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

Olsoy, Peter J.; Forbey, Jennifer S.; Shipley, Lisa A.; Rachlow, Janet L.; Robb, Brecken C.; Nobler, Jordan D.; Thornton, Daniel H.

doi:10.1007/s10980-020-00990-1

Cited by 17 publications

(24 citation statements)

References 46 publications

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“…The dwarf patches were primarily low-growing Wyoming big sagebrush (dwarf Wyoming) mixed with black sagebrush (A. nova). These morphotypes differed in both structural characteristics (Olsoy et al, 2018), thermal properties (Milling et al, 2018) and forage quality (Olsoy et al, 2020).…”

Section: Study Sitementioning

confidence: 99%

“…For monoterpenes, a subset of 100 mg of sample was transferred to a headspace vial and analysed using headspace gas chromatography (Agilent 7694 Headspace Sampler, Agilent 6890 Series GC). See Robb (2020) and Olsoy et al (2020) for more details on chemical analysis.…”

Section: Lab Chemistrymentioning

confidence: 99%

“…Sagebrush leaves contain a complex mixture of plant chemicals to protect against herbivory, including volatile monoterpenes and phenolics, but are also 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). To better understand plant-herbivore interactions, we need to map this plant chemistry across the landscape.…”

Section: Introductionmentioning

confidence: 99%

“…Previous work has shown UAS-based sensors can map shrub structure (Cunliffe et al, 2016;Olsoy et al, 2018), but relatively little work has been done to predict phytochemicals in sagebrush. Recent attempts at landscape mapping of diet quality involved classifying sagebrush structural morphotypes with unique chemical profiles, but relied on regression kriging (Olsoy et al, 2020), a type of spatial interpolation requiring a large amount of leaf sampling and laboratory analysis that does not directly predict plant chemical concentrations. NIRS (Olsoy et al, 2016;Robb, 2020) and airborne hyperspectral sensors (Mitchell et al, 2012b) have potential to link near-and short-wavelength infrared signals to plant chemistry.…”

Section: Introductionmentioning

confidence: 99%

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Scaling Up Sagebrush Chemistry With Near-Infrared Spectroscopy and Uas-Acquired Hyperspectral Imagery

Olsoy

Barrett

Robb

et al. 2021

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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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.

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Section: Study Sitementioning

confidence: 99%

Section: Lab Chemistrymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Scaling Up Sagebrush Chemistry With Near-Infrared Spectroscopy and Uas-Acquired Hyperspectral Imagery

Olsoy

Barrett

Robb

et al. 2021

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…At the micro-scale, microbial features in herbivores interact with metabolite concentrations in the gut after herbivores consume sagebrush . At the macro-scale, features of herbivores and sagebrush are dependent on metabolite concentrations of plant taxa within habitat patches (Ulappa et al, 2014, Frye et al, 2013 and those plant taxa can be detected with aerial remote sensing platforms (Olsoy et al, 2020). Ultimately, the community patterns that emerge from analyzing features across scales could deepen our understanding of plant-herbivore interactions and identify molecular, organismal, and landscape targets within complex communities for management in changing landscapes.…”

Section: Introductionmentioning

confidence: 99%

Molecular Approaches for Analyzing Organismal and Environmental Interactions

Hudon¹

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Our planet is undergoing rapid change due to the expanding human population and climate change, which leads to extreme weather events and habitat loss. It is more important than ever to develop methods which can monitor the impact we are having on the biodiversity of our planet. To influence policy changes in wildlife and resource management practices we need to provide measurable evidence of how we are affecting animal health and fitness and the ecosystems needed for their survival. We also need to pool our resources and work in interdisciplinary teams to find common threads which can help preserve biodiversity and vital habitats. This dissertation showcases how improved molecular biology assays and data analysis approaches can help monitor the fitness of animal populations within changing ecosystems. Chapter 1 details the development of a universal telomere assay for vertebrates. Recent work has shown the utility of telomere assays in tracking animal health. Telomere lengths can predict extinction events in animal populations, life span, and fitness consequences of anthropogenic activity. Telomere length assays are an improvement over other methods of measuring animal stress, such as cortisol levels, since they are stable during capture and sampling of animals. This dissertation provides a telomere length assay which can be used for any vertebrate. The assay was developed using a quantitative polymerase chain reaction platform which requires low DNA input and is rapid. This dissertation also demonstrates how this assay improves on current telomere assays developed for mice and can be used in a vertebrate not previously assayed for telomere lengths, the American kestrel. This work has the potential to propel research in vertebrate systems forward as it alleviates the need to develop new reference primers for each species of interest. This improved assay has shown promise in studies in mouse cell line studies, American kestrels, golden eagles, five species of passerine birds, osprey, northern goshawks and bighorn sheep. Chapter 2 presents a machine learning analysis, using a topic model approach, to integrate big data from remote sensing, leaf area index surveys, metabolomics and metagenomics to analyze community composition in cross-disciplinary datasets. Topic models were applied to understand community organization across a range of distinct, but connected, biological scales within the sagebrush steppe. The sagebrush steppe is home to several threatened species, including the pygmy rabbit (Brachylagus idahoensis) and sage-grouse (Centrocercus urophasianus). It covers vast swaths of the western United States and is subject to habitat fragmentation and land use conversion for both farming and rangeland use. It is also threatened by increases in fire events which can dramatically alter the landscape. Restoration efforts have been hampered by a lack of resources and often by inadequate collaboration between stakeholders and scientists. This work brought together scientists from four disciplines: remote sensing, field ecology, metabolomics and metagenomics, to provide a framework for how studies can be designed and analyzed that integrate patterns of biodiversity from multiple scales, from the molecular to the landscape scale. A topic model approach was used which groups features (chemicals, bacterial and plant taxa, and light spectrum) into “communities” which in turn can be analyzed for their presence within individual samples and time points. Within the landscape, I found communities which contain encroaching plant species, such as juniper (Juniperus spp.) and cheatgrass (Bromus tectorum). Within plants, I found chemicals which are known toxins to herbivores. Within herbivores, I identified differences in bacterial taxonomical communities associated with changes in diet. This work will help to inform restoration efforts and provide a road map for designing interdisciplinary studies.

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Mapping canopy nitrogen‐scapes to assess foraging habitat for a vulnerable arboreal folivore in mixed‐speciesEucalyptusforests

Wagner

Baker

Moore

et al. 2021

Ecology and Evolution

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

Cited by 17 publications

References 46 publications

Scaling Up Sagebrush Chemistry With Near-Infrared Spectroscopy and Uas-Acquired Hyperspectral Imagery

Scaling Up Sagebrush Chemistry With Near-Infrared Spectroscopy and Uas-Acquired Hyperspectral Imagery

Molecular Approaches for Analyzing Organismal and Environmental Interactions

Mapping canopy nitrogen‐scapes to assess foraging habitat for a vulnerable arboreal folivore in mixed‐speciesEucalyptusforests

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