective in predicting plant chemistry under laboratory conditions in a variety of ecosystems, including the sagebrush steppe. Our objectives were to demonstrate the scalability of these models from the laboratory to the field, and in the air with a hyperspectral sensor on an unoccupied aerial system (UAS). Sagebrush leaf samples were collected at a study site in eastern Idaho, USA. Plants were scanned with an ASD FieldSpec 4 spectroradiometer in the field and laboratory, and a subset of the same plants were imaged with a SteadiDrone Hexacopter UAS equipped with a Rikola hyperspectral sensor (HSI). All three sensors generated spectral patterns that were distinct among species and morphotypes of sagebrush at specific wavelengths. Lab-based NIRS was accurate for predicting crude protein and total monoterpenes (R2 = 0.7–0.8), but the same NIRS sensor in the field was unable to predict either crude protein or total monoterpenes (R2 < 0.1). The hyperspectral sensor on the UAS was unable to predict most chemicals (R2 < 0.2), likely due to a combination of too few bands in the Rikola HSI camera (16 bands), the range of wavelengths (500–900 nm), and small sample size of overlapping plants (n = 28–60). These results show both the potential for scaling NIRS from the lab to the field and the challenges in predicting complex plant chemistry with hyperspectral UAS. We conclude with recommendations for next steps in applying UAS to sagebrush ecosystems with a variety of new sensors.
Highlights
Sagebrushes (Artemisia spp.) are the dominant vegetation covering over 40 million ha of the western United States (Renwick et al, 2018), but have declined due to increased wildfires, conversion to cheatgrass (Bromus tectorum), and juniper (Juniperus spp.) encroachment
Sagebrush leaves contain a complex mixture of plant chemicals to protect against herbivory, including volatile monoterpenes and phenolics, but are a good source of crude protein
The broad distribution of sagebrush across the western United States has been coarsely mapped (e.g., LANDFIRE, GAP, NLCD), but these maps are at 30-m to 500-m spatial resolution and do not track finer-scale patterns in distinct species with phytochemical traits that matter to herbivores (Fremgen-Tarantino et al, 2021)
Summary
Sagebrushes (Artemisia spp.) are the dominant vegetation covering over 40 million ha of the western United States (Renwick et al, 2018), but have declined due to increased wildfires, conversion to cheatgrass (Bromus tectorum), and juniper (Juniperus spp.) encroachment. Sagebrush leaves contain a complex mixture of plant chemicals to protect against herbivory, including volatile monoterpenes and phenolics, but are a good source of crude protein. This chemistry is highly variable among and within sites (Robb, 2020, Olsoy et al, 2020) and influences diet and habitat selection by wild herbivores at varying spatial scales (Frye et al, 2013; Ulappa et al, 2014; Fremgen-Taratino et al, 2020). The broad distribution of sagebrush across the western United States has been coarsely mapped (e.g., LANDFIRE, GAP, NLCD), but these maps are at 30-m to 500-m spatial resolution and do not track finer-scale patterns in distinct species with phytochemical traits that matter to herbivores (Fremgen-Tarantino et al, 2021). The spectral signatures measured with NIRS depend on the number and type of C—H, N—H, and O—H chemical bonds, and can be related to plant defensive and nutritional chemistry (Foley et al, 1998; Moore et al, 2010; Robb, 2020)
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